1
|
Takayama J, Makino S, Funayama T, Ueki M, Narita A, Murakami K, Orui M, Ishikuro M, Obara T, Kuriyama S, Yamamoto M, Tamiya G. A fine-scale genetic map of the Japanese population. Clin Genet 2024; 106:284-292. [PMID: 38719617 DOI: 10.1111/cge.14536] [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: 10/03/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 08/13/2024]
Abstract
Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.
Collapse
Affiliation(s)
- Jun Takayama
- Department of AI and Innovative Medicine, Tohoku University School of Medicine, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Satoshi Makino
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Takamitsu Funayama
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Masao Ueki
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Akira Narita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
| | - Masatsugu Orui
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Mami Ishikuro
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Taku Obara
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Shinichi Kuriyama
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Department of AI and Innovative Medicine, Tohoku University School of Medicine, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| |
Collapse
|
2
|
Negi S, Stenton SL, Berger SI, McNulty B, Violich I, Gardner J, Hillaker T, O'Rourke SM, O'Leary MC, Carbonell E, Austin-Tse C, Lemire G, Serrano J, Mangilog B, VanNoy G, Kolmogorov M, Vilain E, O'Donnell-Luria A, Délot E, Miga KH, Monlong J, Paten B. Advancing long-read nanopore genome assembly and accurate variant calling for rare disease detection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.22.24312327. [PMID: 39228712 PMCID: PMC11370519 DOI: 10.1101/2024.08.22.24312327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
More than 50% of families with suspected rare monogenic diseases remain unsolved after whole genome analysis by short read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing, and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare disease cohort of 98 samples, including 41 probands and some family members, using nanopore sequencing, achieving per sample ∼36x average coverage and 32 kilobase (kb) read N50 from a single flow cell. Our Napu pipeline generated assemblies, phased variants, and methylation calls. LRS covered, on average, coding exons in ∼280 genes and ∼5 known Mendelian disease genes that were not covered by SRS. In comparison to SRS, LRS detected additional rare, functionally annotated variants, including SVs and tandem repeats, and completely phased 87% of protein-coding genes. LRS detected additional de novo variants, and could be used to distinguish postzygotic mosaic variants from prezygotic de novos . Eleven probands were solved, with diverse underlying genetic causes including de novo and compound heterozygous variants, large-scale SVs, and epigenetic modifications. Our study demonstrates LRS's potential to enhance diagnostic yield for rare monogenic diseases, implying utility in future clinical genomics workflows.
Collapse
|
3
|
Chair SY, Chow KM, Chan CWL, Chan JYW, Law BMH, Waye MMY. Structural Variations Identified in Patients with Autism Spectrum Disorder (ASD) in the Chinese Population: A Systematic Review of Case-Control Studies. Genes (Basel) 2024; 15:1082. [PMID: 39202440 PMCID: PMC11353326 DOI: 10.3390/genes15081082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 08/08/2024] [Accepted: 08/12/2024] [Indexed: 09/03/2024] Open
Abstract
Autistic spectrum disorder (ASD) is a neurodevelopmental disability characterised by the impairment of social interaction and communication ability. The alarming increase in its prevalence in children urged researchers to obtain a better understanding of the causes of this disease. Genetic factors are considered to be crucial, as ASD has a tendency to run in families. In recent years, with technological advances, the importance of structural variations (SVs) in ASD began to emerge. Most of these studies, however, focus on the Caucasian population. As a populated ethnicity, ASD shall be a significant health issue in China. This systematic review aims to summarise current case-control studies of SVs associated with ASD in the Chinese population. A list of genes identified in the nine included studies is provided. It also reveals that similar research focusing on other genetic backgrounds is demanded to manifest the disease etiology in different ethnic groups, and assist the development of accurate ethnic-oriented genetic diagnosis.
Collapse
Affiliation(s)
- Sek-Ying Chair
- The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (K.-M.C.); (C.W.-L.C.); (J.Y.-W.C.); (B.M.-H.L.); (M.M.-Y.W.)
- Asia-Pacific Genomic and Genetic Nursing Centre, The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- The Croucher Laboratory for Human Genomics, The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Ka-Ming Chow
- The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (K.-M.C.); (C.W.-L.C.); (J.Y.-W.C.); (B.M.-H.L.); (M.M.-Y.W.)
- Asia-Pacific Genomic and Genetic Nursing Centre, The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- The Croucher Laboratory for Human Genomics, The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Cecilia Wai-Ling Chan
- The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (K.-M.C.); (C.W.-L.C.); (J.Y.-W.C.); (B.M.-H.L.); (M.M.-Y.W.)
| | - Judy Yuet-Wa Chan
- The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (K.-M.C.); (C.W.-L.C.); (J.Y.-W.C.); (B.M.-H.L.); (M.M.-Y.W.)
| | - Bernard Man-Hin Law
- The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (K.-M.C.); (C.W.-L.C.); (J.Y.-W.C.); (B.M.-H.L.); (M.M.-Y.W.)
| | - Mary Miu-Yee Waye
- The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China; (K.-M.C.); (C.W.-L.C.); (J.Y.-W.C.); (B.M.-H.L.); (M.M.-Y.W.)
- Asia-Pacific Genomic and Genetic Nursing Centre, The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- The Croucher Laboratory for Human Genomics, The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
4
|
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.
Collapse
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
| |
Collapse
|
5
|
Beichman AC, Zhu L, Harris K. The Evolutionary Interplay of Somatic and Germline Mutation Rates. Annu Rev Biomed Data Sci 2024; 7:83-105. [PMID: 38669515 DOI: 10.1146/annurev-biodatasci-102523-104225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Novel sequencing technologies are making it increasingly possible to measure the mutation rates of somatic cell lineages. Accurate germline mutation rate measurement technologies have also been available for a decade, making it possible to assess how this fundamental evolutionary parameter varies across the tree of life. Here, we review some classical theories about germline and somatic mutation rate evolution that were formulated using principles of population genetics and the biology of aging and cancer. We find that somatic mutation rate measurements, while still limited in phylogenetic diversity, seem consistent with the theory that selection to preserve the soma is proportional to life span. However, germline and somatic theories make conflicting predictions regarding which species should have the most accurate DNA repair. Resolving this conflict will require carefully measuring how mutation rates scale with time and cell division and achieving a better understanding of mutation rate pleiotropy among cell types.
Collapse
Affiliation(s)
- Annabel C Beichman
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA;
| | - Luke Zhu
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | - Kelley Harris
- Computational Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA;
| |
Collapse
|
6
|
Zheng Y, Lin C, Wang WJ, Wang L, Qian Y, Mao L, Li B, Lou L, Mao Y, Li N, Zheng J, Jiang N, He C, Wang Q, Zhou Q, Chen F, Jin F. Post-implantation analysis of genomic variations in the progeny from developing fetus to birth. Hum Genomics 2024; 18:79. [PMID: 39010135 PMCID: PMC11247737 DOI: 10.1186/s40246-024-00634-4] [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: 02/06/2024] [Accepted: 06/06/2024] [Indexed: 07/17/2024] Open
Abstract
The analysis of genomic variations in offspring after implantation has been infrequently studied. In this study, we aim to investigate the extent of de novo mutations in humans from developing fetus to birth. Using high-depth whole-genome sequencing, 443 parent-offspring trios were studied to compare the results of de novo mutations (DNMs) between different groups. The focus was on fetuses and newborns, with DNA samples obtained from the families' blood and the aspirated embryonic tissues subjected to deep sequencing. It was observed that the average number of total DNMs in the newborns group was 56.26 (54.17-58.35), which appeared to be lower than that the multifetal reduction group, which was 76.05 (69.70-82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy body mass index (BMI), significant differences were found between the two groups. The analysis was further divided into single nucleotide variants (SNVs) and insertion/deletion of a small number of bases (indels), and it was discovered that the average number of de novo SNVs associated with the multifetal reduction group and the newborn group was 49.89 (45.59-54.20) and 51.09 (49.22-52.96), respectively. No significant differences were noted between the groups (F = 1.01, P = 0.32). However, a significant difference was observed for de novo indels, with a higher average number found in the multifetal reduction group compared to the newborn group (F = 194.17, P < 0.001). The average number of de novo indels among the multifetal reduction group and the newborn group was 26.26 (23.27-29.05) and 5.17 (4.82-5.52), respectively. To conclude, it has been observed that the quantity of de novo indels in the newborns experiences a significant decrease when compared to that in the aspirated embryonic tissues (7-9 weeks). This phenomenon is evident across all genomic regions, highlighting the adverse effects of de novo indels on the fetus and emphasizing the significance of embryonic implantation and intrauterine growth in human genetic selection mechanisms.
