Synthesis of 53 tissue and cell line expression QTL datasets reveals master eQTLs

BMC Genomics

Andrew D Johnson⁷  Valur Emilsson²  Christopher J O’Donnell³  Stuart K Kim⁴  John Blangero⁵  Matthew P Johnson⁵  Joanne E Curran⁵  Harald HH Goring⁵  Radu Dobrin⁶  Andrew Plump¹  Daniel Levy⁷  Hinco J Gierman⁴  Xiaoling Zhang⁷ 

[1] Sanofi Aventis Pharmaceuticals, Bridgewater, NJ 08807, USA;Icelandic Heart Association, Kopavogur, Iceland;Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA;Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA;Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA;Johnson & Johnson Pharmaceutical Research and Development, Radnor, PA 19477, USA;Division of Intramural Research, National Heart, Lung and Blood Institute, Cardiovascular Epidemiology and Human Genomics Branch, The Framingham Heart Study, 73 Mt. Wayte Ave., Suite #2, Framingham, MA, USA

关键词: Trans;    Cis;    Tissue;    Genome-wide;    GWAS;    Transcriptome;    Genomics;    Gene expression;    RNA;    eQTL;   

Others  :  856990
DOI  :  10.1186/1471-2164-15-532

 received in 2013-12-30, accepted in 2014-06-18,  发布年份 2014

【 摘 要 】

Background

Gene expression genetic studies in human tissues and cells identify cis- and trans-acting expression quantitative trait loci (eQTLs). These eQTLs provide insights into regulatory mechanisms underlying disease risk. However, few studies systematically characterized eQTL results across cell and tissues types. We synthesized eQTL results from >50 datasets, including new primary data from human brain, peripheral plaque and kidney samples, in order to discover features of human eQTLs.

Results

We find a substantial number of robust cis-eQTLs and far fewer trans-eQTLs consistent across tissues. Analysis of 45 full human GWAS scans indicates eQTLs are enriched overall, and above nSNPs, among positive statistical signals in genetic mapping studies, and account for a significant fraction of the strongest human trait effects. Expression QTLs are enriched for gene centricity, higher population allele frequencies, in housekeeping genes, and for coincidence with regulatory features, though there is little evidence of 5′ or 3′ positional bias. Several regulatory categories are not enriched including microRNAs and their predicted binding sites and long, intergenic non-coding RNAs. Among the most tissue-ubiquitous cis-eQTLs, there is enrichment for genes involved in xenobiotic metabolism and mitochondrial function, suggesting these eQTLs may have adaptive origins. Several strong eQTLs (CDK5RAP2, NBPFs) coincide with regions of reported human lineage selection. The intersection of new kidney and plaque eQTLs with related GWAS suggest possible gene prioritization. For example, butyrophilins are now linked to arterial pathogenesis via multiple genetic and expression studies. Expression QTL and GWAS results are made available as a community resource through the NHLBI GRASP database [http://apps.nhlbi.nih.gov/grasp/ webcite].

Conclusions

Expression QTLs inform the interpretation of human trait variability, and may account for a greater fraction of phenotypic variability than protein-coding variants. The synthesis of available tissue eQTL data highlights many strong cis-eQTLs that may have important biologic roles and could serve as positive controls in future studies. Our results indicate some strong tissue-ubiquitous eQTLs may have adaptive origins in humans. Efforts to expand the genetic, splicing and tissue coverage of known eQTLs will provide further insights into human gene regulation.

