1
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Porubsky D, Dashnow H, Sasani TA, Logsdon GA, Hallast P, Noyes MD, Kronenberg ZN, Mokveld T, Koundinya N, Nolan C, Steely CJ, Guarracino A, Dolzhenko E, Harvey WT, Rowell WJ, Grigorev K, Nicholas TJ, Oshima KK, Lin J, Ebert P, Watkins WS, Leung TY, Hanlon VCT, McGee S, Pedersen BS, Goldberg ME, Happ HC, Jeong H, Munson KM, Hoekzema K, Chan DD, Wang Y, Knuth J, Garcia GH, Fanslow C, Lambert C, Lee C, Smith JD, Levy S, Mason CE, Garrison E, Lansdorp PM, Neklason DW, Jorde LB, Quinlan AR, Eberle MA, Eichler EE. A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.05.606142. [PMID: 39149261 PMCID: PMC11326147 DOI: 10.1101/2024.08.05.606142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map (~3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas A Sasani
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Present address: Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Michelle D Noyes
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Nidhi Koundinya
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Cody J Steely
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Andrea Guarracino
- Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William J Rowell
- Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Kirill Grigorev
- Blue Marble Space Institute of Science, Seattle, WA, USA
- Core Unit Bioinformatics, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Thomas J Nicholas
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Keisuke K Oshima
- Present address: Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiadong Lin
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter Ebert
- Core Unit Bioinformatics, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - W Scott Watkins
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Tiffany Y Leung
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
| | | | - Sean McGee
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Brent S Pedersen
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Michael E Goldberg
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Hannah C Happ
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Present address: Altos Labs, San Diego, CA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Daniel D Chan
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
| | - Yanni Wang
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
| | - Jordan Knuth
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Joshua D Smith
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Shawn Levy
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Erik Garrison
- Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - Deborah W Neklason
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Aaron R Quinlan
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | | | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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2
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L Rocha J, Lou RN, Sudmant PH. Structural variation in humans and our primate kin in the era of telomere-to-telomere genomes and pangenomics. Curr Opin Genet Dev 2024; 87:102233. [PMID: 39042999 DOI: 10.1016/j.gde.2024.102233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 07/02/2024] [Accepted: 07/05/2024] [Indexed: 07/25/2024]
Abstract
Structural variants (SVs) account for the majority of base pair differences both within and between primate species. However, our understanding of inter- and intra-species SV has been historically hampered by the quality of draft primate genomes and the absence of genome resources for key taxa. Recently, advances in long-read sequencing and genome assembly have begun to radically reshape our understanding of SVs. Two landmark achievements include the publication of a human telomere-to-telomere (T2T) genome as well as the development of the first human pangenome reference. In this review, we first look back to the major works laying the foundation for these projects. We then examine the ways in which T2T genome assemblies and pangenomes are transforming our understanding of and approach to primate SV. Finally, we discuss what the future of primate SV research may look like in the era of T2T genomes and pangenomics.
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Affiliation(s)
- Joana L Rocha
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA. https://twitter.com/@joanocha
| | - Runyang N Lou
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA. https://twitter.com/@NicolasLou10
| | - Peter H Sudmant
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, USA.
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3
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Bai X, Chen Z, Chen K, Wu Z, Wang R, Liu J, Chang L, Wen L, Tang F. Simultaneous de novo calling and phasing of genetic variants at chromosome-scale using NanoStrand-seq. Cell Discov 2024; 10:74. [PMID: 38977679 PMCID: PMC11231365 DOI: 10.1038/s41421-024-00694-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 05/23/2024] [Indexed: 07/10/2024] Open
Abstract
The successful accomplishment of the first telomere-to-telomere human genome assembly, T2T-CHM13, marked a milestone in achieving completeness of the human reference genome. The upcoming era of genome study will focus on fully phased diploid genome assembly, with an emphasis on genetic differences between individual haplotypes. Most existing sequencing approaches only achieved localized haplotype phasing and relied on additional pedigree information for further whole-chromosome scale phasing. The short-read-based Strand-seq method is able to directly phase single nucleotide polymorphisms (SNPs) at whole-chromosome scale but falls short when it comes to phasing structural variations (SVs). To shed light on this issue, we developed a Nanopore sequencing platform-based Strand-seq approach, which we named NanoStrand-seq. This method allowed for de novo SNP calling with high precision (99.52%) and acheived a superior phasing accuracy (0.02% Hamming error rate) at whole-chromosome scale, a level of performance comparable to Strand-seq for haplotype phasing of the GM12878 genome. Importantly, we demonstrated that NanoStrand-seq can efficiently resolve the MHC locus, a highly polymorphic genomic region. Moreover, NanoStrand-seq enabled independent direct calling and phasing of deletions and insertions at whole-chromosome level; when applied to long genomic regions of SNP homozygosity, it outperformed the strategy that combined Strand-seq with bulk long-read sequencing. Finally, we showed that, like Strand-seq, NanoStrand-seq was also applicable to primary cultured cells. Together, here we provided a novel methodology that enabled interrogation of a full spectrum of haplotype-resolved SNPs and SVs at whole-chromosome scale, with broad applications for species with diploid or even potentially polypoid genomes.
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Affiliation(s)
- Xiuzhen Bai
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
| | - Zonggui Chen
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
- Changping Laboratory, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Kexuan Chen
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Zixin Wu
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Rui Wang
- Department of Medicine, Cancer Institute, Stanford University, Stanford, CA, USA
| | - Jun'e Liu
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
- School of Life Sciences, Peking University, Beijing, China
| | - Liang Chang
- State Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
- National Clinical Research Center for Obstetrics and Gynecology (Peking University Third Hospital), Beijing, China
- Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education Beijing, Beijing, China
- Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing, China
| | - Lu Wen
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China
- Changping Laboratory, Beijing, China
| | - Fuchou Tang
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, China.
- Changping Laboratory, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- School of Life Sciences, Peking University, Beijing, China.
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4
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Grimes K, Jeong H, Amoah A, Xu N, Niemann J, Raeder B, Hasenfeld P, Stober C, Rausch T, Benito E, Jann JC, Nowak D, Emini R, Hoenicka M, Liebold A, Ho A, Shuai S, Geiger H, Sanders AD, Korbel JO. Cell-type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells. Nat Genet 2024; 56:1134-1146. [PMID: 38806714 PMCID: PMC11176070 DOI: 10.1038/s41588-024-01754-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 04/17/2024] [Indexed: 05/30/2024]
Abstract
The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single-cell genomes from 19 human donors of increasing age, and discovered the heterogeneous mSV landscapes of hematopoietic stem and progenitor cells. While mSVs are continuously acquired throughout life, expanded subclones in our cohort are confined to individuals >60. Cells already harboring mSVs are more likely to acquire additional somatic structural variants, including megabase-scale segmental aneuploidies. Capitalizing on comprehensive single-cell micrococcal nuclease digestion with sequencing reference data, we conducted high-resolution cell-typing for eight hematopoietic stem and progenitor cells. Clonally expanded mSVs disrupt normal cellular function by dysregulating diverse cellular pathways, and enriching for myeloid progenitors. Our findings underscore the contribution of mSVs to the cellular and molecular phenotypes associated with the aging hematopoietic system, and establish a foundation for deciphering the molecular links between mSVs, aging and disease susceptibility in normal tissues.
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Affiliation(s)
- Karen Grimes
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Hyobin Jeong
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Systems Biology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea
| | - Amanda Amoah
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Nuo Xu
- Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Julian Niemann
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Benjamin Raeder
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Patrick Hasenfeld
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Catherine Stober
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Tobias Rausch
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
- Bridging Research Division on Mechanisms of Genomic Variation and Data Science, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Eva Benito
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Johann-Christoph Jann
- Department of Hematology and Oncology, Medical Faculty Mannheim of the Heidelberg University, Mannheim, Germany
| | - Daniel Nowak
- Department of Hematology and Oncology, Medical Faculty Mannheim of the Heidelberg University, Mannheim, Germany
| | - Ramiz Emini
- Department of Cardiothoracic and Vascular Surgery, Ulm University Hospital, Ulm, Germany
| | - Markus Hoenicka
- Department of Cardiothoracic and Vascular Surgery, Ulm University Hospital, Ulm, Germany
| | - Andreas Liebold
- Department of Cardiothoracic and Vascular Surgery, Ulm University Hospital, Ulm, Germany
| | - Anthony Ho
- Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
- Department of Medicine V, Hematology, Oncology and Rheumatology, University of Heidelberg, Heidelberg, Germany
| | - Shimin Shuai
- Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Hartmut Geiger
- Institute of Molecular Medicine, Ulm University, Ulm, Germany
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
- Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany.
- Charité-Universitätsmedizin Berlin, Berlin, Germany.
| | - Jan O Korbel
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.
- Bridging Research Division on Mechanisms of Genomic Variation and Data Science, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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5
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Logsdon GA, Rozanski AN, Ryabov F, Potapova T, Shepelev VA, Catacchio CR, Porubsky D, Mao Y, Yoo D, Rautiainen M, Koren S, Nurk S, Lucas JK, Hoekzema K, Munson KM, Gerton JL, Phillippy AM, Ventura M, Alexandrov IA, Eichler EE. The variation and evolution of complete human centromeres. Nature 2024; 629:136-145. [PMID: 38570684 PMCID: PMC11062924 DOI: 10.1038/s41586-024-07278-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 03/07/2024] [Indexed: 04/05/2024]
Abstract
Human centromeres have been traditionally very difficult to sequence and assemble owing to their repetitive nature and large size1. As a result, patterns of human centromeric variation and models for their evolution and function remain incomplete, despite centromeres being among the most rapidly mutating regions2,3. Here, using long-read sequencing, we completely sequenced and assembled all centromeres from a second human genome and compared it to the finished reference genome4,5. We find that the two sets of centromeres show at least a 4.1-fold increase in single-nucleotide variation when compared with their unique flanks and vary up to 3-fold in size. Moreover, we find that 45.8% of centromeric sequence cannot be reliably aligned using standard methods owing to the emergence of new α-satellite higher-order repeats (HORs). DNA methylation and CENP-A chromatin immunoprecipitation experiments show that 26% of the centromeres differ in their kinetochore position by >500 kb. To understand evolutionary change, we selected six chromosomes and sequenced and assembled 31 orthologous centromeres from the common chimpanzee, orangutan and macaque genomes. Comparative analyses reveal a nearly complete turnover of α-satellite HORs, with characteristic idiosyncratic changes in α-satellite HORs for each species. Phylogenetic reconstruction of human haplotypes supports limited to no recombination between the short (p) and long (q) arms across centromeres and reveals that novel α-satellite HORs share a monophyletic origin, providing a strategy to estimate the rate of saltatory amplification and mutation of human centromeric DNA.
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Affiliation(s)
- Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Fedor Ryabov
- Masters Program in National Research University Higher School of Economics, Moscow, Russia
| | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | | | - Claudia R Catacchio
- Department of Biosciences, Biotechnology and Environment, University of Bari Aldo Moro, Bari, Italy
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - DongAhn Yoo
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Oxford Nanopore Technologies, Oxford, United Kingdom
| | - Julian K Lucas
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mario Ventura
- Department of Biosciences, Biotechnology and Environment, University of Bari Aldo Moro, Bari, Italy
| | - Ivan A Alexandrov
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
- Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Dan David Center for Human Evolution and Biohistory Research, Tel Aviv University, Tel Aviv, Israel
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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6
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Youk J, Kwon HW, Lim J, Kim E, Kim T, Kim R, Park S, Yi K, Nam CH, Jeon S, An Y, Choi J, Na H, Lee ES, Cho Y, Min DW, Kim H, Kang YR, Choi SH, Bae MJ, Lee CG, Kim JG, Kim YS, Yu T, Lee WC, Shin JY, Lee DS, Kim TY, Ku T, Kim SY, Lee JH, Koo BK, Lee H, Yi OV, Han EC, Chang JH, Kim KS, Son TG, Ju YS. Quantitative and qualitative mutational impact of ionizing radiation on normal cells. CELL GENOMICS 2024; 4:100499. [PMID: 38359788 PMCID: PMC10879144 DOI: 10.1016/j.xgen.2024.100499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 10/23/2023] [Accepted: 01/09/2024] [Indexed: 02/17/2024]
Abstract
The comprehensive genomic impact of ionizing radiation (IR), a carcinogen, on healthy somatic cells remains unclear. Using large-scale whole-genome sequencing (WGS) of clones expanded from irradiated murine and human single cells, we revealed that IR induces a characteristic spectrum of short insertions or deletions (indels) and structural variations (SVs), including balanced inversions, translocations, composite SVs (deletion-insertion, deletion-inversion, and deletion-translocation composites), and complex genomic rearrangements (CGRs), including chromoplexy, chromothripsis, and SV by breakage-fusion-bridge cycles. Our findings suggest that 1 Gy IR exposure causes an average of 2.33 mutational events per Gb genome, comprising 2.15 indels, 0.17 SVs, and 0.01 CGRs, despite a high level of inter-cellular stochasticity. The mutational burden was dependent on total irradiation dose, regardless of dose rate or cell type. The findings were further validated in IR-induced secondary cancers and single cells without clonalization. Overall, our study highlights a comprehensive and clear picture of IR effects on normal mammalian genomes.