Collapse
Affiliation(s)
- Yingming Zheng
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Chuanping Lin
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
- Reproductive Medical Center, the Second Affiliated Hospital of Wenzhou Medical College and Yuying Children's hospital, Wenzhou, Zhejiang, 325027, China
| | | | - Liya Wang
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Yeqing Qian
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Luna Mao
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Baohua Li
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Lijun Lou
- Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, 322100, China
| | - Yuchan Mao
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Na Li
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Jiayong Zheng
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Nan Jiang
- Reproductive Medical Center, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310003, China
| | - Chaying He
- Hangzhou Women's Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, Zhejiang, 310008, China
| | - Qijing Wang
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China
| | - Qing Zhou
- BGI Research, Shenzhen, Guangdong, 518083, China
| | - Fang Chen
- BGI Research, Shenzhen, Guangdong, 518083, China
| | - Fan Jin
- Department of Reproductive Endocrinology, Key Laboratory of Reproductive Genetics of National Ministry of Education, Women's Reproductive Health Laboratory of Zhejiang Province, Women's Hospital, School of Medicine, Zhejiang University, 1 Xueshi Road, Hangzhou, Zhejiang, 310006, China.
| |
Collapse
|
7
|
Jia H, Tan S, Zhang YE. Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs. GENOMICS, PROTEOMICS & BIOINFORMATICS 2024; 22:qzae024. [PMID: 38991976 DOI: 10.1093/gpbjnl/qzae024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 07/13/2024]
Abstract
Next-generation sequencing (NGS), represented by Illumina platforms, has been an essential cornerstone of basic and applied research. However, the sequencing error rate of 1 per 1000 bp (10-3) represents a serious hurdle for research areas focusing on rare mutations, such as somatic mosaicism or microbe heterogeneity. By examining the high-fidelity sequencing methods developed in the past decade, we summarized three major factors underlying errors and the corresponding 12 strategies mitigating these errors. We then proposed a novel framework to classify 11 preexisting representative methods according to the corresponding combinatory strategies and identified three trends that emerged during methodological developments. We further extended this analysis to eight long-read sequencing methods, emphasizing error reduction strategies. Finally, we suggest two promising future directions that could achieve comparable or even higher accuracy with lower costs in both NGS and long-read sequencing.
Collapse
Affiliation(s)
- Hangxing Jia
- CAS Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shengjun Tan
- CAS Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yong E Zhang
- CAS Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| |
Collapse
|
8
|
Kramer M, Goodwin S, Wappel R, Borio M, Offit K, Feldman DR, Stadler ZK, McCombie WR. Exploring the genetic and epigenetic underpinnings of early-onset cancers: Variant prioritization for long read whole genome sequencing from family cancer pedigrees. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.27.601096. [PMID: 39005350 PMCID: PMC11244929 DOI: 10.1101/2024.06.27.601096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Despite significant advances in our understanding of genetic cancer susceptibility, known inherited cancer predisposition syndromes explain at most 20% of early-onset cancers. As early-onset cancer prevalence continues to increase, the need to assess previously inaccessible areas of the human genome, harnessing a trio or quad family-based architecture for variant filtration, may reveal further insights into cancer susceptibility. To assess a broader spectrum of variation than can be ascertained by multi-gene panel sequencing, or even whole genome sequencing with short reads, we employed long read whole genome sequencing using an Oxford Nanopore Technology (ONT) PromethION of 3 families containing an early-onset cancer proband using a trio or quad family architecture. Analysis included 2 early-onset colorectal cancer family trios and one quad consisting of two siblings with testicular cancer, all with unaffected parents. Structural variants (SVs), epigenetic profiles and single nucleotide variants (SNVs) were determined for each individual, and a filtering strategy was employed to refine and prioritize candidate variants based on the family architecture. The family architecture enabled us to focus on inapposite variants while filtering variants shared with the unaffected parents, significantly decreasing background variation that can hamper identification of potentially disease causing differences. Candidate d e novo and compound heterozygous variants were identified in this way. Gene expression, in matched neoplastic and pre-neoplastic lesions, was assessed for one trio. Our study demonstrates the feasibility of a streamlined analysis of genomic variants from long read ONT whole genome sequencing and a way to prioritize key variants for further evaluation of pathogenicity, while revealing what may be missing from panel based analyses.
Collapse
|
9
|
Parmar JM, Laing NG, Kennerson ML, Ravenscroft G. Genetics of inherited peripheral neuropathies and the next frontier: looking backwards to progress forwards. J Neurol Neurosurg Psychiatry 2024:jnnp-2024-333436. [PMID: 38744462 DOI: 10.1136/jnnp-2024-333436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 04/10/2024] [Indexed: 05/16/2024]
Abstract
Inherited peripheral neuropathies (IPNs) encompass a clinically and genetically heterogeneous group of disorders causing length-dependent degeneration of peripheral autonomic, motor and/or sensory nerves. Despite gold-standard diagnostic testing for pathogenic variants in over 100 known associated genes, many patients with IPN remain genetically unsolved. Providing patients with a diagnosis is critical for reducing their 'diagnostic odyssey', improving clinical care, and for informed genetic counselling. The last decade of massively parallel sequencing technologies has seen a rapid increase in the number of newly described IPN-associated gene variants contributing to IPN pathogenesis. However, the scarcity of additional families and functional data supporting variants in potential novel genes is prolonging patient diagnostic uncertainty and contributing to the missing heritability of IPNs. We review the last decade of IPN disease gene discovery to highlight novel genes, structural variation and short tandem repeat expansions contributing to IPN pathogenesis. From the lessons learnt, we provide our vision for IPN research as we anticipate the future, providing examples of emerging technologies, resources and tools that we propose that will expedite the genetic diagnosis of unsolved IPN families.
Collapse
Affiliation(s)
- Jevin M Parmar
- Rare Disease Genetics and Functional Genomics, Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
- Centre for Medical Research, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Nigel G Laing
- Centre for Medical Research, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Preventive Genetics, Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
| | - Marina L Kennerson
- Northcott Neuroscience Laboratory, ANZAC Research Institute, Concord, New South Wales, Australia
- Molecular Medicine Laboratory, Concord Hospital, Concord, New South Wales, Australia
| | - Gianina Ravenscroft
- Rare Disease Genetics and Functional Genomics, Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
- Centre for Medical Research, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Western Australia, Australia
| |
Collapse
|
10
|
English AC, Dolzhenko E, Ziaei Jam H, McKenzie SK, Olson ND, De Coster W, Park J, Gu B, Wagner J, Eberle MA, Gymrek M, Chaisson MJP, Zook JM, Sedlazeck FJ. Analysis and benchmarking of small and large genomic variants across tandem repeats. Nat Biotechnol 2024:10.1038/s41587-024-02225-z. [PMID: 38671154 DOI: 10.1038/s41587-024-02225-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 03/28/2024] [Indexed: 04/28/2024]
Abstract
Tandem repeats (TRs) are highly polymorphic in the human genome, have thousands of associated molecular traits and are linked to over 60 disease phenotypes. However, they are often excluded from at-scale studies because of challenges with variant calling and representation, as well as a lack of a genome-wide standard. Here, to promote the development of TR methods, we created a catalog of TR regions and explored TR properties across 86 haplotype-resolved long-read human assemblies. We curated variants from the Genome in a Bottle (GIAB) HG002 individual to create a TR dataset to benchmark existing and future TR analysis methods. We also present an improved variant comparison method that handles variants greater than 4 bp in length and varying allelic representation. The 8.1% of the genome covered by the TR catalog holds ~24.9% of variants per individual, including 124,728 small and 17,988 large variants for the GIAB HG002 'truth-set' TR benchmark. We demonstrate the utility of this pipeline across short-read and long-read technologies.
Collapse
Affiliation(s)
- Adam C English
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
| | | | - Helyaneh Ziaei Jam
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | | | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Applied and Translational Neurogenomics Group, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jonghun Park
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Bida Gu
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, Houston, TX, USA.
| |
Collapse
|
11
|
Schloissnig S, Pani S, Rodriguez-Martin B, Ebler J, Hain C, Tsapalou V, Söylev A, Hüther P, Ashraf H, Prodanov T, Asparuhova M, Hunt S, Rausch T, Marschall T, Korbel JO. Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590093. [PMID: 38659906 PMCID: PMC11042266 DOI: 10.1101/2024.04.18.590093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Structural variants (SVs) contribute significantly to human genetic diversity and disease 1-4 . Previously, SVs have remained incompletely resolved by population genomics, with short-read sequencing facing limitations in capturing the whole spectrum of SVs at nucleotide resolution 5-7 . Here we leveraged nanopore sequencing 8 to construct an intermediate coverage resource of 1,019 long-read genomes sampled within 26 human populations from the 1000 Genomes Project. By integrating linear and graph-based approaches for SV analysis via pangenome graph-augmentation, we uncover 167,291 sequence-resolved SVs in these samples, considerably advancing SV characterization compared to population-wide short-read sequencing studies 3,4 . Our analysis details diverse SV classes-deletions, duplications, insertions, and inversions-at population-scale. LINE-1 and SVA retrotransposition activities frequently mediate transductions 9,10 of unique sequences, with both mobile element classes transducing sequences at either the 3'- or 5'-end, depending on the source element locus. Furthermore, analyses of SV breakpoint junctions suggest a continuum of homology-mediated rearrangement processes are integral to SV formation, and highlight evidence for SV recurrence involving repeat sequences. Our open-access dataset underscores the transformative impact of long-read sequencing in advancing the characterisation of polymorphic genomic architectures, and provides a resource for guiding variant prioritisation in future long-read sequencing-based disease studies.
