Predicting causal variants affecting expression by using whole-genome sequencing and RNA-seq from multiple human tissues

Nature Genetics

Volumn 49, Issue 12, 2017, Pages 1747-1751

  Brown, Andrew Anand ^a,b,c,d   Viñuela, Ana ^a,b,c   Delaneau, Olivier ^a,b,c   Spector, Tim D ^e   Small, Kerrin S ^e   Dermitzakis, Emmanouil T ^a,b,c  

^a UNIVERSITY OF GENEVA MEDICAL SCHOOL   (Switzerland)

^b UNIVERSITY OF GENEVA   (Switzerland)

^c SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^d OSLO UNIVERSITY HOSPITAL   (Norway)

^e KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FURIN; G PROTEIN COUPLED RECEPTOR 30; GLUCOSE; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; INSULIN; LOW DENSITY LIPOPROTEIN CHOLESTEROL; TRIACYLGLYCEROL;

ADIPOSE TISSUE; ARTICLE; BIRTH WEIGHT; BODY HEIGHT; BODY MASS; CHOLESTEROL BLOOD LEVEL; CHROMATIN IMMUNOPRECIPITATION; COHORT ANALYSIS; CONTROLLED STUDY; CORONARY ARTERY DISEASE; CROHN DISEASE; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE FREQUENCY; GENE LINKAGE DISEQUILIBRIUM; GENE MAPPING; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; GLUCOSE BLOOD LEVEL; HETEROZYGOTE; HUMAN; HUMAN CELL; HUMAN TISSUE; IRRITABLE COLON; LIPID BLOOD LEVEL; LYMPHOBLASTOID CELL LINE; PHENOTYPE; PRIORITY JOURNAL; QUANTITATIVE TRAIT LOCUS; RNA SEQUENCE; SCHIZOPHRENIA; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM; SKIN; ULCERATIVE COLITIS; WHOLE GENOME SEQUENCING; CHROMOSOMAL MAPPING; GENETIC PREDISPOSITION; GENETIC VARIATION; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN GENOME; PROCEDURES; REPRODUCIBILITY;

CHROMOSOME MAPPING; GENE EXPRESSION PROFILING; GENETIC PREDISPOSITION TO DISEASE; GENETIC VARIATION; GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI; REPRODUCIBILITY OF RESULTS;

EID: 85035788095     PISSN: 10614036     EISSN: 15461718     Source Type: Journal    
DOI: 10.1038/ng.3979     Document Type: Article

References (50)

