Rubin CM. The genetic basis of human cancer. Ann Intern Med. 1998;129(9):759. https://doi.org/10.7326/0003-4819-129-9-199811010-00045.
Article
Google Scholar
Martincorena I, Campbell PJ. Somatic mutation in cancer and normal cells. Science (1979). 2015;349(6255):1483–9. https://doi.org/10.1126/science.aab4082.
Article
CAS
Google Scholar
Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–74. https://doi.org/10.1016/j.cell.2011.02.013.
Article
CAS
PubMed
Google Scholar
Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Kinzler KW. Cancer genome landscapes. Science (1979). 2013;340(6127):1546–58. https://doi.org/10.1126/science.1235122.
Article
CAS
Google Scholar
Hall JM, Lee MK, Newman B, et al. Linkage of early-onset familial breast cancer to chromosome 17q21. Science (1979). 1990;250(4988):1684–9. https://doi.org/10.1126/science.2270482.
Article
CAS
Google Scholar
Miki Y, Swensen J, Shattuck-Eidens D, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science (1979). 1994;266(5182):66–71. https://doi.org/10.1126/science.7545954.
Article
CAS
Google Scholar
Wooster R, Neuhausen SL, Mangion J, et al. Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12–13. Science (1979). 1994;265(5181):2088–90. https://doi.org/10.1126/science.8091231.
Article
CAS
Google Scholar
Peltomäki P, Aaltonen LA, Sistonen P, et al. Genetic mapping of a locus predisposing to human colorectal cancer. Science (1979). 1993;260(5109):810–2. https://doi.org/10.1126/science.8484120.
Article
Google Scholar
Lindblom A, Tannergård P, Werelius B, Nordenskjöld M. Genetic mapping of a second locus predisposing to hereditary non-polyposis colon cancer. Nat Genet. 1993;5(3):279–82. https://doi.org/10.1038/ng1193-279.
Article
CAS
PubMed
Google Scholar
Kinzler KW, Nilbert MC, Su LK, et al. Identification of FAP locus genes from chromosome 5q21. Science (1979). 1991;253(5020):661–5. https://doi.org/10.1126/science.1651562.
Article
CAS
Google Scholar
Fishel R, Lescoe MK, Rao MRS, et al. The human mutator gene homolog MSH2 and its association with hereditary nonpolyposis colon cancer. Cell. 1993;75(5):1027–38. https://doi.org/10.1016/0092-8674(93)90546-3.
Article
CAS
PubMed
Google Scholar
Leach FS, Nicolaides NC, Papadopoulos N, et al. Mutations of a mutS homolog in hereditary nonpolyposis colorectal cancer. Cell. 1993;75(6):1215–25. https://doi.org/10.1016/0092-8674(93)90330-S.
Article
CAS
PubMed
Google Scholar
Cannon-Albright LA, Goldgar DE, Meyer LJ, et al. Assignment of a locus for familial melanoma, MLM, to chromosome 9p13-p22. Science (1979). 1992;258(5085):1148–52. https://doi.org/10.1126/science.1439824.
Article
CAS
Google Scholar
Hussussian CJ, Struewing JP, Goldstein AM, et al. Germline p16 mutations in familial melanoma. Nat Genet. 1994;8(1):15–21. https://doi.org/10.1038/ng0994-15.
Article
CAS
PubMed
Google Scholar
Kamb A, Shattuck-Eidens D, Eeles R, et al. Analysis of the p16 gene (CDKN2) as a candidate for the chromosome 9p melanoma susceptibility locus. Nat Genet. 1994;8(1):22–6. https://doi.org/10.1038/ng0994-22.
Article
CAS
Google Scholar
Ponder B, Pharoah PDP, Ponder BAJ, et al. Prevalence and penetrance of BRCA1 and BRCA2 mutations in a population-based series of breast cancer cases. Br J Cancer. 2000;83(10):1301–8. https://doi.org/10.1054/bjoc.2000.1407.
Article
Google Scholar
Chubb D, Broderick P, Dobbins SE, et al. Rare disruptive mutations and their contribution to the heritable risk of colorectal cancer. Nat Commun. 2016. https://doi.org/10.1038/ncomms11883.
Article
PubMed
PubMed Central
Google Scholar
Helgadottir H, Höiom V, Tuominen R, et al. CDKN2a mutation-negative melanoma families have increased risk exclusively for skin cancers but not for other malignancies. Int J Cancer. 2015;137(9):2220–6. https://doi.org/10.1002/ijc.29595.
Article
CAS
PubMed
Google Scholar
Antoniou AC, Easton DF. Models of genetic susceptibility to breast cancer. Oncogene. 2006;25(43):5898–905. https://doi.org/10.1038/sj.onc.1209879.
Article
CAS
PubMed
Google Scholar
Houlston RS, Peto J. The search for low-penetrance cancer susceptibility alleles. Oncogene. 2004;23(38):6471–6. https://doi.org/10.1038/sj.onc.1207951.
Article
CAS
PubMed
Google Scholar
Risch NJ. Searching for genetic determinants in the new millennium. Nature. 2000;405(6788):847–56. https://doi.org/10.1038/35015718.
Article
CAS
PubMed
Google Scholar
Garraway LA, Lander ES. Lessons from the cancer genome. Cell. 2013;153(1):17–37. https://doi.org/10.1016/j.cell.2013.03.002.
Article
CAS
PubMed
Google Scholar
Futreal PA, Coin L, Marshall M, et al. A census of human cancer genes. Nat Rev Cancer. 2004;4(3):177–83. https://doi.org/10.1038/nrc1299.
Article
CAS
PubMed
PubMed Central
Google Scholar
Paez JG, Jänne PA, Lee JC, et al. EGFR mutations in lung, cancer: correlation with clinical response to gefitinib therapy. Science (1979). 2004;304(5676):1497–500. https://doi.org/10.1126/science.1099314.
Article
CAS
Google Scholar
Goldman JM, Melo JV. Chronic myeloid leukemia—advances in biology and new approaches to treatment. N Engl J Med. 2003;349(15):1451–64. https://doi.org/10.1056/nejmra020777.
Article
CAS
PubMed
Google Scholar
Liang B, Ding H, Huang L, Luo H, Zhu X. GWAS in cancer: progress and challenges. Mol Genet Genomics. 2020;295(3):537–61. https://doi.org/10.1007/s00438-020-01647-z.
Article
CAS
PubMed
Google Scholar
Muzny DM, Bainbridge MN, Chang K, et al. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330–7. https://doi.org/10.1038/nature11252.