Collapse
|
12
|
Bucciol G, Delafontaine S, Meyts I, Poli C. Inborn errors of immunity: A field without frontiers. Immunol Rev 2024; 322:15-27. [PMID: 38062988 DOI: 10.1111/imr.13297] [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: 03/20/2024]
Abstract
The study of primary immunodeficiencies or inborn errors of immunity continues to drive our knowledge of the function of the human immune system. From the outset, the study of inborn errors has focused on unraveling genetic etiologies and molecular mechanisms. Aided by the continuous growth in genetic diagnostics, the field has moved from the study of an infection dominated phenotype to embrace and unravel diverse manifestations of autoinflammation, autoimmunity, malignancy, and severe allergy in all medical disciplines. It has now moved from the study of ultrarare presentations to producing meaningful impact in conditions as diverse as inflammatory bowel disease, neurological conditions, and hematology. Beyond offering immunogenetic diagnosis, the study of underlying inborn errors of immunity in these conditions points to targeted treatment which can be lifesaving.
Collapse
Affiliation(s)
- Giorgia Bucciol
- Department of Pediatrics, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Inborn Errors of Immunity, KU Leuven, Leuven, Belgium
| | - Selket Delafontaine
- Department of Pediatrics, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Inborn Errors of Immunity, KU Leuven, Leuven, Belgium
| | - Isabelle Meyts
- Department of Pediatrics, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Inborn Errors of Immunity, KU Leuven, Leuven, Belgium
| | - Cecilia Poli
- Facultad de Medicina Universidad del Desarrollo-Clínica Alemana, Santiago, Chile
- Unidad de Inmunología y Reumatología, Hospital Roberto del Río, Santiago, Chile
| |
Collapse
|
13
|
Lopes-Marques M, Mort M, Carneiro J, Azevedo A, Amaro AP, Cooper DN, Azevedo L. Meta-analysis of 46,000 germline de novo mutations linked to human inherited disease. Hum Genomics 2024; 18:20. [PMID: 38395944 PMCID: PMC10885371 DOI: 10.1186/s40246-024-00587-8] [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: 11/10/2023] [Accepted: 02/15/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND De novo mutations (DNMs) are variants that occur anew in the offspring of noncarrier parents. They are not inherited from either parent but rather result from endogenous mutational processes involving errors of DNA repair/replication. These spontaneous errors play a significant role in the causation of genetic disorders, and their importance in the context of molecular diagnostic medicine has become steadily more apparent as more DNMs have been reported in the literature. In this study, we examined 46,489 disease-associated DNMs annotated by the Human Gene Mutation Database (HGMD) to ascertain their distribution across gene and disease categories. RESULTS Most disease-associated DNMs reported to date are found to be associated with developmental and psychiatric disorders, a reflection of the focus of sequencing efforts over the last decade. Of the 13,277 human genes in which DNMs have so far been found, the top-10 genes with the highest proportions of DNM relative to gene size were H3-3 A, DDX3X, CSNK2B, PURA, ZC4H2, STXBP1, SCN1A, SATB2, H3-3B and TUBA1A. The distribution of CADD and REVEL scores for both disease-associated DNMs and those mutations not reported to be de novo revealed a trend towards higher deleteriousness for DNMs, consistent with the likely lower selection pressure impacting them. This contrasts with the non-DNMs, which are presumed to have been subject to continuous negative selection over multiple generations. CONCLUSION This meta-analysis provides important information on the occurrence and distribution of disease-associated DNMs in association with heritable disease and should make a significant contribution to our understanding of this major type of mutation.
Collapse
Affiliation(s)
- Mónica Lopes-Marques
- CIIMAR-Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Porto, Portugal
| | - Matthew Mort
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - João Carneiro
- CIIMAR-Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Porto, Portugal
| | - António Azevedo
- CHUdSA-Centro Hospitalar Universitário de Santo António, Porto, Portugal
- UMIB-Unit for Multidisciplinary Research in Biomedicine, ICBAS - School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal
- ITR - Laboratory for Integrative and Translational Research in Population Health, Porto, Portugal
| | - Andreia P Amaro
- UMIB-Unit for Multidisciplinary Research in Biomedicine, ICBAS - School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal
- ITR - Laboratory for Integrative and Translational Research in Population Health, Porto, Portugal
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Luísa Azevedo
- UMIB-Unit for Multidisciplinary Research in Biomedicine, ICBAS - School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.
- ITR - Laboratory for Integrative and Translational Research in Population Health, Porto, Portugal.
| |
Collapse
|
14
|
Audano PA, Beck CR. Small polymorphisms are a source of ancestral bias in structural variant breakpoint placement. Genome Res 2024; 34:7-19. [PMID: 38176712 PMCID: PMC10904011 DOI: 10.1101/gr.278203.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/02/2024] [Indexed: 01/06/2024]
Abstract
High-quality genome assemblies and sophisticated algorithms have increased sensitivity for a wide range of variant types, and breakpoint accuracy for structural variants (SVs, ≥50 bp) has improved to near base pair precision. Despite these advances, many SV breakpoint locations are subject to systematic bias affecting variant representation. To understand why SV breakpoints are inconsistent across samples, we reanalyzed 64 phased haplotypes constructed from long-read assemblies released by the Human Genome Structural Variation Consortium (HGSVC). We identify 882 SV insertions and 180 SV deletions with variable breakpoints not anchored in tandem repeats (TRs) or segmental duplications (SDs). SVs called from aligned sequencing reads increase breakpoint disagreements by 2×-16×. Sequence accuracy had a minimal impact on breakpoints, but we observe a strong effect of ancestry. We confirm that SNP and indel polymorphisms are enriched at shifted breakpoints and are also absent from variant callsets. Breakpoint homology increases the likelihood of imprecise SV calls and the distance they are shifted, and tandem duplications are the most heavily affected SVs. Because graph genome methods normalize SV calls across samples, we investigated graphs generated by two different methods and find the resulting breakpoints are subject to other technical biases affecting breakpoint accuracy. The breakpoint inconsistencies we characterize affect ∼5% of the SVs called in a human genome and can impact variant interpretation and annotation. These limitations underscore a need for algorithm development to improve SV databases, mitigate the impact of ancestry on breakpoints, and increase the value of callsets for investigating breakpoint features.
Collapse
Affiliation(s)
- Peter A Audano
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA;
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, Connecticut 06030, USA
| |
Collapse
|
15
|
Mandal AK. Recent insights into crosstalk between genetic parasites and their host genome. Brief Funct Genomics 2024; 23:15-23. [PMID: 36307128 PMCID: PMC10799329 DOI: 10.1093/bfgp/elac032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 09/14/2022] [Accepted: 09/21/2022] [Indexed: 01/21/2024] Open
Abstract
The bulk of higher order organismal genomes is comprised of transposable element (TE) copies, i.e. genetic parasites. The host-parasite relation is multi-faceted, varying across genomic region (genic versus intergenic), life-cycle stages, tissue-type and of course in health versus pathological state. The reach of functional genomics though, in investigating genotype-to-phenotype relations, has been limited when TEs are involved. The aim of this review is to highlight recent progress made in understanding how TE origin biochemical activity interacts with the central dogma stages of the host genome. Such interaction can also bring about modulation of the immune context and this could have important repercussions in disease state where immunity has a role to play. Thus, the review is to instigate ideas and action points around identifying evolutionary adaptations that the host genome and the genetic parasite have evolved and why they could be relevant.
Collapse
Affiliation(s)
- Amit K Mandal
- Corresponding author: A.K. Mandal, Nuffield Department of Surgical Sciences (NDS), University of Oxford, Old Road Campus Research building (ORCRB), Oxford OX3 7DQ, UK. Tel: +44 (0)1865 617123; Fax: +44 (0)1865 768876; E-mail:
| |
Collapse
|
16
|
Ng JK, Turner TN. HAT: de novo variant calling for highly accurate short-read and long-read sequencing data. Bioinformatics 2024; 40:btad775. [PMID: 38175776 PMCID: PMC10777354 DOI: 10.1093/bioinformatics/btad775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 12/05/2023] [Indexed: 01/06/2024] Open
Abstract
MOTIVATION de novo variants (DNVs) are variants that are present in offspring but not in their parents. DNVs are both important for examining mutation rates as well as in the identification of disease-related variation. While efforts have been made to call DNVs, calling of DNVs is still challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) as an automated DNV detection workflow for highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genomics and HAT addresses this need. RESULTS HAT is a computational workflow that begins with aligned read data (i.e. CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from Illumina short-read whole-exome sequencing, Illumina short-read whole-genome sequencing, and highly accurate PacBio HiFi long-read whole-genome sequencing data. The quality of these DNVs is high based on a series of quality metrics including number of DNVs per individual, percent of DNVs at CpG sites, and percent of DNVs phased to the paternal chromosome of origin. AVAILABILITY AND IMPLEMENTATION https://github.com/TNTurnerLab/HAT.
