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The Genetic and Mechanistic Basis for Variation in Gene Regulation


It is now well established that noncoding regulatory variants play a central role in the genetics of common diseases and in evolution. However, until recently, we have known little about the mechanisms by which most regulatory variants act. For instance, what types of functional elements in DNA, RNA, or proteins are most often affected by regulatory variants? Which stages of gene regulation are typically altered? How can we predict which variants are most likely to impact regulation in a given cell type? Recent studies, in many cases using quantitative trait loci (QTL)-mapping approaches in cell lines or tissue samples, have provided us with considerable insight into the properties of genetic loci that have regulatory roles. Such studies have uncovered novel biochemical regulatory interactions and led to the identification of previously unrecognized regulatory mechanisms. We have learned that genetic variation is often directly associated with variation in regulatory activities (namely, we can map regulatory QTLs, not just expression QTLs [eQTLs]), and we have taken the first steps towards understanding the causal order of regulatory events (for example, the role of pioneer transcription factors). Yet, in most cases, we still do not know how to interpret overlapping combinations of regulatory interactions, and we are still far from being able to predict how variation in regulatory mechanisms is propagated through a chain of interactions to eventually result in changes in gene expression profiles.


Vyšlo v časopise: The Genetic and Mechanistic Basis for Variation in Gene Regulation. PLoS Genet 11(1): e32767. doi:10.1371/journal.pgen.1004857
Kategorie: Review
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004857

Souhrn

It is now well established that noncoding regulatory variants play a central role in the genetics of common diseases and in evolution. However, until recently, we have known little about the mechanisms by which most regulatory variants act. For instance, what types of functional elements in DNA, RNA, or proteins are most often affected by regulatory variants? Which stages of gene regulation are typically altered? How can we predict which variants are most likely to impact regulation in a given cell type? Recent studies, in many cases using quantitative trait loci (QTL)-mapping approaches in cell lines or tissue samples, have provided us with considerable insight into the properties of genetic loci that have regulatory roles. Such studies have uncovered novel biochemical regulatory interactions and led to the identification of previously unrecognized regulatory mechanisms. We have learned that genetic variation is often directly associated with variation in regulatory activities (namely, we can map regulatory QTLs, not just expression QTLs [eQTLs]), and we have taken the first steps towards understanding the causal order of regulatory events (for example, the role of pioneer transcription factors). Yet, in most cases, we still do not know how to interpret overlapping combinations of regulatory interactions, and we are still far from being able to predict how variation in regulatory mechanisms is propagated through a chain of interactions to eventually result in changes in gene expression profiles.


Zdroje

1. WrayGA (2007) The evolutionary significance of cis-regulatory mutations. Nat Rev Genet 8: 206–216 Available: http://bejerano.stanford.edu/readings/public/

2. CarrollSB (2008) Evo-devo and an expanding evolutionary synthesis: a genetic theory of morphological evolution. Cell 134: 25–36 doi:10.1016/j.cell.2008.06.030

3. CooksonW, LiangL, AbecasisG, MoffattM, LathropM (2009) Mapping complex disease traits with global gene expression. Nat Rev Genet 10: 184–194 doi:10.1038/nrg2537

4. MontgomerySB, DermitzakisET (2011) From expression QTLs to personalized transcriptomics. Nat Rev Genet 12: 277–282 doi:10.1038/nrg2969

5. PickrellJK (2014) Joint analysis of functional genomic data and genome-wide association studies of 18 human traits. Am J Hum Genet 94: 559–573 doi:10.1016/j.ajhg.2014.03.004

6. KhaitovichP, HellmannI, EnardW, NowickK, LeinweberM, et al. (2005) Parallel patterns of evolution in the genomes and transcriptomes of humans and chimpanzees. Science 309: 1850–1854 doi:10.1126/science.1108296

7. GiladY, OshlackA, SmythGK, SpeedTP, WhiteKP (2006) Expression profiling in primates reveals a rapid evolution of human transcription factors. Nature 440: 242–245 doi:10.1038/nature04559

8. BremRB, YvertG, ClintonR, KruglyakL (2002) Genetic Dissection of Transcriptional Regulation in Budding Yeast. Science 296: 752–755.