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Affiliation(s)
- Jeonghwan Youk
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Hyun Woo Kwon
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Department of Nuclear Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Joonoh Lim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Genome Insight, Inc., San Diego, CA 92121, USA
| | - Eunji Kim
- Department of Radiation Oncology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, 20, Boramae-ro 5 Gil, Dongjak-gu, Seoul 07061, Republic of Korea; Department of Radiation Oncology, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Taewoo Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Ryul Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Genome Insight, Inc., San Diego, CA 92121, USA
| | - Seongyeol Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Genome Insight, Inc., San Diego, CA 92121, USA
| | - Kijong Yi
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Genome Insight, Inc., San Diego, CA 92121, USA
| | - Chang Hyun Nam
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Sara Jeon
- Department of Biological Sciences & IMBG, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Yohan An
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Jinwook Choi
- Wellcome - MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, CB2 0AW Cambridge, UK; Department of Physiology, Development and Neuroscience, University of Cambridge, CB2 3EL Cambridge, UK
| | - Hyelin Na
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Eon-Seok Lee
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Youngwon Cho
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Dong-Wook Min
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - HyoJin Kim
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Yeong-Rok Kang
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Si Ho Choi
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Min Ji Bae
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Chang Geun Lee
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Joon-Goon Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; KI for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - Young Seo Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; KI for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - Tosol Yu
- Department of Radiation Oncology, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Department of Radiation Oncology, Dongnam Institute of Radiological and Medical Science, Busan 46033, Republic of Korea
| | | | | | - Dong Soo Lee
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Tae-You Kim
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Cancer Research Institute, Seoul National University, Seoul, Republic of Korea; Department of Internal Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea
| | - Taeyun Ku
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; KI for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - Su Yeon Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Joo-Hyeon Lee
- Wellcome - MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, CB2 0AW Cambridge, UK; Department of Physiology, Development and Neuroscience, University of Cambridge, CB2 3EL Cambridge, UK
| | - Bon-Kyoung Koo
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Hyunsook Lee
- Department of Biological Sciences & IMBG, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - On Vox Yi
- Department of Breast Surgery, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Eon Chul Han
- Department of Surgery, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea
| | - Ji Hyun Chang
- Department of Radiation Oncology, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Department of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Kyung Su Kim
- Department of Radiation Oncology, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Department of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
| | - Tae Gen Son
- Research Center, Dongnam Institute of Radiological and Medical Science, Busan, Republic of Korea.
| | - Young Seok Ju
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea; Genome Insight, Inc., San Diego, CA 92121, USA.
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7
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Paparella A, L’Abbate A, Palmisano D, Chirico G, Porubsky D, Catacchio CR, Ventura M, Eichler EE, Maggiolini FAM, Antonacci F. Structural Variation Evolution at the 15q11-q13 Disease-Associated Locus. Int J Mol Sci 2023; 24:15818. [PMID: 37958807 PMCID: PMC10648317 DOI: 10.3390/ijms242115818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
The impact of segmental duplications on human evolution and disease is only just starting to unfold, thanks to advancements in sequencing technologies that allow for their discovery and precise genotyping. The 15q11-q13 locus is a hotspot of recurrent copy number variation associated with Prader-Willi/Angelman syndromes, developmental delay, autism, and epilepsy and is mediated by complex segmental duplications, many of which arose recently during evolution. To gain insight into the instability of this region, we characterized its architecture in human and nonhuman primates, reconstructing the evolutionary history of five different inversions that rearranged the region in different species primarily by accumulation of segmental duplications. Comparative analysis of human and nonhuman primate duplication structures suggests a human-specific gain of directly oriented duplications in the regions flanking the GOLGA cores and HERC segmental duplications, representing potential genomic drivers for the human-specific expansions. The increasing complexity of segmental duplication organization over the course of evolution underlies its association with human susceptibility to recurrent disease-associated rearrangements.
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Affiliation(s)
- Annalisa Paparella
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
| | - Alberto L’Abbate
- Institute of Biomembranes, Bioenergetics, and Molecular Biotechnology (IBIOM), 70125 Bari, Italy
| | - Donato Palmisano
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
| | - Gerardina Chirico
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Claudia R. Catacchio
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
| | - Mario Ventura
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Howard Hughes Medical Institute (HHMI), University of Washington, Seattle, WA 98195, USA
| | - Flavia A. M. Maggiolini
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
- Research Centre for Viticulture and Enology, Council for Agricultural Research and Economics (CREA), 70010 Bari, Italy
| | - Francesca Antonacci
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
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8
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Lin D, Zou Y, Li X, Wang J, Xiao Q, Gao X, Lin F, Zhang N, Jiao M, Guo Y, Teng Z, Li S, Wei Y, Zhou F, Yin R, Zhang S, Xing L, Xu W, Wu X, Yang B, Xiao K, Wu C, Tao Y, Yang X, Zhang J, Hu S, Dong S, Li X, Ye S, Hong Z, Pan Y, Yang Y, Sun H, Cao G. MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing. Genome Biol 2023; 24:247. [PMID: 37904244 PMCID: PMC10614391 DOI: 10.1186/s13059-023-03081-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 10/04/2023] [Indexed: 11/01/2023] Open
Abstract
Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA's transcriptional regulatory function.
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Affiliation(s)
- Da Lin
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yanyan Zou
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Xinyu Li
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinyue Wang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Bio-Medicine and Health, Huazhong Agricultural University, Wuhan, China
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Qin Xiao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Bio-Medicine and Health, Huazhong Agricultural University, Wuhan, China
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Xiaochen Gao
- Precision Research Center for Refractory Diseases, Institute for Clinical Research, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fei Lin
- Reproductive Medical Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Ningyuan Zhang
- Reproductive Medical Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Ming Jiao
- Department of Laboratory Animal Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Guo
- Department of Laboratory Animal Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhaowei Teng
- The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Shiyi Li
- Baylor College of Medicine, Houston, TX, USA
- Department of Radiation & Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yongchang Wei
- Department of Radiation & Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Tumor Biological Behaviors, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Fuling Zhou
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Rong Yin
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Siheng Zhang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Lingyu Xing
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Weize Xu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Xiaofeng Wu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Bing Yang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Ke Xiao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Chengchao Wu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Yingfeng Tao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Xiaoqing Yang
- Hospital of Huazhong Agricultural University, Wuhan, China
| | - Jing Zhang
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sheng Hu
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shuang Dong
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyu Li
- Department of Medical Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shengwei Ye
- Department of Gastrointestinal Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhidan Hong
- Dapartment of Reproductive Medicine Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yihang Pan
- Precision Medicine Center, Scientific Research Center, School of Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Yuqin Yang
- Department of Laboratory Animal Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haixiang Sun
- Reproductive Medical Center, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
| | - Gang Cao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.
- College of Bio-Medicine and Health, Huazhong Agricultural University, Wuhan, China.
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
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9
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Rautiainen M, Nurk S, Walenz BP, Logsdon GA, Porubsky D, Rhie A, Eichler EE, Phillippy AM, Koren S. Telomere-to-telomere assembly of diploid chromosomes with Verkko. Nat Biotechnol 2023; 41:1474-1482. [PMID: 36797493 PMCID: PMC10427740 DOI: 10.1038/s41587-023-01662-6] [Citation(s) in RCA: 90] [Impact Index Per Article: 90.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 01/03/2023] [Indexed: 02/18/2023]
Abstract
The Telomere-to-Telomere consortium recently assembled the first truly complete sequence of a human genome. To resolve the most complex repeats, this project relied on manual integration of ultra-long Oxford Nanopore sequencing reads with a high-resolution assembly graph built from long, accurate PacBio high-fidelity reads. We have improved and automated this strategy in Verkko, an iterative, graph-based pipeline for assembling complete, diploid genomes. Verkko begins with a multiplex de Bruijn graph built from long, accurate reads and progressively simplifies this graph by integrating ultra-long reads and haplotype-specific markers. The result is a phased, diploid assembly of both haplotypes, with many chromosomes automatically assembled from telomere to telomere. Running Verkko on the HG002 human genome resulted in 20 of 46 diploid chromosomes assembled without gaps at 99.9997% accuracy. The complete assembly of diploid genomes is a critical step towards the construction of comprehensive pangenome databases and chromosome-scale comparative genomics.
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Affiliation(s)
- Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Oxford Nanopore Technologies, Oxford, UK
| | - Brian P Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
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10
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Yi D, Nam JW, Jeong H. Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches. Brief Bioinform 2023; 24:bbad297. [PMID: 37587831 PMCID: PMC10516374 DOI: 10.1093/bib/bbad297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/05/2023] [Accepted: 07/23/2023] [Indexed: 08/18/2023] Open
Abstract
Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.
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Affiliation(s)
- Dohun Yi
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Jin-Wu Nam
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Research Institute for Convergence of Basic Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Bio-BigData Center, Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Hyobin Jeong
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Bio-BigData Center, Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
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11
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Hallast P, Ebert P, Loftus M, Yilmaz F, Audano PA, Logsdon GA, Bonder MJ, Zhou W, Höps W, Kim K, Li C, Hoyt SJ, Dishuck PC, Porubsky D, Tsetsos F, Kwon JY, Zhu Q, Munson KM, Hasenfeld P, Harvey WT, Lewis AP, Kordosky J, Hoekzema K, O'Neill RJ, Korbel JO, Tyler-Smith C, Eichler EE, Shi X, Beck CR, Marschall T, Konkel MK, Lee C. Assembly of 43 human Y chromosomes reveals extensive complexity and variation. Nature 2023; 621:355-364. [PMID: 37612510 PMCID: PMC10726138 DOI: 10.1038/s41586-023-06425-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 07/11/2023] [Indexed: 08/25/2023]
Abstract
The prevalence of highly repetitive sequences within the human Y chromosome has prevented its complete assembly to date1 and led to its systematic omission from genomic analyses. Here we present de novo assemblies of 43 Y chromosomes spanning 182,900 years of human evolution and report considerable diversity in size and structure. Half of the male-specific euchromatic region is subject to large inversions with a greater than twofold higher recurrence rate compared with all other chromosomes2. Ampliconic sequences associated with these inversions show differing mutation rates that are sequence context dependent, and some ampliconic genes exhibit evidence for concerted evolution with the acquisition and purging of lineage-specific pseudogenes. The largest heterochromatic region in the human genome, Yq12, is composed of alternating repeat arrays that show extensive variation in the number, size and distribution, but retain a 1:1 copy-number ratio. Finally, our data suggest that the boundary between the recombining pseudoautosomal region 1 and the non-recombining portions of the X and Y chromosomes lies 500 kb away from the currently established1 boundary. The availability of fully sequence-resolved Y chromosomes from multiple individuals provides a unique opportunity for identifying new associations of traits with specific Y-chromosomal variants and garnering insights into the evolution and function of complex regions of the human genome.