Collapse
Affiliation(s)
- Jeffrey K Ng
- Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Tychele N Turner
- Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA
| |
Collapse
|
17
|
Owusu R, Savarese M. Long-read sequencing improves diagnostic rate in neuromuscular disorders. ACTA MYOLOGICA : MYOPATHIES AND CARDIOMYOPATHIES : OFFICIAL JOURNAL OF THE MEDITERRANEAN SOCIETY OF MYOLOGY 2023; 42:123-128. [PMID: 38406378 PMCID: PMC10883326 DOI: 10.36185/2532-1900-394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 02/27/2024]
Abstract
Massive parallel sequencing methods, such as exome, genome, and targeted DNA sequencing, have aided molecular diagnosis of genetic diseases in the last 20 years. However, short-read sequencing methods still have several limitations, such inaccurate genome assembly, the inability to detect large structural variants, and variants located in hard-to-sequence regions like highly repetitive areas. The recently emerged PacBio single-molecule real-time (SMRT) and Oxford nanopore technology (ONT) long-read sequencing (LRS) methods have been shown to overcome most of these technical issues, leading to an increase in diagnostic rate. LRS methods are contributing to the detection of repeat expansions in novel disease-causing genes (e.g., ABCD3, NOTCH2NLC and RILPL1 causing an Oculopharyngodistal myopathy or PLIN4 causing a Myopathy with rimmed ubiquitin-positive autophagic vacuolation), of structural variants (e.g., in DMD), and of single nucleotide variants in repetitive regions (TTN and NEB). Moreover, these methods have simplified the characterization of the D4Z4 repeats in DUX4, facilitating the diagnosis of Facioscapulohumeral muscular dystrophy (FSHD). We review recent studies that have used either ONT or PacBio SMRT sequencing methods and discuss different types of variants that have been detected using these approaches in individuals with neuromuscular disorders.
Collapse
Affiliation(s)
| | - Marco Savarese
- Folkhälsan Research Center, Helsinki, Finland
- University of Helsinki, Faculty of Medicine, Helsinki, Finland
| |
Collapse
|
18
|
Bai S, Luo H, Tong H, Wu Y. Application and Technical Challenges in Design, Cloning, and Transfer of Large DNA. Bioengineering (Basel) 2023; 10:1425. [PMID: 38136016 PMCID: PMC10740618 DOI: 10.3390/bioengineering10121425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 11/23/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
In the field of synthetic biology, rapid advancements in DNA assembly and editing have made it possible to manipulate large DNA, even entire genomes. These advancements have facilitated the introduction of long metabolic pathways, the creation of large-scale disease models, and the design and assembly of synthetic mega-chromosomes. Generally, the introduction of large DNA in host cells encompasses three critical steps: design-cloning-transfer. This review provides a comprehensive overview of the three key steps involved in large DNA transfer to advance the field of synthetic genomics and large DNA engineering.
Collapse
Affiliation(s)
- Song Bai
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| | - Han Luo
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| | - Hanze Tong
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| | - Yi Wu
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin 300072, China
| |
Collapse
|
19
|
Chaisson MJP, Sulovari A, Valdmanis PN, Miller DE, Eichler EE. Advances in the discovery and analyses of human tandem repeats. Emerg Top Life Sci 2023; 7:361-381. [PMID: 37905568 PMCID: PMC10806765 DOI: 10.1042/etls20230074] [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: 06/12/2023] [Revised: 10/18/2023] [Accepted: 10/18/2023] [Indexed: 11/02/2023]
Abstract
Long-read sequencing platforms provide unparalleled access to the structure and composition of all classes of tandemly repeated DNA from STRs to satellite arrays. This review summarizes our current understanding of their organization within the human genome, their importance with respect to disease, as well as the advances and challenges in understanding their genetic diversity and functional effects. Novel computational methods are being developed to visualize and associate these complex patterns of human variation with disease, expression, and epigenetic differences. We predict accurate characterization of this repeat-rich form of human variation will become increasingly relevant to both basic and clinical human genetics.
Collapse
Affiliation(s)
- Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, U.S.A
- The Genomic and Epigenomic Regulation Program, USC Norris Cancer Center, University of Southern California, Los Angeles, CA 90089, U.S.A
| | - Arvis Sulovari
- Computational Biology, Cajal Neuroscience Inc, Seattle, WA 98102, U.S.A
| | - Paul N Valdmanis
- Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA 98195, U.S.A
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, U.S.A
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, U.S.A
| | - Danny E Miller
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, U.S.A
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA 98195, U.S.A
- Department of Pediatrics, University of Washington, Seattle, WA 98195, U.S.A
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, U.S.A
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, U.S.A
| |
Collapse
|
20
|
Pagnamenta AT, Camps C, Giacopuzzi E, Taylor JM, Hashim M, Calpena E, Kaisaki PJ, Hashimoto A, Yu J, Sanders E, Schwessinger R, Hughes JR, Lunter G, Dreau H, Ferla M, Lange L, Kesim Y, Ragoussis V, Vavoulis DV, Allroggen H, Ansorge O, Babbs C, Banka S, Baños-Piñero B, Beeson D, Ben-Ami T, Bennett DL, Bento C, Blair E, Brasch-Andersen C, Bull KR, Cario H, Cilliers D, Conti V, Davies EG, Dhalla F, Dacal BD, Dong Y, Dunford JE, Guerrini R, Harris AL, Hartley J, Hollander G, Javaid K, Kane M, Kelly D, Kelly D, Knight SJL, Kreins AY, Kvikstad EM, Langman CB, Lester T, Lines KE, Lord SR, Lu X, Mansour S, Manzur A, Maroofian R, Marsden B, Mason J, McGowan SJ, Mei D, Mlcochova H, Murakami Y, Németh AH, Okoli S, Ormondroyd E, Ousager LB, Palace J, Patel SY, Pentony MM, Pugh C, Rad A, Ramesh A, Riva SG, Roberts I, Roy N, Salminen O, Schilling KD, Scott C, Sen A, Smith C, Stevenson M, Thakker RV, Twigg SRF, Uhlig HH, van Wijk R, Vona B, Wall S, Wang J, Watkins H, Zak J, Schuh AH, Kini U, Wilkie AOM, Popitsch N, Taylor JC. Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases. Genome Med 2023; 15:94. [PMID: 37946251 PMCID: PMC10636885 DOI: 10.1186/s13073-023-01240-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 09/27/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. METHODS We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. RESULTS Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. CONCLUSIONS Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.
Collapse
Affiliation(s)
- Alistair T Pagnamenta
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Carme Camps
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Edoardo Giacopuzzi
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Human Technopole, Viale Rita Levi Montalcini 1, 20157, Milan, Italy
| | - John M Taylor
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Mona Hashim
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Eduardo Calpena
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Pamela J Kaisaki
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Akiko Hashimoto
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Jing Yu
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Edward Sanders
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Ron Schwessinger
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Jim R Hughes
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Gerton Lunter
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- University Medical Center Groningen, Groningen University, PO Box 72, 9700 AB, Groningen, The Netherlands
| | - Helene Dreau
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Matteo Ferla
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Lukas Lange
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Yesim Kesim
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Vassilis Ragoussis
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Dimitrios V Vavoulis
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Holger Allroggen
- Neurosciences Department, UHCW NHS Trust, Clifford Bridge Road, Coventry, CV2 2DX, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Christian Babbs
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Siddharth Banka
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Oxford Road, Manchester, M13 9WL, UK
| | - Benito Baños-Piñero
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - David Beeson
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Tal Ben-Ami
- Pediatric Hematology-Oncology Unit, Kaplan Medical Center, Rehovot, Israel
| | - David L Bennett
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Celeste Bento
- Hematology Department, Hospitais da Universidade de Coimbra, Coimbra, Portugal
| | - Edward Blair
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Charlotte Brasch-Andersen
- Department of Clinical Genetics, Odense University Hospital and Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Katherine R Bull
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Holger Cario
- Department of Pediatrics and Adolescent Medicine, University Medical Center, Eythstrasse 24, 89075, Ulm, Germany
| | - Deirdre Cilliers
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Valerio Conti
- Neuroscience Department, Meyer Children's Hospital IRCCS, Viale Pieraccini 24, 50139, Florence, Italy
| | - E Graham Davies
- Department of Immunology, Great Ormond Street Hospital for Children NHS Trust and UCL Great Ormond Street Institute of Child Health, Zayed Centre for Research, 2Nd Floor, 20C Guilford Street, London, WC1N 1DZ, UK
| | - Fatima Dhalla
- Department of Paediatrics, Institute of Developmental and Regenerative Medicine, IMS-Tetsuya Nakamura Building, Old Road Campus, Roosevelt Drive, Oxford, OX3 7TY, UK
| | - Beatriz Diez Dacal
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Yin Dong
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - James E Dunford
- Oxford NIHR Musculoskeletal BRC and Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Old Road, Oxford, OX3 7HE, UK
| | - Renzo Guerrini
- Neuroscience Department, Meyer Children's Hospital IRCCS, Viale Pieraccini 24, 50139, Florence, Italy
| | - Adrian L Harris
- Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Jane Hartley
- Liver Unit, Birmingham Women's & Children's Hospital and University of Birmingham, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Georg Hollander
- Department of Paediatrics, University of Oxford, Level 2, Children's Hospital, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Kassim Javaid
- Oxford NIHR Musculoskeletal BRC and Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Old Road, Oxford, OX3 7HE, UK
| | - Maureen Kane
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Pharmacy Hall North, Room 731, 20 N. Pine Street, Baltimore, MD, 21201, USA
