Loss-of-function tolerance of enhancers in the human genome

Autoři: Duo Xu aff001;  Omer Gokcumen aff005;  Ekta Khurana aff001
Působiště autorů: Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York, United States of America aff001;  Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, United States of America aff002;  Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, New York, United States of America aff003;  Meyer Cancer Center, Weill Cornell Medicine, New York, New York, United States of America aff004;  Department of Biological Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America aff005
Vyšlo v časopise: Loss-of-function tolerance of enhancers in the human genome. PLoS Genet 16(4): e32767. doi:10.1371/journal.pgen.1008663
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008663


Previous studies have surveyed the potential impact of loss-of-function (LoF) variants and identified LoF-tolerant protein-coding genes. However, the tolerance of human genomes to losing enhancers has not yet been evaluated. Here we present the catalog of LoF-tolerant enhancers using structural variants from whole-genome sequences. Using a conservative approach, we estimate that individual human genomes possess at least 28 LoF-tolerant enhancers on average. We assessed the properties of LoF-tolerant enhancers in a unified regulatory network constructed by integrating tissue-specific enhancers and gene-gene interactions. We find that LoF-tolerant enhancers tend to be more tissue-specific and regulate fewer and more dispensable genes relative to other enhancers. They are enriched in immune-related cells while enhancers with low LoF-tolerance are enriched in kidney and brain/neuronal stem cells. We developed a supervised learning approach to predict the LoF-tolerance of all enhancers, which achieved an area under the receiver operating characteristics curve (AUROC) of 98%. We predict 3,519 more enhancers would be likely tolerant to LoF and 129 enhancers that would have low LoF-tolerance. Our predictions are supported by a known set of disease enhancers and novel deletions from PacBio sequencing. The LoF-tolerance scores provided here will serve as an important reference for disease studies.

Klíčová slova:

Centrality – Gene expression – Gene regulation – Gene regulatory networks – Genetic networks – Human genomics – Network analysis – Protein-protein interactions


1. Ng PC, Levy S, Huang J, Stockwell TB, Walenz BP, Li K, et al. Genetic variation in an individual human exome. PLoS Genet. 2008;4(8):e1000160. doi: 10.1371/journal.pgen.1000160 PubMed Central PMCID: PMC2493042. 18704161

2. Pelak K, Shianna KV, Ge D, Maia JM, Zhu M, Smith JP, et al. The characterization of twenty sequenced human genomes. PLoS Genet. 2010;6(9):e1001111. doi: 10.1371/journal.pgen.1001111 PubMed Central PMCID: PMC2936541. 20838461

3. Genomes Project C, Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, et al. A map of human genome variation from population-scale sequencing. Nature. 2010;467(7319):1061–73. doi: 10.1038/nature09534 20981092

4. Telenti A, Pierce LCT, Biggs WH, di Iulio J, Wong EHM, Fabani MM, et al. Deep sequencing of 10,000 human genomes. Proc Natl Acad Sci U S A. 2016;113(42):11901–6. doi: 10.1073/pnas.1613365113 27702888

5. MacArthur DG, Balasubramanian S, Frankish A, Huang N, Morris J, Walter K, et al. A systematic survey of loss-of-function variants in human protein-coding genes. Science. 2012;335(6070):823–8. doi: 10.1126/science.1215040 PubMed Central PMCID: PMC3299548. 22344438

6. Genomes Project C, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature. 2015;526(7571):68–74. doi: 10.1038/nature15393 26432245

7. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–91. doi: 10.1038/nature19057 27535533; PubMed Central PMCID: PMC5018207.