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Affiliation(s)
- Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Core Unit Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Mark Loftus
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC, USA
- Center for Human Genetics, Clemson University, Greenwood, SC, USA
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Peter A Audano
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marc Jan Bonder
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Weichen Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Wolfram Höps
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Kwondo Kim
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Chong Li
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Savannah J Hoyt
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Fotios Tsetsos
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Jee Young Kwon
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Patrick Hasenfeld
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Kordosky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Rachel J O'Neill
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- The University of Connecticut Health Center, Farmington, CT, USA
| | - Jan O Korbel
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | | | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Xinghua Shi
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- The University of Connecticut Health Center, Farmington, CT, USA
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Miriam K Konkel
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC, USA
- Center for Human Genetics, Clemson University, Greenwood, SC, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
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12
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Xie H, Li W, Guo Y, Su X, Chen K, Wen L, Tang F. Long-read-based single sperm genome sequencing for chromosome-wide haplotype phasing of both SNPs and SVs. Nucleic Acids Res 2023; 51:8020-8034. [PMID: 37351613 PMCID: PMC10450174 DOI: 10.1093/nar/gkad532] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 06/01/2023] [Accepted: 06/09/2023] [Indexed: 06/24/2023] Open
Abstract
Although localized haploid phasing can be achieved using long read genome sequencing without parental data, reliable chromosome-scale phasing remains a great challenge. Given that sperm is a natural haploid cell, single-sperm genome sequencing can provide a chromosome-wide phase signal. Due to the limitation of read length, current short-read-based single-sperm genome sequencing methods can only achieve SNP haplotyping and come with difficulties in detecting and haplotyping structural variations (SVs) in complex genomic regions. To overcome these limitations, we developed a long-read-based single-sperm genome sequencing method and a corresponding data analysis pipeline that can accurately identify crossover events and chromosomal level aneuploidies in single sperm and efficiently detect SVs within individual sperm cells. Importantly, without parental genome information, our method can accurately conduct de novo phasing of heterozygous SVs as well as SNPs from male individuals at the whole chromosome scale. The accuracy for phasing of SVs was as high as 98.59% using 100 single sperm cells, and the accuracy for phasing of SNPs was as high as 99.95%. Additionally, our method reliably enabled deduction of the repeat expansions of haplotype-resolved STRs/VNTRs in single sperm cells. Our method provides a new opportunity for studying haplotype-related genetics in mammals.
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Affiliation(s)
- Haoling Xie
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
- Changping Laboratory, Changping Laboratory, Yard 28, Science Park Road, Changping District, Beijing 102206, China
| | - Wen Li
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Yuqing Guo
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Xinjie Su
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Kexuan Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Lu Wen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
| | - Fuchou Tang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Beijing Advanced Innovation Center for Genomics (ICG), Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China
- Changping Laboratory, Changping Laboratory, Yard 28, Science Park Road, Changping District, Beijing 102206, China
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13
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Abstract
DNA sequencing has revolutionized medicine over recent decades. However, analysis of large structural variation and repetitive DNA, a hallmark of human genomes, has been limited by short-read technology, with read lengths of 100-300 bp. Long-read sequencing (LRS) permits routine sequencing of human DNA fragments tens to hundreds of kilobase pairs in size, using both real-time sequencing by synthesis and nanopore-based direct electronic sequencing. LRS permits analysis of large structural variation and haplotypic phasing in human genomes and has enabled the discovery and characterization of rare pathogenic structural variants and repeat expansions. It has also recently enabled the assembly of a complete, gapless human genome that includes previously intractable regions, such as highly repetitive centromeres and homologous acrocentric short arms. With the addition of protocols for targeted enrichment, direct epigenetic DNA modification detection, and long-range chromatin profiling, LRS promises to launch a new era of understanding of genetic diversity and pathogenic mutations in human populations.
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Affiliation(s)
- Peter E Warburton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; ,
- Center for Advanced Genomics Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert P Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; ,
- Center for Advanced Genomics Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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14
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Soto DC, Uribe-Salazar JM, Shew CJ, Sekar A, McGinty S, Dennis MY. Genomic structural variation: A complex but important driver of human evolution. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023; 181 Suppl 76:118-144. [PMID: 36794631 PMCID: PMC10329998 DOI: 10.1002/ajpa.24713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 01/21/2023] [Accepted: 02/05/2023] [Indexed: 02/17/2023]
Abstract
Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.
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Affiliation(s)
- Daniela C. Soto
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - José M. Uribe-Salazar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Aarthi Sekar
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Sean McGinty
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA, USA
- Integrative Genetics and Genomics Graduate Group, University of California, Davis, CA, USA
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15
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Shinde SS, Sharma A, Vijay N. Decoding the fibromelanosis locus complex chromosomal rearrangement of black-bone chicken: genetic differentiation, selective sweeps and protein-coding changes in Kadaknath chicken. Front Genet 2023; 14:1180658. [PMID: 37424723 PMCID: PMC10325862 DOI: 10.3389/fgene.2023.1180658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/05/2023] [Indexed: 07/11/2023] Open
Abstract
Black-bone chicken (BBC) meat is popular for its distinctive taste and texture. A complex chromosomal rearrangement at the fibromelanosis (Fm) locus on the 20th chromosome results in increased endothelin-3 (EDN3) gene expression and is responsible for melanin hyperpigmentation in BBC. We use public long-read sequencing data of the Silkie breed to resolve high-confidence haplotypes at the Fm locus spanning both Dup1 and Dup2 regions and establish that the Fm_2 scenario is correct of the three possible scenarios of the complex chromosomal rearrangement. The relationship between Chinese and Korean BBC breeds with Kadaknath native to India is underexplored. Our data from whole-genome re-sequencing establish that all BBC breeds, including Kadaknath, share the complex chromosomal rearrangement junctions at the fibromelanosis (Fm) locus. We also identify two Fm locus proximal regions (∼70 Kb and ∼300 Kb) with signatures of selection unique to Kadaknath. These regions harbor several genes with protein-coding changes, with the bactericidal/permeability-increasing-protein-like gene having two Kadaknath-specific changes within protein domains. Our results indicate that protein-coding changes in the bactericidal/permeability-increasing-protein-like gene hitchhiked with the Fm locus in Kadaknath due to close physical linkage. Identifying this Fm locus proximal selective sweep sheds light on the genetic distinctiveness of Kadaknath compared to other BBC.
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Affiliation(s)
| | | | - Nagarjun Vijay
- Computational Evolutionary Genomics Lab, Department of Biological Sciences, IISER Bhopal, Bhauri, Madhya Pradesh, India
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16
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Logsdon GA, Rozanski AN, Ryabov F, Potapova T, Shepelev VA, Mao Y, Rautiainen M, Koren S, Nurk S, Porubsky D, Lucas JK, Hoekzema K, Munson KM, Gerton JL, Phillippy AM, Alexandrov IA, Eichler EE. The variation and evolution of complete human centromeres. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.30.542849. [PMID: 37398417 PMCID: PMC10312506 DOI: 10.1101/2023.05.30.542849] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
We completely sequenced and assembled all centromeres from a second human genome and used two reference sets to benchmark genetic, epigenetic, and evolutionary variation within centromeres from a diversity panel of humans and apes. We find that centromere single-nucleotide variation can increase by up to 4.1-fold relative to other genomic regions, with the caveat that up to 45.8% of centromeric sequence, on average, cannot be reliably aligned with current methods due to the emergence of new α-satellite higher-order repeat (HOR) structures and two to threefold differences in the length of the centromeres. The extent to which this occurs differs depending on the chromosome and haplotype. Comparing the two sets of complete human centromeres, we find that eight harbor distinctly different α-satellite HOR array structures and four contain novel α-satellite HOR variants in high abundance. DNA methylation and CENP-A chromatin immunoprecipitation experiments show that 26% of the centromeres differ in their kinetochore position by at least 500 kbp-a property not readily associated with novel α-satellite HORs. To understand evolutionary change, we selected six chromosomes and sequenced and assembled 31 orthologous centromeres from the common chimpanzee, orangutan, and macaque genomes. Comparative analyses reveal nearly complete turnover of α-satellite HORs, but with idiosyncratic changes in structure characteristic to each species. Phylogenetic reconstruction of human haplotypes supports limited to no recombination between the p- and q-arms of human chromosomes and reveals that novel α-satellite HORs share a monophyletic origin, providing a strategy to estimate the rate of saltatory amplification and mutation of human centromeric DNA.
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Affiliation(s)
- Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Allison N. Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Fedor Ryabov
- Masters Program in National Research University Higher School of Economics, Moscow, Russia
| | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | | | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Julian K. Lucas
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M. Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ivan A. Alexandrov
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
- Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Dan David Center for Human Evolution and Biohistory Research, Tel Aviv University, Tel Aviv, Israel
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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17
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Chamorro González R, Conrad T, Stöber MC, Xu R, Giurgiu M, Rodriguez-Fos E, Kasack K, Brückner L, van Leen E, Helmsauer K, Dorado Garcia H, Stefanova ME, Hung KL, Bei Y, Schmelz K, Lodrini M, Mundlos S, Chang HY, Deubzer HE, Sauer S, Eggert A, Schulte JH, Schwarz RF, Haase K, Koche RP, Henssen AG. Parallel sequencing of extrachromosomal circular DNAs and transcriptomes in single cancer cells. Nat Genet 2023; 55:880-890. [PMID: 37142849 PMCID: PMC10181933 DOI: 10.1038/s41588-023-01386-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 03/28/2023] [Indexed: 05/06/2023]
Abstract
Extrachromosomal DNAs (ecDNAs) are common in cancer, but many questions about their origin, structural dynamics and impact on intratumor heterogeneity are still unresolved. Here we describe single-cell extrachromosomal circular DNA and transcriptome sequencing (scEC&T-seq), a method for parallel sequencing of circular DNAs and full-length mRNA from single cells. By applying scEC&T-seq to cancer cells, we describe intercellular differences in ecDNA content while investigating their structural heterogeneity and transcriptional impact. Oncogene-containing ecDNAs were clonally present in cancer cells and drove intercellular oncogene expression differences. In contrast, other small circular DNAs were exclusive to individual cells, indicating differences in their selection and propagation. Intercellular differences in ecDNA structure pointed to circular recombination as a mechanism of ecDNA evolution. These results demonstrate scEC&T-seq as an approach to systematically characterize both small and large circular DNA in cancer cells, which will facilitate the analysis of these DNA elements in cancer and beyond.
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Affiliation(s)
- Rocío Chamorro González
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Thomas Conrad
- Genomics Technology Platform, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Maja C Stöber
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Charité-Universitätsmedizin Berlin, Berlin, Germany
- Faculty of Life Science, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Robin Xu
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Mădălina Giurgiu
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
- Freie Universität Berlin, Berlin, Germany
| | - Elias Rodriguez-Fos
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Katharina Kasack
- Fraunhofer Institute for Cell Therapy and Immunology, Branch Bioanalytics and Bioprocesses IZI-BB, Potsdam, Germany
| | - Lotte Brückner
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
- Max-Delbrück-Centrum für Molekulare Medizin, Berlin, Germany
| | - Eric van Leen
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Konstantin Helmsauer
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Heathcliff Dorado Garcia
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Maria E Stefanova
- RG Development and Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - King L Hung
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
| | - Yi Bei
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
| | - Karin Schmelz
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marco Lodrini
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stefan Mundlos
- RG Development and Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Institute for Medical Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin-Brandenburg Center for Regenerative Therapies, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Hedwig E Deubzer
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
- German Cancer Consortium, partner site Berlin, and German Cancer Research Center, Heidelberg, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Sascha Sauer
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Angelika Eggert
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- German Cancer Consortium, partner site Berlin, and German Cancer Research Center, Heidelberg, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Johannes H Schulte
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- German Cancer Consortium, partner site Berlin, and German Cancer Research Center, Heidelberg, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Roland F Schwarz
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Institute for Computational Cancer Biology, Center for Integrated Oncology, Cancer Research Center Cologne Essen Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
| | - Kerstin Haase
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany
- German Cancer Consortium, partner site Berlin, and German Cancer Research Center, Heidelberg, Germany
| | - Richard P Koche
- Center for Epigenetics Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anton G Henssen
- Department of Pediatric Oncology and Hematology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
- Experimental and Clinical Research Center of the MDC and Charité Berlin, Berlin, Germany.