| | - Deirdre Kelly
- Liver Unit, Birmingham Women's & Children's Hospital and University of Birmingham, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Dominic Kelly
- Children's Hospital, OUH NHS Foundation Trust, NIHR Oxford BRC, Headley Way, Oxford, OX3 9DU, UK
| | - Samantha J L Knight
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Alexandra Y Kreins
- Department of Immunology, Great Ormond Street Hospital for Children NHS Trust and UCL Great Ormond Street Institute of Child Health, Zayed Centre for Research, 2Nd Floor, 20C Guilford Street, London, WC1N 1DZ, UK
| | - Erika M Kvikstad
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Craig B Langman
- Feinberg School of Medicine, Northwestern University, 211 E Chicago Avenue, Chicago, IL, MS37, USA
| | - Tracy Lester
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Kate E Lines
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- University of Oxford, Academic Endocrine Unit, OCDEM, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Simon R Lord
- Early Phase Clinical Trials Unit, Department of Oncology, University of Oxford, Cancer and Haematology Centre, Level 2 Administration Area, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Xin Lu
- Nuffield Department of Clinical Medicine, Ludwig Institute for Cancer Research, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Sahar Mansour
- St George's University Hospitals NHS Foundation Trust, Blackshore Road, Tooting, London, SW17 0QT, UK
| | - Adnan Manzur
- MRC Centre for Neuromuscular Diseases, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK
| | - Reza Maroofian
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, WC1N 3BG, UK
| | - Brian Marsden
- Nuffield Department of Medicine, Kennedy Institute, University of Oxford, Oxford, OX3 7BN, UK
| | - Joanne Mason
- Yourgene Health Headquarters, Skelton House, Lloyd Street North, Manchester Science Park, Manchester, M15 6SH, UK
| | - Simon J McGowan
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Davide Mei
- Neuroscience Department, Meyer Children's Hospital IRCCS, Viale Pieraccini 24, 50139, Florence, Italy
| | - Hana Mlcochova
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Yoshiko Murakami
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Steven Okoli
- Imperial College NHS Trust, Department of Haematology, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK
| | - Elizabeth Ormondroyd
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- University of Oxford, Level 6 West Wing, Oxford, OX3 9DU, JR, UK
| | - Lilian Bomme Ousager
- Department of Clinical Genetics, Odense University Hospital and Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Smita Y Patel
- Clinical Immunology, John Radcliffe Hospital, Level 4A, Oxford, OX3 9DU, UK
| | - Melissa M Pentony
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Chris Pugh
- Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Aboulfazl Rad
- Department of Otolaryngology-Head & Neck Surgery, Tübingen Hearing Research Centre, Eberhard Karls University, Elfriede-Aulhorn-Str. 5, 72076, Tübingen, Germany
| | - Archana Ramesh
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Simone G Riva
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Irene Roberts
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- Department of Paediatrics, University of Oxford, Level 2, Children's Hospital, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Noémi Roy
- Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Level 4, Haematology, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Outi Salminen
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Kyleen D Schilling
- Ann & Robert H. Lurie Children's Hospital of Chicago, 225 E Chicago Avenue, Chicago, IL, 60611, USA
| | - Caroline Scott
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Arjune Sen
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Conrad Smith
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Mark Stevenson
- University of Oxford, Academic Endocrine Unit, OCDEM, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Rajesh V Thakker
- University of Oxford, Academic Endocrine Unit, OCDEM, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Stephen R F Twigg
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Holm H Uhlig
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Paediatrics, University of Oxford, Level 2, Children's Hospital, John Radcliffe Hospital, Oxford, OX3 9DU, UK
- Translational Gastroenterology Unit, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Richard van Wijk
- UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Barbara Vona
- Department of Otolaryngology-Head & Neck Surgery, Tübingen Hearing Research Centre, Eberhard Karls University, Elfriede-Aulhorn-Str. 5, 72076, Tübingen, Germany
- Institute of Human Genetics, University Medical Center Göttingen, Heinrich-Düker-Weg 12, 37073, Göttingen, Germany
- Institute for Auditory Neuroscience and InnerEarLab, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Germany
| | - Steven Wall
- Oxford Craniofacial Unit, John Radcliffe Hospital, Level LG1, West Wing, Oxford, OX3 9DU, UK
| | - Jing Wang
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Hugh Watkins
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- University of Oxford, Level 6 West Wing, Oxford, OX3 9DU, JR, UK
| | - Jaroslav Zak
- Nuffield Department of Clinical Medicine, Ludwig Institute for Cancer Research, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Immunology and Microbiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA
| | - Anna H Schuh
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Usha Kini
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Andrew O M Wilkie
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Niko Popitsch
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Biochemistry and Cell Biology, Max Perutz Labs, University of Vienna, Vienna BioCenter(VBC), Dr.-Bohr-Gasse 9, 1030, Vienna, Austria
| | - Jenny C Taylor
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK.
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK.
| |
Collapse
|
21
|
English A, Dolzhenko E, Jam HZ, Mckenzie S, Olson ND, De Coster W, Park J, Gu B, Wagner J, Eberle MA, Gymrek M, Chaisson MJP, Zook JM, Sedlazeck FJ. Benchmarking of small and large variants across tandem repeats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.29.564632. [PMID: 37961319 PMCID: PMC10634962 DOI: 10.1101/2023.10.29.564632] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Tandem repeats (TRs) are highly polymorphic in the human genome, have thousands of associated molecular traits, and are linked to over 60 disease phenotypes. However, their complexity often excludes them from at-scale studies due to challenges with variant calling, representation, and lack of a genome-wide standard. To promote TR methods development, we create a comprehensive catalog of TR regions and explore its properties across 86 samples. We then curate variants from the GIAB HG002 individual to create a tandem repeat benchmark. We also present a variant comparison method that handles small and large alleles and varying allelic representation. The 8.1% of the genome covered by the TR catalog holds ∼24.9% of variants per individual, including 124,728 small and 17,988 large variants for the GIAB HG002 TR benchmark. We work with the GIAB community to demonstrate the utility of this benchmark across short and long read technologies.
Collapse
|
22
|
Peng XP, Al-Ddafari MS, Caballero-Oteyza A, El Mezouar C, Mrovecova P, Dib SE, Massen Z, Smahi MCE, Faiza A, Hassaïne RT, Lefranc G, Aribi M, Grimbacher B. Next generation sequencing (NGS)-based approach to diagnosing Algerian patients with suspected inborn errors of immunity (IEIs). Clin Immunol 2023; 256:109758. [PMID: 37678716 DOI: 10.1016/j.clim.2023.109758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/23/2023] [Accepted: 09/02/2023] [Indexed: 09/09/2023]
Abstract
The advent of next-generation sequencing (NGS) technologies has greatly expanded our understanding of both the clinical spectra and genetic landscape of inborn errors of immunity (IEIs). Endogamous populations may be enriched for unique, ancestry-specific disease-causing variants, a consideration that significantly impacts molecular testing and analysis strategies. Herein, we report on the application of a 2-step NGS-based testing approach beginning with targeted gene panels (TGPs) tailored to specific IEI subtypes and reflexing to whole exome sequencing (WES) if negative for Northwest Algerian patients with suspected IEIs. Our overall diagnostic yield of 57% is comparable to others broadly applying short-read NGS to IEI detection, but data from our localized cohort show some similarities and differences from NGS studies performed on larger regional IEI cohorts. This suggests the importance of tailoring diagnostic strategies to local demographics and needs, but also highlights ongoing concerns inherent to the application of genomics for clinical IEI diagnostics.
Collapse
Affiliation(s)
- Xiao P Peng
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Germany; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
| | - Moudjahed Saleh Al-Ddafari
- Laboratory of Applied Molecular Biology and Immunology, W0414100, University of Tlemcen, Algeria; Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Germany
| | - Andres Caballero-Oteyza
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Germany; RESIST - Cluster of Excellence 2155 to Hanover Medical School, Satellite Center Freiburg, Germany
| | - Chahrazed El Mezouar
- Laboratory of Applied Molecular Biology and Immunology, W0414100, University of Tlemcen, Algeria; Pediatric Department, Medical Center University of Tlemcen, Faculty of Medicine, University of Tlemcen, Algeria
| | - Pavla Mrovecova
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Germany
| | - Saad Eddin Dib
- Pediatric Department, Medical Center University of Tlemcen, Faculty of Medicine, University of Tlemcen, Algeria
| | - Zoheir Massen
- Pediatric Department, Medical Center University of Tlemcen, Faculty of Medicine, University of Tlemcen, Algeria
| | - Mohammed Chems-Eddine Smahi
- Laboratory of Applied Molecular Biology and Immunology, W0414100, University of Tlemcen, Algeria; Specialized Mother-Child Hospital of Tlemcen, Department of Neonatology, Faculty of Medicine, University of Tlemcen, Algeria
| | - Alddafari Faiza
- Department of Internal Medicine, Medical Center University of Tlemcen, Faculty of Medicine, University of Tlemcen, Tlemcen, Algeria
| | | | - Gérard Lefranc
- Institute of Human Genetics, UMR 9002 CNRS-University of Montpellier, France
| | - Mourad Aribi
- Laboratory of Applied Molecular Biology and Immunology, W0414100, University of Tlemcen, Algeria.
| | - Bodo Grimbacher
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Germany; DZIF - German Center for Infection Research, Satellite Center Freiburg, Germany; CIBSS - Centre for Integrative Biological Signalling Studies, Albert-Ludwigs University, Freiburg, Germany; RESIST - Cluster of Excellence 2155 to Hanover Medical School, Satellite Center Freiburg, Germany.
