Haplotype-resolved diverse human genomes and integrated analysis of structural variation-Reference-Cited by-同舟云学术

Haplotype-resolved diverse human genomes and integrated analysis of structural variation

Published:2021-04-02 Issue:6537 Volume:372 Page:
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Ebert Peter¹^ORCID,Audano Peter A.²^ORCID,Zhu Qihui³^ORCID,Rodriguez-Martin Bernardo⁴^ORCID,Porubsky David²^ORCID,Bonder Marc Jan⁴⁵^ORCID,Sulovari Arvis²^ORCID,Ebler Jana¹^ORCID,Zhou Weichen⁶^ORCID,Serra Mari Rebecca¹^ORCID,Yilmaz Feyza³^ORCID,Zhao Xuefang⁷⁸^ORCID,Hsieh PingHsun²^ORCID,Lee Joyce⁹^ORCID,Kumar Sushant¹⁰^ORCID,Lin Jiadong¹¹^ORCID,Rausch Tobias⁴^ORCID,Chen Yu¹²^ORCID,Ren Jingwen¹³,Santamarina Martin¹⁴¹⁵,Höps Wolfram⁴,Ashraf Hufsah¹,Chuang Nelson T.¹⁶,Yang Xiaofei¹⁷^ORCID,Munson Katherine M.²^ORCID,Lewis Alexandra P.²^ORCID,Fairley Susan¹⁸^ORCID,Tallon Luke J.¹⁶^ORCID,Clarke Wayne E.¹⁹,Basile Anna O.¹⁹^ORCID,Byrska-Bishop Marta¹⁹^ORCID,Corvelo André¹⁹^ORCID,Evani Uday S.¹⁹,Lu Tsung-Yu¹³^ORCID,Chaisson Mark J. P.¹³,Chen Junjie²⁰^ORCID,Li Chong²⁰,Brand Harrison⁷⁸,Wenger Aaron M.²¹^ORCID,Ghareghani Maryam¹²²²³,Harvey William T.²^ORCID,Raeder Benjamin⁴^ORCID,Hasenfeld Patrick⁴^ORCID,Regier Allison A.²⁴^ORCID,Abel Haley J.²⁴,Hall Ira M.²⁵^ORCID,Flicek Paul¹⁸^ORCID,Stegle Oliver⁴⁵^ORCID,Gerstein Mark B.¹⁰^ORCID,Tubio Jose M. C.¹⁴¹⁵^ORCID,Mu Zepeng²⁶^ORCID,Li Yang I.²⁷^ORCID,Shi Xinghua²⁰,Hastie Alex R.⁹^ORCID,Ye Kai¹¹²⁸^ORCID,Chong Zechen¹²^ORCID,Sanders Ashley D.⁴^ORCID,Zody Michael C.¹⁹^ORCID,Talkowski Michael E.⁷⁸^ORCID,Mills Ryan E.⁶²⁸^ORCID,Devine Scott E.¹⁶^ORCID,Lee Charles³²⁹³⁰^ORCID,Korbel Jan O.⁴¹⁸^ORCID,Marschall Tobias¹^ORCID,Eichler Evan E.²³¹^ORCID

Affiliation:

1. Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 20, 40225 Düsseldorf, Germany.

2. Department of Genome Sciences, University of Washington School of Medicine, 3720 15th Avenue NE, Seattle, WA 98195-5065, USA.

3. The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.

4. European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany.

5. Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.

6. Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, 100 Washtenaw Avenue, Ann Arbor, MI 48109, USA.

7. Center for Genomic Medicine, Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, MA 02114, USA.

8. Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

9. Bionano Genomics, San Diego, CA 92121, USA.

10. Program in Computational Biology and Bioinformatics, Yale University, BASS 432 and 437, 266 Whitney Avenue, New Haven, CT 06520, USA.

11. School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, China.

12. Department of Genetics and Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

13. Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.

14. Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.

15. Department of Zoology, Genetics, and Physical Anthropology, Universidade de Santiago de Compostela, Santiago de Compostela, Spain.

16. Institute for Genome Sciences, University of Maryland School of Medicine, 670 W Baltimore Street, Baltimore, MD 21201, USA.

17. School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, China.

18. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

19. New York Genome Center, New York, NY 10013, USA.

20. Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA.

21. Pacific Biosciences of California, Menlo Park, CA 94025, USA.

22. Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, 66123 Saarbrücken, Germany.

23. Saarbrücken Graduate School of Computer Science, Saarland University, Saarland Informatics Campus E1.3, 66123 Saarbrücken, Germany.

24. Department of Medicine, Washington University, St. Louis, MO 63108, USA.

25. Department of Genetics, Yale School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA.

26. Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL 60637, USA.

27. Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.

28. Department of Human Genetics, University of Michigan, 1241 E. Catherine Street, Ann Arbor, MI 48109, USA.

29. Precision Medicine Center, The First Affiliated Hospital of Xi’an Jiaotong University, 277 West Yanta Road, Xi’an, 710061, Shaanxi, China.

30. Department of Graduate Studies–Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, South Korea.

31. Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.

Abstract

Resolving genomic structural variation Many human genomes have been reported using short-read technology, but it is difficult to resolve structural variants (SVs) using these data. These genomes thus lack comprehensive comparisons among individuals and populations. Ebert et al. used long-read structural variation calling across 64 human genomes representing diverse populations and developed new methods for variant discovery. This approach allowed the authors to increase the number of confirmed SVs and to describe the patterns of variation across populations. From this dataset, they identified quantitative trait loci affected by these SVs and determined how they may affect gene expression and potentially explain genome-wide association study hits. This information provides insights into patterns of normal human genetic variation and generates reference genomes that better represent the diversity of our species. Science , this issue p. eabf7117

Funder

National Institutes of Health

National Human Genome Research Institute

National Science Foundation of China

Wellcome

Bundesministerium für Bildung und Forschung

Deutsche Forschungsgemeinschaft

European Research Council

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary