51
|
Hübner S. Are we there yet? Driving the road to evolutionary graph-pangenomics. CURRENT OPINION IN PLANT BIOLOGY 2022; 66:102195. [PMID: 35217472 DOI: 10.1016/j.pbi.2022.102195] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
With increase in the number of sequenced genomes, it is now recognized that graph-based pangenomes can provide a comprehensive platform to study diversity in a population or species, from point mutations to large chromosomal rearrangements. By incorporating concepts from graph theory, a graph-pangenome can be studied directly to identify genomic regions and genes that underlie important evolutionary processes and traits. Here, I discuss how basic concepts in graph theory can be implemented to address questions in evolutionary genomics and guide future breeding efforts. Despite its compelling versatility, a graph-pangenome assembly is still challenging especially in species with large complex genomes. As technology is rapidly improving, the graph-pangenome is expected to become a central platform in genomics studies and applications. Thus, development of tools and methods that exploit the graph structure are urged to pave the route to evolutionary graph-pangenomics.
Collapse
Affiliation(s)
- Sariel Hübner
- Galilee Research Institute (Migal), Tel-Hai Academic College, Upper Galilee, 12210, Israel.
| |
Collapse
|
52
|
Ebler J, Ebert P, Clarke WE, Rausch T, Audano PA, Houwaart T, Mao Y, Korbel JO, Eichler EE, Zody MC, Dilthey AT, Marschall T. Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes. Nat Genet 2022; 54:518-525. [PMID: 35410384 PMCID: PMC9005351 DOI: 10.1038/s41588-022-01043-w] [Citation(s) in RCA: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 03/03/2022] [Indexed: 12/30/2022]
Abstract
Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (≥50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.
Collapse
Affiliation(s)
- Jana Ebler
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Peter Ebert
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Tobias Rausch
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- European Molecular Biology Laboratory, GeneCore, Heidelberg, Germany
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Torsten Houwaart
- Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jan O Korbel
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | | | - Alexander T Dilthey
- Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Medical Statistics and Computational Biology, University of Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Tobias Marschall
- Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| |
Collapse
|
53
|
Skuladottir AT, Bjornsdottir G, Ferkingstad E, Einarsson G, Stefansdottir L, Nawaz MS, Oddsson A, Olafsdottir TA, Saevarsdottir S, Walters GB, Magnusson SH, Bjornsdottir A, Sveinsson OA, Vikingsson A, Hansen TF, Jacobsen RL, Erikstrup C, Schwinn M, Brunak S, Banasik K, Ostrowski SR, Troelsen A, Henkel C, Pedersen OB, Jonsdottir I, Gudbjartsson DF, Sulem P, Thorgeirsson TE, Stefansson H, Stefansson K. A genome-wide meta-analysis identifies 50 genetic loci associated with carpal tunnel syndrome. Nat Commun 2022; 13:1598. [PMID: 35332129 PMCID: PMC8948232 DOI: 10.1038/s41467-022-29133-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/28/2022] [Indexed: 12/24/2022] Open
Abstract
Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy and has a largely unknown underlying biology. In a genome-wide association study of CTS (48,843 cases and 1,190,837 controls), we found 53 sequence variants at 50 loci associated with the syndrome. The most significant association is with a missense variant (p.Glu366Lys) in SERPINA1 that protects against CTS (P = 2.9 × 10-24, OR = 0.76). Through various functional analyses, we conclude that at least 22 genes mediate CTS risk and highlight the role of 19 CTS variants in the biology of the extracellular matrix. We show that the genetic component to the risk is higher in bilateral/recurrent/persistent cases than nonrecurrent/nonpersistent cases. Anthropometric traits including height and BMI are genetically correlated with CTS, in addition to early hormonal-replacement therapy, osteoarthritis, and restlessness. Our findings suggest that the components of the extracellular matrix play a key role in the pathogenesis of CTS.
Collapse
Affiliation(s)
| | | | | | | | | | - Muhammad Sulaman Nawaz
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | | | - Saedis Saevarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Landspitali-the National University Hospital of Iceland, Reykjavik, Iceland
| | - G Bragi Walters
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Arnor Vikingsson
- Landspitali-the National University Hospital of Iceland, Reykjavik, Iceland
| | - Thomas Folkmann Hansen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Glostrup, Denmark.,Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rikke Louise Jacobsen
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | - Michael Schwinn
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anders Troelsen
- Department of Orthopaedic Surgery, CAG ROAD - Research OsteoArthritis Denmark, Copenhagen University Hospital, Hvidovre, Denmark
| | - Cecilie Henkel
- Department of Orthopaedic Surgery, CORH, Copenhagen University Hospital, Hvidovre, Denmark
| | - Ole Birger Pedersen
- Department of Clinical Immunology, Zealand University Hospital-Køge, Køge, Denmark.
| | | | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland. .,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
| |
Collapse
|
54
|
Zanini SF, Bayer PE, Wells R, Snowdon RJ, Batley J, Varshney RK, Nguyen HT, Edwards D, Golicz AA. Pangenomics in crop improvement-from coding structural variations to finding regulatory variants with pangenome graphs. THE PLANT GENOME 2022; 15:e20177. [PMID: 34904403 DOI: 10.1002/tpg2.20177] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/07/2021] [Indexed: 05/15/2023]
Abstract
Since the first reported crop pangenome in 2014, advances in high-throughput and cost-effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.], rice (Oryza sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.). Compared with single-reference genomes, pangenomes provide a more accurate representation of the genetic variation present in a species. By combining the genomic data of multiple accessions, pangenomes allow for the detection and annotation of complex DNA polymorphisms such as structural variations (SVs), one of the major determinants of genetic diversity within a species. In this review we summarize the current literature on crop pangenomics, focusing on their application to find candidate SVs involved in traits of agronomic interest. We then highlight the potential of pangenomes in the discovery and functional characterization of noncoding regulatory sequences and their variations. We conclude with a summary and outlook on innovative data structures representing the complete content of plant pangenomes including annotations of coding and noncoding elements and outcomes of transcriptomic and epigenomic experiments.
Collapse
Affiliation(s)
- Silvia F Zanini
- Dep. of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig Univ. Giessen, Giessen, 35392, Germany
| | - Philipp E Bayer
- School of Biological Sciences and Institute of Agriculture, Univ. of Western Australia, Perth, Western Australia, Australia
| | - Rachel Wells
- Dep. of Crop Genetics, John Innes Centre, Norwich Research Park, Norwich, NR47UH, UK
| | - Rod J Snowdon
- Dep. of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig Univ. Giessen, Giessen, 35392, Germany
| | - Jacqueline Batley
- School of Biological Sciences and Institute of Agriculture, Univ. of Western Australia, Perth, Western Australia, Australia
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- State Agricultural Biotechnology Centre, Centre for Crop Food Innovation, Food Futures Institute, Murdoch Univ., Murdoch, WA, Australia
| | - Henry T Nguyen
- Division of Plant Sciences, Univ. of Missouri, Columbia, MO, USA
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, Univ. of Western Australia, Perth, Western Australia, Australia
| | - Agnieszka A Golicz
- Dep. of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig Univ. Giessen, Giessen, 35392, Germany
| |
Collapse
|
55
|
Hansen CCR, Westfall KM, Pálsson S. Evaluation of four methods to identify the homozygotic sex chromosome in small populations. BMC Genomics 2022; 23:160. [PMID: 35209843 PMCID: PMC8867824 DOI: 10.1186/s12864-022-08393-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 02/15/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Whole genomes are commonly assembled into a collection of scaffolds and often lack annotations of autosomes, sex chromosomes, and organelle genomes (i.e., mitochondrial and chloroplast). As these chromosome types differ in effective population size and can have highly disparate evolutionary histories, it is imperative to take this information into account when analysing genomic variation. Here we assessed the accuracy of four methods for identifying the homogametic sex chromosome in a small population using two whole genome sequences (WGS) and 133 RAD sequences of white-tailed eagles (Haliaeetus albicilla): i) difference in read depth per scaffold in a male and a female, ii) heterozygosity per scaffold in a male and a female, iii) mapping to the reference genome of a related species (chicken) with annotated sex chromosomes, and iv) analysis of SNP-loadings from a principal components analysis (PCA), based on the low-depth RADseq data. RESULTS The best performing approach was the reference mapping (method iii), which identified 98.12% of the expected homogametic sex chromosome (Z). Read depth per scaffold (method i) identified 86.41% of the homogametic sex chromosome with few false positives. SNP-loading scores (method iv) identified 78.6% of the Z-chromosome and had a false positive discovery rate of more than 10%. Heterozygosity per scaffold (method ii) did not provide clear results due to a lack of diversity in both the Z and autosomal chromosomes, and potential interference from the heterogametic sex chromosome (W). The evaluation of these methods also revealed 10 Mb of putative PAR and gametologous regions. CONCLUSION Identification of the homogametic sex chromosome in a small population is best accomplished by reference mapping or examining differences in read depth between sexes.
Collapse
Affiliation(s)
| | - Kristen M Westfall
- Department of Life and Environmental Sciences, University of Iceland, Reykjavik, Iceland.,Current: Fisheries and Oceans Canada, Pacific Biological Station, Nanaimo, BC, Canada
| | - Snæbjörn Pálsson
- Department of Life and Environmental Sciences, University of Iceland, Reykjavik, Iceland
| |
Collapse
|
56
|
Lou H, Gao Y, Xie B, Wang Y, Zhang H, Shi M, Ma S, Zhang X, Liu C, Xu S. Haplotype-resolved de novo assembly of a Tujia genome suggests the necessity for high-quality population-specific genome references. Cell Syst 2022; 13:321-333.e6. [PMID: 35180379 DOI: 10.1016/j.cels.2022.01.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 11/09/2021] [Accepted: 01/27/2022] [Indexed: 12/17/2022]
Abstract
Even though the human reference genome assembly is continually being improved, it remains debatable whether a population-specific reference is necessary for every ethnic group. Here, we de novo assembled an individual genome (TJ1) from the Tujia population, an ethnic minority group most closely related to the Han Chinese. TJ1 provided a high-quality haplotype-resolved assembly of chromosome-scale with a scaffold N50 size >78 Mb. Compared with GRCh38 and other de novo assemblies, TJ1 improved short-read mapping, enhanced calling precision for structural variants, and detected rare and low-frequency variants. This revealed fine-scale differences between the closely related Han and Tujia populations, such as population-stratified variants of LCT and UBXN8, and improved screening for ancestry informative markers. We demonstrated that TJ1 could reduce false positives in clinical diagnosis and analyzed the PRSS1-PRSS2 locus as a test case. Our results suggest that population-specific assemblies are necessary for genetic and medical analysis, especially when closely related populations are studied. A record of this paper's transparent peer review process is included in the supplemental information.