| |
Collapse
|
23
|
Hansen MH, Cédile O, Kjeldsen MLG, Thomassen M, Preiss B, von Neuhoff N, Abildgaard N, Nyvold CG. Toward Cytogenomics: Technical Assessment of Long-Read Nanopore Whole-Genome Sequencing for Detecting Large Chromosomal Alterations in Mantle Cell Lymphoma. J Mol Diagn 2023; 25:796-805. [PMID: 37683892 DOI: 10.1016/j.jmoldx.2023.08.004] [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: 11/23/2022] [Revised: 06/20/2023] [Accepted: 08/14/2023] [Indexed: 09/10/2023] Open
Abstract
The current advances and success of next-generation sequencing hold the potential for the transition of cancer cytogenetics toward comprehensive cytogenomics. However, the conventional use of short reads impedes the resolution of chromosomal aberrations. Thus, this study evaluated the detection and reproducibility of extensive copy number alterations and chromosomal translocations using long-read Oxford Nanopore Technologies whole-genome sequencing compared with short-read Illumina sequencing. Using the mantle cell lymphoma cell line Granta-519, almost 99% copy-number reproducibility at the 100-kilobase resolution between replicates was demonstrated, with 98% concordance to Illumina. Collectively, the performance of copy number calling from 1.5 million to 7.5 million long reads was comparable to 1 billion Illumina-based reads (50× coverage). Expectedly, the long-read resolution of canonical translocation t(11;14)(q13;q32) was superior, with a sequence similarity of 89% to the already published CCND1/IGH junction (9× coverage), spanning up to 69 kilobases. The cytogenetic profile of Granta-519 was in general agreement with the literature and karyotype, although several differences remained unresolved. In conclusion, contemporary long-read sequencing is primed for future cytogenomics or sequencing-guided cytogenetics. The combined strength of long- and short-read sequencing is apparent, where the high-precision junctional mapping complements and splits paired-end reads. The potential is emphasized by the flexible single-sample genomic data acquisition of Oxford Nanopore Technologies with the high resolution of allelic imbalances using Illumina short-read sequencing.
Collapse
Affiliation(s)
- Marcus H Hansen
- Hematology-Pathology Research Laboratory, Research Unit of Hematology and Research Unit of Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark; Department of Hematology, Odense University Hospital, Odense, Denmark.
| | - Oriane Cédile
- Hematology-Pathology Research Laboratory, Research Unit of Hematology and Research Unit of Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark; Department of Hematology, Odense University Hospital, Odense, Denmark; OPEN, Odense Patient Data Explorative Network, Odense University Hospital, Odense, Denmark
| | - Marie L G Kjeldsen
- Hematology-Pathology Research Laboratory, Research Unit of Hematology and Research Unit of Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark
| | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Birgitte Preiss
- Hematology-Pathology Research Laboratory, Research Unit of Hematology and Research Unit of Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark; Department of Pathology, Odense University Hospital, Odense, Denmark
| | - Nils von Neuhoff
- Department of Pediatric Hematology and Oncology, Essen University Hospital and University of Duisburg-Essen, Essen, Germany
| | - Niels Abildgaard
- Hematology-Pathology Research Laboratory, Research Unit of Hematology and Research Unit of Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark; Department of Hematology, Odense University Hospital, Odense, Denmark
| | - Charlotte G Nyvold
- Hematology-Pathology Research Laboratory, Research Unit of Hematology and Research Unit of Pathology, University of Southern Denmark and Odense University Hospital, Odense, Denmark; Department of Hematology, Odense University Hospital, Odense, Denmark; OPEN, Odense Patient Data Explorative Network, Odense University Hospital, Odense, Denmark
| |
Collapse
|
24
|
Steyaert W, Haer-Wigman L, Pfundt R, Hellebrekers D, Steehouwer M, Hampstead J, de Boer E, Stegmann A, Yntema H, Kamsteeg EJ, Brunner H, Hoischen A, Gilissen C. Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation. Nat Commun 2023; 14:6845. [PMID: 37891200 PMCID: PMC10611741 DOI: 10.1038/s41467-023-42531-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 10/13/2023] [Indexed: 10/29/2023] Open
Abstract
The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurately identifies single nucleotide variants and small insertions/deletions (SNVs/Indels), copy number variants and ectopic gene conversion events in duplicated genomic regions using whole-exome sequencing data. Application to a cohort of 41,755 exome samples yields 20,432 rare homozygous deletions and 2,529,791 rare SNVs/Indels, of which we show that 338,084 are due to gene conversion events. None of the SNVs/Indels are detectable using regular analysis techniques. Validation by high-fidelity long-read sequencing in 20 samples confirms >88% of called variants. Focusing on variation in known disease genes leads to a direct molecular diagnosis in 25 previously undiagnosed patients. Our method can readily be applied to existing exome data.
Collapse
Affiliation(s)
- Wouter Steyaert
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands
| | - Lonneke Haer-Wigman
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Rolph Pfundt
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Debby Hellebrekers
- Maastricht University Medical Center + , Department of Clinical Genetics, Maastricht, Netherlands
| | - Marloes Steehouwer
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Juliet Hampstead
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Elke de Boer
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Alexander Stegmann
- Maastricht University Medical Center + , Department of Clinical Genetics, Maastricht, Netherlands
| | - Helger Yntema
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Erik-Jan Kamsteeg
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
| | - Han Brunner
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Maastricht University Medical Center + , Department of Clinical Genetics, Maastricht, Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands
- Radboud University Medical Center, Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Nijmegen, Netherlands
| | - Christian Gilissen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands.
- Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands.
| |
Collapse
|
25
|
Bonaglia MC, Salvo E, Sironi M, Bertuzzo S, Errichiello E, Mattina T, Zuffardi O. Case Report: Decrypting an interchromosomal insertion associated with Marfan's syndrome: how optical genome mapping emphasizes the morbid burden of copy-neutral variants. Front Genet 2023; 14:1244983. [PMID: 37811140 PMCID: PMC10551147 DOI: 10.3389/fgene.2023.1244983] [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: 06/23/2023] [Accepted: 09/01/2023] [Indexed: 10/10/2023] Open
Abstract
Optical genome mapping (OGM), which allows analysis of ultra-high molecular weight (UHMW) DNA molecules, represents a response to the restriction created by short-read next-generation-sequencing, even in cases where the causative variant is a neutral copy-number-variant insensitive to quantitative investigations. This study aimed to provide a molecular diagnosis to a boy with Marfan syndrome (MFS) and intellectual disability (ID) carrying a de novo translocation involving chromosomes 3, 4, and 13 and a 1.7 Mb deletion at the breakpoint of chromosome 3. No FBN1 alteration explaining his Marfan phenotype was highlighted. UHMW gDNA was isolated from both the patient and his parents and processed using OGM. Genome assembly was followed by variant calling and annotation. Multiple strategies confirmed the results. The 3p deletion, which disrupted ROBO2, (MIM*602431) included three copy-neutral insertions. Two came from chromosome 13; the third contained 15q21.1, including the FBN1 from intron-45 onwards, thus explaining the MFS phenotype. We could not attribute the ID to a specific gene variant nor to the reshuffling of topologically associating domains (TADs). Our patient did not have vesicular reflux-2, as reported by missense alterations of ROBO2 (VUR2, MIM#610878), implying that reduced expression of all or some isoforms has a different effect than some of the point mutations. Indeed, the ROBO2 expression pattern and its role as an axon-guide suggests that its partial deletion is responsible for the patient's neurological phenotype. Conclusion: OGM testing 1) highlights copy-neutral variants that could remain invisible if no loss of heterozygosity is observed and 2) is mandatory before other molecular studies in the presence of any chromosomal rearrangement for an accurate genotype-phenotype relationship.
Collapse
Affiliation(s)
| | - Eliana Salvo
- Cytogenetics Laboratory, Scientific Institute, IRCCS E. Medea, Lecco, Italy
| | - Manuela Sironi
- Bioinformatics, Scientific Institute, IRCCS E. Medea, Lecco, Italy
| | - Sara Bertuzzo
- Cytogenetics Laboratory, Scientific Institute, IRCCS E. Medea, Lecco, Italy
| | - Edoardo Errichiello
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Neurogenetics Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Teresa Mattina
- Medical Genetics Unit, University of Catania, Catania, Italy
- Clinic G.B. Morgagni, Catania, Italy
| | - Orsetta Zuffardi
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
| |
Collapse
|
26
|
de Souza LM, de Oliveira ID, Sales FCS, da Costa AC, Campos KR, Abbud A, Guerra JM, Dos Santos Cirqueira Borges C, Takahashi CPFJ, de Araújo LJT. Technical comparison of MinIon and Illumina technologies for genotyping Chikungunya virus in clinical samples. J Genet Eng Biotechnol 2023; 21:88. [PMID: 37642827 PMCID: PMC10465416 DOI: 10.1186/s43141-023-00536-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 07/27/2023] [Indexed: 08/31/2023]
Abstract
New-generation sequencing (NGS) techniques have brought the opportunity for genomic monitoring of several microorganisms potentially relevant to public health. The establishment of different methods with different mechanisms provides a wide choice, taking into account several aspects. With that in mind, the present aim of the study was to compare basic genomic sequencing metrics that could potentially impact genotyping by nanopores from Oxford Nanopore Technologies and by synthesis from Illumina in clinical samples positive for Chikungunya (CHIKV). Among the metrics studied, running time, read production, and Q score were better represented in Illumina sequencing, while the MinIOn platform showed better response time and greater diversity of generated files. That said, it was possible to establish differences between the studied metrics in addition to verifying that the distinctions in the methods did not impact the identification of the CHIKV virus genotype.