Article
CAS
Google Scholar
Creighton CJ, Morgan M, Gunaratne PH, et al. Comprehensivemolecular characterization of clear cell renal cell carcinoma. Nature. 2013;499(7456):43–9. https://doi.org/10.1038/nature12222.
Article
CAS
Google Scholar
Koboldt DC, Fulton RS, McLellan MD, et al. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70. https://doi.org/10.1038/nature11412.
Article
CAS
Google Scholar
Varela I, Tarpey P, Raine K, et al. Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature. 2011;469(7331):539–42. https://doi.org/10.1038/nature09639.
Article
CAS
PubMed
PubMed Central
Google Scholar
Stephens PJ, Tarpey PS, Davies H, et al. The landscape of cancer genes and mutational processes in breast cancer. Nature. 2012;486(7403):400–4. https://doi.org/10.1038/nature11017.
Article
CAS
PubMed
PubMed Central
Google Scholar
McLendon R, Friedman A, Bigner D, et al. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455(7216):1061–8. https://doi.org/10.1038/nature07385.
Article
CAS
Google Scholar
Hammerman PS, Voet D, Lawrence MS, et al. Comprehensive genomic characterization of squamous cell lung cancers. Nature. 2012;489(7417):519–25. https://doi.org/10.1038/nature11404.
Article
CAS
Google Scholar
Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013;368(22):2059–74. https://doi.org/10.1056/nejmoa1301689.
Article
Google Scholar
Getz G, Gabriel SB, Cibulskis K, et al. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497(7447):67–73. https://doi.org/10.1038/nature12113.
Article
CAS
Google Scholar
Weinstein JN, Collisson EA, Mills GB, et al. The cancer genome atlas pan-cancer analysis project. Nat Genet. 2013;45(10):1113–20. https://doi.org/10.1038/ng.2764.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hudson TJ, Anderson W, Aretz A, et al. International network of cancer genome projects. Nature. 2010;464(7291):993–8. https://doi.org/10.1038/nature08987.
Article
CAS
PubMed
Google Scholar
Edwards SL, Beesley J, French JD, Dunning M. Beyond GWASs: illuminating the dark road from association to function. Am J Hum Genet. 2013;93(5):779–97. https://doi.org/10.1016/j.ajhg.2013.10.012.
Article
CAS
PubMed
PubMed Central
Google Scholar
Khurana E, Fu Y, Chakravarty D, Demichelis F, Rubin MA, Gerstein M. Role of non-coding sequence variants in cancer. Nat Rev Genet. 2016;17(2):93–108. https://doi.org/10.1038/nrg.2015.17.
Article
CAS
PubMed
Google Scholar
Huang FW, Hodis E, Xu MJ, Kryukov GV, Chin L, Garraway LA. Highly recurrent TERT promoter mutations in human melanoma. Science (1979). 2013;339(6122):957–9. https://doi.org/10.1126/science.1229259.
Article
CAS
Google Scholar
Khurana E, Fu Y, Colonna V, et al. Integrative annotation of variants from 1092 humans: application to cancer genomics. Science (1979). 2013. https://doi.org/10.1126/science.1235587.
Article
Google Scholar
Bailey SD, Desai K, Kron KJ, et al. Noncoding somatic and inherited single-nucleotide variants converge to promote ESR1 expression in breast cancer. Nat Genet. 2016;48(10):1260–6. https://doi.org/10.1038/ng.3650.
Article
CAS
PubMed
PubMed Central
Google Scholar
Gupta RA, Shah N, Wang KC, et al. Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature. 2010;464(7291):1071–6. https://doi.org/10.1038/nature08975.
Article
CAS
PubMed
PubMed Central
Google Scholar
Rheinbay E, Nielsen MM, Abascal F, et al. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature. 2020;578(7793):102–11. https://doi.org/10.1038/s41586-020-1965-x.
Article
CAS
PubMed
PubMed Central
Google Scholar
Liu EM, Martinez-Fundichely A, Diaz BJ, et al. Identification of cancer drivers at CTCF insulators in whole genomes. Cell Syst. 2019;8(5):446–55. https://doi.org/10.1016/j.cels.2019.04.001.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bell RJA, Rube HT, Xavier-Magalhães A, et al. Understanding TERT promoter mutations: a common path to immortality. Mol Cancer Res. 2016;14(4):315–23. https://doi.org/10.1158/1541-7786.MCR-16-0003.
Article
CAS
PubMed
PubMed Central
Google Scholar
Heidenreich B, Kumar R. TERT promoter mutations in telomere biology. Mutat Res Rev Mutat Res. 2017;771:15–31. https://doi.org/10.1016/j.mrrev.2016.11.002.
Article
CAS
PubMed
Google Scholar
Horn S, Figl A, Rachakonda PS, et al. TERT promoter mutations in familial and sporadic melanoma. Science (1979). 2013;339(6122):959–61. https://doi.org/10.1126/science.1230062.
Article
CAS
Google Scholar
Stern JL, Theodorescu D, Vogelstein B, Papadopoulos N, Cech TR. Mutation of the TERT promoter, switch to active chromatin, and monoallelic TERT expression in multiple cancers. Genes Dev. 2015;29(21):2219–24. https://doi.org/10.1101/gad.269498.115.
Article
CAS
PubMed
PubMed Central
Google Scholar
Li Z, Abraham BJ, Berezovskaya A, et al. APOBEC signature mutation generates an oncogenic enhancer that drives LMO1 expression in T-ALL. Leukemia. 2017;31(10):2057–64. https://doi.org/10.1038/leu.2017.75.
Article
CAS
PubMed
PubMed Central
Google Scholar
Campbell PJ, Getz G, Korbel JO, et al. Pan-cancer analysis of whole genomes. Nature. 2020;578(7793):82–93. https://doi.org/10.1038/s41586-020-1969-6.
Article
CAS
Google Scholar
Alexander RP, Fang G, Rozowsky J, Snyder M, Gerstein MB. Annotating non-coding regions of the genome. Nat Rev Genet. 2010;11(8):559–71. https://doi.org/10.1038/nrg2814.
Article
CAS
PubMed
Google Scholar
Dunham I, Kundaje A, Aldred SF, et al. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74. https://doi.org/10.1038/nature11247.
Article
CAS
Google Scholar
Noonan JP, McCallion AS. Genomics of long-range regulatory elements. Annu Rev Genomics Hum Genet. 2010;11:1–23. https://doi.org/10.1146/annurev-genom-082509-141651.
Article
CAS
PubMed
Google Scholar
Boyle AP, Davis S, Shulha HP, et al. High-resolution mapping and characterization of open chromatin across the genome. Cell. 2008;132(2):311–22. https://doi.org/10.1016/j.cell.2007.12.014.
Article
CAS
PubMed
PubMed Central
Google Scholar
Giresi PG, Kim J, McDaniell RM, Iyer VR, Lieb JD. FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin. Genome Res. 2007;17(6):877–85. https://doi.org/10.1101/gr.5533506.
Article
CAS
PubMed
PubMed Central
Google Scholar
Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. Transposition of native chromatin for multimodal regulatory analysis and personal epigenomics. Nat Methods. 2013;10(12):1213. https://doi.org/10.1038/NMETH.2688.
Article
CAS
PubMed
PubMed Central
Google Scholar
Johnson DS, Mortazavi A, Myers RM, Wold B. Genome-wide mapping of in vivo protein-DNA interactions. Science (1979). 2007;316(5830):1497–502. https://doi.org/10.1126/science.1141319.
Article
CAS
Google Scholar
Calo E, Wysocka J. Modification of enhancer chromatin: what, how, and why? Mol Cell. 2013;49(5):825–37. https://doi.org/10.1016/j.molcel.2013.01.038.
Article
CAS
PubMed
Google Scholar
Andersson R, Gebhard C, Miguel-Escalada I, et al. An atlas of active enhancers across human cell types and tissues. Nature. 2014;507(7493):455–61. https://doi.org/10.1038/nature12787.
Article
CAS
PubMed
PubMed Central
Google Scholar
Core LJ, Waterfall JJ, Lis JT. Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters. Science (1979). 2008;322(5909):1845–8. https://doi.org/10.1126/science.1162228.
Article
CAS
Google Scholar
Mahat DB, Kwak H, Booth GT, et al. Base-pair-resolution genome-wide mapping of active RNA polymerases using precision nuclear run-on (PRO-seq). Nat Protoc. 2016;11(8):1455–76. https://doi.org/10.1038/nprot.2016.086.
Article
PubMed
PubMed Central
Google Scholar
Bernstein BE, Stamatoyannopoulos JA, Costello JF, et al. The NIH roadmap epigenomics mapping consortium. Nat Biotechnol. 2010;28(10):1045–8. https://doi.org/10.1038/nbt1010-1045.
Article
CAS
PubMed
PubMed Central
Google Scholar
Stunnenberg HG, Abrignani S, Adams D, et al. The international human epigenome consortium: a blueprint for scientific collaboration and discovery. Cell. 2016;167(5):1145–9. https://doi.org/10.1016/j.cell.2016.11.007.
Article
CAS
PubMed
Google Scholar
Lizio M, Harshbarger J, Shimoji H, et al. Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biol. 2015. https://doi.org/10.1186/s13059-014-0560-6.
Article
PubMed
PubMed Central
Google Scholar
McLaren W, Gil L, Hunt SE, et al. The ensembl variant effect predictor. Genome Biol. 2016. https://doi.org/10.1186/s13059-016-0974-4.
Article
PubMed
PubMed Central
Google Scholar
Coetzee SG, Rhie SK, Berman BP, Coetzee GA, Noushmehr H. FunciSNP: an R/bioconductor tool integrating functional non-coding data sets with genetic association studies to identify candidate regulatory SNPs. Nucleic Acids Res. 2012. https://doi.org/10.1093/nar/gks542.
Article
PubMed
PubMed Central
Google Scholar
Ritchie GRS, Dunham I, Zeggini E, Flicek P. Functional annotation of noncoding sequence variants. Nat Methods. 2014;11(3):294–6. https://doi.org/10.1038/nmeth.2832.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhou J, Theesfeld CL, Yao K, Chen KM, Wong AK, Troyanskaya OG. Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk. Nat Genet. 2018;50(8):1171–9. https://doi.org/10.1038/s41588-018-0160-6.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chen KM, Wong AK, Troyanskaya OG, Zhou J. A sequence-based global map of regulatory activity for deciphering human genetics. Nat Genet. 2022. https://doi.org/10.1038/s41588-022-01102-2.
Article
PubMed
PubMed Central
Google Scholar
Zhu Y, Tian J, Peng X, et al. A genetic variant conferred high expression of CAV2 promotes pancreatic cancer progression and associates with poor prognosis. Eur J Cancer. 2021;151:94–105. https://doi.org/10.1016/j.ejca.2021.04.008.
Article
CAS
PubMed
Google Scholar
Nishizaki SS, Boyle AP. Mining the unknown: assigning function to noncoding single nucleotide polymorphisms. Trends Genet. 2017;33(1):34–45. https://doi.org/10.1016/j.tig.2016.10.008.
Article
CAS
PubMed
Google Scholar
Lenhard B, Sandelin A, Carninci P. Metazoan promoters: emerging characteristics and insights into transcriptional regulation. Nat Rev Genet. 2012;13(4):233–45. https://doi.org/10.1038/nrg3163.
Article
CAS
PubMed
Google Scholar
Panigrahi A, O’Malley BW. Mechanisms of enhancer action: the known and the unknown. Genome Biol. 2021. https://doi.org/10.1186/s13059-021-02322-1.
Article
PubMed
PubMed Central
Google Scholar
Lettice LA, Heaney SJH, Purdie LA, et al. A long-range Shh enhancer regulates expression in the developing limb and fin and is associated with preaxial polydactyly. Hum Mol Genet. 2003;12(14):1725–35. https://doi.org/10.1093/hmg/ddg180.
Article
CAS
PubMed
Google Scholar
Dina C, Meyre D, Gallina S, et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet. 2007;39(6):724–6. https://doi.org/10.1038/ng2048.
Article
CAS
PubMed
Google Scholar
Frayling TM, Timpson NJ, Weedon MN, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science (1979). 2007;316(5826):889–94. https://doi.org/10.1126/science.1141634.
Article
CAS
Google Scholar
Ragvin A, Moro E, Fredman D, et al. Long-range gene regulation links genomic type 2 diabetes and obesity risk regions to HHEX, SOX4, and IRX3. Proc Natl Acad Sci U S A. 2010;107(2):775–80. https://doi.org/10.1073/pnas.0911591107.
Article
PubMed
Google Scholar
Smemo S, Tena JJ, Kim KH, et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature. 2014;507(7492):371–5. https://doi.org/10.1038/nature13138.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hormozdiari F, van de Bunt M, Segrè AV, et al. Colocalization of GWAS and eQTL signals detects target genes. Am J Hum Genet. 2016;99(6):1245–60. https://doi.org/10.1016/j.ajhg.2016.10.003.
Article
CAS
PubMed
PubMed Central
Google Scholar
Boyle AP, Hong EL, Hariharan M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22(9):1790–7. https://doi.org/10.1101/gr.137323.112.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012. https://doi.org/10.1093/nar/gkr917.
Article
PubMed
PubMed Central
Google Scholar
Kircher M, Witten DM, Jain P, O’roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014;46(3):310–5. https://doi.org/10.1038/ng.2892.
Article
CAS
PubMed
PubMed Central
Google Scholar
Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010. https://doi.org/10.1093/nar/gkq603.
Article
PubMed
PubMed Central
Google Scholar
He X, Fuller CK, Song Y, et al. Sherlock: detecting gene-disease associations by matching patterns of expression QTL and GWAS. Am J Hum Genet. 2013;92(5):667–80. https://doi.org/10.1016/j.ajhg.2013.03.022.
Article
CAS
PubMed
PubMed Central
Google Scholar
Wallace C. A more accurate method for colocalisation analysis allowing for multiple causal variants. bioRxiv. 2021;17:e1009440.
CAS
Google Scholar
Gettler K, Giri M, Kenigsberg E, et al. Prioritizing Crohn’s disease genes by integrating association signals with gene expression implicates monocyte subsets. Genes Immun. 2019;20(7):577–88. https://doi.org/10.1038/s41435-019-0059-y.
Article
PubMed
PubMed Central
Google Scholar
Bodea CA, Mitchell AA, Bloemendal A, Day-Williams AG, Runz H, Sunyaev SR. PINES: phenotype-informed tissue weighting improves prediction of pathogenic noncoding variants. Genome Biol. 2018. https://doi.org/10.1186/s13059-018-1546-6.
Article
PubMed
PubMed Central
Google Scholar
Li MJ, Wang LY, Xia Z, Sham PC, Wang J. GWAS3D: detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications. Nucleic Acids Res. 2013. https://doi.org/10.1093/nar/gkt456.
Article
PubMed
PubMed Central
Google Scholar
Sey NYA, Hu B, Mah W, et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nat Neurosci. 2020;23(4):583–93. https://doi.org/10.1038/s41593-020-0603-0.
Article
CAS
PubMed
PubMed Central
Google Scholar
Fadason T, Ekblad C, Ingram JR, Schierding WS, O’Sullivan JM. Physical interactions and expression quantitative traits loci identify regulatory connections for obesity and type 2 diabetes associated SNPs. Front Genet. 2017. https://doi.org/10.3389/fgene.2017.00150.
Article
PubMed
PubMed Central
Google Scholar
Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017. https://doi.org/10.1038/s41467-017-01261-5.
Article
PubMed
PubMed Central
Google Scholar
Dong S, Boyle AP. Predicting functional variants in enhancer and promoter elements using RegulomeDB. Hum Mutat. 2019;40(9):1292–8. https://doi.org/10.1002/humu.23791.
Article
CAS
PubMed
PubMed Central
Google Scholar
Vandiedonck C. Genetic association of molecular traits: a help to identify causative variants in complex diseases. Clin Genet. 2018;93(3):520–32. https://doi.org/10.1111/cge.13187.
Article
CAS
PubMed
Google Scholar
Nica AC, Dermitzakis ET. Expression quantitative trait loci: present and future. Philos Trans R Soc B Biol Sci. 2013. https://doi.org/10.1098/rstb.2012.0362.
Article
Google Scholar
Stranger BE, Nica AC, Forrest MS, et al. Population genomics of human gene expression. Nat Genet. 2007;39(10):1217–24. https://doi.org/10.1038/ng2142.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pickrell JK, Marioni JC, Pai AA, et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature. 2010;464(7289):768–72. https://doi.org/10.1038/nature08872.
Article
CAS
PubMed
PubMed Central
Google Scholar
Nica AC, Parts L, Glass D, et al. The architecture of gene regulatory variation across multiple human tissues: the muTHER study. PLoS Genet. 2011. https://doi.org/10.1371/journal.pgen.1002003.
Article
PubMed
PubMed Central
Google Scholar
Ding J, Gudjonsson JE, Liang L, et al. Gene expression in skin and lymphoblastoid cells: refined statistical method reveals extensive overlap in cis-eQTL signals. Am J Hum Genet. 2010;87(6):779–89. https://doi.org/10.1016/j.ajhg.2010.10.024.
Article
CAS
PubMed
PubMed Central
Google Scholar
Heinzen EL, Ge D, Cronin KD, et al. Tissue-specific genetic control of splicing: implications for the study of complex traits. PLoS Biol. 2008;6(12):2869–79. https://doi.org/10.1371/journal.pbio.1000001.
Article
CAS
Google Scholar
de Klein N, Tsai EA, Vochteloo M, et al. Brain expression quantitative trait locus and network analysis reveals downstream effects and putative drivers for brain-related diseases. bioRxiv.
Aguet F, Barbeira AN, Bonazzola R, et al. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science (1979). 2020;369(6509):1318–30. https://doi.org/10.1126/SCIENCE.AAZ1776.
Article
CAS
Google Scholar
Raj T, Rothamel K, Mostafavi S, et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science (1979). 2014;344(6183):519–23. https://doi.org/10.1126/science.1249547.
Article
CAS
Google Scholar
Wills QF, Livak KJ, Tipping AJ, et al. Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments. Nat Biotechnol. 2013;31(8):748–52. https://doi.org/10.1038/nbt.2642.
Article
CAS
PubMed
Google Scholar
van der Wijst MGP, Brugge H, de Vries DH, Deelen P, Swertz MA, Franke L. Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs. Nat Genet. 2018;50(4):493–7. https://doi.org/10.1038/s41588-018-0089-9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Patel D, Zhang X, Farrell JJ, et al. Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue. Transl Psychiatry. 2021;11(1):250. https://doi.org/10.1038/s41398-021-01373-z.
Article
CAS
PubMed
PubMed Central
Google Scholar
van der Wijst MGP, de Vries DH, Groot HE, et al. The single-cell eQTLGen consortium. Elife. 2020. https://doi.org/10.7554/eLife.52155.
Article
PubMed
PubMed Central
Google Scholar
Fairfax BP, Makino S, Radhakrishnan J, et al. Genetics of gene expression in primary immune cells identifies cell type-specific master regulators and roles of HLA alleles. Nat Genet. 2012;44(5):502–10. https://doi.org/10.1038/ng.2205.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang T, Choi J, Kovacs MA, et al. Cell-type-specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes. Genome Res. 2018;28(11):1621–35. https://doi.org/10.1101/gr.233304.117.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mandric I, Schwarz T, Majumdar A, et al. Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis. Nat Commun. 2020. https://doi.org/10.1038/s41467-020-19365-w.
Article
PubMed
PubMed Central
Google Scholar
Choi J, Xu M, Makowski MM, et al. A common intronic variant of PARP1 confers melanoma risk and mediates melanocyte growth via regulation of MITF. Nat Genet. 2017;49(9):1326–35. https://doi.org/10.1038/ng.3927.
Article
CAS
PubMed
Google Scholar
Montoliu L, Grønskov K, Wei AH, et al. Increasing the complexity: new genes and new types of albinism. Pigment Cell Melanoma Res. 2014;27(1):11–8. https://doi.org/10.1111/pcmr.12167.
Article
CAS
PubMed
Google Scholar
Lappalainen T, Sammeth M, Friedländer MR, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature. 2013;501(7468):506–11. https://doi.org/10.1038/nature12531.
Article
CAS
PubMed
PubMed Central
Google Scholar
Battle A, Mostafavi S, Zhu X, et al. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 2014;24(1):14–24. https://doi.org/10.1101/gr.155192.113.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ramasamy A, Trabzuni D, Guelfi S, et al. Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat Neurosci. 2014;17(10):1418–28. https://doi.org/10.1038/nn.3801.
Article
CAS
PubMed
PubMed Central
Google Scholar
Gamazon ER, Wheeler HE, Shah KP, et al. A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. 2015;47(9):1091–8. https://doi.org/10.1038/ng.3367.
Article
CAS
PubMed
PubMed Central
Google Scholar
Gusev A, Ko A, Shi H, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48(3):245–52. https://doi.org/10.1038/ng.3506.
Article
CAS
PubMed
PubMed Central
Google Scholar
Barbeira AN, Dickinson SP, Bonazzola R, et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun. 2018. https://doi.org/10.1038/s41467-018-03621-1.
Article
PubMed
PubMed Central
Google Scholar
Bhattacharya A, Li Y, Love MI. MOSTWAS: multi-omic strategies for transcriptome-wide association studies. PLoS Genet. 2021. https://doi.org/10.1371/journal.pgen.1009398.
Article
PubMed
PubMed Central
Google Scholar
Rodriguez-Fontenla C, Carracedo A. UTMOST, a single and cross-tissue TWAS (Transcriptome Wide Association Study), reveals new ASD (Autism Spectrum Disorder) associated genes. Transl Psychiatry. 2021. https://doi.org/10.1038/s41398-021-01378-8.
Article
PubMed
PubMed Central
Google Scholar
Landi MT, Bishop DT, MacGregor S, et al. Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility. Nat Genet. 2020;52(5):494–504. https://doi.org/10.1038/s41588-020-0611-8.
Article
CAS
PubMed
PubMed Central
Google Scholar
Duffy DL, Zhu G, Li X, et al. Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways. Nat Commun. 2018. https://doi.org/10.1038/s41467-018-06649-5.
Article
PubMed
PubMed Central
Google Scholar
Wainberg M, Sinnott-Armstrong N, Mancuso N, et al. Opportunities and challenges for transcriptome-wide association studies. Nat Genet. 2019. https://doi.org/10.1038/s41588-019-0385-z.
Article
PubMed
PubMed Central
Google Scholar
Hoadley KA, Yau C, Wolf DM, et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell. 2014;158(4):929–44. https://doi.org/10.1016/j.cell.2014.06.049.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang W, Bojorquez-Gomez A, Velez DO, et al. A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nat Genet. 2018;50(4):613–20. https://doi.org/10.1038/s41588-018-0091-2.
Article
CAS
PubMed
PubMed Central
Google Scholar
Habas R, Kato Y, He X. Wnt/Frizzled activation of Rho regulates vertebrate gastrulation and requires a novel formin homology protein Daam1. Cell. 2001;107(7):843–54. https://doi.org/10.1016/S0092-8674(01)00614-6.
Article
CAS
PubMed
Google Scholar
Liu W, Sato A, Khadka D, et al. Mechanism of activation of the Formin protein Daam1. Proc Natl Acad Sci U S A. 2008;105(1):210–5. https://doi.org/10.1073/pnas.0707277105.
Article
PubMed
Google Scholar
Zhu Y, Tian Y, Du J, et al. Dvl2-dependent activation of Daam1 and RhoA regulates Wnt5a-induced breast cancer cell migration. PLoS ONE. 2012. https://doi.org/10.1371/journal.pone.0037823.
Article
PubMed
PubMed Central
Google Scholar
Ashiuchi M, Misono H. Biochemical evidence that Escherichia coli hyi (orf b0508, gip) gene encodes hydroxypyruvate isomerase. Biochim Biophys Acta Protein Struct Mol Enzymol. 1999;1435(1–2):153–9. https://doi.org/10.1016/S0167-4838(99)00216-2.
Article
CAS
Google Scholar
Hormozdiari F, Kostem E, Kang EY, Pasaniuc B, Eskin E. Identifying causal variants at loci with multiple signals of association. Genetics. 2014;198(2):497–508. https://doi.org/10.1534/genetics.114.167908.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chen W, Larrabee BR, Ovsyannikova IG, et al. Fine mapping causal variants with an approximate bayesian method using marginal test statistics. Genetics. 2015;200(3):719–36. https://doi.org/10.1534/genetics.115.176107.
Article
CAS
PubMed
PubMed Central
Google Scholar
Benner C, Spencer CCA, Havulinna AS, Salomaa V, Ripatti S, Pirinen M. FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics. 2016;32(10):1493–501. https://doi.org/10.1093/bioinformatics/btw018.
Article
CAS
PubMed
PubMed Central
Google Scholar
Brown AA, Viñuela A, Delaneau O, Spector TD, Small KS, Dermitzakis ET. Predicting causal variants affecting expression by using whole-genome sequencing and RNA-seq from multiple human tissues. Nat Genet. 2017;49(12):1747–51. https://doi.org/10.1038/ng.3979.
Article
CAS
PubMed
Google Scholar
Wang G, Sarkar A, Carbonetto P, Stephens M. A simple new approach to variable selection in regression, with application to genetic fine mapping. J R Stat Soc Ser B Stat Methodol. 2020;82(5):1273–300. https://doi.org/10.1111/rssb.12388.
Article
Google Scholar
Cremer T, Cremer M. Chromosome territories. Cold Spring Harb Perspect Biol. 2010. https://doi.org/10.1101/cshperspect.a003889.
Article
PubMed
PubMed Central
Google Scholar
Lieberman-Aiden E, van Berkum NL, Williams L, et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science (1979). 2009;326(5950):289–93. https://doi.org/10.1126/science.1181369.
Article
CAS
Google Scholar
Yu M, Ren B. The three-dimensional organization of mammalian genomes. Annu Rev Cell Dev Biol. 2017;33:265–89. https://doi.org/10.1146/annurev-cellbio-100616-060531.
Article
CAS
PubMed
PubMed Central
Google Scholar
McArthur E, Capra JA. Topologically associating domain boundaries that are stable across diverse cell types are evolutionarily constrained and enriched for heritability. Am J Hum Genet. 2021;108(2):269–83. https://doi.org/10.1016/j.ajhg.2021.01.001.
Article
CAS
PubMed
PubMed Central
Google Scholar
Dixon JR, Jung I, Selvaraj S, et al. Chromatin architecture reorganization during stem cell differentiation. Nature. 2015;518(7539):331–6. https://doi.org/10.1038/nature14222.
Article
CAS
PubMed
PubMed Central
Google Scholar
Merkenschlager M, Nora EP. CTCF and cohesin in genome folding and transcriptional gene regulation. Annu Rev Genomics Hum Genet. 2016;17:17–43. https://doi.org/10.1146/annurev-genom-083115-022339.
Article
CAS
PubMed
Google Scholar
Weintraub AS, Li CH, Zamudio AV, et al. YY1 is a structural regulator of enhancer-promoter loops. Cell. 2017;171(7):1573–88. https://doi.org/10.1016/j.cell.2017.11.008.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bailey SD, Zhang X, Desai K, et al. ZNF143 provides sequence specificity to secure chromatin interactions at gene promoters. Nat Commun. 2015;6(1):1–10. https://doi.org/10.1038/ncomms7186.
Article
CAS
Google Scholar
Furlong EEM, Levine M. Developmental enhancers and chromosome topology. Science (1979). 2018;361(6409):1341–5. https://doi.org/10.1126/science.aau0320.
Article
CAS
Google Scholar
Dekker J, Rippe K, Dekker M, Kleckner N. Capturing chromosome conformation. Science (1979). 2002;295(5558):1306–11. https://doi.org/10.1126/science.1067799.
Article
CAS
Google Scholar
Simonis M, Klous P, Splinter E, et al. Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture-on-chip (4C). Nat Genet. 2006;38(11):1348–54. https://doi.org/10.1038/ng1896.
Article
CAS
PubMed
Google Scholar
Zhao Z, Tavoosidana G, Sjölinder M, et al. Circular chromosome conformation capture (4C) uncovers extensive networks of epigenetically regulated intra- and interchromosomal interactions. Nat Genet. 2006;38(11):1341–7. https://doi.org/10.1038/ng1891.
Article
CAS
PubMed
Google Scholar
Dostie J, Richmond TA, Arnaout RA, et al. Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements. Genome Res. 2006;16(10):1299–309. https://doi.org/10.1101/gr.5571506.
Article
CAS
PubMed
PubMed Central
Google Scholar
Rodley CDM, Bertels F, Jones B, O’Sullivan JM. Global identification of yeast chromosome interactions using Genome conformation capture. Fungal Genet Biol. 2009;46(11):879–86. https://doi.org/10.1016/j.fgb.2009.07.006.
Article
CAS
PubMed
Google Scholar
Denker A, de Laat W. The second decade of 3C technologies: detailed insights into nuclear organization. Genes Dev. 2016;30(12):1357–82. https://doi.org/10.1101/gad.281964.116.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hill VK, Kim JS, Waldman T. Cohesin mutations in human cancer. Biochim Biophys Acta Rev Cancer. 2016;1866(1):1–11. https://doi.org/10.1016/j.bbcan.2016.05.002.
Article
CAS
Google Scholar
Cuartero S, Innes AJ, Merkenschlager M. Towards a better understanding of cohesin mutations in AML. Front Oncol. 2019. https://doi.org/10.3389/fonc.2019.00867.
Article
PubMed
PubMed Central
Google Scholar
Viny AD, Levine RL. Cohesin mutations in myeloid malignancies made simple. Curr Opin Hematol. 2018;25(2):61–6. https://doi.org/10.1097/MOH.0000000000000405.
Article
CAS
PubMed
PubMed Central
Google Scholar
Leeke B, Marsman J, O’Sullivan JM, Horsfield JA. Cohesin mutations in myeloid malignancies: underlying mechanisms. Exp Hematol Oncol. 2014. https://doi.org/10.1186/2162-3619-3-13.
Article
PubMed
PubMed Central
Google Scholar
Viny AD, Ott CJ, Spitzer B, et al. Dose-dependent role of the cohesin complex in normal and malignant hematopoiesis. J Exp Med. 2015;212(11):1819–32. https://doi.org/10.1084/jem.20151317.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mazumdar C, Shen Y, Xavy S, et al. Leukemia-associated cohesin mutants dominantly enforce stem cell programs and impair human hematopoietic progenitor differentiation. Cell Stem Cell. 2015;17(6):675–88. https://doi.org/10.1016/j.stem.2015.09.017.
Article
CAS
PubMed
PubMed Central
Google Scholar
Liu Y, Li C, Shen S, et al. Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X. Nat Genet. 2020;52(8):811–8. https://doi.org/10.1038/s41588-020-0659-5.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ye B, Yang G, Li Y, Zhang C, Wang Q, Yu G. ZNF143 in chromatin looping and gene regulation. Front Genet. 2020;11:338. https://doi.org/10.3389/FGENE.2020.00338/BIBTEX.
Article
CAS
PubMed
PubMed Central
Google Scholar
Grubert F, Zaugg JB, Kasowski M, et al. Genetic control of chromatin states in humans involves local and distal chromosomal interactions. Cell. 2015;162(5):1051–65. https://doi.org/10.1016/j.cell.2015.07.048.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mifsud B, Tavares-Cadete F, Young AN, et al. Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C. Nat Genet. 2015;47(6):598–606. https://doi.org/10.1038/ng.3286.
Article
CAS
PubMed
Google Scholar
Dryden NH, Broome LR, Dudbridge F, et al. Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C. Genome Res. 2014;24(11):1854–68. https://doi.org/10.1101/gr.175034.114.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jäger R, Migliorini G, Henrion M, et al. Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci. Nat Commun. 2015. https://doi.org/10.1038/ncomms7178.
Article
PubMed
Google Scholar
Sotelo J, Esposito D, Duhagon MA, et al. Long-range enhancers on 8q24 regulate c-Myc. Proc Natl Acad Sci U S A. 2010;107(7):3001–5. https://doi.org/10.1073/pnas.0906067107.
Article
PubMed
PubMed Central
Google Scholar
Du M, Tillmans L, Gao J, et al. Chromatin interactions and candidate genes at ten prostate cancer risk loci. Sci Rep. 2016. https://doi.org/10.1038/srep23202.
Article
PubMed
PubMed Central
Google Scholar
Cai M, Kim S, Wang K, Farnham PJ, Coetzee GA, Lu W. 4C-seq revealed long-range interactions of a functional enhancer at the 8q24 prostate cancer risk locus. Sci Rep. 2016. https://doi.org/10.1038/srep22462.
Article
PubMed
PubMed Central
Google Scholar
Hoskins JW, Ibrahim A, Emmanuel MA, et al. Functional characterization of a chr13q22.1 pancreatic cancer risk locus reveals long-range interaction and allele-specific effects on DIS3 expression. Hum Mol Genet. 2016;25(21):4726–38. https://doi.org/10.1093/hmg/ddw300.
Article
CAS
PubMed
PubMed Central
Google Scholar
He H, Li W, Liyanarachchi S, et al. Multiple functional variants in long-range enhancer elements contribute to the risk of SNP rs965513 in thyroid cancer. Proc Natl Acad Sci U S A. 2015;112(19):6128–33. https://doi.org/10.1073/pnas.1506255112.
Article
CAS
PubMed
PubMed Central
Google Scholar
Xu M, Mehl L, Zhang T, et al. A UVB-responsive common variant at chromosome band 7p21.1 confers tanning response and melanoma risk via regulation of the aryl hydrocarbon receptor, AHR. Am J Hum Genet. 2021;108(9):1611. https://doi.org/10.1016/J.AJHG.2021.07.002.
Article
CAS
PubMed
PubMed Central
Google Scholar
Law MH, Bishop DT, Lee JE, et al. Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma. Nat Genet. 2015;47(9):987–95. https://doi.org/10.1038/ng.3373.
Article
CAS
PubMed
PubMed Central
Google Scholar
Visconti A, Duffy DL, Liu F, et al. Genome-wide association study in 176,678 Europeans reveals genetic loci for tanning response to sun exposure. Nat Commun. 2018. https://doi.org/10.1038/s41467-018-04086-y.
Article
PubMed
PubMed Central
Google Scholar
Chahal HS, Lin Y, Ransohoff KJ, et al. Genome-wide association study identifies novel susceptibility loci for cutaneous squamous cell carcinoma. Nat Commun. 2016. https://doi.org/10.1038/ncomms12048.
Article
PubMed
PubMed Central
Google Scholar
Vogeley C, Esser C, Tüting T, Krutmann J, Haarmann-Stemmann T. Role of the aryl hydrocarbon receptor in environmentally induced skin aging and skin carcinogenesis. Int J Mol Sci. 2019. https://doi.org/10.3390/ijms20236005.
Article
PubMed
PubMed Central
Google Scholar
Jux B, Kadow S, Luecke S, Rannug A, Krutmann J, Esser C. The aryl hydrocarbon receptor mediates UVB radiation-induced skin tanning. J Investig Dermatol. 2011;131(1):203–10. https://doi.org/10.1038/jid.2010.269.
Article
CAS
PubMed
Google Scholar
Luecke S, Backlund M, Jux B, Esser C, Krutmann J, Rannug A. The aryl hydrocarbon receptor (AHR), a novel regulator of human melanogenesis. Pigment Cell Melanoma Res. 2010;23(6):828–33. https://doi.org/10.1111/j.1755-148X.2010.00762.x.
Article
CAS
PubMed
Google Scholar
Nakamura M, Ueda Y, Hayashi M, Kato H, Furuhashi T, Morita A. Tobacco smoke-induced skin pigmentation is mediated by the aryl hydrocarbon receptor. Exp Dermatol. 2013;22(8):556–8. https://doi.org/10.1111/exd.12170.
Article
CAS
PubMed
Google Scholar
Kim K, Jang K, Yang W, et al. Chromatin structure-based prediction of recurrent noncoding mutations in cancer. Nat Genet. 2016;48(11):1321–6. https://doi.org/10.1038/ng.3682.
Article
CAS
PubMed
Google Scholar
Zhu H, Uusküla-Reimand L, Isaev K, et al. Candidate cancer driver mutations in distal regulatory elements and long-range chromatin interaction networks. Mol Cell. 2020;77(6):1307-1321.e10. https://doi.org/10.1016/j.molcel.2019.12.027.
Article
CAS
PubMed
Google Scholar
Shuai S, Abascal F, Amin SB, et al. Combined burden and functional impact tests for cancer driver discovery using DriverPower. Nat Commun. 2020;11(1):1–12. https://doi.org/10.1038/s41467-019-13929-1.
Article
CAS
Google Scholar
Lochovsky L, Zhang J, Fu Y, Khurana E, Gerstein M. LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations. Nucleic Acids Res. 2015;43(17):8123–34. https://doi.org/10.1093/NAR/GKV803.
Article
CAS
PubMed
PubMed Central
Google Scholar
Lawrence MS, Stojanov P, Mermel CH, et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature. 2014;505(7484):495–501. https://doi.org/10.1038/nature12912.
Article
CAS
PubMed
PubMed Central
Google Scholar
Nik-Zainal S, Davies H, Staaf J, et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature. 2016;534(7605):47–54. https://doi.org/10.1038/nature17676.
Article
CAS
PubMed
PubMed Central
Google Scholar
Juul M, Bertl J, Guo Q, et al. Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate. Elife. 2017. https://doi.org/10.7554/ELIFE.21778.
Article
PubMed
PubMed Central
Google Scholar
Hornshøj H, Nielsen MM, Sinnott-Armstrong NA, et al. Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival. npj Genomic Med. 2018;3(1):1–14. https://doi.org/10.1038/s41525-017-0040-5.