Collapse
Affiliation(s)
- Haiyi Lou
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai 200438, China.
| | - Yang Gao
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bo Xie
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yimin Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Miao Shi
- Berry Genomics, Beijing 102200, China
| | - Sen Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoxi Zhang
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chang Liu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai 200438, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China; Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou 221116, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450052, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Human Phenome Institute, Fudan University, Shanghai 201203, China.
| |
Collapse
|
57
|
Bjornsdottir G, Stefansdottir L, Thorleifsson G, Sulem P, Norland K, Ferkingstad E, Oddsson A, Zink F, Lund SH, Nawaz MS, Bragi Walters G, Skuladottir AT, Gudjonsson SA, Einarsson G, Halldorsson GH, Bjarnadottir V, Sveinbjornsson G, Helgadottir A, Styrkarsdottir U, Gudmundsson LJ, Pedersen OB, Hansen TF, Werge T, Banasik K, Troelsen A, Skou ST, Thørner LW, Erikstrup C, Nielsen KR, Mikkelsen S, Jonsdottir I, Bjornsson A, Olafsson IH, Ulfarsson E, Blondal J, Vikingsson A, Brunak S, Ostrowski SR, Ullum H, Thorsteinsdottir U, Stefansson H, Gudbjartsson DF, Thorgeirsson TE, Stefansson K. Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology. Nat Commun 2022; 13:634. [PMID: 35110524 PMCID: PMC8810832 DOI: 10.1038/s41467-022-28167-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 01/12/2022] [Indexed: 12/12/2022] Open
Abstract
Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (ORIDD = 0.92, P = 1.6 × 10−39; ORdorsalgia = 0.92, P = 7.2 × 10−15) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10−11); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes. Little is known about the biology of back pain, a leading cause of disability. Here the authors report 30 new back pain loci, implicating genes involved in cartilage/bone biology, as well as neurological and inflammatory processes.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Muhammad S Nawaz
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - G Bragi Walters
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Gisli H Halldorsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Folkmann Hansen
- Danish Headache Center, Dept. Neurology, Rigshospitalet-Glostrup, Glostrup, Denmark.,Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Werge
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark.,Lundbeck Foundation for GeoGenetics, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anders Troelsen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Orthopaedic Surgery, CAG ROAD-Research OsteoArthritis Denmark, Copenhagen University Hospital, Hvidovre, Denmark
| | - Soren T Skou
- Research Unit for Musculoskeletal Function and Physiotherapy, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.,The Research Unit PROgrez, Department of Physiotherapy and Occupational Therapy, Næstved-Slagelse-Ringsted Hospitals, Næstved, Denmark
| | - Lise Wegner Thørner
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | - Kaspar Rene Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
| | - Susan Mikkelsen
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | | | | | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Aron Bjornsson
- Department of Neurosurgery, Landspitali University Hospital, Reykjavik, Iceland
| | - Ingvar H Olafsson
- Department of Neurosurgery, Landspitali University Hospital, Reykjavik, Iceland
| | - Elfar Ulfarsson
- Department of Neurosurgery, Landspitali University Hospital, Reykjavik, Iceland
| | - Josep Blondal
- Health Care Institution of West Iceland, Stykkisholmur, Iceland
| | | | - Soren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sisse R Ostrowski
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Henrik Ullum
- Statens Serum Institut, Copenhagen, Copenhagen, Denmark
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland. .,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
| |
Collapse
|
58
|
Bland R, Waite-Cusic J, Weisberg AJ, Riutta ER, Chang JH, Kovacevic J. Adaptation to a Commercial Quaternary Ammonium Compound Sanitizer Leads to Cross-Resistance to Select Antibiotics in Listeria monocytogenes Isolated From Fresh Produce Environments. Front Microbiol 2022; 12:782920. [PMID: 35082767 PMCID: PMC8784610 DOI: 10.3389/fmicb.2021.782920] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 12/06/2021] [Indexed: 12/12/2022] Open
Abstract
The effective elimination of Listeria monocytogenes through cleaning and sanitation is of great importance to the food processing industry. Specifically in fresh produce operations, the lack of a kill step requires effective cleaning and sanitation to mitigate the risk of cross-contamination from the environment. As facilities rely on sanitizers to control L. monocytogenes, reports of the development of tolerance to sanitizers and other antimicrobials through cross-resistance is of particular concern. We investigated the potential for six L. monocytogenes isolates from fresh produce handling and processing facilities and packinghouses to develop cross-resistance between a commercial sanitizer and antibiotics. Experimental adaptation of isolates belonging to hypervirulent clonal complexes (CC2, CC4, and CC6) to a commercial quaternary ammonium compound sanitizer (cQAC) resulted in elevated minimum inhibitory concentrations (2–3 ppm) and minimum bactericidal concentrations (3–4 ppm). Susceptibility to cQAC was restored for all adapted (qAD) isolates in the presence of reserpine, a known efflux pump inhibitor. Reduced sensitivity to 7/17 tested antibiotics (chloramphenicol, ciprofloxacin, clindamycin, kanamycin, novobiocin, penicillin, and streptomycin) was observed in all tested isolates. qAD isolates remained susceptible to antibiotics commonly used in the treatment of listeriosis (i.e., ampicillin and gentamicin). The whole genome sequencing of qAD strains, followed by comparative genomic analysis, revealed several mutations in fepR, the regulator for FepA fluoroquinolone efflux pump. The results suggest that mutations in fepR play a role in the reduction in antibiotic susceptibility following low level adaptation to cQAC. Further investigation into the cross-resistance mechanisms and pressures leading to the development of this phenomenon among L. monocytogenes isolates recovered from different sources is needed to better understand the likelihood of cross-resistance development in food chain isolates and the implications for the food industry.
Collapse
Affiliation(s)
- Rebecca Bland
- Food Innovation Center, Oregon State University, Portland, OR, United States.,Department of Food Science and Technology, Oregon State University, Corvallis, OR, United States
| | - Joy Waite-Cusic
- Department of Food Science and Technology, Oregon State University, Corvallis, OR, United States
| | - Alexandra J Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Elizabeth R Riutta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Jeff H Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Jovana Kovacevic
- Food Innovation Center, Oregon State University, Portland, OR, United States.,Department of Food Science and Technology, Oregon State University, Corvallis, OR, United States
| |
Collapse
|
59
|
Pei Z, Deng K, Lei C, Du D, Yu G, Sun X, Xu C, Zhang S. Identifying Balanced Chromosomal Translocations in Human Embryos by Oxford Nanopore Sequencing and Breakpoints Region Analysis. Front Genet 2022; 12:810900. [PMID: 35116057 PMCID: PMC8804325 DOI: 10.3389/fgene.2021.810900] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/13/2021] [Indexed: 01/02/2023] Open
Abstract
Background: Balanced chromosomal aberrations, especially balanced translocations, can cause infertility, recurrent miscarriage or having chromosomally defective offspring. Preimplantation genetic testing for structural rearrangement (PGT-SR) has been widely implemented to improve the clinical outcomes by selecting euploid embryos for transfer, whereas embryos with balanced translocation karyotype were difficult to be distinguished by routine genetic techniques from those with a normal karyotype. Method: In this present study, we developed a clinically applicable method for reciprocal translocation carriers to reduce the risk of pregnancy loss. In the preclinical phase, we identified reciprocal translocation breakpoints in blood of translocation carriers by long-read Oxford Nanopore sequencing, followed by junction-spanning polymerase chain reaction (PCR) and Sanger sequencing. In the clinical phase of embryo diagnosis, aneuploidies and unbalanced translocations were screened by comprehensive chromosomal screening (CCS) with single nucleotide polymorphism (SNP) microarray, carrier embryos were diagnosed by junction-spanning PCR and family haplotype linkage analysis of the breakpoints region. Amniocentesis and cytogenetic analysis of fetuses in the second trimester were performed after embryo transfer to conform the results diagnosed by the presented method. Results: All the accurate reciprocal translocation breakpoints were effectively identified by Nanopore sequencing and confirmed by Sanger sequencing. Twelve embryos were biopsied and detected, the results of junction-spanning PCR and haplotype linkage analysis were consistent. In total, 12 biopsied blastocysts diagnosed to be euploid, in which 6 were aneuploid or unbalanced, three blastocysts were identified to be balanced translocation carriers and three to be normal karyotypes. Two euploid embryos were subsequently transferred back to patients and late prenatal karyotype analysis of amniotic fluid cells was performed. The outcomes diagnosed by the current approach were totally consistent with the fetal karyotypes. Conclusions: In summary, these investigations in our study illustrated that chromosomal reciprocal translocations in embryos can be accurately diagnosed. Long-read Nanopore sequencing and breakpoint analysis contributes to precisely evaluate the genetic risk of disrupted genes, and provides a way of selecting embryos with normal karyotype, especially for couples those without a reference.
Collapse
Affiliation(s)
- Zhenle Pei
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Ke Deng
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Caixai Lei
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Danfeng Du
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Guoliang Yu
- Chigene (Beijing) Translational Medical Research Center Co. Ltd., Beijing, China
| | - Xiaoxi Sun
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Congjian Xu
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- *Correspondence: Congjian Xu, ; Shuo Zhang,
| | - Shuo Zhang
- Shanghai Ji Ai Genetics and IVF Institute, Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- *Correspondence: Congjian Xu, ; Shuo Zhang,
| |
Collapse
|
60
|
Bergeron LA, Besenbacher S, Turner T, Versoza CJ, Wang RJ, Price AL, Armstrong E, Riera M, Carlson J, Chen HY, Hahn MW, Harris K, Kleppe AS, López-Nandam EH, Moorjani P, Pfeifer SP, Tiley GP, Yoder AD, Zhang G, Schierup MH. The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates. eLife 2022; 11:73577. [PMID: 35018888 PMCID: PMC8830884 DOI: 10.7554/elife.73577] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 01/11/2022] [Indexed: 11/13/2022] Open
Abstract
In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a ‘Mutationathon,’ a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.
Collapse
Affiliation(s)
- Lucie A Bergeron
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Søren Besenbacher
- Department of Molecular Medicine (MOMA), Aarhus University, Aarhus N, Denmark
| | - Tychele Turner
- Department of Genetics, Washington University in St. Louis, Saint Louis, United States
| | - Cyril J Versoza
- Center for Evolution and Medicine, Arizona State University, Tempe, United States
| | - Richard J Wang
- Department of Biology, Indiana University, Bloomington, United States
| | - Alivia Lee Price
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Ellie Armstrong
- Department of Biology, Stanford University, Stanford, United States
| | - Meritxell Riera
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Jedidiah Carlson
- Department of Genome Sciences, University of Washington, Seattle, United States
| | - Hwei-Yen Chen
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Matthew W Hahn
- Department of Biology, Indiana University, Bloomington, United States
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, Seattle, United States
| | | | | | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, United States
| | - George P Tiley
- Department of Biology, Duke University, Durham, United States
| | - Anne D Yoder
- Department of Biology, Duke University, Durham, United States
| | - Guojie Zhang
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | |
Collapse
|
61
|
Bernardini G, Denti L, Previtali M. Alignment-Free Genotyping of Known Variations with MALVA. Methods Mol Biol 2022; 2493:247-256. [PMID: 35751819 DOI: 10.1007/978-1-0716-2293-3_15] [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: 06/15/2023]
Abstract
The discovery and characterization of sequence variations in human populations are crucial in genetic studies. Standard methods for addressing this problem are computationally expensive and highly time consuming, thus impractical for clinical applications, where time is often an issue. When the task is to genotype variations that have been previously annotated, alignment-free methods come to the aid. Here, we describe MALVA, an alignment-free approach for genotyping a set of known variations. MALVA is the first mapping-free tool which is able to genotype multi-allelic SNPs and indels, even in high-density genomic regions, and to effectively handle a huge number of variations.
Collapse
Affiliation(s)
| | - Luca Denti
- Department of Computational Biology, C3BI USR 3756 CNRS, Institut Pasteur, Paris, France.
| | - Marco Previtali
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy
| |
Collapse
|
62
|
Björnsson HK, Gudbjornsson B, Björnsson ES. Infliximab-induced liver injury: Clinical phenotypes, autoimmunity and the role of corticosteroid treatment. J Hepatol 2022; 76:86-92. [PMID: 34487751 DOI: 10.1016/j.jhep.2021.08.024] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 08/12/2021] [Accepted: 08/25/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND & AIMS Infliximab has been associated with drug-induced liver injury (DILI), particularly drug-induced autoimmune hepatitis (DIAIH). DIAIH is commonly treated with corticosteroids, but there is limited data on the efficacy of corticosteroids in infliximab-induced DILI. METHODS Patients were included for assessment if they had been treated with infliximab between 2009-2020 in Iceland and had developed elevated liver tests. Other specific etiologies of liver enzyme elevations were excluded. Patients treated with corticosteroids were compared to patients not receiving corticosteroids. RESULTS A total of 36 patients with infliximab-induced DILI were identified: median age was 46 years (IQR 32-54) and 28 (78%) were female. Type of liver injury was predominantly hepatocellular (64%). Median peak liver enzymes were: alanine aminotransferase (ALT) 393 (328-695) U/L, aspartate aminotransferase 283 (158-564) U/L, alkaline phosphatase 116 (83-205) U/L, and bilirubin (10-20) 13 μmol/L. A total of 25 (69%) were positive for anti-nuclear antibody and/or had elevated IgG. Corticosteroids were initiated in 17 (47%). Median time from onset of liver injury to peak ALT value was longer in patients treated with corticosteroids, 22 (12-59) vs. 0 (0-3) days (p = 0.001). Time from peak ALT to normalization of liver enzymes was 45 days in the corticosteroid group vs. 77 days in others (p = 0.062). Corticosteroids were tapered in all patients, with no cases of relapse during the follow-up period of 1,245 (820-2,698) days. Overall 75% received another biologic, mostly adalimumab, without evidence of liver injury. CONCLUSION Approximately half of patients with infliximab-induced liver injury had slow improvement in ALT despite cessation of therapy and were treated with corticosteroids. Treatment response was good with prompt resolution of liver test abnormalities. Relapse of liver injury was not observed after tapering of corticosteroids despite prolonged follow-up and no patients developed DILI due to a second biologic. LAY SUMMARY A rare side effect of infliximab, a biologic medicine used to treat multiple inflammatory diseases, is liver injury and liver inflammation. Steroid treatment has been used in some patients with liver injury caused by infliximab, but there have been few studies supporting this treatment. In this study of 36 patients with infliximab-induced liver injury, approximately half of patients were treated with steroids and the results suggest that patients receiving steroids recover more quickly.