Collapse
Affiliation(s)
- Leandro Menezes de Souza
- Centro de Patologia, Instituto Adolfo Lutz, Sao Paulo, Brazil
- Programa de Pós Graduação em Ciências da Saúde do Instituto de Assistência Médica ao Servidor Público Estadual - IAMSPE, Sao Paulo, Brazil
| | - Isabelle Dias de Oliveira
- Centro de Patologia, Instituto Adolfo Lutz, Sao Paulo, Brazil
- Programa de Pós Graduação em Ciências da Saúde do Instituto de Assistência Médica ao Servidor Público Estadual - IAMSPE, Sao Paulo, Brazil
| | - Flávia Cristina Silva Sales
- Departamento de Moléstias Infecciosas e Parasitárias, Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, Brazil
| | - Antonio Charlys da Costa
- Departamento de Moléstias Infecciosas e Parasitárias, Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, Brazil
| | | | - Adriano Abbud
- Centro de Respostas Rápidas, Instituto Adolfo Lutz, Sao Paulo, Brazil
| | | | | | | | - Leonardo José Tadeu de Araújo
- Centro de Patologia, Instituto Adolfo Lutz, Sao Paulo, Brazil.
- Programa de Pós Graduação em Ciências da Saúde do Instituto de Assistência Médica ao Servidor Público Estadual - IAMSPE, Sao Paulo, Brazil.
- Departamento de Moléstias Infecciosas e Parasitárias, Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, Sao Paulo, Brazil.
| |
Collapse
|
27
|
Hård J, Mold JE, Eisfeldt J, Tellgren-Roth C, Häggqvist S, Bunikis I, Contreras-Lopez O, Chin CS, Nordlund J, Rubin CJ, Feuk L, Michaëlsson J, Ameur A. Long-read whole-genome analysis of human single cells. Nat Commun 2023; 14:5164. [PMID: 37620373 PMCID: PMC10449900 DOI: 10.1038/s41467-023-40898-3] [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: 02/06/2023] [Accepted: 08/07/2023] [Indexed: 08/26/2023] Open
Abstract
Long-read sequencing has dramatically increased our understanding of human genome variation. Here, we demonstrate that long-read technology can give new insights into the genomic architecture of individual cells. Clonally expanded CD8+ T-cells from a human donor were subjected to droplet-based multiple displacement amplification (dMDA) to generate long molecules with reduced bias. PacBio sequencing generated up to 40% genome coverage per single-cell, enabling detection of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, also in regions inaccessible by short reads. 28 somatic SNVs were detected, including one case of mitochondrial heteroplasmy. 5473 high-confidence SVs/cell were discovered, a sixteen-fold increase compared to Illumina-based results from clonally related cells. Single-cell de novo assembly generated a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, our work shows the promise of long-read sequencing toward characterization of the full spectrum of genetic variation in single cells.
Collapse
Affiliation(s)
- Joanna Hård
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden.
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
- ETH AI Center, ETH Zurich, Zurich, Switzerland.
| | - Jeff E Mold
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Christian Tellgren-Roth
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Susana Häggqvist
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Ignas Bunikis
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | | | | | - Jessica Nordlund
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Carl-Johan Rubin
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Lars Feuk
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Jakob Michaëlsson
- Center for Infectious Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Adam Ameur
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
| |
Collapse
|
28
|
Hadar N, Narkis G, Amar S, Varnavsky M, Palti GC, Safran A, Birk OS. STRavinsky STR database and PGTailor PGT tool demonstrate superiority of CHM13-T2T over hg38 and hg19 for STR-based applications. Eur J Hum Genet 2023; 31:738-743. [PMID: 37055538 PMCID: PMC10325972 DOI: 10.1038/s41431-023-01352-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 03/18/2023] [Accepted: 03/23/2023] [Indexed: 04/15/2023] Open
Abstract
Short-Tandem-Repeats (STRs) have long been studied for possible roles in biological phenomena, and are utilized in multiple applications such as forensics, evolutionary studies and pre-implantation-genetic-testing (PGT). The two reference genomes most used by clinicians and researchers are GRCh37/hg19 and GRCh38/hg38, both constructed using mainly short-read-sequencing (SRS) in which all-STR-containing-reads cannot be assembled to the reference genome. With the introduction of long-read-sequencing (LRS) methods and the generation of the CHM13 reference genome, also known as T2T, many previously unmapped STRs were finally localized within the human genome. We generated STRavinsky, a compact STR database for three reference genomes, including T2T. We proceeded to demonstrate the advantages of T2T over hg19 and hg38, identifying nearly double the number of STRs throughout all chromosomes. Through STRavinsky, providing a resolution down to a specific genomic coordinate, we demonstrated extreme propensity of TGGAA repeats in p arms of acrocentric chromosomes, substantially corroborating early molecular studies suggesting a possible role in formation of Robertsonian translocations. Moreover, we delineated unique propensity of TGGAA repeats specifically in chromosome 16q11.2 and in 9q12. Finally, we harness the superior capabilities of T2T and STRavinsky to generate PGTailor, a novel web application dramatically facilitating design of STR-based PGT tests in mere minutes.
Collapse
Affiliation(s)
- Noam Hadar
- Morris Kahn Laboratory of Human Genetics, NIBN and Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Ginat Narkis
- Morris Kahn Laboratory of Human Genetics, NIBN and Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel
- Genetics Institute, Soroka Medical Center, Beer Sheva, Israel
| | - Shirly Amar
- Genetics Institute, Soroka Medical Center, Beer Sheva, Israel
| | | | | | - Amit Safran
- Morris Kahn Laboratory of Human Genetics, NIBN and Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel
| | - Ohad S Birk
- Morris Kahn Laboratory of Human Genetics, NIBN and Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel.
- Genetics Institute, Soroka Medical Center, Beer Sheva, Israel.
| |
Collapse
|
29
|
Yang S, Kim SH, Kang M, Joo JY. Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges. Arch Pharm Res 2023:10.1007/s12272-023-01450-5. [PMID: 37261600 DOI: 10.1007/s12272-023-01450-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/26/2023] [Indexed: 06/02/2023]
Abstract
The relevant study of transcriptome-wide variations and neurological disorders in the evolved field of genomic data science is on the rise. Deep learning has been highlighted utilizing algorithms on massive amounts of data in a human-like manner, and is expected to predict the dependency or druggability of hidden mutations within the genome. Enormous mutational variants in coding and noncoding transcripts have been discovered along the genome by far, despite of the fine-tuned genetic proofreading machinery. These variants could be capable of inducing various pathological conditions, including neurological disorders, which require lifelong care. Several limitations and questions emerge, including the use of conventional processes via limited patient-driven sequence acquisitions and decoding-based inferences as well as how rare variants can be deduced as a population-specific etiology. These puzzles require harnessing of advanced systems for precise disease prediction, drug development and drug applications. In this review, we summarize the pathophysiological discoveries of pathogenic variants in both coding and noncoding transcripts in neurological disorders, and the current advantage of deep learning applications. In addition, we discuss the challenges encountered and how to outperform them with advancing interpretation.
Collapse
Affiliation(s)
- Sumin Yang
- Department of Pharmacy, College of Pharmacy, Hanyang University, Rm 407, Bldg.42, 55 Hanyangdaehak-Ro, Sangnok-Gu Ansan, Ansan, Gyeonggi-Do, 15588, Republic of Korea
| | - Sung-Hyun Kim
- Department of Pharmacy, College of Pharmacy, Hanyang University, Rm 407, Bldg.42, 55 Hanyangdaehak-Ro, Sangnok-Gu Ansan, Ansan, Gyeonggi-Do, 15588, Republic of Korea
| | - Mingon Kang
- Department of Computer Science, University of Nevada, Las Vegas, NV, 89154, USA
| | - Jae-Yeol Joo
- Department of Pharmacy, College of Pharmacy, Hanyang University, Rm 407, Bldg.42, 55 Hanyangdaehak-Ro, Sangnok-Gu Ansan, Ansan, Gyeonggi-Do, 15588, Republic of Korea.
| |
Collapse
|
30
|
Vollger MR, Dishuck PC, Harvey WT, DeWitt WS, Guitart X, Goldberg ME, Rozanski AN, Lucas J, Asri M, Munson KM, Lewis AP, Hoekzema K, Logsdon GA, Porubsky D, Paten B, Harris K, Hsieh P, Eichler EE. Increased mutation and gene conversion within human segmental duplications. Nature 2023; 617:325-334. [PMID: 37165237 PMCID: PMC10172114 DOI: 10.1038/s41586-023-05895-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 02/28/2023] [Indexed: 05/12/2023]
Abstract
Single-nucleotide variants (SNVs) in segmental duplications (SDs) have not been systematically assessed because of the limitations of mapping short-read sequencing data1,2. Here we constructed 1:1 unambiguous alignments spanning high-identity SDs across 102 human haplotypes and compared the pattern of SNVs between unique and duplicated regions3,4. We find that human SNVs are elevated 60% in SDs compared to unique regions and estimate that at least 23% of this increase is due to interlocus gene conversion (IGC) with up to 4.3 megabase pairs of SD sequence converted on average per human haplotype. We develop a genome-wide map of IGC donors and acceptors, including 498 acceptor and 454 donor hotspots affecting the exons of about 800 protein-coding genes. These include 171 genes that have 'relocated' on average 1.61 megabase pairs in a subset of human haplotypes. Using a coalescent framework, we show that SD regions are slightly evolutionarily older when compared to unique sequences, probably owing to IGC. SNVs in SDs, however, show a distinct mutational spectrum: a 27.1% increase in transversions that convert cytosine to guanine or the reverse across all triplet contexts and a 7.6% reduction in the frequency of CpG-associated mutations when compared to unique DNA. We reason that these distinct mutational properties help to maintain an overall higher GC content of SD DNA compared to that of unique DNA, probably driven by GC-biased conversion between paralogous sequences5,6.