【 授权许可】

   
2014 Zhang et al.; licensee BioMed Central Ltd.

【 图 表 】

【 参考文献 】

• [1]Cheung VG, Spielman RS: Genetics of human gene expression: mapping DNA variants that influence gene expression. Nat Rev Genet 2009, 10:595-604.
• [2]Montgomery SB, Dermitzakis ET: From expression QTLs to personalized transcriptomics. Nat Rev Genet 2011, 12:277-282.
• [3]Montgomery SB, Sammeth M, Gutierrez-Arcelus M, Lach RP, Ingle C, Nisbett J, Guigo R, Dermitzakis ET: Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 2010, 464:773-777.
• [4]Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, Nkadori E, Veyrieras JB, Stephens M, Gilad Y, Pritchard JK: Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 2010, 464:768-772.
• [5]Chess A: Mechanisms and consequences of widespread random monoallelic expression. Nat Rev Genet 2012, 13:421-428.
• [6]Johnson AD, Zhang Y, Papp AC, Pinsonneault JK, Lim JE, Saffen D, Dai Z, Wang D, Sadee W: Polymorphisms affecting gene transcription and mRNA processing in pharmacogenetic candidate genes: detection through allelic expression imbalance in human target tissues. Pharmacogenet Genomics 2008, 18:781-791.
• [7]Rockman MV, Wray GA: Abundant raw material for cis-regulatory evolution in humans. Mol Biol Evol 2002, 19:1991-2004.
• [8]Ehret GB, Munroe PB, Rice KM, Bochud M, Johnson AD, Chasman DI, Smith AV, Tobin MD, Verwoert GC, Hwang SJ, Pihur V, Vollenweider P, O’Reilly PF, Amin N, Bragg-Gresham JL, Teumer A, Glazer NL, Launer L, Zhao JH, Aulchenko Y, Heath S, Sober S, Parsa A, Luan J, Arora P, Dehghan A, Zhang F, Lucas G, Hicks AA, Jackson AU, et al.: Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 2011, 478:103-109.
• [9]Greenawalt DM, Dobrin R, Chudin E, Hatoum IJ, Suver C, Beaulaurier J, Zhang B, Castro V, Zhu J, Sieberts SK, Wang S, Molony C, Heymsfield SB, Kemp DM, Reitman ML, Lum PY, Schadt EE, Kaplan LM: A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort. Genome Res 2011, 21:1008-1016.
• [10]Knight J, Barnes MR, Breen G, Weale ME: Using functional annotation for the empirical determination of Bayes Factors for genome-wide association study analysis. PLoS ONE 2011, 6:e14808.
• [11]Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ: Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet 2010, 6:e1000888.
• [12]Tang W, Schwienbacher C, Lopez LM, Ben-Shlomo Y, Oudot-Mellakh T, Johnson AD, Samani NJ, Basu S, Gogele M, Davies G, Lowe GD, Tregouet DA, Tan A, Pankow JS, Tenesa A, Levy D, Volpato CB, Rumley A, Gow AJ, Minelli C, Yarnell JW, Porteous DJ, Starr JM, Gallacher J, Boerwinkle E, Visscher PM, Pramstaller PP, Cushman M, Emilsson V, Plump AS, et al.: Genetic associations for activated partial thromboplastin time and prothrombin time, their gene expression profiles, and risk of coronary artery disease. Am J Hum Genet 2012, 91:152-162.
• [13]Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin CY, Jin GM, Jin KY, et al.: Biological, clinical and population relevance of 95 loci for blood lipids. Nature 2010, 466:707-713.
• [14]Innocenti F, Cooper GM, Stanaway IB, Gamazon ER, Smith JD, Mirkov S, Ramirez J, Liu W, Lin YS, Moloney C, Aldred SF, Trinklein ND, Schuetz E, Nickerson DA, Thummel KE, Rieder MJ, Rettie AE, Ratain MJ, Cox NJ, Brown CD: Identification, replication, and functional fine-mapping of expression quantitative trait loci in primary human liver tissue. PLoS Genet 2011, 7:e1002078.