9. SchadtEE, MonksSA, DrakeTA, LusisAJ, CheN, et al. (2003) Genetics of gene expression surveyed in maize, mouse and man. Nature 422: 297–302 doi:10.1038/nature01434

10. CheungVG, ConlinLK, WeberTM, ArcaroM, JenK-Y, et al. (2003) Natural variation in human gene expression assessed in lymphoblastoid cells. Nat Genet 33: 422–425 doi:10.1038/ng1094

11. VeyrierasJ-B, KudaravalliS, KimSY, DermitzakisET, GiladY, et al. (2008) High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet 4: e1000214 doi:10.1371/journal.pgen.1000214

12. StrangerBE, NicaAC, ForrestMS, DimasA, BirdCP, et al. (2007) Population genomics of human gene expression. Nat Genet 39: 1217–1224 doi:10.1038/ng2142

13. GöringHHH, CurranJE, JohnsonMP, DyerTD, CharlesworthJ, et al. (2007) Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet 39: 1208–1216 doi:10.1038/ng2119

14. RomeroIG, RuvinskyI, GiladY (2012) Comparative studies of gene expression and the evolution of gene regulation. Nat Rev Genet 13: 505–516 doi:10.1038/nrg3229

15. GaffneyDJ, VeyrierasJ-B, DegnerJF, RogerP-R, PaiAA, et al. (2012) Dissecting the regulatory architecture of gene expression QTLs. Genome Biology 13: R7 doi:10.1186/gb-2012-13-1-r7

16. KasowskiM, Kyriazopoulou-PanagiotopoulouS, GrubertF, ZauggJB, KundajeA, et al. (2013) Extensive variation in chromatin states across humans. Science 342: 750–752 doi:10.1126/science.1242510

17. KasowskiM, GrubertF, HeffelfingerC, HariharanM, AsabereA, et al. (2010) Variation in transcription factor binding among humans. Science 328: 232–235 doi:10.1126/science.1183621

18. SchmidtD, WilsonMD, BallesterB, SchwaliePC, BrownGD, et al. (2010) Five-vertebrate ChIP-seq reveals the evolutionary dynamics of transcription factor binding. Science 328: 1036–1040 doi:10.1126/science.1186176

19. DegnerJF, PaiAA, Pique-RegiR, VeyrierasJ-B, GaffneyDJ, et al. (2012) DNase I sensitivity QTLs are a major determinant of human expression variation. Nature 482: 390–394 doi:10.1038/nature10808

20. StefflovaK, ThybertD, WilsonMD, StreeterI, AleksicJ, et al. (2013) Cooperativity and rapid evolution of cobound transcription factors in closely related mammals. Cell 154: 530–540 doi:10.1016/j.cell.2013.07.007

21. BellJT, PaiAA, PickrellJK, GaffneyDJ, Pique-RegiR, et al. (2011) DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biology 12: R10 doi:10.1186/gb-2011-12-1-r10

22. CainCE, BlekhmanR, MarioniJC, GiladY (2011) Gene expression differences among primates are associated with changes in a histone epigenetic modification. Genetics 187: 1225–1234 doi:10.1534/genetics.110.126177

23. PaiAA, BellJT, MarioniJC, PritchardJK, GiladY (2011) A genome-wide study of DNA methylation patterns and gene expression levels in multiple human and chimpanzee tissues. PLoS Genet 7: e1001316 doi:10.1371/journal.pgen.1001316

24. KilpinenH, WaszakSM, GschwindAR, RaghavSK, WitwickiRM, et al. (2013) Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription. Science 342: 744–747 doi:10.1126/science.1242463

25. McVickerG, van de GeijnB, DegnerJF, CainCE, BanovichNE, et al. (2013) Identification of genetic variants that affect histone modifications in human cells. Science 342: 747–749 doi:10.1126/science.1242429

26. PickrellJK, MarioniJC, PaiAA, DegnerJF, EngelhardtBE, et al. (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464: 768–772 doi:10.1038/nature08872

27. Barbosa-MoraisNL, IrimiaM, PanQ, XiongHY, GueroussovS, et al. (2012) The Evolutionary Landscape of Alternative Splicing in Vertebrate Species. Science 338: 1587–1593 doi:10.1126/science.1230612