- Max-Delbrück-Centrum für Molekulare Medizin, Berlin, Germany.
- German Cancer Consortium, partner site Berlin, and German Cancer Research Center, Heidelberg, Germany.
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18
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Porubsky D, Harvey WT, Rozanski AN, Ebler J, Höps W, Ashraf H, Hasenfeld P, Paten B, Sanders AD, Marschall T, Korbel JO, Eichler EE. Inversion polymorphism in a complete human genome assembly. Genome Biol 2023; 24:100. [PMID: 37122002 PMCID: PMC10150506 DOI: 10.1186/s13059-023-02919-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/31/2023] [Indexed: 05/02/2023] Open
Abstract
The telomere-to-telomere (T2T) complete human reference has significantly improved our ability to characterize genome structural variation. To understand its impact on inversion polymorphisms, we remapped data from 41 genomes against the T2T reference genome and compared it to the GRCh38 reference. We find a ~ 21% increase in sensitivity improving mapping of 63 inversions on the T2T reference. We identify 26 misorientations within GRCh38 and show that the T2T reference is three times more likely to represent the correct orientation of the major human allele. Analysis of 10 additional samples reveals novel rare inversions at chromosomes 15q25.2, 16p11.2, 16q22.1-23.1, and 22q11.21.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Jana Ebler
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Hufsah Ashraf
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Helmholtz Association, 10115, Berlin, Germany
- Berlin Institute of Health (BIH), 10178, Berlin, Germany
- Charité-Universitätsmedizin, 10117, Berlin, Germany
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117, Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, 98195, USA.
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19
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Hunt JMT, Samson CA, Rand AD, Sheppard HM. Unintended CRISPR-Cas9 editing outcomes: a review of the detection and prevalence of structural variants generated by gene-editing in human cells. Hum Genet 2023; 142:705-720. [PMID: 37093294 PMCID: PMC10182114 DOI: 10.1007/s00439-023-02561-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/13/2023] [Indexed: 04/25/2023]
Abstract
Genome editing using the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) gene-editing system (CRISPR-Cas) is a valuable tool for fundamental and applied research applications. Significant improvements in editing efficacy have advanced genome editing strategies into phase 3 human clinical trials. However, recent studies suggest that our understanding of editing outcomes has lagged behind the developments made in generating the edits themselves. While many researchers have analyzed on- and off-target events through the lens of small insertions or deletions at predicted sites, screens for larger structural variants (SVs) and chromosomal abnormalities are not routinely performed. Full and comprehensive validation of on- and off-target effects is required to ensure reproducibility and to accurately assess the safety of future editing applications. Here we review SVs associated with CRISPR-editing in cells of human origin and highlight the methods used to detect and avoid them.
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Affiliation(s)
| | | | - Alex du Rand
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Hilary M Sheppard
- School of Biological Sciences, University of Auckland, Auckland, New Zealand.
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20
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Olson ND, Wagner J, Dwarshuis N, Miga KH, Sedlazeck FJ, Salit M, Zook JM. Variant calling and benchmarking in an era of complete human genome sequences. Nat Rev Genet 2023:10.1038/s41576-023-00590-0. [PMID: 37059810 DOI: 10.1038/s41576-023-00590-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2023] [Indexed: 04/16/2023]
Abstract
Genetic variant calling from DNA sequencing has enabled understanding of germline variation in hundreds of thousands of humans. Sequencing technologies and variant-calling methods have advanced rapidly, routinely providing reliable variant calls in most of the human genome. We describe how advances in long reads, deep learning, de novo assembly and pangenomes have expanded access to variant calls in increasingly challenging, repetitive genomic regions, including medically relevant regions, and how new benchmark sets and benchmarking methods illuminate their strengths and limitations. Finally, we explore the possible future of more complete characterization of human genome variation in light of the recent completion of a telomere-to-telomere human genome reference assembly and human pangenomes, and we consider the innovations needed to benchmark their newly accessible repetitive regions and complex variants.
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Affiliation(s)
- Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan Dwarshuis
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Fritz J Sedlazeck
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | | | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
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21
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Wang D, Liu B, Zhang Z. Accelerating the understanding of cancer biology through the lens of genomics. Cell 2023; 186:1755-1771. [PMID: 37059071 DOI: 10.1016/j.cell.2023.02.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 01/11/2023] [Accepted: 02/08/2023] [Indexed: 04/16/2023]
Abstract
A core mission of cancer genomics is to comprehensively chart molecular underpinnings of cancer-driving events and to provide personalized therapeutic strategies. Primarily focused on cancer cells, cancer genomics studies have successfully uncovered many drivers for major cancer types. Since the emergence of cancer immune evasion as a critical cancer hallmark, the paradigm has been elevated to the holistic tumor ecosystem, with distinct cellular components and their functional states elucidated. We highlight the milestones of cancer genomics, depict the evolving path of the field, and discuss future directions in completing the understanding of the tumor ecosystem and in advancing therapeutic strategies.
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Affiliation(s)
- Dongfang Wang
- Biomedical Pioneering Innovative Center and School of Life Sciences, Peking University, Beijing 100871, China
| | - Baolin Liu
- Biomedical Pioneering Innovative Center and School of Life Sciences, Peking University, Beijing 100871, China
| | - Zemin Zhang
- Biomedical Pioneering Innovative Center and School of Life Sciences, Peking University, Beijing 100871, China; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Changping Laboratory, Beijing, China.
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22
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Porubsky D, Vollger MR, Harvey WT, Rozanski AN, Ebert P, Hickey G, Hasenfeld P, Sanders AD, Stober C, Korbel JO, Paten B, Marschall T, Eichler EE. Gaps and complex structurally variant loci in phased genome assemblies. Genome Res 2023; 33:496-510. [PMID: 37164484 PMCID: PMC10234299 DOI: 10.1101/gr.277334.122] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 12/07/2022] [Indexed: 05/12/2023]
Abstract
There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Allison N Rozanski
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, 40225 Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Glenn Hickey
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, California 95064, USA
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
- Berlin Institute of Health (BIH), 10178 Berlin, Germany
- Charité-Universitätsmedizin, 10117 Berlin, Germany
| | - Catherine Stober
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, California 95064, USA
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, 40225 Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA;
- Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA
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23
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A non-genetic switch triggers alternative telomere lengthening and cellular immortalization in ATRX deficient cells. Nat Commun 2023; 14:939. [PMID: 36805596 PMCID: PMC9941109 DOI: 10.1038/s41467-023-36294-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 01/25/2023] [Indexed: 02/22/2023] Open
Abstract
Alternative Lengthening of Telomeres (ALT) is an aberrant DNA recombination pathway which grants replicative immortality to approximately 10% of all cancers. Despite this high prevalence of ALT in cancer, the mechanism and genetics by which cells activate this pathway remain incompletely understood. A major challenge in dissecting the events that initiate ALT is the extremely low frequency of ALT induction in human cell systems. Guided by the genetic lesions that have been associated with ALT from cancer sequencing studies, we genetically engineered primary human pluripotent stem cells to deterministically induce ALT upon differentiation. Using this genetically defined system, we demonstrate that disruption of the p53 and Rb pathways in combination with ATRX loss-of-function is sufficient to induce all hallmarks of ALT and results in functional immortalization in a cell type-specific manner. We further demonstrate that ALT can be induced in the presence of telomerase, is neither dependent on telomere shortening nor crisis, but is rather driven by continuous telomere instability triggered by the induction of differentiation in ATRX-deficient stem cells.
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24
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Abstract
Dense local haplotypes can now readily be extracted from long-read or droplet-based sequence data. However, these methods struggle to combine subchromosomal haplotype blocks into global chromosome-length haplotypes. Strand-seq is a single cell sequencing technique that uses read orientation to capture sparse global phase information by sequencing only one of two DNA strands for each parental homolog. In combination with dense local haplotypes from other technologies, Strand-seq data can be used to obtain complete chromosome-length phase information. In this chapter, we run the R package StrandPhaseR to phase SNVs using publicly available sequence data for sample HG005 of the Genome in a Bottle project.
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Affiliation(s)
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
| | - Peter M Lansdorp
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
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25
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Athanasopoulou K, Daneva GN, Boti MA, Dimitroulis G, Adamopoulos PG, Scorilas A. The Transition from Cancer "omics" to "epi-omics" through Next- and Third-Generation Sequencing. LIFE (BASEL, SWITZERLAND) 2022; 12:life12122010. [PMID: 36556377 PMCID: PMC9785810 DOI: 10.3390/life12122010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 11/25/2022] [Accepted: 11/30/2022] [Indexed: 12/05/2022]
Abstract
Deciphering cancer etiopathogenesis has proven to be an especially challenging task since the mechanisms that drive tumor development and progression are far from simple. An astonishing amount of research has revealed a wide spectrum of defects, including genomic abnormalities, epigenomic alterations, disturbance of gene transcription, as well as post-translational protein modifications, which cooperatively promote carcinogenesis. These findings suggest that the adoption of a multidimensional approach can provide a much more precise and comprehensive picture of the tumor landscape, hence serving as a powerful tool in cancer research and precision oncology. The introduction of next- and third-generation sequencing technologies paved the way for the decoding of genetic information and the elucidation of cancer-related cellular compounds and mechanisms. In the present review, we discuss the current and emerging applications of both generations of sequencing technologies, also referred to as massive parallel sequencing (MPS), in the fields of cancer genomics, transcriptomics and proteomics, as well as in the progressing realms of epi-omics. Finally, we provide a brief insight into the expanding scope of sequencing applications in personalized cancer medicine and pharmacogenomics.
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26
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Jeong H, Grimes K, Rauwolf KK, Bruch PM, Rausch T, Hasenfeld P, Benito E, Roider T, Sabarinathan R, Porubsky D, Herbst SA, Erarslan-Uysal B, Jann JC, Marschall T, Nowak D, Bourquin JP, Kulozik AE, Dietrich S, Bornhauser B, Sanders AD, Korbel JO. Functional analysis of structural variants in single cells using Strand-seq. Nat Biotechnol 2022:10.1038/s41587-022-01551-4. [PMID: 36424487 DOI: 10.1038/s41587-022-01551-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 10/07/2022] [Indexed: 11/27/2022]
Abstract
Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We present a computational method, scNOVA, which uses Strand-seq to perform haplotype-aware integration of SV discovery and molecular phenotyping in single cells by using nucleosome occupancy to infer gene expression as a readout. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation, and consequences of SVs on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T cell acute lymphoblastic leukemia, which revealed c-Myb activation, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture, using a Notch inhibitor. By directly linking SVs to their functional effects, scNOVA enables systematic single-cell multiomic studies of structural variation in heterogeneous cell populations.