• [15]Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum PY, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, GuhaThakurta D, Derry J, Storey JD, vila-Campillo I, Kruger MJ, Johnson JM, Rohl CA, van Nas A, Mehrabian M, Drake TA, Lusis AJ, Smith RC, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, et al.: Mapping the genetic architecture of gene expression in human liver. PLoS Biol 2008, 6:e107.
• [16]Schroder A, Klein K, Winter S, Schwab M, Bonin M, Zell A, Zanger UM: Genomics of ADME gene expression: mapping expression quantitative trait loci relevant for absorption, distribution, metabolism and excretion of drugs in human liver. Pharmacogenomics J 2011, 13:12-20.
• [17]Dimas AS, Deutsch S, Stranger BE, Montgomery SB, Borel C, ttar-Cohen H, Ingle C, Beazley C, Gutierrez Arcelus M, Sekowska M, Gagnebin M, Nisbett J, Deloukas P, Dermitzakis ET, Antonarakis SE: Common regulatory variation impacts gene expression in a cell type-dependent manner. Science 2009, 325:1246-1250.
• [18]Dixon AL, Liang L, Moffatt MF, Chen W, Heath S, Wong KC, Taylor J, Burnett E, Gut I, Farrall M, Lathrop GM, Abecasis GR, Cookson WO: A genome-wide association study of global gene expression. Nat Genet 2007, 39:1202-1207.
• [19]Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, Carlson S, Helgason A, Walters GB, Gunnarsdottir S, Mouy M, Steinthorsdottir V, Eiriksdottir GH, Bjornsdottir G, Reynisdottir I, Gudbjartsson D, Helgadottir A, Jonasdottir A, Styrkarsdottir U, Gretarsdottir S, Magnusson KP, Stefansson H, Fossdal R, Kristjansson K, Gislason HG, Stefansson T, Leifsson BG, Thorsteinsdottir U, Lamb JR, Gulcher JR, et al.: Genetics of gene expression and its effect on disease. Nature 2008, 452:423-428.
• [20]Fehrmann RS, Jansen RC, Veldink JH, Westra HJ, Arends D, Bonder MJ, Fu J, Deelen P, Groen HJ, Smolonska A, Weersma RK, Hofstra RM, Buurman WA, Rensen S, Wolfs MG, Platteel M, Zhernakova A, Elbers CC, Festen EM, Trynka G, Hofker MH, Saris CG, Ophoff RA, van den Berg LH, van Heel DA, Wijmenga C, Te Meerman GJ, Franke L: Trans-eQTLs reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the HLA. PLoS Genet 2011, 7:e1002197.
• [21]Goring HH, Curran JE, Johnson MP, Dyer TD, Charlesworth J, Cole SA, Jowett JB, Abraham LJ, Rainwater DL, Comuzzie AG, Mahaney MC, Almasy L, MacCluer JW, Kissebah AH, Collier GR, Moses EK, Blangero J: Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet 2007, 39:1208-1216.
• [22]Grundberg E, Kwan T, Ge B, Lam KC, Koka V, Kindmark A, Mallmin H, Dias J, Verlaan DJ, Ouimet M, Sinnett D, Rivadeneira F, Estrada K, Hofman A, van Meurs JM, Uitterlinden A, Beaulieu P, Graziani A, Harmsen E, Ljunggren O, Ohlsson C, Mellstrom D, Karlsson MK, Nilsson O, Pastinen T: Population genomics in a disease targeted primary cell model. Genome Res 2009, 19:1942-1952.
• [23]Heap GA, Trynka G, Jansen RC, Bruinenberg M, Swertz MA, Dinesen LC, Hunt KA, Wijmenga C, Vanheel DA, Franke L: Complex nature of SNP genotype effects on gene expression in primary human leucocytes. BMC Med Genomics 2009, 2:1.
• [24]Heinzen EL, Ge D, Cronin KD, Maia JM, Shianna KV, Gabriel WN, Welsh-Bohmer KA, Hulette CM, Denny TN, Goldstein DB: Tissue-specific genetic control of splicing: implications for the study of complex traits. PLoS Biol 2008, 6:e1.
• [25]Idaghdour Y, Czika W, Shianna KV, Lee SH, Visscher PM, Martin HC, Miclaus K, Jadallah SJ, Goldstein DB, Wolfinger RD, Gibson G: Geographical genomics of human leukocyte gene expression variation in southern Morocco. Nat Genet 2010, 42:62-67.