Collapse
Affiliation(s)
- Helgi Kristinn Björnsson
- Landspitali - The National University Hospital of Iceland, Section of Gastroenterology and Hepatology, Reykjavik, Iceland; Sahlgrenska University Hospital, Department of Internal Medicine, Division of Gastroenterology and Hepatology, Gothenburg, Sweden; University of Iceland, Faculty of Medicine, Reykjavik, Iceland.
| | - Bjorn Gudbjornsson
- Landspitali - The National University Hospital of Iceland, Centre for Rheumatology Research, Reykjavik, Iceland; University of Iceland, Faculty of Medicine, Reykjavik, Iceland
| | - Einar Stefan Björnsson
- Landspitali - The National University Hospital of Iceland, Section of Gastroenterology and Hepatology, Reykjavik, Iceland; University of Iceland, Faculty of Medicine, Reykjavik, Iceland
| |
Collapse
|
63
|
Guo H, Fu Y, Gao Y, Li J, Wang Y, Liu B. deGSM: Memory Scalable Construction Of Large Scale de Bruijn Graph. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021; 18:2157-2166. [PMID: 31056509 DOI: 10.1109/tcbb.2019.2913932] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The de Bruijn graph, a fundamental data structure to represent and organize genome sequence, plays important roles in various kinds of sequence analysis tasks. With the rapid development of HTS data and ever-increasing number of assembled genomes, there is a high demand to construct the very large de Bruijn graph for sequences up to Tera-base-pair level. Current approaches may have unaffordable memory footprints to handle such a large de Bruijn graph. We propose a lightweight parallel de Bruijn graph construction approach: de Bruijn Graph Constructor in Scalable Memory (deGSM). The main idea of deGSM is to efficiently construct the Burrows-Wheeler Transformation (BWT) of the unipaths of the de Bruijn graph in constant RAM space and transform the BWT into the original unitigs. The experimental results demonstrate that, just with a commonly available machine, deGSM is able to handle very large genome sequence(s), e.g., the contigs (305 Gbp) and scaffolds (1.1 Tbp) recorded in GenBank database and Picea abies HTS dataset (9.7 Tbp). Moreover, deGSM also has faster or comparable construction speed compared with state-of-the-art approaches. With its high scalability and efficiency, deGSM has enormous potential in many large scale genomics studies. The deGSM is publicly available at: https://github.com/hitbc/deGSM.
Collapse
|
64
|
Bland RN, Johnson JD, Waite-Cusic JG, Weisberg AJ, Riutta ER, Chang JH, Kovacevic J. Application of Whole Genome Sequencing to Understand Diversity and Presence of Genes Associated with Sanitizer Tolerance in Listeria monocytogenes from Produce Handling Sources. Foods 2021; 10:2454. [PMID: 34681501 PMCID: PMC8536156 DOI: 10.3390/foods10102454] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/09/2021] [Accepted: 10/11/2021] [Indexed: 12/13/2022] Open
Abstract
Recent listeriosis outbreaks linked to fresh produce suggest the need to better understand and mitigate L. monocytogenes contamination in packing and processing environments. Using whole genome sequencing (WGS) and phenotype screening assays for sanitizer tolerance, we characterized 48 L. monocytogenes isolates previously recovered from environmental samples in five produce handling facilities. Within the studied population there were 10 sequence types (STs) and 16 cgMLST types (CTs). Pairwise single nucleotide polymorphisms (SNPs) ranged from 0 to 3047 SNPs within a CT, revealing closely and distantly related isolates indicative of both sporadic and continuous contamination events within the facility. Within Facility 1, we identified a closely related cluster (0-2 SNPs) of isolates belonging to clonal complex 37 (CC37; CT9492), with isolates recovered during sampling events 1-year apart and in various locations inside and outside the facility. The accessory genome of these CC37 isolates varied from 94 to 210 genes. Notable genetic elements and mutations amongst the isolates included the bcrABC cassette (2/48), associated with QAC tolerance; mutations in the actA gene on the Listeria pathogenicity island (LIPI) 1 (20/48); presence of LIPI-3 (21/48) and LIPI-4 (23/48). This work highlights the potential use of WGS in tracing the pathogen within a facility and understanding properties of L. monocytogenes in produce settings.
Collapse
Affiliation(s)
- Rebecca N. Bland
- Food Innovation Center, Oregon State University, Portland, OR 97209, USA;
| | - Jared D. Johnson
- Department of Food Science and Technology, Oregon State University, Corvallis, OR 97331, USA; (J.D.J.); (J.G.W.-C.)
| | - Joy G. Waite-Cusic
- Department of Food Science and Technology, Oregon State University, Corvallis, OR 97331, USA; (J.D.J.); (J.G.W.-C.)
| | - Alexandra J. Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA; (A.J.W.); (E.R.R.); (J.H.C.)
| | - Elizabeth R. Riutta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA; (A.J.W.); (E.R.R.); (J.H.C.)
| | - Jeff H. Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA; (A.J.W.); (E.R.R.); (J.H.C.)
| | - Jovana Kovacevic
- Food Innovation Center, Oregon State University, Portland, OR 97209, USA;
| |
Collapse
|
65
|
Skuladottir AT, Bjornsdottir G, Nawaz MS, Petersen H, Rognvaldsson S, Moore KHS, Olafsson PI, Magnusson SH, Bjornsdottir A, Sveinsson OA, Sigurdardottir GR, Saevarsdottir S, Ivarsdottir EV, Stefansdottir L, Gunnarsson B, Muhlestein JB, Knowlton KU, Jones DA, Nadauld LD, Hartmann AM, Rujescu D, Strupp M, Walters GB, Thorgeirsson TE, Jonsdottir I, Holm H, Thorleifsson G, Gudbjartsson DF, Sulem P, Stefansson H, Stefansson K. A genome-wide meta-analysis uncovers six sequence variants conferring risk of vertigo. Commun Biol 2021; 4:1148. [PMID: 34620984 PMCID: PMC8497462 DOI: 10.1038/s42003-021-02673-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/09/2021] [Indexed: 11/17/2022] Open
Abstract
Vertigo is the leading symptom of vestibular disorders and a major risk factor for falls. In a genome-wide association study of vertigo (Ncases = 48,072, Ncontrols = 894,541), we uncovered an association with six common sequence variants in individuals of European ancestry, including missense variants in ZNF91, OTOG, OTOGL, and TECTA, and a cis-eQTL for ARMC9. The association of variants in ZNF91, OTOGL, and OTOP1 was driven by an association with benign paroxysmal positional vertigo. Using previous reports of sequence variants associating with age-related hearing impairment and motion sickness, we found eight additional variants that associate with vertigo. Although disorders of the auditory and the vestibular system may co-occur, none of the six genome-wide significant vertigo variants were associated with hearing loss and only one was associated with age-related hearing impairment. Our results uncovered sequence variants associating with vertigo in a genome-wide association study and implicated genes with known roles in inner ear development, maintenance, and disease.
Collapse
Affiliation(s)
| | | | - Muhammad Sulaman Nawaz
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Hannes Petersen
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Akureyri Hospital, Akureyri, Iceland
| | | | | | | | | | | | - Olafur A Sveinsson
- Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Saedis Saevarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | | | | | | | - Joseph B Muhlestein
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT, USA
- University of Utah, School of Medicine, Salt Lake City, UT, USA
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT, USA
- University of Utah, School of Medicine, Salt Lake City, UT, USA
| | - David A Jones
- Precision Genomics, Intermountain Healthcare, Saint George, UT, USA
| | - Lincoln D Nadauld
- Precision Genomics, Intermountain Healthcare, Saint George, UT, USA
- Stanford University, School of Medicine, Stanford, CA, USA
| | - Annette M Hartmann
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Dan Rujescu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Michael Strupp
- Department of Neurology and German Center for Vertigo and Balance Disorders, Ludwig Maximilians University, Munich, Germany
| | - G Bragi Walters
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | | | | | | | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
| |
Collapse
|
66
|
Björnsson E, Thorgeirsson G, Helgadóttir A, Thorleifsson G, Sveinbjörnsson G, Kristmundsdóttir S, Jónsson H, Jónasdóttir A, Jónasdóttir Á, Sigurðsson Á, Guðnason T, Ólafsson Í, Sigurðsson EL, Sigurðardóttir Ó, Viðarsson B, Baldvinsson M, Bjarnason R, Danielsen R, Matthíasson SE, Thórarinsson BL, Grétarsdóttir S, Steinthórsdóttir V, Halldórsson BV, Andersen K, Arnar DO, Jónsdóttir I, Guðbjartsson DF, Hólm H, Thorsteinsdóttir U, Sulem P, Stefánsson K. Large-Scale Screening for Monogenic and Clinically Defined Familial Hypercholesterolemia in Iceland. Arterioscler Thromb Vasc Biol 2021; 41:2616-2628. [PMID: 34407635 PMCID: PMC8454500 DOI: 10.1161/atvbaha.120.315904] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 08/02/2021] [Indexed: 01/07/2023]
Abstract
Objective: Familial hypercholesterolemia (FH) is traditionally defined as a monogenic disease characterized by severely elevated LDL-C (low-density lipoprotein cholesterol) levels. In practice, FH is commonly a clinical diagnosis without confirmation of a causative mutation. In this study, we sought to characterize and compare monogenic and clinically defined FH in a large sample of Icelanders. Approach and Results: We whole-genome sequenced 49 962 Icelanders and imputed the identified variants into an overall sample of 166 281 chip-genotyped Icelanders. We identified 20 FH mutations in LDLR, APOB, and PCSK9 with combined prevalence of 1 in 836. Monogenic FH was associated with severely elevated LDL-C levels and increased risk of premature coronary disease, aortic valve stenosis, and high burden of coronary atherosclerosis. We used a modified version of the Dutch Lipid Clinic Network criteria to screen for the clinical FH phenotype among living adult participants (N=79 058). Clinical FH was found in 2.2% of participants, of whom only 5.2% had monogenic FH. Mutation-negative clinical FH has a strong polygenic basis. Both individuals with monogenic FH and individuals with mutation-negative clinical FH were markedly undertreated with cholesterol-lowering medications and only a minority attained an LDL-C target of <2.6 mmol/L (<100 mg/dL; 11.0% and 24.9%, respectively) or <1.8 mmol/L (<70 mg/dL; 0.0% and 5.2%, respectively), as recommended for primary prevention by European Society of Cardiology/European Atherosclerosis Society cholesterol guidelines. Conclusions: Clinically defined FH is a relatively common phenotype that is explained by monogenic FH in only a minority of cases. Both monogenic and clinical FH confer high cardiovascular risk but are markedly undertreated.