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Affiliation(s)
- Hyobin Jeong
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.,Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul, Republic of Korea
| | - Karen Grimes
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.,Faculty of Biosciences, EMBL and Heidelberg University, Heidelberg, Germany
| | - Kerstin K Rauwolf
- Division of Pediatric Oncology, University Children's Hospital, Zürich, Switzerland
| | - Peter-Martin Bruch
- Department of Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.,Department of Hematology and Oncology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Tobias Rausch
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
| | - Patrick Hasenfeld
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Eva Benito
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Tobias Roider
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.,Department of Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
| | | | - David Porubsky
- Center for Bioinformatics, Saarland University, Saarbrücken, Germany.,Max Planck Institute for Informatics, Saarbrücken, Germany.,Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sophie A Herbst
- Department of Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany
| | - Büşra Erarslan-Uysal
- Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.,Department of Pediatric Oncology, Hematology, and Immunology, University of Heidelberg and Hopp Children's Cancer Center, Heidelberg, Germany
| | - Johann-Christoph Jann
- Department of Hematology and Oncology, Medical Faculty Mannheim of the Heidelberg University, Heidelberg, Germany
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Daniel Nowak
- Department of Hematology and Oncology, Medical Faculty Mannheim of the Heidelberg University, Heidelberg, Germany
| | - Jean-Pierre Bourquin
- Division of Pediatric Oncology, University Children's Hospital, Zürich, Switzerland
| | - Andreas E Kulozik
- Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.,Department of Pediatric Oncology, Hematology, and Immunology, University of Heidelberg and Hopp Children's Cancer Center, Heidelberg, Germany
| | - Sascha Dietrich
- Department of Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.,Department of Hematology and Oncology, University Hospital Düsseldorf, Düsseldorf, Germany.,Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Beat Bornhauser
- Division of Pediatric Oncology, University Children's Hospital, Zürich, Switzerland
| | - Ashley D Sanders
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany. .,Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany. .,Berlin Institute of Health (BIH), Berlin, Germany. .,Charité-Universitätsmedizin, Berlin, Germany.
| | - Jan O Korbel
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany. .,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany. .,Bridging Research Division on Mechanisms of Genomic Variation and Data Science, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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27
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Sister chromatid exchanges induced by perturbed replication can form independently of BRCA1, BRCA2 and RAD51. Nat Commun 2022; 13:6722. [PMID: 36344511 PMCID: PMC9640580 DOI: 10.1038/s41467-022-34519-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 10/27/2022] [Indexed: 11/09/2022] Open
Abstract
Sister chromatid exchanges (SCEs) are products of joint DNA molecule resolution, and are considered to form through homologous recombination (HR). Indeed, SCE induction upon irradiation requires the canonical HR factors BRCA1, BRCA2 and RAD51. In contrast, replication-blocking agents, including PARP inhibitors, induce SCEs independently of BRCA1, BRCA2 and RAD51. PARP inhibitor-induced SCEs are enriched at difficult-to-replicate genomic regions, including common fragile sites (CFSs). PARP inhibitor-induced replication lesions are transmitted into mitosis, suggesting that SCEs can originate from mitotic processing of under-replicated DNA. Proteomics analysis reveals mitotic recruitment of DNA polymerase theta (POLQ) to synthetic DNA ends. POLQ inactivation results in reduced SCE numbers and severe chromosome fragmentation upon PARP inhibition in HR-deficient cells. Accordingly, analysis of CFSs in cancer genomes reveals frequent allelic deletions, flanked by signatures of POLQ-mediated repair. Combined, we show PARP inhibition generates under-replicated DNA, which is processed into SCEs during mitosis, independently of canonical HR factors.
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28
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Downes DJ, Hughes JR. Natural and Experimental Rewiring of Gene Regulatory Regions. Annu Rev Genomics Hum Genet 2022; 23:73-97. [PMID: 35472292 DOI: 10.1146/annurev-genom-112921-010715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The successful development and ongoing functioning of complex organisms depend on the faithful execution of the genetic code. A critical step in this process is the correct spatial and temporal expression of genes. The highly orchestrated transcription of genes is controlled primarily by cis-regulatory elements: promoters, enhancers, and insulators. The medical importance of this key biological process can be seen by the frequency with which mutations and inherited variants that alter cis-regulatory elements lead to monogenic and complex diseases and cancer. Here, we provide an overview of the methods available to characterize and perturb gene regulatory circuits. We then highlight mechanisms through which regulatory rewiring contributes to disease, and conclude with a perspective on how our understanding of gene regulation can be used to improve human health.
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Affiliation(s)
- Damien J Downes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;
| | - Jim R Hughes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;
- MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;
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29
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Hamdan A, Ewing A. Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis. J Pathol 2022; 257:479-493. [PMID: 35355264 PMCID: PMC9321913 DOI: 10.1002/path.5901] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/16/2022] [Accepted: 03/28/2022] [Indexed: 11/15/2022]
Abstract
Structural variants (SVs) represent a major source of aberration in tumour genomes. Given the diversity in the size and type of SVs present in tumours, the accurate detection and interpretation of SVs in tumours is challenging. New classes of complex structural events in tumours are discovered frequently, and the definitions of the genomic consequences of complex events are constantly being refined. Detailed analyses of short-read whole-genome sequencing (WGS) data from large tumour cohorts facilitate the interrogation of SVs at orders of magnitude greater scale and depth. However, the inherent technical limitations of short-read WGS prevent us from accurately detecting and investigating the impact of all the SVs present in tumours. The expanded use of long-read WGS will be critical for improving the accuracy of SV detection, and in fully resolving complex SV events, both of which are crucial for determining the impact of SVs on tumour progression and clinical outcome. Despite the present limitations, we demonstrate that SVs play an important role in tumourigenesis. In particular, SVs contribute significantly to late-stage tumour development and to intratumoural heterogeneity. The evolutionary trajectories of SVs represent a window into the clonal dynamics in tumours, a comprehensive understanding of which will be vital for influencing patient outcomes in the future. Recent findings have highlighted many clinical applications of SVs in cancer, from early detection to biomarkers for treatment response and prognosis. As the methods to detect and interpret SVs improve, elucidating the full breadth of the complex SV landscape and determining how these events modulate tumour evolution will improve our understanding of cancer biology and our ability to capitalise on the utility of SVs in the clinical management of cancer patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Alhafidz Hamdan
- MRC Human Genetics Unit, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
- Cancer Research UK Edinburgh Centre, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Ailith Ewing
- MRC Human Genetics Unit, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
- Cancer Research UK Edinburgh Centre, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
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30
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Porubsky D, Höps W, Ashraf H, Hsieh P, Rodriguez-Martin B, Yilmaz F, Ebler J, Hallast P, Maria Maggiolini FA, Harvey WT, Henning B, Audano PA, Gordon DS, Ebert P, Hasenfeld P, Benito E, Zhu Q, Lee C, Antonacci F, Steinrücken M, Beck CR, Sanders AD, Marschall T, Eichler EE, Korbel JO. Recurrent inversion polymorphisms in humans associate with genetic instability and genomic disorders. Cell 2022; 185:1986-2005.e26. [PMID: 35525246 PMCID: PMC9563103 DOI: 10.1016/j.cell.2022.04.017] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/14/2022] [Accepted: 04/08/2022] [Indexed: 12/13/2022]
Abstract
Unlike copy number variants (CNVs), inversions remain an underexplored genetic variation class. By integrating multiple genomic technologies, we discover 729 inversions in 41 human genomes. Approximately 85% of inversions <2 kbp form by twin-priming during L1 retrotransposition; 80% of the larger inversions are balanced and affect twice as many nucleotides as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or retrotransposons. Since flanking repeats promote non-allelic homologous recombination, we developed complementary approaches to identify recurrent inversion formation. We describe 40 recurrent inversions encompassing 0.6% of the genome, showing inversion rates up to 2.7 × 10-4 per locus per generation. Recurrent inversions exhibit a sex-chromosomal bias and co-localize with genomic disorder critical regions. We propose that inversion recurrence results in an elevated number of heterozygous carriers and structural SD diversity, which increases mutability in the population and predisposes specific haplotypes to disease-causing CNVs.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Hufsah Ashraf
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Bernardo Rodriguez-Martin
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Jana Ebler
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Flavia Angela Maria Maggiolini
- Department of Biology, University of Bari "Aldo Moro", 70125 Bari, Italy; Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria-Centro di Ricerca Viticoltura ed Enologia (CREA-VE), Via Casamassima 148, 70010 Turi, Italy
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Barbara Henning
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Peter Ebert
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Eva Benito
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | | | - Matthias Steinrücken
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA; Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA; The University of Connecticut Health Center, 400 Farmington Rd., Farmington, CT 06032, USA
| | - Ashley D Sanders
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany; Charité-Universitätsmedizin, Berlin, Berlin, Germany
| | - Tobias Marschall
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, 40225 Düsseldorf, Germany.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstr. 1, 69117 Heidelberg, Germany; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
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31
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Hamadeh Z, Hanlon V, Lansdorp PM. Mapping of sister chromatid exchange events and genome alterations in single cells. Methods 2022; 204:64-72. [PMID: 35483548 DOI: 10.1016/j.ymeth.2022.04.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 04/08/2022] [Accepted: 04/22/2022] [Indexed: 12/14/2022] Open
Abstract
Mammalian genomes encode over a hundred different helicases, many of which are implicated in the repair of DNA lesions by acting on DNA structures arising during DNA replication, recombination or transcription. Defining the in vivo substrates of such DNA helicases is a major challenge given the large number of helicases in the genome, the breadth of potential substrates in the genome and the degree of genetic pleiotropy among DNA helicases in resolving diverse substrates. Helicases such as WRN, BLM and RECQL5 are implicated in the resolution of error-free recombination events known as sister chromatid exchange events (SCEs). Single cell Strand-seq can be used to map the genomic location of individual SCEs at a resolution that exceeds that of classical cytogenetic techniques by several orders of magnitude. By mapping the genomic locations of SCEs in the absence of different helicases, it should in principle be possible to infer the substrate specificity of specific helicases. Here we describe how the genome can be interrogated for such DNA repair events using single-cell template strand sequencing (Strand-seq) and bioinformatic tools. SCEs and copy-number alterations were mapped to genomic locations at kilobase resolution in haploid KBM7 cells. Strategies, possibilities, and limitations of Strand-seq to study helicase function are illustrated using these cells before and after CRISPR/Cas9 knock out of WRN, BLM and/or RECQL5.
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Affiliation(s)
- Zeid Hamadeh
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada; Department of Genome Science and Technology, University of British Columbia, Vancouver, BC, Canada
| | - Vincent Hanlon
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada
| | - Peter M Lansdorp
- Departments of Medical Genetics and Hematology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
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32
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Noyes MD, Harvey WT, Porubsky D, Sulovari A, Li R, Rose NR, Audano PA, Munson KM, Lewis AP, Hoekzema K, Mantere T, Graves-Lindsay TA, Sanders AD, Goodwin S, Kramer M, Mokrab Y, Zody MC, Hoischen A, Korbel JO, McCombie WR, Eichler EE. Familial long-read sequencing increases yield of de novo mutations. Am J Hum Genet 2022; 109:631-646. [PMID: 35290762 PMCID: PMC9069071 DOI: 10.1016/j.ajhg.2022.02.014] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/16/2022] [Indexed: 12/11/2022] Open
Abstract
Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.
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Affiliation(s)
- Michelle D Noyes
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Ruiyang Li
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Nicholas R Rose
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Tuomo Mantere
- Department of Human Genetics, Radboud University Medical Center, 6500 Nijmegen, the Netherlands; Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit and Biocenter Oulu, University of Oulu, 90220 Oulu, Finland
| | | | - Ashley D Sanders
- European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
| | - Sara Goodwin
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Melissa Kramer
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Younes Mokrab
- Department of Human Genetics, Sidra Medicine, PO Box 26999, Doha, Qatar; Weill Cornell Medicine, PO Box 24144, Doha, Qatar; College of Health and Life Sciences, Hamad Bin Khalifa University, PO Box 34110, Doha, Qatar
| | | | - Alexander Hoischen
- Department of Human Genetics, Radboud University Medical Center, 6500 Nijmegen, the Netherlands; Radboud Institute of Medical Life Sciences and Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6500 Nijmegen, the Netherlands
| | - Jan O Korbel
- European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
| | - W Richard McCombie
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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33
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Vollger MR, Guitart X, Dishuck PC, Mercuri L, Harvey WT, Gershman A, Diekhans M, Sulovari A, Munson KM, Lewis AP, Hoekzema K, Porubsky D, Li R, Nurk S, Koren S, Miga KH, Phillippy AM, Timp W, Ventura M, Eichler EE. Segmental duplications and their variation in a complete human genome. Science 2022; 376:eabj6965. [PMID: 35357917 PMCID: PMC8979283 DOI: 10.1126/science.abj6965] [Citation(s) in RCA: 104] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Despite their importance in disease and evolution, highly identical segmental duplications (SDs) are among the last regions of the human reference genome (GRCh38) to be fully sequenced. Using a complete telomere-to-telomere human genome (T2T-CHM13), we present a comprehensive view of human SD organization. SDs account for nearly one-third of the additional sequence, increasing the genome-wide estimate from 5.4 to 7.0% [218 million base pairs (Mbp)]. An analysis of 268 human genomes shows that 91% of the previously unresolved T2T-CHM13 SD sequence (68.3 Mbp) better represents human copy number variation. Comparing long-read assemblies from human (n = 12) and nonhuman primate (n = 5) genomes, we systematically reconstruct the evolution and structural haplotype diversity of biomedically relevant and duplicated genes. This analysis reveals patterns of structural heterozygosity and evolutionary differences in SD organization between humans and other primates.