1. Welter, D., et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 42, D1001-D1006 (2014).
2. Spain, S.L. , Barrett, J.C. Strategies for fine-mapping complex traits. Hum. Mol. Genet. 24, R111-R119 (2015).
3. Marchini, J. , Howie, B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499-511 (2010).
4. Lappalainen, T., et al. Transcriptome, genome sequencing uncovers functional variation in humans. Nature 501, 506-511 (2013).
5. Brown, A.A., et al. Genetic interactions affecting human gene expression identified by variance association mapping. eLife 3, e01381 (2014).
6. Buil, A., et al. Gene-gene, gene-environment interactions detected by transcriptome sequence analysis in twins. Nat. Genet. 47, 88-91 (2015).
7. UK10K Consortium., et al. The UK10K project identifies rare variants in health, disease. Nature 526, 82-90 (2015).
8. Grundberg, E., et al. Mapping cis-, trans-regulatory effects across multiple tissues in twins. Nat. Genet. 44, 1084-1089 (2012).
9. Timpson, N.J., et al. A rare variant in APOC3 is associated with plasma triglyceride, VLDL levels in Europeans. Nat. Commun. 5, 4871 (2014).
10. Iotchkova, V., et al. Discovery, refinement of genetic loci associated with cardiometabolic risk using dense imputation maps. Nat. Genet. 48, 1303-1312 (2016).
11. Kundaje, A., et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317-330 (2015).
12. Lebreton, C.M. , Visscher, P.M. Empirical nonparametric bootstrap strategies in quantitative trait loci mapping: Conditioning on the genetic model. Genetics 148, 525-535 (1998).
13. Visscher, P.M., Thompson, R. , Haley, C.S. Confidence intervals in QTL mapping by bootstrapping. Genetics 143, 1013-1020 (1996).
14. Hormozdiari, F., Kostem, E., Kang, E.Y., Pasaniuc, B. , Eskin, E. Identifying causal variants at loci with multiple signals of association. Genetics 198, 497-508 (2014).
15. Wen, X., Lee, Y., Luca, F. , Pique-Regi, R. Efficient integrative multi-SNP association analysis via deterministic approximation of posteriors. Am. J. Hum. Genet. 98, 1114-1129 (2016).
16. Manolio, T.A., et al. Finding the missing heritability of complex diseases. Nature 461, 747-753 (2009).
17. Storey, J.D. , Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA 100, 9440-9445 (2003).
18. Nica, A.C., et al. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLoS Genet. 6, e1000895 (2010).
19. Ongen, H., et al. Estimating the causal tissues for complex traits, diseases. Nat. Genet. http://dx.doi.org/10.1038/ng.3981 2017).
20. Giambartolomei, C., et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).
21. Sharma, G., et al. GPER deficiency in male mice results in insulin resistance, dyslipidemia, a proinflammatory state. Endocrinology 154, 4136-4145 (2013).
22. Meyre, D., et al. Genome-wide association study for early-onset, morbid adult obesity identifies three new risk loci in European populations. Nat. Genet. 41, 157-159 (2009).
23. Jelinek, D., Heidenreich, R.A., Erickson, R.P. , Garver, W.S. Decreased Npc1 gene dosage in mice is associated with weight gain. Obesity (Silver Spring) 18, 1457-1459 (2010).
24. Jelinek, D., et al. Npc1 haploinsufficiency promotes weight gain, metabolic features associated with insulin resistance. Hum. Mol. Genet. 20, 312-321 (2011).
25. Bambace, C., Dahlman, I., Arner, P. , Kulyté, A. NPC1 in human white adipose tissue, obesity. BMC Endocr. Disord. 13, 5 (2013).
26. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421-427 (2014).
27. Fromer, M., et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci. 19, 1442-1453 (2016).
28. Hormozdiari, F., et al. Colocalization of GWAS, eQTL signals detects target genes. Am. J. Hum. Genet. 99, 1245-1260 (2016).
29. Lander, E.S., et al. Initial sequencing, analysis of the human genome. Nature 409, 860-921 (2001).
30. Marco-Sola, S., Sammeth, M., Guigó, R. , Ribeca, P. The GEM mapper: Fast, accurate, versatile alignment by filtration. Nat. Methods 9, 1185-1188 (2012).
31. Harrow, J., et al. GENCODE: The reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760-1774 (2012).
32. 1000 Genomes Project Consortium., et al. A global reference for human genetic variation. Nature 526, 68-74 (2015).
33. Ongen, H., Buil, A., Brown, A.A., Dermitzakis, E.T. , Delaneau, O. Fast, efficient QTL mapper for thousands of molecular phenotypes. Bioinformatics 32, 1479-1485 (2016).
34. Flutre, T., Wen, X., Pritchard, J. , Stephens, M. A statistical framework for joint eQTL analysis in multiple tissues. PLoS Genet. 9, e1003486 (2013).
35. Wen, X., Luca, F. , Pique-Regi, R. Cross-population joint analysis of eQTLs: Fine mapping, functional annotation. PLoS Genet. 11, e1005176 (2015).
36. Servin, B. , Stephens, M. Imputation-based analysis of association studies: Candidate regions, quantitative traits. PLoS Genet. 3, e114 (2007).
37. The International Multiple Sclerosis Genetics Consortium. Analysis of immunerelated loci identifies 48 new susceptibility variants for multiple sclerosis. Nat. Genet. 45, 1353-1360 (2013).
38. Chen, W., et al. Fine mapping causal variants with an approximate Bayesian method using marginal test statistics. Genetics 200, 719-736 (2015).
39. Benner, C., et al. FINEMAP: Efficient variable selection using summary data from genome-wide association studies. Bioinformatics 32, 1493-1501 (2016).
40. Robinson, E.B., et al. Genetic risk for autism spectrum disorders, neuropsychiatric variation in the general population. Nat. Genet. 48, 552-555 (2016).
41. Horikoshi, M., et al. Genome-wide associations for birth weight, correlations with adult disease. Nature 538, 248-252 (2016).
42. Locke, A.E., et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197-206 (2015).
43. Nikpay, M., et al. A comprehensive 1, 000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat. Genet. 47, 1121-1130 (2015).
44. Liu, J.Z., et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease, highlight shared genetic risk across populations. Nat. Genet. 47, 979-986 (2015).
45. Fuchsberger, C., et al. The genetic architecture of type 2 diabetes. Nature 536, 41-47 (2016).
46. Manning, A.K., et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits, insulin resistance. Nat. Genet. 44, 659-669 (2012).
47. Wood, A.R., et al. Defining the role of common variation in the genomic, biological architecture of adult human height. Nat. Genet. 46, 1173-1186 (2014).
48. Willer, C.J., et al.; Global Lipid Genetics Consortium. Discovery, refinement of loci associated with lipid levels. Nat. Genet. 45, 1274-1283 (2013).
49. Sherry, S.T., et al. dbSNP: The NCBI database of genetic variation. Nucleic Acids Res. 29, 308-311 (2001).
50. Delaneau, O., et al. A complete tool set for molecular QTL discovery, analysis. Nat. Commun. 8, 15452 (2017).