• [26]Murphy A, Chu JH, Xu M, Carey VJ, Lazarus R, Liu A, Szefler SJ, Strunk R, Demuth K, Castro M, Hansel NN, Diette GB, Vonakis BM, Adkinson NF Jr, Klanderman BJ, Senter-Sylvia J, Ziniti J, Lange C, Pastinen T, Raby BA: Mapping of numerous disease-associated expression polymorphisms in primary peripheral blood CD4+ lymphocytes. Hum Mol Genet 2010, 19:4745-4757.
• [27]Stranger BE, Nica AC, Forrest MS, Dimas A, Bird CP, Beazley C, Ingle CE, Dunning M, Flicek P, Koller D, Montgomery S, Tavare S, Deloukas P, Dermitzakis ET: Population genomics of human gene expression. Nat Genet 2007, 39:1217-1224.
• [28]Gibbs JR, van der Brug MP, Hernandez DG, Traynor BJ, Nalls MA, Lai SL, Arepalli S, Dillman A, Rafferty IP, Troncoso J, Johnson R, Zielke HR, Ferrucci L, Longo DL, Cookson MR, Singleton AB: Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain. PLoS Genet 2010, 6:e1000952.
• [29]Liu C, Cheng L, Badner JA, Zhang D, Craig DW, Redman M, Gershon ES: Whole-genome association mapping of gene expression in the human prefrontal cortex. Mol Psychiatry 2010, 15:779-784.
• [30]Myers AJ, Gibbs JR, Webster JA, Rohrer K, Zhao A, Marlowe L, Kaleem M, Leung D, Bryden L, Nath P, Zismann VL, Joshipura K, Huentelman MJ, Hu-Lince D, Coon KD, Craig DW, Pearson JV, Holmans P, Heward CB, Reiman EM, Stephan D, Hardy J: A survey of genetic human cortical gene expression. Nat Genet 2007, 39:1494-1499.
• [31]Zhang B, Gaiteri C, Bodea LG, Wang Z, McElwee J, Podtelezhnikov AA, Zhang C, Xie T, Tran L, Dobrin R, Fluder E, Clurman B, Melquist S, Narayanan M, Suver C, Shah H, Mahajan M, Gillis T, Mysore J, MacDonald ME, Lamb JR, Bennett DA, Molony C, Stone DJ, Gudnason V, Myers AJ, Schadt EE, Neumann H, Zhu J, Emilsson V: Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 2013, 153:707-720.
• [32]Romanoski CE, Che N, Yin F, Mai N, Pouldar D, Civelek M, Pan C, Lee S, Vakili L, Yang WP, Kayne P, Mungrue IN, Araujo JA, Berliner JA, Lusis AJ: Network for activation of human endothelial cells by oxidized phospholipids: a critical role of heme oxygenase 1. Circ Res 2011, 109:e27-e41.
• [33]Ding J, Gudjonsson JE, Liang L, Stuart PE, Li Y, Chen W, Weichenthal M, Ellinghaus E, Franke A, Cookson W, Nair RP, Elder JT, Abecasis GR: Gene expression in skin and lymphoblastoid cells: refined statistical method reveals extensive overlap in cis-eQTL signals. Am J Hum Genet 2010, 87:779-789.
• [34]Gaffney DJ: Global properties and functional complexity of human gene regulatory variation. PLoS Genet 2013, 9:e1003501.
• [35]Bosse Y: Genome-wide expression quantitative trait loci analysis in asthma. Curr Opin Allergy Clin Immunol 2013, 13:487-494.
• [36]Nica AC, Parts L, Glass D, Nisbet J, Barrett A, Sekowska M, Travers M, Potter S, Grundberg E, Small K, Hedman AK, Bataille V, Tzenova Bell J, Surdulescu G, Dimas AS, Ingle C, Nestle FO, di Meglio P, Min JL, Wilk A, Hammond CJ, Hassanali N, Yang TP, Montgomery SB, O’Rahilly S, Lindgren CM, Zondervan KT, Soranzo N, Barroso I, Durbin R, et al.: The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLoS Genet 2011, 7:e1002003.
• [37]Flutre T, Wen X, Pritchard J, Stephens M: A statistical framework for joint eQTL analysis in multiple tissues. PLoS Genet 2013, 9:e1003486.
• [38]NHLBI Genome-wide Repository of Associations between SNPs and Phenotypes (GRASPdb) [http://apps.nhlbi.nih.gov/grasp/ webcite] edition; 2014
• [39]Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, Castagne R, Maouche S, Germain M, Lackner K, Rossmann H, Eleftheriadis M, Sinning CR, Schnabel RB, Lubos E, Mennerich D, Rust W, Perret C, Proust C, Nicaud V, Loscalzo J, Hubner N, Tregouet D, Munzel T, Ziegler A, Tiret L, Blankenberg S, Cambien F: Genetics and beyond–the transcriptome of human monocytes and disease susceptibility. PLoS ONE 2010, 5:e10693.