Collapse
Affiliation(s)
- Eythór Björnsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
- Department of Internal Medicine (E.B.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Guðmundur Thorgeirsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- Division of Cardiology, Department of Internal Medicine (G. Thorgeirsson, R.D., K.A., D.O.A.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Anna Helgadóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Guðmar Thorleifsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Garðar Sveinbjörnsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Snaedís Kristmundsdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Hákon Jónsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Aðalbjörg Jónasdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Áslaug Jónasdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Ásgeir Sigurðsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | | | - Ísleifur Ólafsson
- Department of Clinical Biochemistry (I.O.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Emil L. Sigurðsson
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
- Development Centre for the Primary Care, Reykjavík, Iceland (E.L.S.)
| | | | - Brynjar Viðarsson
- Department of Hematology (B.V.), Landspítali-The National University Hospital of Iceland, Reykjavík
- The Laboratory in Mjódd, Reykjavík, Iceland (B.V.)
| | | | - Ragnar Bjarnason
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
- Children’s Medical Center (R.B.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Ragnar Danielsen
- Division of Cardiology, Department of Internal Medicine (G. Thorgeirsson, R.D., K.A., D.O.A.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | | | - Björn L. Thórarinsson
- Department of Neurology (B.L.T.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Sólveig Grétarsdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Valgerður Steinthórsdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Bjarni V. Halldórsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Karl Andersen
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
- Division of Cardiology, Department of Internal Medicine (G. Thorgeirsson, R.D., K.A., D.O.A.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Davíð O. Arnar
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
- Division of Cardiology, Department of Internal Medicine (G. Thorgeirsson, R.D., K.A., D.O.A.), Landspítali-The National University Hospital of Iceland, Reykjavík
| | - Ingileif Jónsdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
| | - Daníel F. Guðbjartsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- School of Engineering and Natural Sciences, University of Iceland, Reykjavík (D.F.G.)
| | - Hilma Hólm
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Unnur Thorsteinsdóttir
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
| | - Patrick Sulem
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
| | - Kári Stefánsson
- deCODE genetics/Amgen, Inc, Reykjavík, Iceland (E.B., G. Thorgeirsson, A.H., G. Thorleifsson, G.S., S.K., H.J., Aðalbjörg Jónasdóttir, Áslaug Jónasdóttir, A.S., S.G., V.S., B.V.H., D.O.A., I.J., D.F.G., H.H., U.T., P.S., K.S.)
- Faculty of Medicine, University of Iceland, Reykjavík (E.B., E.L.S., R.B., K.A., D.O.A., I.J., U.T., K.S.)
| |
Collapse
|
67
|
Colquhoun RM, Hall MB, Lima L, Roberts LW, Malone KM, Hunt M, Letcher B, Hawkey J, George S, Pankhurst L, Iqbal Z. Pandora: nucleotide-resolution bacterial pan-genomics with reference graphs. Genome Biol 2021; 22:267. [PMID: 34521456 PMCID: PMC8442373 DOI: 10.1186/s13059-021-02473-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 08/19/2021] [Indexed: 12/21/2022] Open
Abstract
We present pandora, a novel pan-genome graph structure and algorithms for identifying variants across the full bacterial pan-genome. As much bacterial adaptability hinges on the accessory genome, methods which analyze SNPs in just the core genome have unsatisfactory limitations. Pandora approximates a sequenced genome as a recombinant of references, detects novel variation and pan-genotypes multiple samples. Using a reference graph of 578 Escherichia coli genomes, we compare 20 diverse isolates. Pandora recovers more rare SNPs than single-reference-based tools, is significantly better than picking the closest RefSeq reference, and provides a stable framework for analyzing diverse samples without reference bias.
Collapse
Affiliation(s)
- Rachel M Colquhoun
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, UK
- Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh, UK
| | - Michael B Hall
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
| | - Leandro Lima
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
| | - Leah W Roberts
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
| | - Kerri M Malone
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
| | - Martin Hunt
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Brice Letcher
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK
| | - Jane Hawkey
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, 3004, Australia
| | - Sophie George
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Louise Pankhurst
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Zoology, University of Oxford, Mansfield Road, Oxford, UK
| | - Zamin Iqbal
- European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD, UK.
| |
Collapse
|
68
|
Letcher B, Hunt M, Iqbal Z. Gramtools enables multiscale variation analysis with genome graphs. Genome Biol 2021; 22:259. [PMID: 34488837 PMCID: PMC8420074 DOI: 10.1186/s13059-021-02474-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 08/20/2021] [Indexed: 11/24/2022] Open
Abstract
Genome graphs allow very general representations of genetic variation; depending on the model and implementation, variation at different length-scales (single nucleotide polymorphisms (SNPs), structural variants) and on different sequence backgrounds can be incorporated with different levels of transparency. We implement a model which handles this multiscale variation and develop a JSON extension of VCF (jVCF) allowing for variant calls on multiple references, both implemented in our software gramtools. We find gramtools outperforms existing methods for genotyping SNPs overlapping large deletions in M. tuberculosis and is able to genotype on multiple alternate backgrounds in P. falciparum, revealing previously hidden recombination.
Collapse
Affiliation(s)
| | - Martin Hunt
- EMBL-EBI, Hinxton, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | |
Collapse
|
69
|
Jonsdottir GA, Einarsson G, Thorleifsson G, Magnusson SH, Gunnarsson AF, Frigge ML, Gisladottir RS, Unnsteinsdottir U, Gunnarsson B, Walters GB, Steinthorsdottir V, Helgadottir A, Jonsdottir I, Gislason T, Thorsteinsson HS, Sigurdsson E, Haraldsson M, Sigurdsson EL, Bjarnason R, Olafsson I, Thorgeirsson G, Sulem P, Holm H, Thorsteinsdottir U, Gudbjartsson DF, Bjornsdottir G, Thorgeirsson TE, Stefansson H, Stefansson K. Genetic propensities for verbal and spatial ability have opposite effects on body mass index and risk of schizophrenia. INTELLIGENCE 2021. [DOI: 10.1016/j.intell.2021.101565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
|
70
|
Weisberg AJ, Grünwald NJ, Savory EA, Putnam ML, Chang JH. Genomic Approaches to Plant-Pathogen Epidemiology and Diagnostics. ANNUAL REVIEW OF PHYTOPATHOLOGY 2021; 59:311-332. [PMID: 34030448 DOI: 10.1146/annurev-phyto-020620-121736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Diseases have a significant cost to agriculture. Findings from analyses of whole-genome sequences show great promise for informing strategies to mitigate risks from diseases caused by phytopathogens. Genomic approaches can be used to dramatically shorten response times to outbreaks and inform disease management in novel ways. However, the use of these approaches requires expertise in working with big, complex data sets and an understanding of their pitfalls and limitations to infer well-supported conclusions. We suggest using an evolutionary framework to guide the use of genomic approaches in epidemiology and diagnostics of plant pathogens. We also describe steps that are necessary for realizing these as standard approaches in disease surveillance.
Collapse
Affiliation(s)
- Alexandra J Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon 97331, USA;
| | - Niklaus J Grünwald
- Horticultural Crops Research Laboratory, USDA Agricultural Research Service, Corvallis, Oregon 97331, USA
| | | | - Melodie L Putnam
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon 97331, USA;
| | - Jeff H Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon 97331, USA;
| |
Collapse
|
71
|
Abstract
Pangenomes are organized collections of the genomic information from related individuals or groups. Graphical pangenomics is the study of these pangenomes using graphical methods to identify and analyze genes, regions, and mutations of interest to an array of biological questions. This field has seen significant progress in recent years including the development of graph based models that better resolve biological phenomena, and an explosion of new tools for mapping reads, creating graphical genomes, and performing pangenome analysis. In this review, we discuss recent developments in models, algorithms associated with graphical genomes, and comparisons between similar tools. In addition we briefly discuss what these developments may mean for the future of genomics.
Collapse
|
72
|
Wold J, Koepfli KP, Galla SJ, Eccles D, Hogg CJ, Le Lec MF, Guhlin J, Santure AW, Steeves TE. Expanding the conservation genomics toolbox: Incorporating structural variants to enhance genomic studies for species of conservation concern. Mol Ecol 2021; 30:5949-5965. [PMID: 34424587 PMCID: PMC9290615 DOI: 10.1111/mec.16141] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 07/28/2021] [Accepted: 08/18/2021] [Indexed: 12/28/2022]
Abstract
Structural variants (SVs) are large rearrangements (>50 bp) within the genome that impact gene function and the content and structure of chromosomes. As a result, SVs are a significant source of functional genomic variation, that is, variation at genomic regions underpinning phenotype differences, that can have large effects on individual and population fitness. While there are increasing opportunities to investigate functional genomic variation in threatened species via single nucleotide polymorphism (SNP) data sets, SVs remain understudied despite their potential influence on fitness traits of conservation interest. In this future-focused Opinion, we contend that characterizing SVs offers the conservation genomics community an exciting opportunity to complement SNP-based approaches to enhance species recovery. We also leverage the existing literature-predominantly in human health, agriculture and ecoevolutionary biology-to identify approaches for readily characterizing SVs and consider how integrating these into the conservation genomics toolbox may transform the way we manage some of the world's most threatened species.
Collapse
Affiliation(s)
- Jana Wold
- School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
| | - Klaus-Peter Koepfli
- Smithsonian-Mason School of Conservation, Front Royal, Virginia, USA.,Centre for Species Survival, Smithsonian Conservation Biology Institute, National Zoological Park, Washington, District of Columbia, USA.,Computer Technologies Laboratory, ITMO University, Saint Petersburg, Russia
| | - Stephanie J Galla
- School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.,Department of Biological Sciences, Boise State University, Boise, Idaho, USA
| | - David Eccles
- Malaghan Institute of Medical Research, Wellington, New Zealand
| | - Carolyn J Hogg
- School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Marissa F Le Lec
- Department of Biochemistry, University of Otago, Dunedin, Otago, New Zealand
| | - Joseph Guhlin
- Department of Biochemistry, University of Otago, Dunedin, Otago, New Zealand.,Genomics Aotearoa, Dunedin, Otago, New Zealand
| | - Anna W Santure
- School of Biological Sciences, The University of Auckland, Auckland, New Zealand
| | - Tammy E Steeves
- School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
| |
Collapse
|
73
|
Pandey P, Gao Y, Kingsford C. VariantStore: an index for large-scale genomic variant search. Genome Biol 2021; 22:231. [PMID: 34412679 PMCID: PMC8375130 DOI: 10.1186/s13059-021-02442-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 07/27/2021] [Indexed: 11/18/2022] Open
Abstract
Efficiently scaling genomic variant search indexes to thousands of samples is computationally challenging due to the presence of multiple coordinate systems to avoid reference biases. We present VariantStore, a system that indexes genomic variants from multiple samples using a variation graph and enables variant queries across any sample-specific coordinate system. We show the scalability of VariantStore by indexing genomic variants from the TCGA project in 4 h and the 1000 Genomes project in 3 h. Querying for variants in a gene takes between 0.002 and 3 seconds using memory only 10% of the size of the full representation.
Collapse
Affiliation(s)
- Prashant Pandey
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, USA
| | - Yinjie Gao
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, USA
| | - Carl Kingsford
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, USA
| |
Collapse
|
74
|
Eggertsson HP, Halldorsson BV. read_haps: using read haplotypes to detect same species contamination in DNA sequences. Bioinformatics 2021; 37:2215-2217. [PMID: 33135043 DOI: 10.1093/bioinformatics/btaa936] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 09/10/2020] [Accepted: 10/22/2020] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Data analysis is requisite on reliable data. In genetics this includes verifying that the sample is not contaminated with another, a problem ubiquitous in biology. RESULTS In human, and other diploid species, DNA contamination from the same species can be found by the presence of three haplotypes between polymorphic SNPs. read_haps is a tool that detects sample contamination from short read whole genome sequencing data. AVAILABILITYAND IMPLEMENTATION github.com/DecodeGenetics/read_haps.