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Affiliation(s)
- Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Xavi Guitart
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ludovica Mercuri
- Department of Biology, University of Bari, Aldo Moro, Bari 70125, Italy
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ruiyang Li
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Mario Ventura
- Department of Biology, University of Bari, Aldo Moro, Bari 70125, Italy
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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34
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Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, Alonge M, Antonarakis SE, Borchers M, Bouffard GG, Brooks SY, Caldas GV, Chen NC, Cheng H, Chin CS, Chow W, de Lima LG, Dishuck PC, Durbin R, Dvorkina T, Fiddes IT, Formenti G, Fulton RS, Fungtammasan A, Garrison E, Grady PG, Graves-Lindsay TA, Hall IM, Hansen NF, Hartley GA, Haukness M, Howe K, Hunkapiller MW, Jain C, Jain M, Jarvis ED, Kerpedjiev P, Kirsche M, Kolmogorov M, Korlach J, Kremitzki M, Li H, Maduro VV, Marschall T, McCartney AM, McDaniel J, Miller DE, Mullikin JC, Myers EW, Olson ND, Paten B, Peluso P, Pevzner PA, Porubsky D, Potapova T, Rogaev EI, Rosenfeld JA, Salzberg SL, Schneider VA, Sedlazeck FJ, Shafin K, Shew CJ, Shumate A, Sims Y, Smit AFA, Soto DC, Sović I, Storer JM, Streets A, Sullivan BA, Thibaud-Nissen F, Torrance J, Wagner J, Walenz BP, Wenger A, Wood JMD, Xiao C, Yan SM, Young AC, Zarate S, Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O’Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM. The complete sequence of a human genome. Science 2022; 376:44-53. [PMID: 35357919 PMCID: PMC9186530 DOI: 10.1126/science.abj6987] [Citation(s) in RCA: 1097] [Impact Index Per Article: 548.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.
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Affiliation(s)
- Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego; La Jolla, CA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Nicolas Altemose
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
| | - Lev Uralsky
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Michael Alonge
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | | | | | - Gerard G. Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Shelise Y. Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | | | | | | | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Richard Durbin
- Wellcome Sanger Institute; Cambridge, UK
- Department of Genetics, University of Cambridge; Cambridge, UK
| | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | | | - Giulio Formenti
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Robert S. Fulton
- Department of Genetics, Washington University School of Medicine; St. Louis, MO, USA
| | | | - Erik Garrison
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- University of Tennessee Health Science Center; Memphis, TN, USA
| | - Patrick G.S. Grady
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | | | - Ira M. Hall
- Department of Genetics, Yale University School of Medicine; New Haven, CT, USA
| | - Nancy F. Hansen
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | | | - Chirag Jain
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
- Department of Computational and Data Sciences, Indian Institute of Science; Bangalore KA, India
| | - Miten Jain
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Erich D. Jarvis
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | | | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | | | - Milinn Kremitzki
- McDonnell Genome Institute, Washington University in St. Louis; St. Louis, MO, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | - Valerie V. Maduro
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Tobias Marschall
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics; Düsseldorf, Germany
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Jennifer McDaniel
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Danny E. Miller
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital; Seattle, WA, USA
| | - James C. Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Eugene W. Myers
- Max-Planck Institute of Molecular Cell Biology and Genetics; Dresden, Germany
| | - Nathan D. Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research; Kansas City, MO, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School; Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University; Moscow, Russia
| | | | - Steven L. Salzberg
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine; Houston TX, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Ying Sims
- Wellcome Sanger Institute; Cambridge, UK
| | | | - Daniela C. Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan Sović
- Pacific Biosciences; Menlo Park, CA, USA
- Digital BioLogic d.o.o.; Ivanić-Grad, Croatia
| | | | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
- Chan Zuckerberg Biohub; San Francisco, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine; Durham, NC, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | | | - Justin Wagner
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Brian P. Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Stephanie M. Yan
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Alice C. Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Urvashi Surti
- Department of Pathology, University of Pittsburgh; Pittsburgh, PA, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan A. Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences; Moscow, Russia
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research; Kansas City, MO, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical School; Kansas City, MO, USA
| | - Rachel J. O’Neill
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
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35
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Liu Z, Roberts R, Mercer TR, Xu J, Sedlazeck FJ, Tong W. Towards accurate and reliable resolution of structural variants for clinical diagnosis. Genome Biol 2022; 23:68. [PMID: 35241127 PMCID: PMC8892125 DOI: 10.1186/s13059-022-02636-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 02/15/2022] [Indexed: 12/17/2022] Open
Abstract
Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts.
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Affiliation(s)
- Zhichao Liu
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Ruth Roberts
- ApconiX, BioHub at Alderley Park, Alderley Edge, SK10 4TG, UK
- University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Timothy R Mercer
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
- Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Joshua Xu
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Weida Tong
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
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36
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Xie M, Yang L, Jiang C, Wu S, Luo C, Yang X, He L, Chen S, Deng T, Ye M, Yan J, Yang N. gcaPDA: a haplotype-resolved diploid assembler. BMC Bioinformatics 2022; 23:68. [PMID: 35164674 PMCID: PMC8842951 DOI: 10.1186/s12859-022-04591-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 01/29/2022] [Indexed: 11/13/2022] Open
Abstract
Background Generating chromosome-scale haplotype resolved assembly is important for functional studies. However, current de novo assemblers are either haploid assemblers that discard allelic information, or diploid assemblers that can only tackle genomes of low complexity. Results Here, Using robust programs, we build a diploid genome assembly pipeline called gcaPDA (gamete cells assisted Phased Diploid Assembler), which exploits haploid gamete cells to assist in resolving haplotypes. We demonstrate the effectiveness of gcaPDA based on simulated HiFi reads of maize genome which is highly heterozygous and repetitive, and real data from rice. Conclusions With applicability of coping with complex genomes and fewer restrictions on application than most of diploid assemblers, gcaPDA is likely to find broad applications in studies of eukaryotic genomes. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04591-4.
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Affiliation(s)
- Min Xie
- Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Linfeng Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.,Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Chenglin Jiang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Shenshen Wu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Cheng Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xin Yang
- Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Lijuan He
- Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Shixuan Chen
- Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Tianquan Deng
- Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Mingzhi Ye
- Guangdong Engineering Research Center of Plant and Animal Genomics, BGI Genomics, BGI-Shenzhen, Shenzhen, 518083, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.,Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Ning Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China. .,Hubei Hongshan Laboratory, Wuhan, 430070, China.
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37
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Hanlon VC, Chan DD, Hamadeh Z, Wang Y, Mattsson CA, Spierings DC, Coope RJ, Lansdorp PM. Construction of Strand-seq libraries in open nanoliter arrays. CELL REPORTS METHODS 2022; 2:100150. [PMID: 35474869 PMCID: PMC9017222 DOI: 10.1016/j.crmeth.2021.100150] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 10/22/2021] [Accepted: 12/17/2021] [Indexed: 12/22/2022]
Abstract
Single-cell Strand-seq generates directional genomic information to study DNA repair, assemble genomes, and map structural variation onto chromosome-length haplotypes. We report a nanoliter-volume, one-pot (OP) Strand-seq library preparation protocol in which reagents are added cumulatively, DNA purification steps are avoided, and enzymes are inactivated with a thermolabile protease. OP-Strand-seq libraries capture 10%-25% of the genome from a single-cell with reduced costs and increased throughput.
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Affiliation(s)
| | - Daniel D. Chan
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada
| | - Zeid Hamadeh
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada
| | - Yanni Wang
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada
| | | | - Diana C.J. Spierings
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, 9713 AV Groningen, the Netherlands
| | - Robin J.N. Coope
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada
| | - Peter M. Lansdorp
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC V5Z 1L3, Canada
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, 9713 AV Groningen, the Netherlands
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
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38
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Roberts ML, Kotchen TA, Pan X, Li Y, Yang C, Liu P, Wang T, Laud PW, Chelius TH, Munyura Y, Mattson DL, Liu Y, Cowley AW, Kidambi S, Liang M. Unique Associations of DNA Methylation Regions With 24-Hour Blood Pressure Phenotypes in Blacks. Hypertension 2022; 79:761-772. [PMID: 34994206 PMCID: PMC8917053 DOI: 10.1161/hypertensionaha.121.18584] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Epigenetic marks (eg, DNA methylation) may capture the effect of gene-environment interactions. DNA methylation is involved in blood pressure (BP) regulation and hypertension development; however, no studies have evaluated its relationship with 24-hour BP phenotypes (daytime, nighttime, and 24-hour average BPs). METHODS We examined the association of whole blood DNA methylation with 24-hour BP phenotypes and clinic BPs in a discovery cohort of 281 Blacks using reduced representation bisulfite sequencing. We developed a deep and region-specific methylation sequencing method, Bisulfite ULtrapLEx Targeted Sequencing and utilized it to validate our findings in a separate validation cohort (n=117). RESULTS Analysis of 38 215 DNA methylation regions (MRs), derived from 1 549 368 CpG sites across the genome, identified up to 72 regions that were significantly associated with 24-hour BP phenotypes. No MR was significantly associated with clinic BP. Two to 3 MRs were significantly associated with various 24-hour BP phenotypes after adjustment for age, sex, and body mass index. Together, these MRs explained up to 16.5% of the variance of 24-hour average BP, while age, sex, and BMI explained up to 11.0% of the variance. Analysis of one of the MRs in an independent cohort using Bisulfite ULtrapLEx Targeted Sequencing confirmed its association with 24-hour average BP phenotype. CONCLUSIONS We identified several MRs that explain a substantial portion of variances in 24-hour BP phenotypes, which might be excellent markers of cumulative effect of factors influencing 24-hour BP levels. The Bisulfite ULtrapLEx Targeted Sequencing workflow has potential to be suitable for clinical testing and population screenings on a large scale.
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Affiliation(s)
- Michelle L Roberts
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
| | - Theodore A Kotchen
- Department of Medicine, Medical College of Wisconsin, Milwaukee. (T.A.K., Y.M., S.K.)
| | - Xiaoqing Pan
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.).,Department of Mathematics, Shanghai Normal University, China (X.P.)
| | - Yingchuan Li
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.).,Department of Critical Care Medicine, Shanghai JiaoTong University affiliated the Sixth People's Hospital, China (Y.L.)
| | - Chun Yang
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
| | - Pengyuan Liu
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.).,The Sir Run Run Shaw Hospital, Institute of Translational Medicine, Zhejiang University, China (P.L.)
| | | | - Purushottam W Laud
- Division of Biostatistics, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee. (P.W.L.)
| | - Thomas H Chelius
- Division of Epidemiology, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee. (T.H.C.)
| | - Yannick Munyura
- Department of Medicine, Medical College of Wisconsin, Milwaukee. (T.A.K., Y.M., S.K.)
| | - David L Mattson
- Department of Physiology, Medical College of Georgia, Augusta (D.L.M.)
| | | | - Allen W Cowley
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
| | - Srividya Kidambi
- Department of Medicine, Medical College of Wisconsin, Milwaukee. (T.A.K., Y.M., S.K.)
| | - Mingyu Liang
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
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Trost B, Loureiro LO, Scherer SW. Discovery of genomic variation across a generation. Hum Mol Genet 2021; 30:R174-R186. [PMID: 34296264 PMCID: PMC8490016 DOI: 10.1093/hmg/ddab209] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/09/2021] [Accepted: 07/19/2021] [Indexed: 11/12/2022] Open
Abstract
Over the past 30 years (the timespan of a generation), advances in genomics technologies have revealed tremendous and unexpected variation in the human genome and have provided increasingly accurate answers to long-standing questions of how much genetic variation exists in human populations and to what degree the DNA complement changes between parents and offspring. Tracking the characteristics of these inherited and spontaneous (or de novo) variations has been the basis of the study of human genetic disease. From genome-wide microarray and next-generation sequencing scans, we now know that each human genome contains over 3 million single nucleotide variants when compared with the ~ 3 billion base pairs in the human reference genome, along with roughly an order of magnitude more DNA—approximately 30 megabase pairs (Mb)—being ‘structurally variable’, mostly in the form of indels and copy number changes. Additional large-scale variations include balanced inversions (average of 18 Mb) and complex, difficult-to-resolve alterations. Collectively, ~1% of an individual’s genome will differ from the human reference sequence. When comparing across a generation, fewer than 100 new genetic variants are typically detected in the euchromatic portion of a child’s genome. Driven by increasingly higher-resolution and higher-throughput sequencing technologies, newer and more accurate databases of genetic variation (for instance, more comprehensive structural variation data and phasing of combinations of variants along chromosomes) of worldwide populations will emerge to underpin the next era of discovery in human molecular genetics.