• [40]Genotype Tissue-Expression Portal (GTex) [http://www.gtexportal.org/home/ webcite] edition; 2014
• [41]Ramasamy A, Trabzuni D, Gibbs JR, Dillman A, Hernandez DG, Arepalli S, Walker R, Smith C, Ilori GP, Shabalin AA, Li Y, Singleton AB, Cookson MR, Hardy J, Ryten M, Weale ME: Resolving the polymorphism-in-probe problem is critical for correct interpretation of expression QTL studies. Nucleic Acids Res 2013, 41:e88.
• [42]Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O’Donnell CJ, de Bakker PI: SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 2008, 24:2938-2939.
• [43]Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, Karczewski KJ, Park J, Hitz BC, Weng S, Cherry JM, Snyder M: Annotation of functional variation in personal genomes using RegulomeDB. Genome Res 2012, 22:1790-1797.
• [44]Latourelle JC, Dumitriu A, Hadzi TC, Beach TG, Myers RH: Evaluation of Parkinson disease risk variants as expression-QTLs. PLoS ONE 2012, 7:e46199.
• [45]Shen Q, Wang X, Chen Y, Xu L, Wang X, Lu L: Expression QTL and regulatory network analysis of microtubule-associated protein tau gene. Parkinsonism Relat Disord 2009, 15:525-531.
• [46]Sankaran VG, Xu J, Ragoczy T, Ippolito GC, Walkley CR, Maika SD, Fujiwara Y, Ito M, Groudine M, Bender MA, Tucker PW, Orkin SH: Developmental and species-divergent globin switching are driven by BCL11A. Nature 2009, 460:1093-1097.
• [47]Tang XF, Zhang Z, Hu DY, Xu AE, Zhou HS, Sun LD, Gao M, Gao TW, Gao XH, Chen HD, Xie HF, Tu CX, Hao F, Wu RN, Zhang FR, Liang L, Pu XM, Zhang JZ, Han JW, Pan GP, Wu JQ, Li K, Su MW, Du WD, Zhang WJ, Liu JJ, Xiang LH, Yang S, Zhou YW, Zhang XJ: Association analyses identify three susceptibility Loci for vitiligo in the Chinese Han population. J Invest Dermatol 2013, 133:403-410.
• [48]Rotival M, Zeller T, Wild PS, Maouche S, Szymczak S, Schillert A, Castagne R, Deiseroth A, Proust C, Brocheton J, Godefroy T, Perret C, Germain M, Eleftheriadis M, Sinning CR, Schnabel RB, Lubos E, Lackner KJ, Rossmann H, Munzel T, Rendon A, Erdmann J, Deloukas P, Hengstenberg C, Diemert P, Montalescot G, Ouwehand WH, Samani NJ, Schunkert H, Tregouet DA, et al.: Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans. PLoS Genet 2011, 7:e1002367.
• [49]Kent WJ: BLAT–the BLAST-like alignment tool. Genome Res 2002, 12:656-664.
• [50]Sanyal A, Lajoie BR, Jain G, Dekker J: The long-range interaction landscape of gene promoters. Nature 2012, 489:109-113.
• [51]Zhu J, He F, Song S, Wang J, Yu J: How many human genes can be defined as housekeeping with current expression data? BMC Genomics 2008, 9:172.
• [52]Kottgen A, Pattaro C, Boger CA, Fuchsberger C, Olden M, Glazer NL, Parsa A, Gao X, Yang Q, Smith AV, O’Connell JR, Li M, Schmidt H, Tanaka T, Isaacs A, Ketkar S, Hwang SJ, Johnson AD, Dehghan A, Teumer A, Pare G, Atkinson EJ, Zeller T, Lohman K, Cornelis MC, Probst-Hensch NM, Kronenberg F, Tonjes A, Hayward C, Aspelund T, et al.: New loci associated with kidney function and chronic kidney disease. Nat Genet 2010, 42:376-384.
• [53]Chung SA, Taylor KE, Graham RR, Nititham J, Lee AT, Ortmann WA, Jacob CO, Alarcon-Riquelme ME, Tsao BP, Harley JB, Gaffney PM, Moser KL, Petri M, Demirci FY, Kamboh MI, Manzi S, Gregersen PK, Langefeld CD, Behrens TW, Criswell LA: Differential genetic associations for systemic lupus erythematosus based on anti-dsDNA autoantibody production. PLoS Genet 2011, 7:e1001323.
