1. Pickrell, J. K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768–772 (2010).

2. GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580–585 (2013).

3. Gamazon, E. R. et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091–1098 (2015).

4. Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239–243 (2017).

5. Edwards, S. L., Beesley, J., French, J. D. & Dunning, A. M. Beyond GWASs: illuminating the dark road from association to function. Am. J. Hum. Genet. 93, 779–797 (2013).

6. Segal, E., Raveh-Sadka, T., Schroeder, M., Unnerstall, U. & Gaul, U. Predicting expression patterns from regulatory sequence in Drosophila segmentation. Nature 451, 535–540 (2008).

7. Beer, M. A. & Tavazoie, S. Predicting gene expression from sequence. Cell 117, 185–198 (2004).

8. Yuan, Y., Guo, L., Shen, L. & Liu, J. S. Predicting gene expression from sequence: a reexamination. PLoS Comput. Biol. 3, e243 (2007).

9. Bussemaker, H. J., Li, H. & Siggia, E. D. Regulatory element detection using correlation with expression. Nat. Genet. 27, 167–171 (2001).

10. Kreimer, A. et al. Predicting gene expression in massively parallel reporter assays: a comparative study. Hum. Mutat. 38, 1240–1250 (2017).

11. Zhou, J. & Troyanskaya, O. G. Predicting effects of noncoding variants with deep-learning-based sequence model. Nat. Methods 12, 931–934 (2015).

12. Aguet, F. et al. Local genetic effects on gene expression across 44 human tissues. Nature 550, 204–213 (2017).

13. Battle, A., Brown, C. D., Engelhardt, B. E. & Montgomery, S. B. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

14. Westra, H.-J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238–1243 (2013).

15. Ramasamy, A. et al. Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat. Neurosci. 17, 1418–1428 (2014).

16. Fairfax, B. P. et al. Genetics of gene expression in primary immune cells identifies cell-type-specific master regulators and roles of HLA alleles. Nat. Genet. 44, 502–510 (2012).

17. Tewhey, R. et al. Direct identification of hundreds of expression-modulating variants using a multiplexed reporter assay. Cell 165, 1519–1529 (2016).

18. MacArthur, J. et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 45, D896–D901 (2017).

19. Germain, M. et al. Genetics of venous thrombosis: insights from a new genome-wide association study. PLoS One 6, e25581 (2011).

20. Tang, W. et al. A genome-wide association study for venous thromboembolism: the extended cohorts for heart and aging research in genomic epidemiology (CHARGE) consortium. Genet. Epidemiol. 37, 512–521 (2013).

21. Plagnol, V. et al. Genome-wide association analysis of autoantibody positivity in type 1 diabetes cases. PLoS Genet. 7, e1002216 (2011).

22. Chu, X. et al. A genome-wide association study identifies two new risk loci for Graves’ disease. Nat. Genet. 43, 897–901 (2011).

23. Sawcer, S. et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature 476, 214–219 (2011).

24. Graham, R. R. et al. Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus. Nat. Genet. 40, 1059–1061 (2008).

25. Bentham, J. et al. Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus. Nat. Genet. 47, 1457–1464 (2015).

26. Lee, Y.-C. et al. Two new susceptibility loci for Kawasaki disease identified through genome-wide association analysis. Nat. Genet. 44, 522–525 (2012).

27. Xi, H. et al. Analysis of overrepresented motifs in human core promoters reveals dual regulatory roles of YY1. Genome Res. 17, 798–806 (2007).

28. Stenson, P. D. et al. The Human Gene Mutation Database: 2008 update. Genome Med. 1, 13 (2009).

29. Nagaizumi, K. et al. Two double-heterozygous mutations in the F7 gene show different manifestations. Br. J. Haematol. 119, 1052–1058 (2002).

30. Feldmann, J. et al. Munc13-4 is essential for cytolytic granules fusion and is mutated in a form of familial hemophagocytic lymphohistiocytosis (FHL3). Cell 115, 461–473 (2003).

31. Ng, Y.-S., Wardemann, H., Chelnis, J., Cunningham-Rundles, C. & Meffre, E. Bruton’s tyrosine kinase is essential for human B cell tolerance. J. Exp. Med. 200, 927–934 (2004).

32. Yamagata, K. et al. Mutations in the hepatocyte nuclear factor-4α gene in maturity-onset diabetes of the young (MODY1). Nature 384, 458–460 (1996).

33. Servitja, J.-M. et al. Hnf-1α (MODY3) controls tissue-specific transcriptional programs and exerts opposed effects on cell growth in pancreatic islets and liver. Mol. Cell. Biol. 29, 2945–2959 (2009).

34. Huang, F. W. et al. Highly recurrent TERT promoter mutations in human melanoma. Science 339, 957–959 (2013).

35. Vinagre, J. et al. Frequency of TERT promoter mutations in human cancers. Nat. Commun. 4, 2185 (2013).

36. Pasaniuc, B. & Price, A. L. Dissecting the genetics of complex traits using summary-association statistics. Nat. Rev. Genet. 18, 117–127 (2017).

37. Parkes, M. et al. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn’s disease susceptibility. Nat. Genet. 39, 830–832 (2007).

38. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

39. Barrett, J. C. et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat. Genet. 40, 955–962 (2008).

40. Franke, A. et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat. Genet. 42, 1118–1125 (2010).

41. Jostins, L. et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012).

42. Liu, J. Z. et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet. 47, 979–986 (2015).

43. Kirino, Y. et al. Genome-wide association analysis identifies new susceptibility loci for Behçet’s disease and epistasis between HLA-B*51 and ERAP1. Nat. Genet. 45, 202–207 (2013).

44. Jiang, D. K. et al. Genetic variants in five novel loci including CFB and CD40 predispose to chronic hepatitis B. Hepatology 62, 118–128 (2015).

45. de Souza, N. The ENCODE project. Nat. Methods 9, 1046 (2012).

46. Bernstein, B. E. et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat. Biotechnol. 28, 1045–1048 (2010).

47. Chen, T. & Guestrin, C. XGBoost. in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785–794 (ACM, San Francisco, 2016).

48. Bühlmann, P. Boosting for high-dimensional linear models. Ann. Stat. 34, 559–583 (2006).

49. 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015).

50. Efron, B. Size, power and false discovery rates. Ann. Stat. 35, 1351–1377 (2007).

51. Kircher, M. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310–315 (2014).

52. Gonzàlez-Porta, M., Frankish, A., Rung, J., Harrow, J. & Brazma, A. Transcriptome analysis of human tissues and cell lines reveals one dominant transcript per gene. Genome Biol. 14, R70 (2013).

53. Uhlen, M. et al. Tissue-based map of the human proteome. Science 347, 1260419–1260419 (2015).