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Affiliation(s)
- Brett Trost
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Livia O Loureiro
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Stephen W Scherer
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada.,McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
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40
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Zhao X, Collins RL, Lee WP, Weber AM, Jun Y, Zhu Q, Weisburd B, Huang Y, Audano PA, Wang H, Walker M, Lowther C, Fu J, Gerstein MB, Devine SE, Marschall T, Korbel JO, Eichler EE, Chaisson MJP, Lee C, Mills RE, Brand H, Talkowski ME. Expectations and blind spots for structural variation detection from long-read assemblies and short-read genome sequencing technologies. Am J Hum Genet 2021; 108:919-928. [PMID: 33789087 PMCID: PMC8206509 DOI: 10.1016/j.ajhg.2021.03.014] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 03/12/2021] [Indexed: 12/13/2022] Open
Abstract
Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and medical genetic initiatives are reliant upon short-read whole-genome sequencing (srWGS), which presents challenges for the detection of structural variants (SVs) relative to emerging long-read WGS (lrWGS) technologies. Given this ubiquity of srWGS in large-scale genomics initiatives, we sought to establish expectations for routine SV detection from this data type by comparison with lrWGS assembly, as well as to quantify the genomic properties and added value of SVs uniquely accessible to each technology. Analyses from the Human Genome Structural Variation Consortium (HGSVC) of three families captured ~11,000 SVs per genome from srWGS and ~25,000 SVs per genome from lrWGS assembly. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplication (SD) and simple repeat (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of reference sequence, we observed extremely high (93.8%) concordance between technologies for deletions in these datasets. In contrast, lrWGS was superior for detection of insertions across all genomic contexts. Given that non-SD/SR sequences encompass 95.9% of currently annotated disease-associated exons, improved sensitivity from lrWGS to discover novel pathogenic deletions in these currently interpretable genomic regions is likely to be incremental. However, these analyses highlight the considerable added value of assembly-based lrWGS to create new catalogs of insertions and transposable elements, as well as disease-associated repeat expansions in genomic sequences that were previously recalcitrant to routine assessment.
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Affiliation(s)
- Xuefang Zhao
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Division of Medical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Wan-Ping Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Alexandra M Weber
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan Medical School, 1241 East Catherine Street, Ann Arbor, MI 48109, USA
| | - Yukyung Jun
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Ben Weisburd
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Yongqing Huang
- Data Sciences Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Harold Wang
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Mark Walker
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Chelsea Lowther
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jack Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Mark B Gerstein
- Yale University Medical School, Computational Biology and Bioinformatics Program, New Haven, CT 06520, USA
| | - Scott E Devine
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA; Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Mark J P Chaisson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Graduate Studies - Life Sciences, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, South Korea; Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an 710061, Shaanxi, People's Republic of China
| | - Ryan E Mills
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan Medical School, 1241 East Catherine Street, Ann Arbor, MI 48109, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Disorders, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Division of Medical Sciences, Harvard Medical School, Boston, MA 02115, USA.
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41
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Garg S. Computational methods for chromosome-scale haplotype reconstruction. Genome Biol 2021; 22:101. [PMID: 33845884 PMCID: PMC8040228 DOI: 10.1186/s13059-021-02328-9] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 03/25/2021] [Indexed: 12/13/2022] Open
Abstract
High-quality chromosome-scale haplotype sequences of diploid genomes, polyploid genomes, and metagenomes provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information spanning whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent and discuss methodological progress and perspectives in these areas.
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Affiliation(s)
- Shilpa Garg
- Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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42
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Ebert P, Audano PA, Zhu Q, Rodriguez-Martin B, Porubsky D, Bonder MJ, Sulovari A, Ebler J, Zhou W, Serra Mari R, Yilmaz F, Zhao X, Hsieh P, Lee J, Kumar S, Lin J, Rausch T, Chen Y, Ren J, Santamarina M, Höps W, Ashraf H, Chuang NT, Yang X, Munson KM, Lewis AP, Fairley S, Tallon LJ, Clarke WE, Basile AO, Byrska-Bishop M, Corvelo A, Evani US, Lu TY, Chaisson MJP, Chen J, Li C, Brand H, Wenger AM, Ghareghani M, Harvey WT, Raeder B, Hasenfeld P, Regier AA, Abel HJ, Hall IM, Flicek P, Stegle O, Gerstein MB, Tubio JMC, Mu Z, Li YI, Shi X, Hastie AR, Ye K, Chong Z, Sanders AD, Zody MC, Talkowski ME, Mills RE, Devine SE, Lee C, Korbel JO, Marschall T, Eichler EE. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science 2021; 372:eabf7117. [PMID: 33632895 PMCID: PMC8026704 DOI: 10.1126/science.abf7117] [Citation(s) in RCA: 316] [Impact Index Per Article: 105.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.
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Affiliation(s)
- Peter Ebert
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Bernardo Rodriguez-Martin
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Marc Jan Bonder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Jana Ebler
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Weichen Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
| | - Rebecca Serra Mari
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA
| | - Xuefang Zhao
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA 92121, USA
| | - Sushant Kumar
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA
| | - Jiadong Lin
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
| | - Tobias Rausch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Yu Chen
- Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Jingwen Ren
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Martin Santamarina
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Wolfram Höps
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Hufsah Ashraf
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - Nelson T Chuang
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | - Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Susan Fairley
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Luke J Tallon
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | | | | | | | | | | | - Tsung-Yu Lu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Junjie Chen
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Chong Li
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aaron M Wenger
- Pacific Biosciences of California, Menlo Park, CA 94025, USA
| | - Maryam Ghareghani
- Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, 66123 Saarbrücken, Germany
- Saarbrücken Graduate School of Computer Science, Saarland University, Saarland Informatics Campus E1.3, 66123 Saarbrücken, Germany
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA
| | - Benjamin Raeder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Patrick Hasenfeld
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Allison A Regier
- Department of Medicine, Washington University, St. Louis, MO 63108, USA
| | - Haley J Abel
- Department of Medicine, Washington University, St. Louis, MO 63108, USA
| | - Ira M Hall
- Department of Genetics, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA
| | - Jose M C Tubio
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Zepeng Mu
- Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - Yang I Li
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Xinghua Shi
- Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | | | - Kai Ye
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China
- Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA
| | - Zechen Chong
- Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Ashley D Sanders
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | | | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ryan E Mills
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA
| | - Scott E Devine
- Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
- Department of Graduate Studies-Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, South Korea
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Tobias Marschall
- Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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Pauper M, Kucuk E, Wenger AM, Chakraborty S, Baybayan P, Kwint M, van der Sanden B, Nelen MR, Derks R, Brunner HG, Hoischen A, Vissers LELM, Gilissen C. Long-read trio sequencing of individuals with unsolved intellectual disability. Eur J Hum Genet 2021; 29:637-648. [PMID: 33257779 PMCID: PMC8115091 DOI: 10.1038/s41431-020-00770-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 10/27/2020] [Indexed: 02/06/2023] Open
Abstract
Long-read sequencing (LRS) has the potential to comprehensively identify all medically relevant genome variation, including variation commonly missed by short-read sequencing (SRS) approaches. To determine this potential, we performed LRS around 15×-40× genome coverage using the Pacific Biosciences Sequel I System for five trios. The respective probands were diagnosed with intellectual disability (ID) whose etiology remained unresolved after SRS exomes and genomes. Systematic assessment of LRS coverage showed that ~35 Mb of the human reference genome was only accessible by LRS and not SRS. Genome-wide structural variant (SV) calling yielded on average 28,292 SV calls per individual, totaling 12.9 Mb of sequence. Trio-based analyses which allowed to study segregation, showed concordance for up to 95% of these SV calls across the genome, and 80% of the LRS SV calls were not identified by SRS. De novo mutation analysis did not identify any de novo SVs, confirming that these are rare events. Because of high sequence coverage, we were also able to call single nucleotide substitutions. On average, we identified 3 million substitutions per genome, with a Mendelian inheritance concordance of up to 97%. Of these, ~100,000 were located in the ~35 Mb of the genome that was only captured by LRS. Moreover, these variants affected the coding sequence of 64 genes, including 32 known Mendelian disease genes. Our data show the potential added value of LRS compared to SRS for identifying medically relevant genome variation.
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Affiliation(s)
- Marc Pauper
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Erdi Kucuk
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands
| | | | | | | | - Michael Kwint
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Bart van der Sanden
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 HR, Nijmegen, The Netherlands
| | - Marcel R Nelen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ronny Derks
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Han G Brunner
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands
- Department of Internal Medicine, Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Lisenka E L M Vissers
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 HR, Nijmegen, The Netherlands
| | - Christian Gilissen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
- Radboud Institute for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands.
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44
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Eimer C, Sanders AD, Korbel JO, Marschall T, Ebert P. ASHLEYS: automated quality control for single-cell Strand-seq data. Bioinformatics 2021; 37:3356-3357. [PMID: 33792647 PMCID: PMC8504637 DOI: 10.1093/bioinformatics/btab221] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 02/15/2021] [Accepted: 03/31/2021] [Indexed: 11/18/2022] Open
Abstract
Summary Single-cell DNA template strand sequencing (Strand-seq) enables chromosome length haplotype phasing, construction of phased assemblies, mapping sister-chromatid exchange events and structural variant discovery. The initial quality control of potentially thousands of single-cell libraries is still done manually by domain experts. ASHLEYS automates this tedious task, delivers near-expert performance and labels even large datasets in seconds. Availability and implementation github.com/friendsofstrandseq/ashleys-qc, MIT license. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Christina Eimer
- Center for Bioinformatics Saar, Saarland University, 66123 Saarbrücken, Germany
| | - Ashley D Sanders
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg, Germany
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Heinrich Heine University, 40225 Düsseldorf, Germany
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45
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Construction of Whole Genomes from Scaffolds Using Single Cell Strand-Seq Data. Int J Mol Sci 2021; 22:ijms22073617. [PMID: 33807210 PMCID: PMC8037727 DOI: 10.3390/ijms22073617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 03/23/2021] [Accepted: 03/27/2021] [Indexed: 12/26/2022] Open
Abstract
Accurate reference genome sequences provide the foundation for modern molecular biology and genomics as the interpretation of sequence data to study evolution, gene expression, and epigenetics depends heavily on the quality of the genome assembly used for its alignment. Correctly organising sequenced fragments such as contigs and scaffolds in relation to each other is a critical and often challenging step in the construction of robust genome references. We previously identified misoriented regions in the mouse and human reference assemblies using Strand-seq, a single cell sequencing technique that preserves DNA directionality Here we demonstrate the ability of Strand-seq to build and correct full-length chromosomes by identifying which scaffolds belong to the same chromosome and determining their correct order and orientation, without the need for overlapping sequences. We demonstrate that Strand-seq exquisitely maps assembly fragments into large related groups and chromosome-sized clusters without using new assembly data. Using template strand inheritance as a bi-allelic marker, we employ genetic mapping principles to cluster scaffolds that are derived from the same chromosome and order them within the chromosome based solely on directionality of DNA strand inheritance. We prove the utility of our approach by generating improved genome assemblies for several model organisms including the ferret, pig, Xenopus, zebrafish, Tasmanian devil and the Guinea pig.