• [54]Erdmann J, Grosshennig A, Braund PS, Konig IR, Hengstenberg C, Hall AS, Linsel-Nitschke P, Kathiresan S, Wright B, Tregouet DA, Cambien F, Bruse P, Aherrahrou Z, Wagner AK, Stark K, Schwartz SM, Salomaa V, Elosua R, Melander O, Voight BF, O’Donnell CJ, Peltonen L, Siscovick DS, Altshuler D, Merlini PA, Peyvandi F, Bernardinelli L, Ardissino D, Schillert A, Blankenberg S, et al.: New susceptibility locus for coronary artery disease on chromosome 3q22.3. Nat Genet 2009, 41:280-282.
• [55]Yamada Y, Nishida T, Ichihara S, Sawabe M, Fuku N, Nishigaki Y, Aoyagi Y, Tanaka M, Fujiwara Y, Yoshida H, Shinkai S, Satoh K, Kato K, Fujimaki T, Yokoi K, Oguri M, Yoshida T, Watanabe S, Nozawa Y, Hasegawa A, Kojima T, Han BG, Ahn Y, Lee M, Shin DJ, Lee JH, Jang Y: Association of a polymorphism of BTN2A1 with myocardial infarction in East Asian populations. Atherosclerosis 2011, 215:145-152.
• [56]Avery CL, He Q, North KE, Ambite JL, Boerwinkle E, Fornage M, Hindorff LA, Kooperberg C, Meigs JB, Pankow JS, Pendergrass SA, Psaty BM, Ritchie MD, Rotter JI, Taylor KD, Wilkens LR, Heiss G, Lin DY: A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. PLoS Genet 2011, 7:e1002322.
• [57]Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, Preuss M, Stewart AF, Barbalic M, Gieger C, Absher D, Aherrahrou Z, Allayee H, Altshuler D, Anand SS, Andersen K, Anderson JL, Ardissino D, Ball SG, Balmforth AJ, Barnes TA, Becker DM, Becker LC, Berger K, Bis JC, Boekholdt SM, Boerwinkle E, Braund PS, Brown MJ, Burnett MS, et al.: Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet 2011, 43:333-338.
• [58]Wellcome Trust Case Control Consortium: Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007, 447:661-678.
• [59]Gimelbrant A, Hutchinson JN, Thompson BR, Chess A: Widespread monoallelic expression on human autosomes. Science 2007, 318:1136-1140.
• [60]Westra HJ, Jansen RC, Fehrmann RS, Te Meerman GJ, van Heel D, Wijmenga C, Franke L: MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects. Bioinformatics 2011, 27:2104-2111.
• [61]Powell JE, Henders AK, McRae AF, Wright MJ, Martin NG, Dermitzakis ET, Montgomery GW, Visscher PM: Genetic control of gene expression in whole blood and lymphoblastoid cell lines is largely independent. Genome Res 2012, 22:456-466.
• [62]Moyer AM, Salavaggione OE, Hebbring SJ, Moon I, Hildebrandt MA, Eckloff BW, Schaid DJ, Wieben ED, Weinshilboum RM: Glutathione S-transferase T1 and M1: gene sequence variation and functional genomics. Clin Cancer Res 2007, 13:7207-7216.
• [63]Zhao Y, Marotta M, Eichler EE, Eng C, Tanaka H: Linkage disequilibrium between two high-frequency deletion polymorphisms: implications for association studies involving the glutathione-S transferase (GST) genes. PLoS Genet 2009, 5:e1000472.
• [64]O’Bleness M, Searles VB, Varki A, Gagneux P, Sikela JM: Evolution of genetic and genomic features unique to the human lineage. Nat Rev Genet 2012, 13:853-866.
• [65]Evans PD, Vallender EJ, Lahn BT: Molecular evolution of the brain size regulator genes CDK5RAP2 and CENPJ. Gene 2006, 375:75-79.
• [66]Rimol LM, Agartz I, Djurovic S, Brown AA, Roddey JC, Kahler AK, Mattingsdal M, Athanasiu L, Joyner AH, Schork NJ, Halgren E, Sundet K, Melle I, Dale AM, Andreassen OA: Sex-dependent association of common variants of microcephaly genes with brain structure. Proc Natl Acad Sci U S A 2010, 107:384-388.