8. Kathiresan S, Srivastava D. Genetics of human cardiovascular disease. Cell. 2012;148(6):1242–57. doi: 10.1016/j.cell.2012.03.001 PubMed Central PMCID: PMC3319439. 22424232

9. Tg and Hdl Working Group of the Exome Sequencing Project NHLaBI, Crosby J, Peloso GM, Auer PL, Crosslin DR, Stitziel NO, et al. Loss-of-function mutations in APOC3, triglycerides, and coronary disease. N Engl J Med. 2014;371(1):22–31. doi: 10.1056/NEJMoa1307095 PubMed Central PMCID: PMC4180269. 24941081

10. Gilissen C, Hehir-Kwa JY, Thung DT, van de Vorst M, van Bon BWM, Willemsen MH, et al. Genome sequencing identifies major causes of severe intellectual disability. Nature. 2014;511(7509):344–7. doi: 10.1038/nature13394 24896178

11. Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K, Landén M, et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci. 2016;19(11):1433–41. doi: 10.1038/nn.4402 PubMed Central PMCID: PMC5104192. 27694994

12. Yu Y, Lin Y, Takasaki Y, Wang C, Kimura H, Xing J, et al. Rare loss of function mutations in N-methyl-D-aspartate glutamate receptors and their contributions to schizophrenia susceptibility. Transl Psychiatry. 2018;8(1):12. doi: 10.1038/s41398-017-0061-y PubMed Central PMCID: PMC5802496. 29317596

13. Khurana E, Fu Y, Chen J, Gerstein M. Interpretation of genomic variants using a unified biological network approach. PLoS Comput Biol. 2013;9(3):e1002886. doi: 10.1371/journal.pcbi.1002886 PubMed Central PMCID: PMC3591262. 23505346

14. Consortium EP. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74. doi: 10.1038/nature11247 PubMed Central PMCID: PMC3439153. 22955616

15. Davis CA, Hitz BC, Sloan CA, Chan ET, Davidson JM, Gabdank I, et al. The Encyclopedia of DNA elements (ENCODE): data portal update. Nucleic Acids Res. 2018;46(D1):D794–D801. doi: 10.1093/nar/gkx1081 29126249; PubMed Central PMCID: PMC5753278.

16. Roadmap Epigenomics C, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518(7539):317–30. doi: 10.1038/nature14248 PubMed Central PMCID: PMC4530010. 25693563

17. Andersson R, Gebhard C, Miguel-Escalada I, Hoof I, Bornholdt J, Boyd M, et al. An atlas of active enhancers across human cell types and tissues. Nature. 2014;507(7493):455–61. doi: 10.1038/nature12787 PubMed Central PMCID: PMC5215096. 24670763

18. Hong J-W, Hendrix DA, Levine MS. Shadow enhancers as a source of evolutionary novelty. Science. 2008;321(5894):1314. doi: 10.1126/science.1160631 PubMed Central PMCID: PMC4257485. 18772429

19. Perry MW, Boettiger AN, Bothma JP, Levine M. Shadow enhancers foster robustness of Drosophila gastrulation. Curr Biol. 2010;20(17):1562–7. doi: 10.1016/j.cub.2010.07.043 PubMed Central PMCID: PMC4257487. 20797865

20. Frankel N, Davis GK, Vargas D, Wang S, Payre F, Stern DL. Phenotypic robustness conferred by apparently redundant transcriptional enhancers. Nature. 2010;466(7305):490–3. doi: 10.1038/nature09158 PubMed Central PMCID: PMC2909378. 20512118

21. Osterwalder M, Barozzi I, Tissières V, Fukuda-Yuzawa Y, Mannion BJ, Afzal SY, et al. Enhancer redundancy provides phenotypic robustness in mammalian development. Nature. 2018;554(7691):239–43. doi: 10.1038/nature25461 PubMed Central PMCID: PMC5808607. 29420474

22. Macneil LT, Walhout AJM. Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression. Genome Res. 2011;21(5):645–57. doi: 10.1101/gr.097378.109 PubMed Central PMCID: PMC3083081. 21324878

23. Ghiasvand NM, Rudolph DD, Mashayekhi M, Brzezinski JA, Goldman D, Glaser T. Deletion of a remote enhancer near ATOH7 disrupts retinal neurogenesis, causing NCRNA disease. Nat Neurosci. 2011;14(5):578–86. Epub 2011/03/27. doi: 10.1038/nn.2798 21441919; PubMed Central PMCID: PMC3083485.

24. Albuisson J, Isidor B, Giraud M, Pichon O, Marsaud T, David A, et al. Identification of two novel mutations in Shh long-range regulator associated with familial pre-axial polydactyly. Clin Genet. 2011;79(4):371–7. doi: 10.1111/j.1399-0004.2010.01465.x 20569257.