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46
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Single-cell sequencing technology in tumor research. Clin Chim Acta 2021; 518:101-109. [PMID: 33766554 DOI: 10.1016/j.cca.2021.03.013] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 03/13/2021] [Accepted: 03/15/2021] [Indexed: 12/24/2022]
Abstract
Tumor heterogeneity is a key characteristic of malignant tumors and a significant obstacle in cancer treatment and research. Although bulk tissue sequencing has wide coverage and high accuracy, it can only represent the dominant cell signal information of each sample, while masking the unique gene expression of rare cells; therefore it cannot represent genes that are unstable within a subgroup, but unchanged in a majority of cells. With the progress of genomic technology, the emergence of single-cell sequencing (SCS) has effectively solved the above problem. Genetic, transcriptomic and epigenetic sequencing at the single-cell level provides an important basis for us to correctly classify the cell subsets of heterogeneous tumor populations and to reveal the process of complex changes in tumor cells at the molecular level. Single-cell sequencing technology has been applied to the field of cancer, revealing exciting discoveries in the potential mechanisms of tumor driver gene mutation, clonal evolution, invasion and metastasis. It also provides favorable conditions for developing new tumor biomarkers and providing more accurate and individualized targeted tumor therapy. Herein, we review the steps and methods of single-cell sequencing and highlight the application of SCS in tumor diagnosis and clinical treatment.
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47
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Porubsky D, Ebert P, Audano PA, Vollger MR, Harvey WT, Marijon P, Ebler J, Munson KM, Sorensen M, Sulovari A, Haukness M, Ghareghani M, Lansdorp PM, Paten B, Devine SE, Sanders AD, Lee C, Chaisson MJP, Korbel JO, Eichler EE, Marschall T. Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads. Nat Biotechnol 2021; 39:302-308. [PMID: 33288906 PMCID: PMC7954704 DOI: 10.1038/s41587-020-0719-5] [Citation(s) in RCA: 88] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 09/16/2020] [Indexed: 12/18/2022]
Abstract
Human genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter Ebert
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Düsseldorf, Germany
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Pierre Marijon
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Düsseldorf, Germany
| | - Jana Ebler
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Düsseldorf, Germany
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Melanie Sorensen
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Maryam Ghareghani
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Düsseldorf, Germany
- Center for Bioinformatics, Saarland University, and Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Peter M Lansdorp
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Scott E Devine
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ashley D Sanders
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Department of Life Science, Ewha Womans University, Seoul, Republic of Korea
| | - Mark J P Chaisson
- Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Jan O Korbel
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
| | - Tobias Marschall
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Düsseldorf, Germany.
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48
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Minoche AE, Lundie B, Peters GB, Ohnesorg T, Pinese M, Thomas DM, Zankl A, Roscioli T, Schonrock N, Kummerfeld S, Burnett L, Dinger ME, Cowley MJ. ClinSV: clinical grade structural and copy number variant detection from whole genome sequencing data. Genome Med 2021; 13:32. [PMID: 33632298 PMCID: PMC7908648 DOI: 10.1186/s13073-021-00841-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 02/02/2021] [Indexed: 01/09/2023] Open
Abstract
Whole genome sequencing (WGS) has the potential to outperform clinical microarrays for the detection of structural variants (SV) including copy number variants (CNVs), but has been challenged by high false positive rates. Here we present ClinSV, a WGS based SV integration, annotation, prioritization, and visualization framework, which identified 99.8% of simulated pathogenic ClinVar CNVs > 10 kb and 11/11 pathogenic variants from matched microarrays. The false positive rate was low (1.5-4.5%) and reproducibility high (95-99%). In clinical practice, ClinSV identified reportable variants in 22 of 485 patients (4.7%) of which 35-63% were not detectable by current clinical microarray designs. ClinSV is available at https://github.com/KCCG/ClinSV .
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Affiliation(s)
- Andre E Minoche
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia.
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia.
| | - Ben Lundie
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
| | - Greg B Peters
- Sydney Genome Diagnostics, The Children's Hospital at Westmead, Hawkesbury Road & Hainsworth Street, Westmead, NSW, Australia
| | - Thomas Ohnesorg
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- Genome.One, Darlinghurst, NSW, Australia
| | - Mark Pinese
- Children's Cancer Institute, University of New South Wales, Randwick, Sydney, NSW, Australia
- School of Women's and Children's Health, UNSW, Sydney, NSW, Australia
| | - David M Thomas
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia
- The Kinghorn Cancer Centre and Cancer Division, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
| | - Andreas Zankl
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- Department of Clinical Genetics, The Children's Hospital at Westmead, Hawkesbury Road, Westmead, NSW, Australia
- Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
| | - Tony Roscioli
- NSW Health Pathology Randwick, Sydney, NSW, Australia
- Centre for Clinical Genetics, Sydney Children's Hospital, Randwick, NSW, Australia
- Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, University of New South Wales, Randwick, Sydney, NSW, Australia
| | - Nicole Schonrock
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- Genome.One, Darlinghurst, NSW, Australia
| | - Sarah Kummerfeld
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia
| | - Leslie Burnett
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia
- Genome.One, Darlinghurst, NSW, Australia
- Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
| | - Marcel E Dinger
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW, Sydney, NSW, Australia
| | - Mark J Cowley
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia.
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia.
- Children's Cancer Institute, University of New South Wales, Randwick, Sydney, NSW, Australia.
- School of Women's and Children's Health, UNSW, Sydney, NSW, Australia.
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49
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Warren WC, Harris RA, Haukness M, Fiddes IT, Murali SC, Fernandes J, Dishuck PC, Storer JM, Raveendran M, Hillier LW, Porubsky D, Mao Y, Gordon D, Vollger MR, Lewis AP, Munson KM, DeVogelaere E, Armstrong J, Diekhans M, Walker JA, Tomlinson C, Graves-Lindsay TA, Kremitzki M, Salama SR, Audano PA, Escalona M, Maurer NW, Antonacci F, Mercuri L, Maggiolini FAM, Catacchio CR, Underwood JG, O'Connor DH, Sanders AD, Korbel JO, Ferguson B, Kubisch HM, Picker L, Kalin NH, Rosene D, Levine J, Abbott DH, Gray SB, Sanchez MM, Kovacs-Balint ZA, Kemnitz JW, Thomasy SM, Roberts JA, Kinnally EL, Capitanio JP, Skene JHP, Platt M, Cole SA, Green RE, Ventura M, Wiseman RW, Paten B, Batzer MA, Rogers J, Eichler EE. Sequence diversity analyses of an improved rhesus macaque genome enhance its biomedical utility. Science 2021; 370:370/6523/eabc6617. [PMID: 33335035 DOI: 10.1126/science.abc6617] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 10/29/2020] [Indexed: 12/15/2022]
Abstract
The rhesus macaque (Macaca mulatta) is the most widely studied nonhuman primate (NHP) in biomedical research. We present an updated reference genome assembly (Mmul_10, contig N50 = 46 Mbp) that increases the sequence contiguity 120-fold and annotate it using 6.5 million full-length transcripts, thus improving our understanding of gene content, isoform diversity, and repeat organization. With the improved assembly of segmental duplications, we discovered new lineage-specific genes and expanded gene families that are potentially informative in studies of evolution and disease susceptibility. Whole-genome sequencing (WGS) data from 853 rhesus macaques identified 85.7 million single-nucleotide variants (SNVs) and 10.5 million indel variants, including potentially damaging variants in genes associated with human autism and developmental delay, providing a framework for developing noninvasive NHP models of human disease.
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Affiliation(s)
- Wesley C Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA. .,Department of Surgery, School of Medicine, University of Missouri, Columbia, MO 65211, USA.,Institute of Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
| | - R Alan Harris
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Marina Haukness
- Computational Genomics Laboratory, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Shwetha C Murali
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.,Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Jason Fernandes
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Jessica M Storer
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.,Institue for Systems Biology, Seattle, WA 98109, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - LaDeana W Hillier
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Yafei Mao
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - David Gordon
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.,Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth DeVogelaere
- Computational Genomics Laboratory, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Joel Armstrong
- Computational Genomics Laboratory, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mark Diekhans
- Computational Genomics Laboratory, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Jerilyn A Walker
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Chad Tomlinson
- McDonnell Genome Institute, Washington University, St. Louis, MO 63108, USA
| | | | - Milinn Kremitzki
- McDonnell Genome Institute, Washington University, St. Louis, MO 63108, USA
| | - Sofie R Salama
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Merly Escalona
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Nicholas W Maurer
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Ludovica Mercuri
- Department of Biology, University of Bari 'Aldo Moro', 70125 Bari, Italy
| | | | | | | | - David H O'Connor
- Department of Pathology and Laboratory Medicine, Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53711, USA
| | - Ashley D Sanders
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Jan O Korbel
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Betsy Ferguson
- Division of Genetics, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR 97006, USA
| | | | - Louis Picker
- Oregon National Primate Research Center and Vaccine and Gene Therapy Institute, Oregon Health Sciences University, Beaverton, OR 97006, USA
| | - Ned H Kalin
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI 53719, USA
| | - Douglas Rosene
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Jon Levine
- Department of Neuroscience, University of Wisconsin, Madison, WI 53175, USA.,Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53171, USA
| | - David H Abbott
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53171, USA.,Department of Obstetrics and Gynecology, Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715, USA
| | - Stanton B Gray
- The University of Texas MD Anderson Cancer Center, Michale E. Keeling Center for Comparative Medicine and Research, Bastrop, TX 78602, USA
| | - Mar M Sanchez
- Yerkes National Primate Research Center, Atlanta, GA 30329, USA.,Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30329, USA
| | | | - Joseph W Kemnitz
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53171, USA.,Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI 53706, USA
| | - Sara M Thomasy
- Department of Surgical and Radiological Sciences, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA.,Department of Ophthalmology and Vision Science, School of Medicine, University of California-Davis, Davis, CA 95817, USA
| | | | - Erin L Kinnally
- California National Primate Research Center, Davis, CA 95616, USA.,Department of Psychology, University of California, Davis, CA 95616, USA
| | - John P Capitanio
- California National Primate Research Center, Davis, CA 95616, USA.,Department of Psychology, University of California, Davis, CA 95616, USA
| | - J H Pate Skene
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Michael Platt
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute and Southwest National Primate Research Center, San Antonio, TX 78227, USA
| | - Richard E Green
- Department of Biomolecular Engineering, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mario Ventura
- Department of Biology, University of Bari 'Aldo Moro', 70125 Bari, Italy
| | - Roger W Wiseman
- Department of Pathology and Laboratory Medicine, Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53711, USA
| | - Benedict Paten
- Computational Genomics Laboratory, University of California-Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mark A Batzer
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. .,Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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50
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The structure, function and evolution of a complete human chromosome 8. Nature 2021; 593:101-107. [PMID: 33828295 PMCID: PMC8099727 DOI: 10.1038/s41586-021-03420-7] [Citation(s) in RCA: 179] [Impact Index Per Article: 59.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 03/04/2021] [Indexed: 02/07/2023]
Abstract
The complete assembly of each human chromosome is essential for understanding human biology and evolution1,2. Here we use complementary long-read sequencing technologies to complete the linear assembly of human chromosome 8. Our assembly resolves the sequence of five previously long-standing gaps, including a 2.08-Mb centromeric α-satellite array, a 644-kb copy number polymorphism in the β-defensin gene cluster that is important for disease risk, and an 863-kb variable number tandem repeat at chromosome 8q21.2 that can function as a neocentromere. We show that the centromeric α-satellite array is generally methylated except for a 73-kb hypomethylated region of diverse higher-order α-satellites enriched with CENP-A nucleosomes, consistent with the location of the kinetochore. In addition, we confirm the overall organization and methylation pattern of the centromere in a diploid human genome. Using a dual long-read sequencing approach, we complete high-quality draft assemblies of the orthologous centromere from chromosome 8 in chimpanzee, orangutan and macaque to reconstruct its evolutionary history. Comparative and phylogenetic analyses show that the higher-order α-satellite structure evolved in the great ape ancestor with a layered symmetry, in which more ancient higher-order repeats locate peripherally to monomeric α-satellites. We estimate that the mutation rate of centromeric satellite DNA is accelerated by more than 2.2-fold compared to the unique portions of the genome, and this acceleration extends into the flanking sequence.
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