• [67]Charrier C, Joshi K, Coutinho-Budd J, Kim JE, Lambert N, de Marchena J, Jin WL, Vanderhaeghen P, Ghosh A, Sassa T, Polleux F: Inhibition of SRGAP2 function by its human-specific paralogs induces neoteny during spine maturation. Cell 2012, 149:923-935.
• [68]Dennis MY, Nuttle X, Sudmant PH, Antonacci F, Graves TA, Nefedov M, Rosenfeld JA, Sajjadian S, Malig M, Kotkiewicz H, Curry CJ, Shafer S, Shaffer LG, de Jong PJ, Wilson RK, Eichler EE: Evolution of human-specific neural SRGAP2 genes by incomplete segmental duplication. Cell 2012, 149:912-922.
• [69]Fortna A, Kim Y, MacLaren E, Marshall K, Hahn G, Meltesen L, Brenton M, Hink R, Burgers S, Hernandez-Boussard T, Karimpour-Fard A, Glueck D, McGavran L, Berry R, Pollack J, Sikela JM: Lineage-specific gene duplication and loss in human and great ape evolution. PLoS Biol 2004, 2:E207.
• [70]Gaffney DJ, Veyrieras JB, Degner JF, Pique-Regi R, Pai AA, Crawford GE, Stephens M, Gilad Y, Pritchard JK: Dissecting the regulatory architecture of gene expression QTLs. Genome Biol 2012, 13:R7.
• [71]Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, Reynolds AP, Sandstrom R, Qu H, Brody J, Shafer A, Neri F, Lee K, Kutyavin T, Stehling-Sun S, Johnson AK, Canfield TK, Giste E, Diegel M, Bates D, Hansen RS, Neph S, Sabo PJ, Heimfeld S, Raubitschek A, Ziegler S, Cotsapas C, Sotoodehnia N, Glass I, Sunyaev SR, et al.: Systematic localization of common disease-associated variation in regulatory DNA. Science 2012, 337:1190-1195.
• [72]Holmquist GP, Wienberg J: Human Chromosome Evolution. Chichester: Wiley; 2008.
• [73]Small KS, Hedman AK, Grundberg E, Nica AC, Thorleifsson G, Kong A, Thorsteindottir U, Shin SY, Richards HB, Soranzo N, Ahmadi KR, Lindgren CM, Stefansson K, Dermitzakis ET, Deloukas P, Spector TD, McCarthy MI: Identification of an imprinted master trans regulator at the KLF14 locus related to multiple metabolic phenotypes. Nat Genet 2011, 43:561-564.
• [74]Vernot B, Stergachis AB, Maurano MT, Vierstra J, Neph S, Thurman RE, Stamatoyannopoulos JA, Akey JM: Personal and population genomics of human regulatory variation. Genome Res 2012, 22:1689-1697.
• [75]Vavassori S, Kumar A, Wan GS, Ramanjaneyulu GS, Cavallari M, El DS, Beddoe T, Theodossis A, Williams NK, Gostick E, Price DA, Soudamini DU, Voon KK, Olivo M, Rossjohn J, Mori L, De LG: Butyrophilin 3A1 binds phosphorylated antigens and stimulates human gammadelta T cells. Nat Immunol 2013, 14:908-916.
• [76]Kumar V, Westra HJ, Karjalainen J, Zhernakova DV, Esko T, Hrdlickova B, Almeida R, Zhernakova A, Reinmaa E, Vosa U, Hofker MH, Fehrmann RS, Fu J, Withoff S, Metspalu A, Franke L, Wijmenga C: Human disease-associated genetic variation impacts large intergenic non-coding RNA expression. PLoS Genet 2013, 9:e1003201.
• [77]Gamazon ER, Ziliak D, Im HK, LaCroix B, Park DS, Cox NJ, Huang RS: Genetic architecture of microRNA expression: implications for the transcriptome and complex traits. Am J Hum Genet 2012, 90:1046-1063.
• [78]Rantalainen M, Herrera BM, Nicholson G, Bowden R, Wills QF, Min JL, Neville MJ, Barrett A, Allen M, Rayner NW, Fleckner J, McCarthy MI, Zondervan KT, Karpe F, Holmes CC, Lindgren CM: MicroRNA expression in abdominal and gluteal adipose tissue is associated with mRNA expression levels and partly genetically driven. PLoS ONE 2011, 6:e27338.
• [79]Liang L, Morar N, Dixon AL, Lathrop GM, Abecasis GR, Moffatt MF, Cookson WO: A cross-platform analysis of 14,177 expression quantitative trait loci derived from lymphoblastoid cell lines. Genome Res 2013, 23:716-726.
• [80]GTEx Consortium: The genotype-tissue expression (GTEx) project. Nat Genet 2013, 45:580-585.