Collapse
Affiliation(s)
| | - Bjarni V Halldorsson
- deCODE Genetics, Reykjavík 102, Iceland.,Department of Engineering, School of Technology, Reykjavík University, Reykjavík 102, Iceland
| |
Collapse
|
75
|
Almarri MA, Haber M, Lootah RA, Hallast P, Al Turki S, Martin HC, Xue Y, Tyler-Smith C. The genomic history of the Middle East. Cell 2021; 184:4612-4625.e14. [PMID: 34352227 PMCID: PMC8445022 DOI: 10.1016/j.cell.2021.07.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 05/17/2021] [Accepted: 07/09/2021] [Indexed: 11/22/2022]
Abstract
The Middle East region is important to understand human evolution and migrations but is underrepresented in genomic studies. Here, we generated 137 high-coverage physically phased genome sequences from eight Middle Eastern populations using linked-read sequencing. We found no genetic traces of early expansions out-of-Africa in present-day populations but found Arabians have elevated Basal Eurasian ancestry that dilutes their Neanderthal ancestry. Population sizes within the region started diverging 15–20 kya, when Levantines expanded while Arabians maintained smaller populations that derived ancestry from local hunter-gatherers. Arabians suffered a population bottleneck around the aridification of Arabia 6 kya, while Levantines had a distinct bottleneck overlapping the 4.2 kya aridification event. We found an association between movement and admixture of populations in the region and the spread of Semitic languages. Finally, we identify variants that show evidence of selection, including polygenic selection. Our results provide detailed insights into the genomic and selective histories of the Middle East. Middle Easterners do not have ancestry from an early out-of-Africa expansion Basal Eurasian and African ancestry in Arabians deplete their Neanderthal ancestry Populations experienced bottlenecks overlapping aridification events Identification of recent single and polygenic signals of selection in Arabia
Collapse
Affiliation(s)
- Mohamed A Almarri
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK; Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates.
| | - Marc Haber
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham B15 2TT, UK; Centre for Computational Biology, University of Birmingham, Birmingham B15 2TT, UK.
| | - Reem A Lootah
- Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates
| | - Pille Hallast
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK; Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu 50411, Estonia
| | - Saeed Al Turki
- Translational Pathology, Department of Pathology and Laboratory Medicine, King Abdulaziz Medical City, Ministry of National Guard-Health Affairs, Riyadh, Saudi Arabia; Department of Genetics & Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Hilary C Martin
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Yali Xue
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Chris Tyler-Smith
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| |
Collapse
|
76
|
Abstract
MOTIVATION Variation graph representations are projected to either replace or supplement conventional single genome references due to their ability to capture population genetic diversity and reduce reference bias. Vast catalogues of genetic variants for many species now exist, and it is natural to ask which among these are crucial to circumvent reference bias during read mapping. RESULTS In this work, we propose a novel mathematical framework for variant selection, by casting it in terms of minimizing variation graph size subject to preserving paths of length α with at most δ differences. This framework leads to a rich set of problems based on the types of variants [e.g. single nucleotide polymorphisms (SNPs), indels or structural variants (SVs)], and whether the goal is to minimize the number of positions at which variants are listed or to minimize the total number of variants listed. We classify the computational complexity of these problems and provide efficient algorithms along with their software implementation when feasible. We empirically evaluate the magnitude of graph reduction achieved in human chromosome variation graphs using multiple α and δ parameter values corresponding to short and long-read resequencing characteristics. When our algorithm is run with parameter settings amenable to long-read mapping (α = 10 kbp, δ = 1000), 99.99% SNPs and 73% SVs can be safely excluded from human chromosome 1 variation graph. The graph size reduction can benefit downstream pan-genome analysis. AVAILABILITY AND IMPLEMENTATION : https://github.com/AT-CG/VF. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Chirag Jain
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, KA 560012, India
| | - Neda Tavakoli
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Srinivas Aluru
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| |
Collapse
|
77
|
Norri T, Cazaux B, Dönges S, Valenzuela D, Mäkinen V. Founder Reconstruction Enables Scalable and Seamless Pangenomic Analysis. Bioinformatics 2021; 37:4611-4619. [PMID: 34260702 PMCID: PMC8665761 DOI: 10.1093/bioinformatics/btab516] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 05/29/2021] [Accepted: 07/08/2021] [Indexed: 11/14/2022] Open
Abstract
Motivation Variant calling workflows that utilize a single reference sequence are the de facto standard elementary genomic analysis routine for resequencing projects. Various ways to enhance the reference with pangenomic information have been proposed, but scalability combined with seamless integration to existing workflows remains a challenge. Results We present PanVC with founder sequences, a scalable and accurate variant calling workflow based on a multiple alignment of reference sequences. Scalability is achieved by removing duplicate parts up to a limit into a founder multiple alignment, that is then indexed using a hybrid scheme that exploits general purpose read aligners. Our implemented workflow uses GATK or BCFtools for variant calling, but the various steps of our workflow (e.g. vcf2multialign tool, founder reconstruction) can be of independent interest as a basis for creating novel pangenome analysis workflows beyond variant calling. Availability and implementation Our open access tools and instructions how to reproduce our experiments are available at the following address: https://github.com/algbio/panvc-founders. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Tuukka Norri
- Department of Computer Science, University of Helsinki, Helsinki, 00014, Finland
| | - Bastien Cazaux
- Department of Computer Science, University of Helsinki, Helsinki, 00014, Finland
| | - Saska Dönges
- Department of Computer Science, University of Helsinki, Helsinki, 00014, Finland
| | - Daniel Valenzuela
- Department of Computer Science, University of Helsinki, Helsinki, 00014, Finland
| | - Veli Mäkinen
- Department of Computer Science, University of Helsinki, Helsinki, 00014, Finland
| |
Collapse
|
78
|
Jayakodi M, Schreiber M, Stein N, Mascher M. Building pan-genome infrastructures for crop plants and their use in association genetics. DNA Res 2021; 28:6117190. [PMID: 33484244 PMCID: PMC7934568 DOI: 10.1093/dnares/dsaa030] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Indexed: 12/20/2022] Open
Abstract
Pan-genomic studies aim at representing the entire sequence diversity within a species to provide useful resources for evolutionary studies, functional genomics and breeding of cultivated plants. Cost reductions in high-throughput sequencing and advances in sequence assembly algorithms have made it possible to create multiple reference genomes along with a catalogue of all forms of genetic variations in plant species with large and complex or polyploid genomes. In this review, we summarize the current approaches to building pan-genomes as an in silico representation of plant sequence diversity and outline relevant methods for their effective utilization in linking structural with phenotypic variation. We propose as future research avenues (i) transcriptomic and epigenomic studies across multiple reference genomes and (ii) the development of user-friendly and feature-rich pan-genome browsers.
Collapse
Affiliation(s)
- Murukarthick Jayakodi
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Mona Schreiber
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Nils Stein
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.,Center for Integrated Breeding Research (CiBreed), Georg-August-University Göttingen, Göttingen, Germany
| | - Martin Mascher
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Saxony, Germany
| |
Collapse
|
79
|
Abstract
A pressing concern in the SARS-CoV-2 epidemic and other viral outbreaks, is the extent to which the containment measures are halting the viral spread. A straightforward way to assess this is to tally the active cases and the recovered ones throughout the epidemic. Here, we show how epidemic control can be assessed with molecular information during a well characterized epidemic in Iceland. We demonstrate how the viral concentration decreased in those newly diagnosed as the epidemic transitioned from exponential growth phase to containment phase. The viral concentration in the cases identified in population screening decreased faster than in those symptomatic and considered at high risk and that were targeted by the healthcare system. The viral concentration persists in recovering individuals as we found that half of the cases are still positive after two weeks. We demonstrate that accumulation of mutations in SARS-CoV-2 genome can be exploited to track the rate of new viral generations throughout the different phases of the epidemic, where the accumulation of mutations decreases as the transmission rate decreases in the containment phase. Overall, the molecular signatures of SARS-CoV-2 infections contain valuable epidemiological information that can be used to assess the effectiveness of containment measures. The concentration of SARS-CoV-2 changes during an individual’s infection, and mutations accumulate as viruses are transmitted between people. Here, the authors use data from Iceland to demonstrate how this information can be exploited at the population-level to determine the phase of the epidemic.
Collapse
|
80
|
Ivarsdottir EV, Holm H, Benonisdottir S, Olafsdottir T, Sveinbjornsson G, Thorleifsson G, Eggertsson HP, Halldorsson GH, Hjorleifsson KE, Melsted P, Gylfason A, Arnadottir GA, Oddsson A, Jensson BO, Jonasdottir A, Jonasdottir A, Juliusdottir T, Stefansdottir L, Tragante V, Halldorsson BV, Petersen H, Thorgeirsson G, Thorsteinsdottir U, Sulem P, Hinriksdottir I, Jonsdottir I, Gudbjartsson DF, Stefansson K. The genetic architecture of age-related hearing impairment revealed by genome-wide association analysis. Commun Biol 2021; 4:706. [PMID: 34108613 PMCID: PMC8190123 DOI: 10.1038/s42003-021-02224-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 05/17/2021] [Indexed: 02/05/2023] Open
Abstract
Age-related hearing impairment (ARHI) is the most common sensory disorder in older adults. We conducted a genome-wide association meta-analysis of 121,934 ARHI cases and 591,699 controls from Iceland and the UK. We identified 21 novel sequence variants, of which 13 are rare, under either additive or recessive models. Of special interest are a missense variant in LOXHD1 (MAF = 1.96%) and a tandem duplication in FBF1 covering 4 exons (MAF = 0.22%) associating with ARHI (OR = 3.7 for homozygotes, P = 1.7 × 10-22 and OR = 4.2 for heterozygotes, P = 5.7 × 10-27, respectively). We constructed an ARHI genetic risk score (GRS) using common variants and showed that a common variant GRS can identify individuals at risk comparable to carriers of rare high penetrance variants. Furthermore, we found that ARHI and tinnitus share genetic causes. This study sheds a new light on the genetic architecture of ARHI, through several rare variants in both Mendelian deafness genes and genes not previously linked to hearing.
Collapse
Affiliation(s)
- Erna V Ivarsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Reykjavik, Iceland
| | | | | | | | | | | | - Gisli H Halldorsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Kristjan E Hjorleifsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Pall Melsted
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | - Hannes Petersen
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Akureyri Hospital, Akureyri, Iceland
| | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Division of Cardiology, Department of Internal Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali University Hospital, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Reykjavik, Iceland.
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland.
| | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
| |
Collapse
|
81
|
Eleven genomic loci affect plasma levels of chronic inflammation marker soluble urokinase-type plasminogen activator receptor. Commun Biol 2021; 4:655. [PMID: 34079037 PMCID: PMC8172928 DOI: 10.1038/s42003-021-02144-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 04/23/2021] [Indexed: 12/12/2022] Open
Abstract
Soluble urokinase-type plasminogen activator receptor (suPAR) is a chronic inflammation marker associated with the development of a range of diseases, including cancer and cardiovascular disease. The genetics of suPAR remain unexplored but may shed light on the biology of the marker and its connection to outcomes. We report a heritability estimate of 60% for the variation in suPAR and performed a genome-wide association meta-analysis on suPAR levels measured in Iceland (N = 35,559) and in Denmark (N = 12,177). We identified 13 independently genome-wide significant sequence variants associated with suPAR across 11 distinct loci. Associated variants were found in and around genes encoding uPAR (PLAUR), its ligand uPA (PLAU), the kidney-disease-associated gene PLA2R1 as well as genes with relations to glycosylation, glycoprotein biosynthesis, and the immune response. These findings provide new insight into the causes of variation in suPAR plasma levels, which may clarify suPAR's potential role in associated diseases, as well as the underlying mechanisms that give suPAR its prognostic value as a unique marker of chronic inflammation.
Collapse
|
82
|
Cai X, Chang L, Zhang T, Chen H, Zhang L, Lin R, Liang J, Wu J, Freeling M, Wang X. Impacts of allopolyploidization and structural variation on intraspecific diversification in Brassica rapa. Genome Biol 2021; 22:166. [PMID: 34059118 PMCID: PMC8166115 DOI: 10.1186/s13059-021-02383-2] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/20/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Despite the prevalence and recurrence of polyploidization in the speciation of flowering plants, its impacts on crop intraspecific genome diversification are largely unknown. Brassica rapa is a mesopolyploid species that is domesticated into many subspecies with distinctive morphotypes. RESULTS Herein, we report the consequences of the whole-genome triplication (WGT) on intraspecific diversification using a pan-genome analysis of 16 de novo assembled and two reported genomes. Among the genes that derive from WGT, 13.42% of polyploidy-derived genes accumulate more transposable elements and non-synonymous mutations than other genes during individual genome evolution. We denote such genes as being "flexible." We construct the Brassica rapa ancestral genome and observe the continuing influence of the dominant subgenome on intraspecific diversification in B. rapa. The gene flexibility is biased to the more fractionated subgenomes (MFs), in contrast to the more intact gene content of the dominant LF (least fractionated) subgenome. Furthermore, polyploidy-derived flexible syntenic genes are implicated in the response to stimulus and the phytohormone auxin; this may reflect adaptation to the environment. Using an integrated graph-based genome, we investigate the structural variation (SV) landscapes in 524 B. rapa genomes. We observe that SVs track morphotype domestication. Four out of 266 candidate genes for Chinese cabbage domestication are speculated to be involved in the leafy head formation. CONCLUSIONS This pan-genome uncovers the possible contributions of allopolyploidization on intraspecific diversification and the possible and underexplored role of SVs in favorable trait domestication. Collectively, our work serves as a rich resource for genome-based B. rapa improvement.