Collapse
Affiliation(s)
- Mitchell R Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Division of Medical Genetics, 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
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William S DeWitt
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA
| | - Xavi Guitart
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Michael E Goldberg
- 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
| | - Julian Lucas
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, 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
| | - 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
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Kelley Harris
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 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.
| |
Collapse
|
31
|
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.
Collapse
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
| |
Collapse
|
32
|
Bernkopf M, Abdullah UB, Bush SJ, Wood KA, Ghaffari S, Giannoulatou E, Koelling N, Maher GJ, Thibaut LM, Williams J, Blair EM, Kelly FB, Bloss A, Burkitt-Wright E, Canham N, Deng AT, Dixit A, Eason J, Elmslie F, Gardham A, Hay E, Holder M, Homfray T, Hurst JA, Johnson D, Jones WD, Kini U, Kivuva E, Kumar A, Lees MM, Leitch HG, Morton JEV, Németh AH, Ramachandrappa S, Saunders K, Shears DJ, Side L, Splitt M, Stewart A, Stewart H, Suri M, Clouston P, Davies RW, Wilkie AOM, Goriely A. Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation. Nat Commun 2023; 14:853. [PMID: 36792598 PMCID: PMC9932158 DOI: 10.1038/s41467-023-36606-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 02/03/2023] [Indexed: 02/17/2023] Open
Abstract
Following the diagnosis of a paediatric disorder caused by an apparently de novo mutation, a recurrence risk of 1-2% is frequently quoted due to the possibility of parental germline mosaicism; but for any specific couple, this figure is usually incorrect. We present a systematic approach to providing individualized recurrence risk. By combining locus-specific sequencing of multiple tissues to detect occult mosaicism with long-read sequencing to determine the parent-of-origin of the mutation, we show that we can stratify the majority of couples into one of seven discrete categories associated with substantially different risks to future offspring. Among 58 families with a single affected offspring (representing 59 de novo mutations in 49 genes), the recurrence risk for 35 (59%) was decreased below 0.1%, but increased owing to parental mixed mosaicism for 5 (9%)-that could be quantified in semen for paternal cases (recurrence risks of 5.6-12.1%). Implementation of this strategy offers the prospect of driving a major transformation in the practice of genetic counselling.
Collapse
Affiliation(s)
- Marie Bernkopf
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- St. Anna Children's Cancer Research Institute (CCRI), Vienna, Austria
| | - Ummi B Abdullah
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Stephen J Bush
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Katherine A Wood
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Sahar Ghaffari
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | | | - Nils Koelling
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Geoffrey J Maher
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Loïc M Thibaut
- Centre for Population Genomics, Garvan Institute of Medical Research, UNSW Sydney, Sydney, NSW, Australia
| | - Jonathan Williams
- Oxford Genetics Laboratories, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Edward M Blair
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Fiona Blanco Kelly
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Angela Bloss
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Emma Burkitt-Wright
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, University of Manchester, Manchester, UK
| | - Natalie Canham
- Department of Clinical Genetics, Liverpool Women's NHS Foundation Trust, Liverpool, UK
| | - Alexander T Deng
- Clinical Genetics Department, Guy's Hospital, Guy's & St Thomas' NHS Foundation Trust, London, UK
| | - Abhijit Dixit
- Nottingham Regional Genetics Service, City Hospital Campus, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Jacqueline Eason
- Nottingham Regional Genetics Service, City Hospital Campus, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Frances Elmslie
- South West Thames Regional Genetics Service, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Alice Gardham
- North West Thames Regional Genetics Service, London North West University Healthcare NHS Trust, Northwick Park Hospital, Harrow, UK
| | - Eleanor Hay
- North East Thames Regional Genetics Service, Great Ormond Street Hospital NHS Foundation Trust, London, UK
| | - Muriel Holder
- Clinical Genetics Department, Guy's Hospital, Guy's & St Thomas' NHS Foundation Trust, London, UK
| | - Tessa Homfray
- South West Thames Regional Genetics Service, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Jane A Hurst
- North East Thames Regional Genetics Service, Great Ormond Street Hospital NHS Foundation Trust, London, UK
| | - Diana Johnson
- Sheffield Clinical Genetics Service, Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | - Wendy D Jones
- North East Thames Regional Genetics Service, Great Ormond Street Hospital NHS Foundation Trust, London, UK
| | - Usha Kini
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Emma Kivuva
- Clinical Genetics, Royal Devon & Exeter Hospital (Heavitree), Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Ajith Kumar
- North East Thames Regional Genetics Service, Great Ormond Street Hospital NHS Foundation Trust, London, UK
| | - Melissa M Lees
- North East Thames Regional Genetics Service, Great Ormond Street Hospital NHS Foundation Trust, London, UK
| | - Harry G Leitch
- Nottingham Regional Genetics Service, City Hospital Campus, Nottingham University Hospitals NHS Trust, Nottingham, UK
- MRC London Institute of Medical Sciences, Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Jenny E V Morton
- West Midlands Regional Clinical Genetics Service and Birmingham Health Partners, Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, UK
| | - Andrea H Németh
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Shwetha Ramachandrappa
- Clinical Genetics Department, Guy's Hospital, Guy's & St Thomas' NHS Foundation Trust, London, UK
| | - Katherine Saunders
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Deborah J Shears
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Lucy Side
- Wessex Clinical Genetics Service, University Hospital Southampton, Princess Anne Hospital, Southampton, UK
| | - Miranda Splitt
- Northern Genetics Service, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
| | - Alison Stewart
- Sheffield Clinical Genetics Service, Sheffield Children's NHS Foundation Trust, Sheffield, UK
| | - Helen Stewart
- Oxford Centre for Genomic Medicine, Nuffield Orthopaedic Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Mohnish Suri
- Nottingham Regional Genetics Service, City Hospital Campus, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Penny Clouston
- Oxford Genetics Laboratories, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Andrew O M Wilkie
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Anne Goriely
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Oxford, UK.
| |
Collapse
|
33
|
The Genetics of Intellectual Disability. Brain Sci 2023; 13:brainsci13020231. [PMID: 36831774 PMCID: PMC9953898 DOI: 10.3390/brainsci13020231] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/23/2022] [Accepted: 01/16/2023] [Indexed: 02/03/2023] Open
Abstract
Intellectual disability (ID) has a prevalence of ~2-3% in the general population, having a large societal impact. The underlying cause of ID is largely of genetic origin; however, identifying this genetic cause has in the past often led to long diagnostic Odysseys. Over the past decades, improvements in genetic diagnostic technologies and strategies have led to these causes being more and more detectable: from cytogenetic analysis in 1959, we moved in the first decade of the 21st century from genomic microarrays with a diagnostic yield of ~20% to next-generation sequencing platforms with a yield of up to 60%. In this review, we discuss these various developments, as well as their associated challenges and implications for the field of ID, which highlight the revolutionizing shift in clinical practice from a phenotype-first into genotype-first approach.
Collapse
|
34
|
Ng JK, Turner TN. HAT: de novo variant calling for highly accurate short-read and long-read sequencing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.27.525940. [PMID: 36747667 PMCID: PMC9900919 DOI: 10.1101/2023.01.27.525940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Motivation de novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics studies (e.g., autism, epilepsy). Results HAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow begins with aligned read data (i.e., CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from short-read whole-exome sequencing, short-read whole-genome sequencing, and highly accurate long-read sequencing data.
Collapse
Affiliation(s)
- Jeffrey K. Ng
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tychele N. Turner
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| |
Collapse
|
35
|
Considering the Genetic Architecture of Hypoplastic Left Heart Syndrome. J Cardiovasc Dev Dis 2022; 9:jcdd9100315. [PMID: 36286267 PMCID: PMC9604382 DOI: 10.3390/jcdd9100315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/16/2022] [Accepted: 09/16/2022] [Indexed: 11/24/2022] Open
Abstract
Hypoplastic left heart syndrome (HLHS) is among the most severe cardiovascular malformations and understanding its causes is crucial to making progress in prevention and treatment. Genetic analysis is a broadly useful tool for dissecting complex causal mechanisms and it is playing a significant role in HLHS research. However, unlike classical Mendelian disorders where a relatively small number of genes are largely determinative of the occurrence and severity of the disease, the picture in HLHS is complex. De novo single-gene and copy number variant (CNV) disorders make an important contribution, but there is emerging evidence for causal contributions from lower penetrance and common variation. Integrating this emerging knowledge into clinical diagnostics and translating the findings into effective prevention and treatment remain challenges for the future.
Collapse
|
36
|
Long-Read Sequencing Allows Increased Detection of De Novo Mutations. Am J Med Genet A 2022; 188:2523-2524. [PMID: 35962729 DOI: 10.1002/ajmg.a.62316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/23/2022] [Accepted: 08/01/2022] [Indexed: 01/24/2023]
|