• [81]Pai AA, Cain CE, Mizrahi-Man O, De LS, Lewellen N, Veyrieras JB, Degner JF, Gaffney DJ, Pickrell JK, Stephens M, Pritchard JK, Gilad Y: The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels. PLoS Genet 2012, 8:e1003000.
• [82]Zhernakova DV, de Klerk E, Westra HJ, Mastrokolias A, Amini S, Ariyurek Y, Jansen R, Penninx BW, Hottenga JJ, Willemsen G, de Geus EJ, Boomsma DI, Veldink JH, van den Berg LH, Wijmenga C, den Dunnen JT, van Ommen GJ, ‘t Hoen PA, Franke L: DeepSAGE reveals genetic variants associated with alternative polyadenylation and expression of coding and non-coding transcripts. PLoS Genet 2013, 9:e1003594.
• [83]Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, Gilad Y, Pritchard JK: DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol 2011, 12:R10.
• [84]Bell JT, Tsai PC, Yang TP, Pidsley R, Nisbet J, Glass D, Mangino M, Zhai G, Zhang F, Valdes A, Shin SY, Dempster EL, Murray RM, Grundberg E, Hedman AK, Nica A, Small KS, Dermitzakis ET, McCarthy MI, Mill J, Spector TD, Deloukas P: Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet 2012, 8:e1002629.
• [85]Schalkwyk LC, Meaburn EL, Smith R, Dempster EL, Jeffries AR, Davies MN, Plomin R, Mill J: Allelic skewing of DNA methylation is widespread across the genome. Am J Hum Genet 2010, 86:196-212.
• [86]Puig O, Yuan J, Stepaniants S, Zieba R, Zycband E, Morris M, Coulter S, Yu X, Menke J, Woods J, Chen F, Ramey DR, He X, O’Neill EA, Hailman E, Johns DG, Hubbard BK, Yee LP, Wright SD, Desouza MM, Plump A, Reiser V: A gene expression signature that classifies human atherosclerotic plaque by relative inflammation status. Circ Cardiovasc Genet 2011, 4:595-604.
• [87]Durinck S, Moreau Y, Kasprzyk A, Davis S, De Moor B, Brazma A, Huber W: BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics 2005, 21:3439-3440.
• [88]Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004, 5:R80.
• [89]NHGRI GWAS catalog [http://www.genome.gov/26525384 webcite] edition; 2014
• [90]Devlin B, Roeder K: Genomic control for association studies. Biometrics 1999, 55:997-1004.
• [91]UCSC Genome Browser [http://genome.ucsc.edu/ webcite] edition; 2014
• [92]Montgomery SB, Griffith OL, Sleumer MC, Bergman CM, Bilenky M, Pleasance ED, Prychyna Y, Zhang X, Jones SJ: ORegAnno: an open access database and curation system for literature-derived promoters, transcription factor binding sites and regulatory variation. Bioinformatics 2006, 22:637-640.
• [93]Pennacchio LA, Ahituv N, Moses AM, Prabhakar S, Nobrega MA, Shoukry M, Minovitsky S, Dubchak I, Holt A, Lewis KD, Plajzer-Frick I, Akiyama J, De VS, Afzal V, Black BL, Couronne O, Eisen MB, Visel A, Rubin EM: In vivo enhancer analysis of human conserved non-coding sequences. Nature 2006, 444:499-502.
• [94]miRBase [http://www.mirbase.org/ webcite] edition; 2014
• [95]Target Scan [http://www.targetscan.org/ webcite] edition; 2014
• [96]Hiard S, Charlier C, Coppieters W, Georges M, Baurain D: Patrocles: a database of polymorphic miRNA-mediated gene regulation in vertebrates. Nucleic Acids Res 2010, 38:D640-D651.
• [97]PolymiRTS [http://compbio.uthsc.edu/miRSNP/ webcite] edition; 2014
• [98]Cabili MN, Trapnell C, Goff L, Koziol M, Tazon-Vega B, Regev A, Rinn JL: Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev 2011, 25:1915-1927.
• [99]Leslie R, O’Donnell CJ, Johnson AD: GRASP: analysis of genotype-phenotype results from 1,390 genome-wide association studies and corresponding open access database. Bioinformatics 2014, 30:i185-i194.