25. Weedon MN, Cebola I, Patch AM, Flanagan SE, De Franco E, Caswell R, et al. Recessive mutations in a distal PTF1A enhancer cause isolated pancreatic agenesis. Nat Genet. 2014;46(1):61–4. Epub 2013/11/10. doi: 10.1038/ng.2826 24212882; PubMed Central PMCID: PMC4131753.

26. Oz-Levi D, Olender T, Bar-Joseph I, Zhu Y, Marek-Yagel D, Barozzi I, et al. Noncoding deletions reveal a gene that is critical for intestinal function. Nature. 2019;571(7763):107–11. Epub 2019/06/19. doi: 10.1038/s41586-019-1312-2 31217582.

27. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009;106(23):9362–7. doi: 10.1073/pnas.0903103106 PubMed Central PMCID: PMC2687147. 19474294

28. Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337(6099):1190–5. doi: 10.1126/science.1222794 PubMed Central PMCID: PMC3771521. 22955828

29. Trynka G, Sandor C, Han B, Xu H, Stranger BE, Liu XS, et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat Genet. 2013;45(2):124–30. doi: 10.1038/ng.2504 PubMed Central PMCID: PMC3826950. 23263488

30. MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 2017;45(D1):D896–D901. doi: 10.1093/nar/gkw1133 PubMed Central PMCID: PMC5210590. 27899670

31. Wang Z, Zhang Q, Zhang W, Lin JR, Cai Y, Mitra J, et al. HEDD: Human Enhancer Disease Database. Nucleic Acids Res. 2018;46(D1):D113–D20. doi: 10.1093/nar/gkx988 29077884; PubMed Central PMCID: PMC5753236.

32. Stark C, Breitkreutz B-J, Reguly T, Boucher L, Breitkreutz A, Tyers M. BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 2006;34(Database issue):D535–9. doi: 10.1093/nar/gkj109 PubMed Central PMCID: PMC1347471. 16381927

33. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 2010;38(Database issue):D355–60. doi: 10.1093/nar/gkp896 PubMed Central PMCID: PMC2808910. 19880382

34. Lin J, Xie Z, Zhu H, Qian J. Understanding protein phosphorylation on a systems level. Brief Funct Genomics. 2010;9(1):32–42. doi: 10.1093/bfgp/elp045 PubMed Central PMCID: PMC3096446. 20056723

35. Korcsmáros T, Farkas IJ, Szalay MS, Rovó P, Fazekas D, Spiró Z, et al. Uniformly curated signaling pathways reveal tissue-specific cross-talks and support drug target discovery. Bioinformatics. 2010;26(16):2042–50. doi: 10.1093/bioinformatics/btq310 20542890

36. He B, Chen C, Teng L, Tan K. Global view of enhancer-promoter interactome in human cells. Proc Natl Acad Sci U S A. 2014;111(21):E2191–9. doi: 10.1073/pnas.1320308111 PubMed Central PMCID: PMC4040567. 24821768

37. Yip KY, Cheng C, Bhardwaj N, Brown JB, Leng J, Kundaje A, et al. Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors. Genome Biol. 2012;13(9):R48. doi: 10.1186/gb-2012-13-9-r48 PubMed Central PMCID: PMC3491392. 22950945

38. Zhu Y, Chen Z, Zhang K, Wang M, Medovoy D, Whitaker JW, et al. Constructing 3D interaction maps from 1D epigenomes. Nat Commun. 2016;7:10812. doi: 10.1038/ncomms10812 PubMed Central PMCID: PMC4792925. 26960733

39. Whalen S, Truty RM, Pollard KS. Enhancer-promoter interactions are encoded by complex genomic signatures on looping chromatin. Nat Genet. 2016;48(5):488–96. doi: 10.1038/ng.3539 PubMed Central PMCID: PMC4910881. 27064255

40. Roy S, Siahpirani AF, Chasman D, Knaack S, Ay F, Stewart R, et al. A predictive modeling approach for cell line-specific long-range regulatory interactions. Nucleic Acids Res. 2016;44(4):1977–8. doi: 10.1093/nar/gkv1181 PubMed Central PMCID: PMC4770215. 26546512

41. Cao Q, Anyansi C, Hu X, Xu L, Xiong L, Tang W, et al. Reconstruction of enhancer-target networks in 935 samples of human primary cells, tissues and cell lines. Nat Genet. 2017;49(10):1428–36. doi: 10.1038/ng.3950 28869592

42. Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, et al. A global reference for human genetic variation. Nature. 2015;526(7571):68–74. doi: 10.1038/nature15393 26432245; PubMed Central PMCID: PMC4750478.

43. Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A, Huddleston J, et al. An integrated map of structural variation in 2,504 human genomes. Nature. 2015;526(7571):75–81. doi: 10.1038/nature15394 PubMed Central PMCID: PMC4617611. 26432246

44. Bejerano G, Pheasant M, Makunin I, Stephen S, Kent WJ, Mattick JS, et al. Ultraconserved elements in the human genome. Science. 2004;304(5675):1321–5. doi: 10.1126/science.1098119 15131266

45. Katzman S, Kern AD, Bejerano G, Fewell G, Fulton L, Wilson RK, et al. Human genome ultraconserved elements are ultraselected. Science. 2007;317(5840):915. doi: 10.1126/science.1142430 17702936.

46. Yanagisawa H, Clouthier DE, Richardson JA, Charité J, Olson EN. Targeted deletion of a branchial arch-specific enhancer reveals a role of dHAND in craniofacial development. Development. 2003;130(6):1069–78. doi: 10.1242/dev.00337 12571099

47. Ahituv N, Zhu Y, Visel A, Holt A, Afzal V, Pennacchio LA, et al. Deletion of ultraconserved elements yields viable mice. PLoS Biol. 2007;5(9):e234. doi: 10.1371/journal.pbio.0050234 PubMed Central PMCID: PMC1964772. 17803355

48. Sagai T. Elimination of a long-range cis-regulatory module causes complete loss of limb-specific Shh expression and truncation of the mouse limb. Development. 2005;132(4):797–803. doi: 10.1242/dev.01613 15677727

49. Nolte MJ, Wang Y, Deng JM, Swinton PG, Wei C, Guindani M, et al. Functional analysis of limb transcriptional enhancers in the mouse. Evol Dev. 2014;16(4):207–23. doi: 10.1111/ede.12084 PubMed Central PMCID: PMC4130292. 24920384

50. Dickel DE, Ypsilanti AR, Pla R, Zhu Y, Barozzi I, Mannion BJ, et al. Ultraconserved Enhancers Are Required for Normal Development. Cell. 2018;172(3):491–9.e15. doi: 10.1016/j.cell.2017.12.017 PubMed Central PMCID: PMC5786478. 29358049

51. Visel A, Minovitsky S, Dubchak I, Pennacchio LA. VISTA Enhancer Browser—a database of tissue-specific human enhancers. Nucleic Acids Res. 2007;35(suppl_1):D88–D92. doi: 10.1093/nar/gkl822 17130149

52. Wunderlich Z, Bragdon MD, Vincent BJ, White JA, Estrada J, DePace AH. Krüppel Expression Levels Are Maintained through Compensatory Evolution of Shadow Enhancers. Cell Rep. 2015;12(11):1740–7. Epub 2015/09/03. doi: 10.1016/j.celrep.2015.08.021 26344774; PubMed Central PMCID: PMC4581983.

53. Khan A, Fornes O, Stigliani A, Gheorghe M, Castro-Mondragon JA, van der Lee R, et al. JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework. Nucleic Acids Res. 2018;46(D1):D260–D6. doi: 10.1093/nar/gkx1126 29140473; PubMed Central PMCID: PMC5753243.

54. Pei Z, Wang B, Chen G, Nagao M, Nakafuku M, Campbell K. Homeobox genes Gsx1 and Gsx2 differentially regulate telencephalic progenitor maturation. Proc Natl Acad Sci U S A. 2011;108(4):1675–80. Epub 2011/01/04. doi: 10.1073/pnas.1008824108 21205889; PubMed Central PMCID: PMC3029701.