28. MerkinJ, RussellC, ChenP, BurgeCB (2012) Evolutionary Dynamics of Gene and Isoform Regulation in Mammalian Tissues. Science 338: 1593–1599 doi:10.1126/science.1228186

29. YoonOK, HsuTY, ImJH, BremRB (2012) Genetics and regulatory impact of alternative polyadenylation in human B-lymphoblastoid cells. PLoS Genet 8: e1002882 doi:10.1371/journal.pgen.1002882

30. PaiAA, CainCE, Mizrahi-ManO, De LeonS, LewellenN, et al. (2012) The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels. PLoS Genet 8: e1003000 doi:10.1371/journal.pgen.1003000

31. WittkoppPJ, KalayG (2011) Cis-regulatory elements: molecular mechanisms and evolutionary processes underlying divergence. Nat Rev Genet 13: 59–69 doi:10.1038/nrg3095

32. MajewskiJ, PastinenT (2011) The study of eQTL variations by RNA-seq: from SNPs to phenotypes. Trends Genet 27: 72–79 doi:10.1016/j.tig.2010.10.006

33. MontgomerySB, SammethM, Gutierrez ArcelusM, LachRP, IngleC, et al. (2010) Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464: 773–777 doi:10.1038/nature08903

34. LappalainenT, SammethM, FriedländerMR, 't HoenPAC, MonlongJ, et al. (2013) Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501: 506–511 doi:10.1038/nature12531

35. WestraH-J, PetersMJ, EskoT, YaghootkarH, SchurmannC, et al. (2013) Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat Genet 45: 1238–1243 doi:10.1038/ng.2756

36. BattleA, MostafaviS, ZhuX, PotashJB, WeissmanMM, et al. (2013) Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Research 24: 14–24 doi:10.1101/gr.155192.113

37. PriceAL, HelgasonA, ThorleifssonG, McCarrollSA, KongA, et al. (2011) Single-Tissue and Cross-Tissue Heritability of Gene Expression Via Identity-by-Descent in Related or Unrelated Individuals. PLoS Genet 7: e1001317 doi:10.1371/journal.pgen.1001317

38. PopadinK, Gutierrez ArcelusM, DermitzakisET, AntonarakisSE (2013) Genetic and epigenetic regulation of human lincRNA gene expression. Am J Hum Genet 93: 1015–1026 doi:10.1016/j.ajhg.2013.10.022

39. LuJ, ClarkAG (2012) Impact of microRNA regulation on variation in human gene expression. Genome Research 22: 1243–1254 doi:10.1101/gr.132514.111

40. GibbsJR, van der BrugMP, HernandezDG, TraynorBJ, NallsMA, et al. (2010) Abundant quantitative trait Loci exist for DNA methylation and gene expression in human brain. PLoS Genet 6: e1000952 doi:10.1371/journal.pgen.1000952

41. ZhangD, ChengL, BadnerJA, ChenC, ChenQ, et al. (2010) Genetic control of individual differences in gene-specific methylation in human brain. Am J Hum Genet 86: 411–419 doi:10.1016/j.ajhg.2010.02.005

42. GamazonER, BadnerJA, ChengL, ZhangC, ZhangD, et al. (2012) Enrichment of cis-regulatory gene expression SNPs and methylation quantitative trait loci among bipolar disorder susceptibility variants. Mol Psychiatry 18: 340–346 doi:10.1038/mp.2011.174

43. McdaniellR, LeeBK, SongL, LiuZ, BoyleAP, et al. (2010) Heritable Individual-Specific and Allele-Specific Chromatin Signatures in Humans. Science 328: 235–239 doi:10.1126/science.1184655

44. ErnstJ, KellisM (2012) ChromHMM: automating chromatin-state discovery and characterization. Nat Meth 9: 215–216 doi:10.1038/nmeth.1906

45. ErnstJ, KellisM (2010) Discovery and characterization of chromatin states for systematic annotation of the human genome. Nature Biotechnology 28: 817–838 doi:10.1038/nbt.1662