Article
CAS
Google Scholar
Umer HM, Cavalli M, Dabrowski MJ, et al. A Significant regulatory mutation burden at a high-affinity position of the CTCF motif in gastrointestinal cancers. Hum Mutat. 2016;37(9):904–13. https://doi.org/10.1002/HUMU.23014.
Article
CAS
PubMed
Google Scholar
Sallari R, Sinnott-Armstrong N, French J, et al. Convergence of dispersed regulatory mutations predicts driver genes in prostate cancer. bioRxiv. 2016. https://doi.org/10.1101/097451.
Article
Google Scholar
Zhou S, Hawley JR, Soares F, et al. Noncoding mutations target cis-regulatory elements of the FOXA1 plexus in prostate cancer. Nat Commun. 2020. https://doi.org/10.1038/s41467-020-14318-9.
Article
PubMed
PubMed Central
Google Scholar
Corona RI, Seo JH, Lin X, et al. Non-coding somatic mutations converge on the PAX8 pathway in ovarian cancer. Nat Commun. 2020. https://doi.org/10.1038/s41467-020-15951-0.
Article
PubMed
PubMed Central
Google Scholar
Sanyal A, Lajoie BR, Jain G, Dekker J. The long-range interaction landscape of gene promoters. Nature. 2012;489(7414):109–13. https://doi.org/10.1038/nature11279.
Article
CAS
PubMed
PubMed Central
Google Scholar
Velagaleti GV, Bien-Willner GA, Northup JK, et al. Position effects due to chromosome breakpoints that map approximately 900 Kb upstream and approximately 1.3 Mb downstream of SOX9 in two patients with campomelic dysplasia. Am J Hum Genet. 2005;76(4):652–62. https://doi.org/10.1086/429252.
Article
CAS
PubMed
PubMed Central
Google Scholar
Herranz D, Ambesi-Impiombato A, Palomero T, et al. A NOTCH1-driven MYC enhancer promotes T cell development, transformation and acute lymphoblastic leukemia. Nat Med. 2014;20(10):1130–7. https://doi.org/10.1038/nm.3665.
Article
CAS
PubMed
PubMed Central
Google Scholar
Westra HJ, Peters MJ, Esko T, et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet. 2013;45(10):1238–43. https://doi.org/10.1038/ng.2756.
Article
CAS
PubMed
PubMed Central
Google Scholar
Cookson W, Liang L, Abecasis G, Moffatt M, Lathrop M. Mapping complex disease traits with global gene expression. Nat Rev Genet. 2009;10(3):184–94. https://doi.org/10.1038/nrg2537.
Article
CAS
PubMed
PubMed Central
Google Scholar
Fagny M, Platig J, Kuijjer ML, Lin X, Quackenbush J. Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function. Br J Cancer. 2020;122(4):569–77. https://doi.org/10.1038/s41416-019-0614-3.
Article
CAS
PubMed
Google Scholar
Gong J, Mei S, Liu C, et al. PancanQTL: systematic identification of cis -eQTLs and trans -eQTLs in 33 cancer types. Nucleic Acids Res. 2018;46(D1):D971–6. https://doi.org/10.1093/nar/gkx861.
Article
CAS
PubMed
Google Scholar
Moreno V, Alonso MH, Closa A, et al. Colon-specific eQTL analysis to inform on functional SNPs. Br J Cancer. 2018;119(8):971–7. https://doi.org/10.1038/s41416-018-0018-9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bicak M, Wang X, Gao X, et al. Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB. Hum Mol Genet. 2020;29(10):1581–91. https://doi.org/10.1093/hmg/ddaa026.
Article
CAS
PubMed
PubMed Central
Google Scholar
Han J, Kraft P, Nan H, et al. A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation. PLoS Genet. 2008. https://doi.org/10.1371/journal.pgen.1000074.
Article
PubMed
PubMed Central
Google Scholar
Pierce BL, Tong L, Chen LS, et al. Mediation analysis demonstrates that trans-eQTLs are often explained by cis-mediation: a genome-wide analysis among 1,800 South Asians. PLoS Genet. 2014. https://doi.org/10.1371/journal.pgen.1004818.
Article
PubMed
PubMed Central
Google Scholar
Fadason T, Schierding W, Lumley T, O’Sullivan JM. Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities. Nat Commun. 2018. https://doi.org/10.1038/s41467-018-07692-y.
Article
PubMed
PubMed Central
Google Scholar
Yang F, Wang J, Pierce BL, et al. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis. Genome Res. 2017;27(11):1859–71. https://doi.org/10.1101/gr.216754.116.
Article
CAS
PubMed
PubMed Central
Google Scholar
Yang F, Gleason KJ, Wang J, et al. CCmed: cross-condition mediation analysis for identifying robust trans-eQTLs and assessing their effects on human traits. BioRxiv. 2019. https://doi.org/10.1101/803106.
Article
Google Scholar
Shan N, Wang Z, Hou L. Identification of trans-eQTLs using mediation analysis with multiple mediators. BMC Bioinform. 2019. https://doi.org/10.1186/s12859-019-2651-6.
Article
Google Scholar
Grundberg E, Small KS, Hedman ÅK, et al. Mapping cis-and trans-regulatory effects across multiple tissues in twins. Nat Genet. 2012;44(10):1084–9. https://doi.org/10.1038/ng.2394.
Article
CAS
PubMed
PubMed Central
Google Scholar
Aguet F, Brown AA, Castel SE, et al. Genetic effects on gene expression across human tissues. Nature. 2017;550(7675):204–13. https://doi.org/10.1038/nature24277.
Article
Google Scholar
Schierding W, Horsfield JA, O’Sullivan JM. Low tolerance for transcriptional variation at cohesin genes is accompanied by functional links to disease-relevant pathways. J Med Genet. 2021;58(8):534–42. https://doi.org/10.1136/jmedgenet-2020-107095.
Article
CAS
PubMed
Google Scholar
Westra HJ, Franke L. From genome to function by studying eQTLs. Biochim Biophys Acta Mol Basis Dis. 2014;1842(10):1896–902. https://doi.org/10.1016/j.bbadis.2014.04.024.
Article
CAS
Google Scholar
Jacobson EC, Perry JK, Long DS, et al. Migration through a small pore disrupts inactive chromatin organization in neutrophil-like cells. BMC Biol. 2018. https://doi.org/10.1186/s12915-018-0608-2.
Article
PubMed
PubMed Central
Google Scholar