Collapse
Affiliation(s)
- Xu Cai
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Lichun Chang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Tingting Zhang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Haixu Chen
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Lei Zhang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Runmao Lin
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Jianli Liang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Jian Wu
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China
| | - Michael Freeling
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
| | - Xiaowu Wang
- Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, No.12, Haidian District, Beijing, 100081, China.
| |
Collapse
|
83
|
Asada K, Kaneko S, Takasawa K, Machino H, Takahashi S, Shinkai N, Shimoyama R, Komatsu M, Hamamoto R. Integrated Analysis of Whole Genome and Epigenome Data Using Machine Learning Technology: Toward the Establishment of Precision Oncology. Front Oncol 2021; 11:666937. [PMID: 34055633 PMCID: PMC8149908 DOI: 10.3389/fonc.2021.666937] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 04/26/2021] [Indexed: 12/17/2022] Open
Abstract
With the completion of the International Human Genome Project, we have entered what is known as the post-genome era, and efforts to apply genomic information to medicine have become more active. In particular, with the announcement of the Precision Medicine Initiative by U.S. President Barack Obama in his State of the Union address at the beginning of 2015, "precision medicine," which aims to divide patients and potential patients into subgroups with respect to disease susceptibility, has become the focus of worldwide attention. The field of oncology is also actively adopting the precision oncology approach, which is based on molecular profiling, such as genomic information, to select the appropriate treatment. However, the current precision oncology is dominated by a method called targeted-gene panel (TGP), which uses next-generation sequencing (NGS) to analyze a limited number of specific cancer-related genes and suggest optimal treatments, but this method causes the problem that the number of patients who benefit from it is limited. In order to steadily develop precision oncology, it is necessary to integrate and analyze more detailed omics data, such as whole genome data and epigenome data. On the other hand, with the advancement of analysis technologies such as NGS, the amount of data obtained by omics analysis has become enormous, and artificial intelligence (AI) technologies, mainly machine learning (ML) technologies, are being actively used to make more efficient and accurate predictions. In this review, we will focus on whole genome sequencing (WGS) analysis and epigenome analysis, introduce the latest results of omics analysis using ML technologies for the development of precision oncology, and discuss the future prospects.
Collapse
Affiliation(s)
- Ken Asada
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Syuzo Kaneko
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Ken Takasawa
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Hidenori Machino
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Satoshi Takahashi
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Norio Shinkai
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
- Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ryo Shimoyama
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Masaaki Komatsu
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Ryuji Hamamoto
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan
- Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| |
Collapse
|
84
|
Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits. Nat Genet 2021; 53:779-786. [PMID: 33972781 DOI: 10.1038/s41588-021-00865-4] [Citation(s) in RCA: 123] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 04/05/2021] [Indexed: 01/05/2023]
Abstract
Long-read sequencing (LRS) promises to improve the characterization of structural variants (SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions). We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association of a rare deletion in PCSK9 with lower low-density lipoprotein (LDL) cholesterol levels, compared to the population average. We also discovered an association of a multiallelic SV in ACAN with height; we found 11 alleles that differed in the number of a 57-bp-motif repeat and observed a linear relationship between the number of repeats carried and height. These results show that SVs can be accurately characterized at the population scale using LRS data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.
Collapse
|
85
|
Novel functional sequences uncovered through a bovine multiassembly graph. Proc Natl Acad Sci U S A 2021; 118:2101056118. [PMID: 33972446 DOI: 10.1073/pnas.2101056118] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Many genomic analyses start by aligning sequencing reads to a linear reference genome. However, linear reference genomes are imperfect, lacking millions of bases of unknown relevance and are unable to reflect the genetic diversity of populations. This makes reference-guided methods susceptible to reference-allele bias. To overcome such limitations, we build a pangenome from six reference-quality assemblies from taurine and indicine cattle as well as yak. The pangenome contains an additional 70,329,827 bases compared to the Bos taurus reference genome. Our multiassembly approach reveals 30 and 10.1 million bases private to yak and indicine cattle, respectively, and between 3.3 and 4.4 million bases unique to each taurine assembly. Utilizing transcriptomes from 56 cattle, we show that these nonreference sequences encode transcripts that hitherto remained undetected from the B. taurus reference genome. We uncover genes, primarily encoding proteins contributing to immune response and pathogen-mediated immunomodulation, differentially expressed between Mycobacterium bovis-infected and noninfected cattle that are also undetectable in the B. taurus reference genome. Using whole-genome sequencing data of cattle from five breeds, we show that reads which were previously misaligned against the Bos taurus reference genome now align accurately to the pangenome sequences. This enables us to discover 83,250 polymorphic sites that segregate within and between breeds of cattle and capture genetic differentiation across breeds. Our work makes a so-far unused source of variation amenable to genetic investigations and provides methods and a framework for establishing and exploiting a more diverse reference genome.
Collapse
|
86
|
Duran-Lozano L, Thorleifsson G, Lopez de Lapuente Portilla A, Niroula A, Went M, Thodberg M, Pertesi M, Ajore R, Cafaro C, Olason PI, Stefansdottir L, Bragi Walters G, Halldorsson GH, Turesson I, Kaiser MF, Weinhold N, Abildgaard N, Andersen NF, Mellqvist UH, Waage A, Juul-Vangsted A, Thorsteinsdottir U, Hansson M, Houlston R, Rafnar T, Stefansson K, Nilsson B. Germline variants at SOHLH2 influence multiple myeloma risk. Blood Cancer J 2021; 11:76. [PMID: 33875642 PMCID: PMC8055668 DOI: 10.1038/s41408-021-00468-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/17/2021] [Accepted: 03/31/2021] [Indexed: 12/17/2022] Open
Abstract
Multiple myeloma (MM) is caused by the uncontrolled, clonal expansion of plasma cells. While there is epidemiological evidence for inherited susceptibility, the molecular basis remains incompletely understood. We report a genome-wide association study totalling 5,320 cases and 422,289 controls from four Nordic populations, and find a novel MM risk variant at SOHLH2 at 13q13.3 (risk allele frequency = 3.5%; odds ratio = 1.38; P = 2.2 × 10-14). This gene encodes a transcription factor involved in gametogenesis that is normally only weakly expressed in plasma cells. The association is represented by 14 variants in linkage disequilibrium. Among these, rs75712673 maps to a genomic region with open chromatin in plasma cells, and upregulates SOHLH2 in this cell type. Moreover, rs75712673 influences transcriptional activity in luciferase assays, and shows a chromatin looping interaction with the SOHLH2 promoter. Our work provides novel insight into MM susceptibility.
Collapse
Affiliation(s)
- Laura Duran-Lozano
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
| | | | | | - Abhishek Niroula
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
- Broad Institute, 415 Main Street, Cambridge, MA, 02124, USA
| | - Molly Went
- Division of Genetics and Epidemiology, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
| | - Malte Thodberg
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
| | - Maroulio Pertesi
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
| | - Ram Ajore
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
| | - Caterina Cafaro
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
| | - Pall I Olason
- deCODE genetics, Sturlugata 8, IS-101, Reykjavik, Iceland
| | | | | | | | - Ingemar Turesson
- Hematology Clinic, Lund University Hospital, 221 85, Lund, Sweden
| | - Martin F Kaiser
- Division of Genetics and Epidemiology, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
| | - Niels Weinhold
- Department of Internal Medicine V, University Hospital of Heidelberg, 69120, Heidelberg, Germany
| | - Niels Abildgaard
- Hematology Research Unit, Department of Clinical Research, University of Southern Denmark and Department of Hematology, Odense University Hospital, Odense, Denmark
| | | | | | - Anders Waage
- Institute of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Department of Hematology, and Biobank1, St Olavs hospital, Trondheim, Norway
| | - Annette Juul-Vangsted
- Department of Haematology, University Hospital of Copenhagen at Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark
| | - Unnur Thorsteinsdottir
- deCODE genetics, Sturlugata 8, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Markus Hansson
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden
- Hematology Clinic, Lund University Hospital, 221 85, Lund, Sweden
| | - Richard Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK
| | - Thorunn Rafnar
- deCODE genetics, Sturlugata 8, IS-101, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics, Sturlugata 8, IS-101, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Björn Nilsson
- Hematology and Transfusion Medicine, Department of Laboratory Medicine, 221 84, Lund, Sweden.
- Broad Institute, 415 Main Street, Cambridge, MA, 02124, USA.
| |
Collapse
|
87
|
Twesigomwe D, Drögemöller BI, Wright GEB, Siddiqui A, da Rocha J, Lombard Z, Hazelhurst S. StellarPGx: A Nextflow Pipeline for Calling Star Alleles in Cytochrome P450 Genes. Clin Pharmacol Ther 2021; 110:741-749. [PMID: 33492672 DOI: 10.1002/cpt.2173] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 01/05/2021] [Indexed: 11/12/2022]
Abstract
Bioinformatics pipelines for calling star alleles (haplotypes) in cytochrome P450 (CYP) genes are important for the implementation of precision medicine. Genotyping CYP genes using high throughput sequencing data is complicated, e.g., by being highly polymorphic, not to mention the structural variations especially in CYP2D6, CYP2A6, and CYP2B6. Genome graph-based variant detection approaches have been shown to be reliable for genotyping HLA alleles. However, their application to enhancing star allele calling in CYP genes has not been extensively explored. We present StellarPGx, a Nextflow pipeline for accurately genotyping CYP genes by combining genome graph-based variant detection, read coverage information from the original reference-based alignments, and combinatorial diplotype assignments. The implementation of StellarPGx using Nextflow facilitates its portability, reproducibility, and scalability on various user platforms. StellarPGx is currently able to genotype 12 important pharmacogenes belonging to the CYP1, 2, and 3 families. For purposes of validation, we use CYP2D6 as a model gene owing to its high degree of polymorphisms (over 130 star alleles defined to date, including complex structural variants) and clinical importance. We applied StellarPGx and three existing callers to 109 whole genome sequenced samples for which the Genetic Testing Reference Material Coordination Program (GeT-RM) has recently provided consensus truth CYP2D6 diplotypes. StellarPGx had the highest CYP2D6 diplotype concordance (99%) with GeT-RM compared with Cyrius (98%), Aldy (82%), and Stargazer (84%). This exemplifies the high accuracy of StellarPGx and highlights its importance for both research and clinical pharmacogenomics applications. The StellarPGx pipeline is open-source and available from https://github.com/SBIMB/StellarPGx.
Collapse
Affiliation(s)
- David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Britt I Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Galen E B Wright
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre and Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada.,Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Azra Siddiqui
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Jorge da Rocha
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Division of Human Genetics, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Zané Lombard
- Division of Human Genetics, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| |
Collapse
|
88
|
Olafsdottir T, Stacey SN, Sveinbjornsson G, Thorleifsson G, Norland K, Sigurgeirsson B, Thorisdottir K, Kristjansson AK, Tryggvadottir L, Sarin KY, Benediktsson R, Jonasson JG, Sigurdsson A, Jonasdottir A, Kristmundsdottir S, Jonsson H, Gylfason A, Oddsson A, Fridriksdottir R, Gudjonsson SA, Zink F, Lund SH, Rognvaldsson S, Melsted P, Steinthorsdottir V, Gudmundsson J, Mikaelsdottir E, Olason PI, Stefansdottir L, Eggertsson HP, Halldorsson BV, Thorsteinsdottir U, Agustsson TT, Olafsson K, Olafsson JH, Sulem P, Rafnar T, Gudbjartsson DF, Stefansson K. Loss-of-Function Variants in the Tumor-Suppressor Gene PTPN14 Confer Increased Cancer Risk. Cancer Res 2021; 81:1954-1964. [PMID: 33602785 DOI: 10.1158/0008-5472.can-20-3065] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/16/2020] [Accepted: 02/11/2021] [Indexed: 11/16/2022]
Abstract
The success of genome-wide association studies (GWAS) in identifying common, low-penetrance variant-cancer associations for the past decade is undisputed. However, discovering additional high-penetrance cancer mutations in unknown cancer predisposing genes requires detection of variant-cancer association of ultra-rare coding variants. Consequently, large-scale next-generation sequence data with associated phenotype information are needed. Here, we used genotype data on 166,281 Icelanders, of which, 49,708 were whole-genome sequenced and 408,595 individuals from the UK Biobank, of which, 41,147 were whole-exome sequenced, to test for association between loss-of-function burden in autosomal genes and basal cell carcinoma (BCC), the most common cancer in Caucasians. A total of 25,205 BCC cases and 683,058 controls were tested. Rare germline loss-of-function variants in PTPN14 conferred substantial risks of BCC (OR, 8.0; P = 1.9 × 10-12), with a quarter of carriers getting BCC before age 70 and over half in their lifetime. Furthermore, common variants at the PTPN14 locus were associated with BCC, suggesting PTPN14 as a new, high-impact BCC predisposition gene. A follow-up investigation of 24 cancers and three benign tumor types showed that PTPN14 loss-of-function variants are associated with high risk of cervical cancer (OR, 12.7, P = 1.6 × 10-4) and low age at diagnosis. Our findings, using power-increasing methods with high-quality rare variant genotypes, highlight future prospects for new discoveries on carcinogenesis. SIGNIFICANCE: This study identifies the tumor-suppressor gene PTPN14 as a high-impact BCC predisposition gene and indicates that inactivation of PTPN14 by germline sequence variants may also lead to increased risk of cervical cancer.