55. Westphal DS, Riedhammer KM, Kovacs-Nagy R, Meitinger T, Hoefele J, Wagner M. A De Novo Missense Variant in POU3F2 Identified in a Child with Global Developmental Delay. Neuropediatrics. 2018;49(6):401–4. Epub 2018/09/10. doi: 10.1055/s-0038-1669926 30199896.

56. Snijders Blok L, Kleefstra T, Venselaar H, Maas S, Kroes HY, Lachmeijer AMA, et al. De Novo Variants Disturbing the Transactivation Capacity of POU3F3 Cause a Characteristic Neurodevelopmental Disorder. Am J Hum Genet. 2019;105(2):403–12. Epub 2019/07/11. doi: 10.1016/j.ajhg.2019.06.007 31303265; PubMed Central PMCID: PMC6698880.

57. Mollaaghababa R, Pavan WJ. The importance of having your SOX on: role of SOX10 in the development of neural crest-derived melanocytes and glia. Oncogene. 2003;22(20):3024–34. doi: 10.1038/sj.onc.1206442 12789277.

58. Bondurand N, Dastot-Le Moal F, Stanchina L, Collot N, Baral V, Marlin S, et al. Deletions at the SOX10 gene locus cause Waardenburg syndrome types 2 and 4. Am J Hum Genet. 2007;81(6):1169–85. Epub 2007/10/22. doi: 10.1086/522090 17999358; PubMed Central PMCID: PMC2276340.

59. Lecerf L, Kavo A, Ruiz-Ferrer M, Baral V, Watanabe Y, Chaoui A, et al. An impairment of long distance SOX10 regulatory elements underlies isolated Hirschsprung disease. Hum Mutat. 2014;35(3):303–7. doi: 10.1002/humu.22499 24357527

60. Breiman L. Classification and Regression Trees: Chapman & Hall; 1984 1984. 358 p.

61. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: Machine Learning in Python. J Mach Learn Res. 2011;12(Oct):2825–30.

62. Chaisson MJP, Huddleston J, Dennis MY, Sudmant PH, Malig M, Hormozdiari F, et al. Resolving the complexity of the human genome using single-molecule sequencing. Nature. 2015;517(7536):608–11. doi: 10.1038/nature13907 PubMed Central PMCID: PMC4317254. 25383537

63. Chin C-S, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods. 2013;10(6):563–9. doi: 10.1038/nmeth.2474 23644548

64. Kronenberg ZN, Fiddes IT, Gordon D, Murali S, Cantsilieris S, Meyerson OS, et al. High-resolution comparative analysis of great ape genomes. Science. 2018;360(6393). doi: 10.1126/science.aar6343 29880660

65. Chaisson MJP, Sanders AD, Zhao X, Malhotra A, Porubsky D, Rausch T, et al. Multi-platform discovery of haplotype-resolved structural variation in human genomes. Nat Commun. 2019;10(1):1784. Epub 2019/04/16. doi: 10.1038/s41467-018-08148-z 30992455; PubMed Central PMCID: PMC6467913.

66. Fuxman Bass JI, Sahni N, Shrestha S, Garcia-Gonzalez A, Mori A, Bhat N, et al. Human gene-centered transcription factor networks for enhancers and disease variants. Cell. 2015;161(3):661–73. doi: 10.1016/j.cell.2015.03.003 PubMed Central PMCID: PMC4409666. 25910213

67. Campbell C, Cucci RA, Prasad S, Green GE, Edeal JB, Galer CE, et al. Pendred syndrome, DFNB4, and PDS/SLC26A4 identification of eight novel mutations and possible genotype-phenotype correlations. Hum Mutat. 2001;17(5):403–11. doi: 10.1002/humu.1116 11317356

68. Tsukamoto K, Suzuki H, Harada D, Namba A, Abe S, Usami S-I. Distribution and frequencies of PDS (SLC26A4) mutations in Pendred syndrome and nonsyndromic hearing loss associated with enlarged vestibular aqueduct: a unique spectrum of mutations in Japanese. Eur J Hum Genet. 2003;11(12):916–22. doi: 10.1038/sj.ejhg.5201073 14508505

