دورية أكاديمية
أعرض في EDS

Powerful eQTL mapping through low-coverage RNA sequencing.

التفاصيل البيبلوغرافية
العنوان: Powerful eQTL mapping through low-coverage RNA sequencing.
المؤلفون: Schwarz T; Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA.; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA., Boltz T; Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA., Hou K; Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA., Bot M; Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA., Duan C; Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA., Loohuis LO; Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.; Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA., Boks MP; Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands., Kahn RS; Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, the Netherlands.; Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA., Ophoff RA; Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA.; Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.; Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands., Pasaniuc B; Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA.; Department of Computational Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.; Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
المصدر: HGG advances [HGG Adv] 2022 Apr 02; Vol. 3 (3), pp. 100103. Date of Electronic Publication: 2022 Apr 02 (Print Publication: 2022).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Elsevier Inc Country of Publication: United States NLM ID: 101772885 Publication Model: eCollection Cited Medium: Internet ISSN: 2666-2477 (Electronic) Linking ISSN: 26662477 NLM ISO Abbreviation: HGG Adv Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: New York : Elsevier Inc., [2020]-
مستخلص: Mapping genetic variants that regulate gene expression (eQTL mapping) in large-scale RNA sequencing (RNA-seq) studies is often employed to understand functional consequences of regulatory variants. However, the high cost of RNA-seq limits sample size, sequencing depth, and, therefore, discovery power in eQTL studies. In this work, we demonstrate that, given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample and increasing the number of individuals sequenced in the assay. We perform RNA-seq of whole-blood tissue across 1,490 individuals at low coverage (5.9 million reads/sample) and show that the effective power is higher than that of an RNA-seq study of 570 individuals at moderate coverage (13.9 million reads/sample). Next, we leverage synthetic datasets derived from real RNA-seq data (50 million reads/sample) to explore the interplay of coverage and number individuals in eQTL studies, and show that a 10-fold reduction in coverage leads to only a 2.5-fold reduction in statistical power to identify eQTLs. Our work suggests that lowering coverage while increasing the number of individuals in RNA-seq is an effective approach to increase discovery power in eQTL studies.
Competing Interests: The authors declare no competing interests.
(© 2022 The Authors.)
References: Nat Genet. 2016 Mar;48(3):245-52. (PMID: 26854917)
Curr Protoc Hum Genet. 2014 Oct 01;83:11.13.1-20. (PMID: 25271838)
PLoS Genet. 2014 May 15;10(5):e1004383. (PMID: 24830394)
Science. 2020 Sep 11;369(6509):1318-1330. (PMID: 32913098)
Am J Hum Genet. 2017 Mar 2;100(3):473-487. (PMID: 28238358)
BMC Bioinformatics. 2018 Nov 14;19(1):423. (PMID: 30428853)
PLoS Comput Biol. 2017 Sep 18;13(9):e1005766. (PMID: 28922377)
Nature. 2015 Jul 30;523(7562):588-91. (PMID: 26176920)
Nat Biotechnol. 2019 Jul;37(7):773-782. (PMID: 31061481)
Nature. 2010 Apr 1;464(7289):768-72. (PMID: 20220758)
Genome Res. 2011 Dec;21(12):2213-23. (PMID: 21903743)
Nat Methods. 2013 Apr;10(4):325-7. (PMID: 23435259)
Genome Med. 2019 Nov 26;11(1):74. (PMID: 31771638)
Nat Biotechnol. 2016 May;34(5):525-7. (PMID: 27043002)
Nat Commun. 2020 Oct 30;11(1):5504. (PMID: 33127880)
Bioinformatics. 2020 Feb 1;36(3):930-933. (PMID: 31393554)
Nat Genet. 2020 Jun;52(6):626-633. (PMID: 32424349)
Bioinformatics. 2014 Dec 1;30(23):3424-6. (PMID: 25189781)
Nature. 2010 Apr 1;464(7289):773-7. (PMID: 20220756)
Nature. 2017 Oct 11;550(7675):204-213. (PMID: 29022597)
Science. 2016 Aug 19;353(6301):827-30. (PMID: 27540175)
Am J Hum Genet. 2001 Jul;69(1):1-14. (PMID: 11410837)
Genome Res. 2008 Sep;18(9):1509-17. (PMID: 18550803)
Am J Hum Genet. 2018 May 3;102(5):717-730. (PMID: 29727686)
Nat Rev Genet. 2009 Jan;10(1):57-63. (PMID: 19015660)
Nat Genet. 2017 Jan;49(1):139-145. (PMID: 27918533)
Psychol Med. 2020 Nov;50(15):2575-2586. (PMID: 31589133)
Nat Genet. 2021 Mar;53(3):412. (PMID: 33473199)
Sci Data. 2019 Sep 24;6(1):180. (PMID: 31551426)
Nature. 2015 Oct 1;526(7571):68-74. (PMID: 26432245)
Nat Genet. 2015 Dec;47(12):1457-1464. (PMID: 26502338)
Genome Biol. 2021 Apr 29;22(1):122. (PMID: 33926512)
PLoS One. 2013 Jun 24;8(6):e66883. (PMID: 23826166)
Am J Hum Genet. 2007 Sep;81(3):559-75. (PMID: 17701901)
Nat Rev Genet. 2014 Feb;15(2):121-32. (PMID: 24434847)
Nat Genet. 2015 Sep;47(9):1091-8. (PMID: 26258848)
Am J Hum Genet. 2017 Feb 2;100(2):228-237. (PMID: 28065468)
Bioinformatics. 2016 May 15;32(10):1479-85. (PMID: 26708335)
Bioinformatics. 2015 Sep 1;31(17):2778-84. (PMID: 25926345)
Nat Genet. 2012 May 20;44(6):631-5. (PMID: 22610117)
Nat Rev Genet. 2006 Nov;7(11):862-72. (PMID: 17047685)
Nat Genet. 2021 Sep;53(9):1300-1310. (PMID: 34475573)
Nature. 2012 Dec 20;492(7429):369-75. (PMID: 23222517)
Nat Commun. 2018 Apr 10;9(1):1366. (PMID: 29636450)
فهرسة مساهمة: Keywords: RNA-seq; association testing; eQTL mapping; low coverage
تواريخ الأحداث: Date Created: 20220506 Latest Revision: 20220716
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC9062329
DOI: 10.1016/j.xhgg.2022.100103
PMID: 35519825
قاعدة البيانات: MEDLINE
الوصف
تدمد:2666-2477
DOI:10.1016/j.xhgg.2022.100103