Collapse
Affiliation(s)
| | | | | | | | | | - Bardur Sigurgeirsson
- Landspitali University Hospital, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Kristin Thorisdottir
- Landspitali University Hospital, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Arni Kjalar Kristjansson
- Landspitali University Hospital, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kavita Y Sarin
- Department of Dermatology, Stanford University School of Medicine, Redwood City, California
| | - Rafn Benediktsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.,Department of Endocrinology and Metabolic Medicine, Landspitali University Hospital, Reykjavík, Iceland
| | - Jon G Jonasson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.,Department of Pathology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | | | | | | | - Pall Melsted
- deCODE Genetics/Amgen, Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Reykjavik, Iceland.,School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Tomas T Agustsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.,Department of Endocrinology and Metabolic Medicine, Landspitali University Hospital, Reykjavík, Iceland.,Faculty of Odontology, School of Health Sciences, University of Iceland, Reykjavík, Iceland
| | - Karl Olafsson
- Department of Obstetrics and Gynecology, Landspitali University Hospital, Reykjavik, Iceland
| | - Jon H Olafsson
- Landspitali University Hospital, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland. .,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| |
Collapse
|
89
|
A meta-analysis uncovers the first sequence variant conferring risk of Bell's palsy. Sci Rep 2021; 11:4188. [PMID: 33602968 PMCID: PMC7893061 DOI: 10.1038/s41598-021-82736-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 01/22/2021] [Indexed: 01/31/2023] Open
Abstract
Bell's palsy is the most common cause of unilateral facial paralysis and is defined as an idiopathic and acute inability to control movements of the facial muscles on the affected side. While the pathogenesis remains unknown, previous studies have implicated post-viral inflammation and resulting compression of the facial nerve. Reported heritability estimates of 4-14% suggest a genetic component in the etiology and an autosomal dominant inheritance has been proposed. Here, we report findings from a meta-analysis of genome-wide association studies uncovering the first unequivocal association with Bell's palsy (rs9357446-A; P = 6.79 × 10-23, OR = 1.23; Ncases = 4714, Ncontrols = 1,011,520). The variant also confers risk of intervertebral disc disorders (P = 2.99 × 10-11, OR = 1.04) suggesting a common pathogenesis in part or a true pleiotropy.
Collapse
|
90
|
Bell S, Rigas AS, Magnusson MK, Ferkingstad E, Allara E, Bjornsdottir G, Ramond A, Sørensen E, Halldorsson GH, Paul DS, Burgdorf KS, Eggertsson HP, Howson JMM, Thørner LW, Kristmundsdottir S, Astle WJ, Erikstrup C, Sigurdsson JK, Vuckovic D, Dinh KM, Tragante V, Surendran P, Pedersen OB, Vidarsson B, Jiang T, Paarup HM, Onundarson PT, Akbari P, Nielsen KR, Lund SH, Juliusson K, Magnusson MI, Frigge ML, Oddsson A, Olafsson I, Kaptoge S, Hjalgrim H, Runarsson G, Wood AM, Jonsdottir I, Hansen TF, Sigurdardottir O, Stefansson H, Rye D, Peters JE, Westergaard D, Holm H, Soranzo N, Banasik K, Thorleifsson G, Ouwehand WH, Thorsteinsdottir U, Roberts DJ, Sulem P, Butterworth AS, Gudbjartsson DF, Danesh J, Brunak S, Di Angelantonio E, Ullum H, Stefansson K. A genome-wide meta-analysis yields 46 new loci associating with biomarkers of iron homeostasis. Commun Biol 2021; 4:156. [PMID: 33536631 PMCID: PMC7859200 DOI: 10.1038/s42003-020-01575-z] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 12/07/2020] [Indexed: 02/07/2023] Open
Abstract
Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation.
Collapse
Affiliation(s)
- Steven Bell
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Andreas S Rigas
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Magnus K Magnusson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
| | | | - Elias Allara
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Anna Ramond
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Dirk S Paul
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kristoffer S Burgdorf
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Joanna M M Howson
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Lise W Thørner
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - William J Astle
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | | | - Dragana Vuckovic
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Khoa M Dinh
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | - Vinicius Tragante
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Rutherford Fund Fellow, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ole B Pedersen
- Department of Clinical Immunology, Næstved Hospital, Næstved, Denmark
| | | | - Tao Jiang
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Helene M Paarup
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | - Pall T Onundarson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Laboratory Hematology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Parsa Akbari
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Kaspar R Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
| | | | | | | | | | | | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Stephen Kaptoge
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Henrik Hjalgrim
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | | | - Angela M Wood
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Thomas F Hansen
- Danish Headache Center, Department of Neurology, Rigshospitalet-Glostrup, Glostrup, Denmark
- Institute of Biological Psychiatry, Copenhagen University Hospital MHC Sct. Hans, Roskilde, Denmark
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | | | | | - David Rye
- Department of Neurology and Program in Sleep, Emory University School of Medicine, Atlanta, GA, USA
| | - James E Peters
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - David Westergaard
- Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Nicole Soranzo
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Karina Banasik
- Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Willem H Ouwehand
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- UK National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - David J Roberts
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- Radcliffe Department of Medicine and National Health Service Blood and Transplant, John Radcliffe Hospital, Oxford, UK
- UK National Health Service Blood and Transplant, John Radcliffe Hospital, Oxford, OX3 9BQ, UK
| | | | - Adam S Butterworth
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - John Danesh
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Søren Brunak
- Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Emanuele Di Angelantonio
- The National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- UK National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK.
| | - Henrik Ullum
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark.
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
| |
Collapse
|
91
|
Niehus S, Jónsson H, Schönberger J, Björnsson E, Beyter D, Eggertsson HP, Sulem P, Stefánsson K, Halldórsson BV, Kehr B. PopDel identifies medium-size deletions simultaneously in tens of thousands of genomes. Nat Commun 2021; 12:730. [PMID: 33526789 PMCID: PMC7851401 DOI: 10.1038/s41467-020-20850-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 12/14/2020] [Indexed: 12/14/2022] Open
Abstract
Thousands of genomic structural variants (SVs) segregate in the human population and can impact phenotypic traits and diseases. Their identification in whole-genome sequence data of large cohorts is a major computational challenge. Most current approaches identify SVs in single genomes and afterwards merge the identified variants into a joint call set across many genomes. We describe the approach PopDel, which directly identifies deletions of about 500 to at least 10,000 bp in length in data of many genomes jointly, eliminating the need for subsequent variant merging. PopDel scales to tens of thousands of genomes as we demonstrate in evaluations on up to 49,962 genomes. We show that PopDel reliably reports common, rare and de novo deletions. On genomes with available high-confidence reference call sets PopDel shows excellent recall and precision. Genotype inheritance patterns in up to 6794 trios indicate that genotypes predicted by PopDel are more reliable than those of previous SV callers. Furthermore, PopDel's running time is competitive with the fastest tested previous tools. The demonstrated scalability and accuracy of PopDel enables routine scans for deletions in large-scale sequencing studies.
Collapse
Affiliation(s)
- Sebastian Niehus
- Regensburg Center for Interventional Immunology (RCI), Regensburg, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Janina Schönberger
- Regensburg Center for Interventional Immunology (RCI), Regensburg, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Eythór Björnsson
- deCODE genetics/Amgen Inc., Reykjavík, Iceland
- Faculty of Medicine, School of Heath Sciences, University of Iceland, Reykjavík, Iceland
- Department of Internal Medicine, Landspítali-The National University Hospital of Iceland, Reykjavík, Iceland
| | | | | | | | - Kári Stefánsson
- deCODE genetics/Amgen Inc., Reykjavík, Iceland
- Faculty of Medicine, School of Heath Sciences, University of Iceland, Reykjavík, Iceland
| | - Bjarni V Halldórsson
- deCODE genetics/Amgen Inc., Reykjavík, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavík, Iceland
| | - Birte Kehr
- Regensburg Center for Interventional Immunology (RCI), Regensburg, Germany.
- Berlin Institute of Health (BIH), Berlin, Germany.
- Charité-Universitätsmedizin Berlin, Berlin, Germany.
- Univeristät Regensburg, Regensburg, Germany.
| |
Collapse
|
92
|
Dilthey AT. State-of-the-art genome inference in the human MHC. Int J Biochem Cell Biol 2021; 131:105882. [PMID: 33189874 DOI: 10.1016/j.biocel.2020.105882] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/29/2020] [Accepted: 11/04/2020] [Indexed: 12/20/2022]
Abstract
The Major Histocompatibility Complex (MHC) on the short arm of chromosome 6 is associated with more diseases than any other region of the genome; it encodes the antigen-presenting Human Leukocyte Antigen (HLA) proteins and is one of the key immunogenetic regions of the genome. Accurate genome inference and interpretation of MHC association signals have traditionally been hampered by the region's uniquely complex features, such as high levels of polymorphism; inter-gene sequence homologies; structural variation; and long-range haplotype structures. Recent algorithmic and technological advances have, however, significantly increased the accessibility of genetic variation in the MHC; these developments include (i) accurate SNP-based HLA type imputation; (ii) genome graph approaches for variation-aware genome inference from next-generation sequencing data; (iii) long-read-based diploid de novo assembly of the MHC; (iv) cost-effective targeted MHC sequencing methods. Applied to hundreds of thousands of samples over the last years, these technologies have already enabled significant biological discoveries, for example in the field of autoimmune disease genetics. Remaining challenges concern the development of integrated methods that leverage haplotype-resolved de novo assembly of the MHC for the development of improved MHC genotyping methods for short reads and the construction of improved reference panels for SNP-based imputation. Improved genome inference in the MHC can crucially contribute to an improved genetic and functional understanding of many immune-related phenotypes and diseases.
Collapse
Affiliation(s)
- Alexander T Dilthey
- Institute of Medical Statistics and Computational Biology, University of Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany; Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| |
Collapse
|
93
|
Differences between germline genomes of monozygotic twins. Nat Genet 2021; 53:27-34. [PMID: 33414551 DOI: 10.1038/s41588-020-00755-1] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 11/20/2020] [Indexed: 12/16/2022]
Abstract
Despite the important role that monozygotic twins have played in genetics research, little is known about their genomic differences. Here we show that monozygotic twins differ on average by 5.2 early developmental mutations and that approximately 15% of monozygotic twins have a substantial number of these early developmental mutations specific to one of them. Using the parents and offspring of twins, we identified pre-twinning mutations. We observed instances where a twin was formed from a single cell lineage in the pre-twinning cell mass and instances where a twin was formed from several cell lineages. CpG>TpG mutations increased in frequency with embryonic development, coinciding with an increase in DNA methylation. Our results indicate that allocations of cells during development shapes genomic differences between monozygotic twins.
Collapse
|
94
|
Abstract
A description of the genetic makeup of a species based on a single genome is often insufficient because it ignores the variability in gene repertoire among multiple strains. The estimation of the pangenome of a species is a solution to this issue as it provides an overview of genes that are shared by all strains and genes that are present in only some of the genomes. These different sets of genes can then be analyzed functionally to explore correlations with unique phenotypes and adaptations. This protocol presents the usage of Roary, a Linux-native pangenome application. Roary is a straightforward software that provides 1) an overview about core and accessory genes for those interested in general trends and, also, 2) detailed information on gene presence/absence in each genome for in-depth analyses. Results are provided both in text and graphic format.
Collapse
Affiliation(s)
- Farrah Sitto
- Department of Biological Sciences, Oakland University, Rochester, MI
| | - Fabia U Battistuzzi
- Department of Biological Sciences, Oakland University, Rochester, MI
- Center for Data Science and Big Data Analytics, Oakland University, Rochester, MI
- Corresponding author: E-mail:
| |
Collapse
|
95
|
Li H, Feng X, Chu C. The design and construction of reference pangenome graphs with minigraph. Genome Biol 2020; 21:265. [PMID: 33066802 PMCID: PMC7568353 DOI: 10.1186/s13059-020-02168-z] [Citation(s) in RCA: 156] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 09/23/2020] [Indexed: 12/21/2022] Open
Abstract
The recent advances in sequencing technologies enable the assembly of individual genomes to the quality of the reference genome. How to integrate multiple genomes from the same species and make the integrated representation accessible to biologists remains an open challenge. Here, we propose a graph-based data model and associated formats to represent multiple genomes while preserving the coordinate of the linear reference genome. We implement our ideas in the minigraph toolkit and demonstrate that we can efficiently construct a pangenome graph and compactly encode tens of thousands of structural variants missing from the current reference genome.
Collapse
Affiliation(s)
- Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, 02215, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02215, MA, USA.
| | - Xiaowen Feng
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, 02215, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02215, MA, USA
| | - Chong Chu
- Department of Biomedical Informatics, Harvard Medical School, Boston, 02215, MA, USA
| |
Collapse
|
96
|
Gisladottir RS, Ivarsdottir EV, Helgason A, Jonsson L, Hannesdottir NK, Rutsdottir G, Arnadottir GA, Skuladottir A, Jonsson BA, Norddahl GL, Ulfarsson MO, Helgason H, Halldorsson BV, Nawaz MS, Tragante V, Sveinbjornsson G, Thorgeirsson T, Oddsson A, Kristjansson RP, Bjornsdottir G, Thorgeirsson G, Jonsdottir I, Holm H, Gudbjartsson DF, Thorsteinsdottir U, Stefansson H, Sulem P, Stefansson K. Sequence Variants in TAAR5 and Other Loci Affect Human Odor Perception and Naming. Curr Biol 2020; 30:4643-4653.e3. [PMID: 33035477 DOI: 10.1016/j.cub.2020.09.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 04/17/2020] [Accepted: 09/03/2020] [Indexed: 11/17/2022]
Abstract
Olfactory receptor (OR) genes in humans form a special class characterized by unusually high DNA sequence diversity, which should give rise to differences in perception and behavior. In the largest genome-wide association study to date based on olfactory testing, we investigated odor perception and naming with smell tasks performed by 9,122 Icelanders, with replication in a separate sample of 2,204 individuals. We discovered an association between a low-frequency missense variant in TAAR5 and reduced intensity rating of fish odor containing trimethylamine (p.Ser95Pro, pcombined = 5.6 × 10-15). We demonstrate that TAAR5 genotype affects aversion to fish odor, reflected by linguistic descriptions of the odor and pleasantness ratings. We also discovered common sequence variants in two canonical olfactory receptor loci that associate with increased intensity and naming of licorice odor (trans-anethole: lead variant p.Lys233Asn in OR6C70, pcombined = 8.8 × 10-16 and pcombined = 1.4 × 10-9) and enhanced naming of cinnamon (trans-cinnamaldehyde; intergenic variant rs317787-T, pcombined = 5.0 × 10-17). Together, our results show that TAAR5 genotype variation influences human odor responses and highlight that sequence diversity in canonical OR genes can lead to enhanced olfactory ability, in contrast to the view that greater tolerance for mutations in the human OR repertoire leads to diminished function.
Collapse
Affiliation(s)
- Rosa S Gisladottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; School of Humanities, University of Iceland, Saemundargata 2, 102 Reykjavik, Iceland.
| | - Erna V Ivarsdottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; School of Engineering and Natural Sciences, University of Iceland, Dunhagi 5, 107 Reykjavik, Iceland
| | - Agnar Helgason
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Department of Anthropology, University of Iceland, Saemundargata 10, 102 Reykjavik, Iceland
| | - Lina Jonsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Department of Pharmacology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 13, SE-405 30, Gothenburg, Sweden; The Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Blå Stråket 15, 413 45, Gothenburg, Sweden
| | | | | | | | | | | | | | - Magnus O Ulfarsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Faculty of Electrical and Computer Engineering, University of Iceland, Dunhagi 5, 107 Reykjavik, Iceland
| | - Hannes Helgason
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | - Bjarni V Halldorsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; School of Technology, Reykjavik University, Menntavegur 1, 101 Reykjavik, Iceland
| | - Muhammad S Nawaz
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | | | | | | | - Asmundur Oddsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | | | | | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali, The National University Hospital of Iceland, Hringbraut, 101 Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland; Department of Immunology, Landspitali, The National University Hospital of Iceland, Hringbraut, 101 Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; School of Engineering and Natural Sciences, University of Iceland, Dunhagi 5, 107 Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | | | - Patrick Sulem
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland.
| |
Collapse
|
97
|
Crysnanto D, Pausch H. Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery. Genome Biol 2020; 21:184. [PMID: 32718320 PMCID: PMC7385871 DOI: 10.1186/s13059-020-02105-0%0a%0a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 07/14/2020] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND The current bovine genomic reference sequence was assembled from a Hereford cow. The resulting linear assembly lacks diversity because it does not contain allelic variation, a drawback of linear references that causes reference allele bias. High nucleotide diversity and the separation of individuals by hundreds of breeds make cattle ideally suited to investigate the optimal composition of variation-aware references. RESULTS We augment the bovine linear reference sequence (ARS-UCD1.2) with variants filtered for allele frequency in dairy (Brown Swiss, Holstein) and dual-purpose (Fleckvieh, Original Braunvieh) cattle breeds to construct either breed-specific or pan-genome reference graphs using the vg toolkit. We find that read mapping is more accurate to variation-aware than linear references if pre-selected variants are used to construct the genome graphs. Graphs that contain random variants do not improve read mapping over the linear reference sequence. Breed-specific augmented and pan-genome graphs enable almost similar mapping accuracy improvements over the linear reference. We construct a whole-genome graph that contains the Hereford-based reference sequence and 14 million alleles that have alternate allele frequency greater than 0.03 in the Brown Swiss cattle breed. Our novel variation-aware reference facilitates accurate read mapping and unbiased sequence variant genotyping for SNPs and Indels. CONCLUSIONS We develop the first variation-aware reference graph for an agricultural animal ( https://doi.org/10.5281/zenodo.3759712 ). Our novel reference structure improves sequence read mapping and variant genotyping over the linear reference. Our work is a first step towards the transition from linear to variation-aware reference structures in species with high genetic diversity and many sub-populations.
Collapse
|
98
|
Crysnanto D, Pausch H. Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery. Genome Biol 2020; 21:184. [PMID: 32718320 PMCID: PMC7385871 DOI: 10.1186/s13059-020-02105-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 07/14/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The current bovine genomic reference sequence was assembled from a Hereford cow. The resulting linear assembly lacks diversity because it does not contain allelic variation, a drawback of linear references that causes reference allele bias. High nucleotide diversity and the separation of individuals by hundreds of breeds make cattle ideally suited to investigate the optimal composition of variation-aware references. RESULTS We augment the bovine linear reference sequence (ARS-UCD1.2) with variants filtered for allele frequency in dairy (Brown Swiss, Holstein) and dual-purpose (Fleckvieh, Original Braunvieh) cattle breeds to construct either breed-specific or pan-genome reference graphs using the vg toolkit. We find that read mapping is more accurate to variation-aware than linear references if pre-selected variants are used to construct the genome graphs. Graphs that contain random variants do not improve read mapping over the linear reference sequence. Breed-specific augmented and pan-genome graphs enable almost similar mapping accuracy improvements over the linear reference. We construct a whole-genome graph that contains the Hereford-based reference sequence and 14 million alleles that have alternate allele frequency greater than 0.03 in the Brown Swiss cattle breed. Our novel variation-aware reference facilitates accurate read mapping and unbiased sequence variant genotyping for SNPs and Indels. CONCLUSIONS We develop the first variation-aware reference graph for an agricultural animal ( https://doi.org/10.5281/zenodo.3759712 ). Our novel reference structure improves sequence read mapping and variant genotyping over the linear reference. Our work is a first step towards the transition from linear to variation-aware reference structures in species with high genetic diversity and many sub-populations.
Collapse
|
99
|
Pourkheirandish M, Golicz AA, Bhalla PL, Singh MB. Global Role of Crop Genomics in the Face of Climate Change. FRONTIERS IN PLANT SCIENCE 2020; 11:922. [PMID: 32765541 PMCID: PMC7378793 DOI: 10.3389/fpls.2020.00922] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Accepted: 06/05/2020] [Indexed: 05/05/2023]
Abstract
The development of climate change resilient crops is necessary if we are to meet the challenge of feeding the growing world's population. We must be able to increase food production despite the projected decrease in arable land and unpredictable environmental conditions. This review summarizes the technological and conceptual advances that have the potential to transform plant breeding, help overcome the challenges of climate change, and initiate the next plant breeding revolution. Recent developments in genomics in combination with high-throughput and precision phenotyping facilitate the identification of genes controlling critical agronomic traits. The discovery of these genes can now be paired with genome editing techniques to rapidly develop climate change resilient crops, including plants with better biotic and abiotic stress tolerance and enhanced nutritional value. Utilizing the genetic potential of crop wild relatives (CWRs) enables the domestication of new species and the generation of synthetic polyploids. The high-quality crop plant genome assemblies and annotations provide new, exciting research targets, including long non-coding RNAs (lncRNAs) and cis-regulatory regions. Metagenomic studies give insights into plant-microbiome interactions and guide selection of optimal soils for plant cultivation. Together, all these advances will allow breeders to produce improved, resilient crops in relatively short timeframes meeting the demands of the growing population and changing climate.
Collapse
Affiliation(s)
| | | | | | - Mohan B. Singh
- Plant Molecular Biology and Biotechnology Laboratory, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC, Australia
| |
Collapse
|
100
|
Weisberg AJ, Davis EW, Tabima J, Belcher MS, Miller M, Kuo CH, Loper JE, Grünwald NJ, Putnam ML, Chang JH. Unexpected conservation and global transmission of agrobacterial virulence plasmids. Science 2020; 368:368/6495/eaba5256. [PMID: 32499412 DOI: 10.1126/science.aba5256] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 02/28/2020] [Accepted: 04/27/2020] [Indexed: 12/21/2022]
Abstract
The accelerated evolution and spread of pathogens are threats to host species. Agrobacteria require an oncogenic Ti or Ri plasmid to transfer genes into plants and cause disease. We developed a strategy to characterize virulence plasmids and applied it to analyze hundreds of strains collected between 1927 and 2017, on six continents and from more than 50 host species. In consideration of prior evidence for prolific recombination, it was surprising that oncogenic plasmids are descended from a few conserved lineages. Characterization of a hierarchy of features that promote or constrain plasticity allowed inference of the evolutionary history across the plasmid lineages. We uncovered epidemiological patterns that highlight the importance of plasmid transmission in pathogen diversification as well as in long-term persistence and the global spread of disease.
Collapse
Affiliation(s)
- Alexandra J Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Edward W Davis
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA.,Molecular and Cellular Biology Program, Oregon State University, Corvallis, OR 97331, USA
| | - Javier Tabima
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Michael S Belcher
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Marilyn Miller
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Chih-Horng Kuo
- Institute of Plant and Microbial Biology, Academia Sinica, Taipei 11529, Taiwan
| | - Joyce E Loper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA.,Molecular and Cellular Biology Program, Oregon State University, Corvallis, OR 97331, USA.,Horticultural Crops Research Laboratory, USDA Agricultural Research Service, Corvallis, OR 97331, USA
| | - Niklaus J Grünwald
- Horticultural Crops Research Laboratory, USDA Agricultural Research Service, Corvallis, OR 97331, USA
| | - Melodie L Putnam
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Jeff H Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA. .,Molecular and Cellular Biology Program, Oregon State University, Corvallis, OR 97331, USA.,Center for Genome Research and Biocomputing (CGRB), Oregon State University, Corvallis, OR 97331, USA
| |
Collapse
|