46. WhiteMA, MyersCA, CorboJC, CohenBA (2013) Massively parallel in vivo enhancer assay reveals that highly local features determine the cis-regulatory function of ChIP-seq peaks. Proc Natl Acad Sci USA 110: 11952–11957 doi:10.1073/pnas.1307449110

47. LalondeE, HaKCH, WangZ, BemmoA, KleinmanCL, et al. (2011) RNA sequencing reveals the role of splicing polymorphisms in regulating human gene expression. Genome Research 21: 545–554 doi:10.1101/gr.111211.110

48. WangL, ObergAL, AsmannYW, SicotteH, McDonnellSK, et al. (2009) Genome-wide transcriptional profiling reveals microRNA-correlated genes and biological processes in human lymphoblastoid cell lines. PLoS One 4: e5878 doi:10.1371/journal.pone.0005878

49. Dori-BachashM, ShemaE, TiroshI (2011) Coupled Evolution of Transcription and mRNA Degradation. PLoS Biol 9: e1001106 doi:10.1371/journal.pbio.1001106.g006

50. WuL, CandilleSI, ChoiY, XieD, JiangL, et al. (2013) Variation and genetic control of protein abundance in humans. Nature 499: 79–82 doi:10.1038/nature12223

51. JohanssonÅ, EnrothS, PalmbladM, DeelderAM, BergquistJ, et al. (2013) Identification of genetic variants influencing the human plasma proteome. Proc Natl Acad Sci USA 110: 4673–4678 doi:10.1073/pnas.1217238110

52. AlbertFW, TreuschS, ShockleyAH, BloomJS, KruglyakL (2014) Genetics of single-cell protein abundance variation in large yeast populations. Nature 506: 494–497 doi:10.1038/nature12904

53. KhanZ, FordMJ, CusanovichDA, MitranoA, PritchardJK, et al. (2013) Primate transcript and protein expression levels evolve under compensatory selection pressures. Science 342: 1100–1104 doi:10.1126/science.1242379

54. ArbizaL, GronauI, AksoyBA, HubiszMJ, GulkoB, et al. (2013) Genome-wide inference of natural selection on human transcription factor binding sites. Nat Genet 45: 723–729 doi:10.1038/ng.2658

55. CusanovichDA, PavlovicB, PritchardJK, GiladY (2014) The functional consequences of variation in transcription factor binding. PLoS Genet 10: e1004226 doi:10.1371/journal.pgen.1004226

56. HeinzS, RomanoskiCE, BennerC, AllisonKA, KaikkonenMU, et al. (2013) Effect of natural genetic variation on enhancer selection and function. Nature 503: 487–492 doi:10.1038/nature12615

57. LamEWF, BrosensJJ, GomesAR, KooC-Y (2013) Forkhead box proteins: tuning forks for transcriptional harmony. Nature Reviews Cancer 13: 482–495 doi:doi:10.1038/nrc3539

58. ZaretKS, CarrollJS (2011) Pioneer transcription factors: establishing competence for gene expression. Genes & Development 25: 2227–2241.

59. StruhlK, SegalE (2013) Determinants of nucleosome positioning. Nature Structural & Molecular Biology 20: 267–273 doi:10.1038/nsmb.2506

60. MarchettoMCN, NarvaizaI, DenliAM, BennerC, LazzariniTA, et al. (2013) Differential L1 regulation in pluripotent stem cells of humans and apes. Nature 503: 525–529 doi:10.1038/nature12686

61. PfefferleLW, WrayGA (2013) Insights from a Chimpanzee Adipose Stromal Cell Population: Opportunities for Adult Stem Cells to Expand Primate Functional Genomics. Genome Biology and Evolution 5: 1995–2005.

62. LeeJH, ParkIH, GaoY, LiJB, LiZ, et al. (2009) A Robust Approach to Identifying Tissue-Specific Gene Expression Regulatory Variants Using Personalized Human Induced Pluripotent Stem Cells. PLoS Genet 5: e1000718.

63. SchreiberJ, JennerRG, MurrayHL, GerberGK, GiffordDK, et al. (2006) Coordinated binding of NF-kappaB family members in the response of human cells to lipopolysaccharide. Proc Natl Acad Sci USA 103: 5899–5904 doi:10.1073/pnas.0510996103

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