69. Yang T, Vidarsson H, Rodrigo-Blomqvist S, Rosengren SS, Enerback S, Smith RJH. Transcriptional control of SLC26A4 is involved in Pendred syndrome and nonsyndromic enlargement of vestibular aqueduct (DFNB4). Am J Hum Genet. 2007;80(6):1055–63. doi: 10.1086/518314 PubMed Central PMCID: PMC1867094. 17503324

70. Lazzereschi D, Nardi F, Turco A, Ottini L, D'Amico C, Mariani-Costantini R, et al. A complex pattern of mutations and abnormal splicing of Smad4 is present in thyroid tumours. Oncogene. 2005;24(34):5344–54. doi: 10.1038/sj.onc.1208603 15940269

71. Gebbia M, Ferrero GB, Pilia G, Bassi MT, Aylsworth A, Penman-Splitt M, et al. X-linked situs abnormalities result from mutations in ZIC3. Nat Genet. 1997;17(3):305–8. doi: 10.1038/ng1197-305 9354794

72. Ware SM, Peng J, Zhu L, Fernbach S, Colicos S, Casey B, et al. Identification and functional analysis of ZIC3 mutations in heterotaxy and related congenital heart defects. Am J Hum Genet. 2004;74(1):93–105. doi: 10.1086/380998 PubMed Central PMCID: PMC1181916. 14681828

73. Purandare SM, Ware SM, Kwan KM, Gebbia M, Bassi MT, Deng JM, et al. A complex syndrome of left-right axis, central nervous system and axial skeleton defects in Zic3 mutant mice. Development. 2002;129(9):2293–302. 11959836

74. Zhang G, Shi J, Zhu S, Lan Y, Xu L, Yuan H, et al. DiseaseEnhancer: a resource of human disease-associated enhancer catalog. Nucleic Acids Res. 2018;46(D1):D78–D84. doi: 10.1093/nar/gkx920 PubMed Central PMCID: PMC5753380. 29059320

75. Pollard KS, Hubisz MJ, Rosenbloom KR, Siepel A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 2010;20(1):110–21. doi: 10.1101/gr.097857.109 PubMed Central PMCID: PMC2798823. 19858363

76. McCarthy MI, Hirschhorn JN. Genome-wide association studies: potential next steps on a genetic journey. Hum Mol Genet. 2008;17(R2):R156–65. doi: 10.1093/hmg/ddn289 PubMed Central PMCID: PMC2782356. 18852205

77. Bamshad MJ, Ng SB, Bigham AW, Tabor HK, Emond MJ, Nickerson DA, et al. Exome sequencing as a tool for Mendelian disease gene discovery. Nat Rev Genet. 2011;12(11):745–55. Epub 2011/09/27. doi: 10.1038/nrg3031 21946919.

78. Chong JX, Buckingham KJ, Jhangiani SN, Boehm C, Sobreira N, Smith JD, et al. The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities. Am J Hum Genet. 2015;97(2):199–215. Epub 2015/07/09. doi: 10.1016/j.ajhg.2015.06.009 26166479; PubMed Central PMCID: PMC4573249.

79. Valente EM, Bhatia KP. Solving Mendelian Mysteries: The Non-coding Genome May Hold the Key. Cell. 2018;172(5):889–91. doi: 10.1016/j.cell.2018.02.022 29474915.

80. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203–9. Epub 2018/10/10. doi: 10.1038/s41586-018-0579-z 30305743.

81. Turnbull C, Scott RH, Thomas E, Jones L, Murugaesu N, Pretty FB, et al. The 100 000 Genomes Project: bringing whole genome sequencing to the NHS. BMJ. 2018;361:k1687. Epub 2018/04/24. doi: 10.1136/bmj.k1687 29691228.

82. Sarnowski C, Satizabal CL, DeCarli C, Pitsillides AN, Cupples LA, Vasan RS, et al. Whole genome sequence analyses of brain imaging measures in the Framingham Study. Neurology. 2018;90(3):e188–e96. Epub 2017/12/27. doi: 10.1212/WNL.0000000000004820 29282330; PubMed Central PMCID: PMC5772158.

83. He KY, Li X, Kelly TN, Liang J, Cade BE, Assimes TL, et al. Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data. Hum Genet. 2019;138(2):199–210. Epub 2019/01/22. doi: 10.1007/s00439-019-01975-0 30671673; PubMed Central PMCID: PMC6404531.

84. Perkins BA, Caskey CT, Brar P, Dec E, Karow DS, Kahn AM, et al. Precision medicine screening using whole-genome sequencing and advanced imaging to identify disease risk in adults. Proc Natl Acad Sci U S A. 2018;115(14):3686–91. Epub 2018/03/19. doi: 10.1073/pnas.1706096114 29555771; PubMed Central PMCID: PMC5889622.

85. Fu Y, Liu Z, Lou S, Bedford J, Mu XJ, Yip KY, et al. FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer. Genome Biol. 2014;15(10):480. doi: 10.1186/s13059-014-0480-5 PubMed Central PMCID: PMC4203974. 25273974

86. Khurana E, Fu Y, Colonna V, Mu XJ, Kang HM, Lappalainen T, et al. Integrative annotation of variants from 1092 humans: application to cancer genomics. Science. 2013;342(6154):1235587. doi: 10.1126/science.1235587 24092746

87. Backenroth D, He Z, Kiryluk K, Boeva V, Pethukova L, Khurana E, et al. FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications. Am J Hum Genet. 2018;102(5):920–42. doi: 10.1016/j.ajhg.2018.03.026 29727691; PubMed Central PMCID: PMC5986983.

88. 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. doi: 10.1038/ng.2892 PubMed Central PMCID: PMC3992975. 24487276

89. Rentzsch P, Witten D, Cooper GM, Shendure J, Kircher M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res. 2019;47(D1):D886–D94. doi: 10.1093/nar/gky1016 30371827; PubMed Central PMCID: PMC6323892.

90. Zhou J, Troyanskaya OG. Predicting effects of noncoding variants with deep learning-based sequence model. Nat Methods. 2015;12(10):931–4. Epub 2015/08/24. doi: 10.1038/nmeth.3547 26301843; PubMed Central PMCID: PMC4768299.

91. Visel A, Prabhakar S, Akiyama JA, Shoukry M, Lewis KD, Holt A, et al. Ultraconservation identifies a small subset of extremely constrained developmental enhancers. Nat Genet. 2008;40(2):158–60. doi: 10.1038/ng.2007.55 PubMed Central PMCID: PMC2647775. 18176564

92. Schep A. motifmatchr: Fast Motif Matching in R. 2018.

93. Hagberg A, Swart P, S Chult D. Exploring network structure, dynamics, and function using NetworkX. Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2008 2008. Report No.

94. Shyu RY, Huang SL, Jiang SY. Retinoic acid increases expression of the calcium-binding protein S100P in human gastric cancer cells. J Biomed Sci. 2003;10(3):313–9. doi: 10.1007/bf02256450 12711858.

95. Ge F, Wang C, Wang W, Wu B. S100P predicts prognosis and drug resistance in gastric cancer. Int J Biol Markers. 2013;28(4):e387–92. Epub 2013/12/17. doi: 10.5301/jbm.5000034 23722300.

96. Waisberg M, Cerqueira GC, Yager SB, Francischetti IM, Lu J, Gera N, et al. Plasmodium falciparum merozoite surface protein 1 blocks the proinflammatory protein S100P. Proc Natl Acad Sci U S A. 2012;109(14):5429–34. Epub 2012/03/19. doi: 10.1073/pnas.1202689109 22431641; PubMed Central PMCID: PMC3325673.

97. Reghunathan R, Jayapal M, Hsu LY, Chng HH, Tai D, Leung BP, et al. Expression profile of immune response genes in patients with Severe Acute Respiratory Syndrome. BMC Immunol. 2005;6:2. Epub 2005/01/18. doi: 10.1186/1471-2172-6-2 15655079; PubMed Central PMCID: PMC546205.

Článek vyšel v časopise

PLOS Genetics

2020 Číslo 4
Nejčtenější tento týden
Nejčtenější v tomto čísle
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.


Nemáte účet?  Registrujte se