#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Genetic Dissection of the Female Head Transcriptome Reveals Widespread Allelic Heterogeneity


For traits with complex genetic inheritance it has generally proven very difficult to identify the majority of the specific causative variants involved. A range of hypotheses have been put forward to explain this so-called “missing heritability”. One idea—allelic heterogeneity, where genes each harbor multiple different causative variants—has received little attention, because it is difficult to detect with most genetic mapping designs. Here we make use of a panel of Drosophila melanogaster lines derived from multiple founders, allowing us to directly test for the presence of multiple alleles at a large set of genetic loci influencing gene expression. We find that the vast majority of loci harbor more than two functional alleles, demonstrating extensive allelic heterogeneity at the level of gene expression and suggesting that such heterogeneity is an important factor determining the genetic basis of complex trait variation in general.


Vyšlo v časopise: Genetic Dissection of the Female Head Transcriptome Reveals Widespread Allelic Heterogeneity. PLoS Genet 10(5): e32767. doi:10.1371/journal.pgen.1004322
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004322

Souhrn

For traits with complex genetic inheritance it has generally proven very difficult to identify the majority of the specific causative variants involved. A range of hypotheses have been put forward to explain this so-called “missing heritability”. One idea—allelic heterogeneity, where genes each harbor multiple different causative variants—has received little attention, because it is difficult to detect with most genetic mapping designs. Here we make use of a panel of Drosophila melanogaster lines derived from multiple founders, allowing us to directly test for the presence of multiple alleles at a large set of genetic loci influencing gene expression. We find that the vast majority of loci harbor more than two functional alleles, demonstrating extensive allelic heterogeneity at the level of gene expression and suggesting that such heterogeneity is an important factor determining the genetic basis of complex trait variation in general.


Zdroje

1. ZukO, HechterE, SunyaevSR, LanderES (2012) The mystery of missing heritability: Genetic interactions create phantom heritability. Proceedings of the National Academy of Sciences 109: 1193–1198 doi:10.1073/pnas.1119675109

2. Lango AllenH, EstradaK, LettreG, BerndtSI, WeedonMN, et al. (2010) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467: 832–838 doi:10.1038/nature09410

3. YangJ, BenyaminB, McevoyBP, GordonS, HendersAK, et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42: 565–569 doi:10.1038/ng.608

4. RockmanMV (2012) The QTN program and the alleles that matter for evolution: all that's gold does not glitter. Evolution 66: 1–17 doi:10.1111/j.1558-5646.2011.01486.x

5. PritchardJ (2001) Are rare variants responsible for susceptibility to complex diseases? Am J Hum Genet 69: 124–137.

6. BansalV, LibigerO, TorkamaniA, SchorkNJ (2010) Statistical analysis strategies for association studies involving rare variants. Nat Rev Genet 11: 773–785 doi:10.1038/nrg2867

7. ThorntonKR, ForanAJ, LongAD (2013) Properties and Modeling of GWAS when Complex Disease Risk Is Due to Non-Complementing, Deleterious Mutations in Genes of Large Effect. PLoS Genet 9: e1003258 doi:10.1371/journal.pgen.1003258.s011

8. ChurchillGA, AireyDC, AllayeeH, AngelJM, AttieAD, et al. (2004) The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nat Genet 36: 1133–1137 doi:10.1038/ng1104-1133

9. AylorDL, ValdarW, Foulds-MathesW, BuusRJ, VerdugoRA, et al. (2011) Genetic analysis of complex traits in the emerging Collaborative Cross. Genome Res 21: 1213–1222 doi:10.1101/gr.111310.110

10. PhilipVM, SokoloffG, Ackert-BicknellCL, StrizM, BranstetterL, et al. (2011) Genetic analysis in the Collaborative Cross breeding population. Genome Res 21: 1223–1238 doi:10.1101/gr.113886.110

11. KoverPX, ValdarW, TrakaloJ, ScarcelliN, EhrenreichIM, et al. (2009) A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana. PLoS Genet 5: e1000551 doi:10.1371/journal.pgen.1000551

12. HuangX, PauloM-J, BoerM, EffgenS, KeizerP, et al. (2011) Analysis of natural allelic variation in Arabidopsis using a multiparent recombinant inbred line population. P Natl Acad Sci Usa 108: 4488–4493 doi:10.1073/pnas.1100465108

13. YuJ, HollandJB, McMullenMD, BucklerES (2008) Genetic design and statistical power of nested association mapping in maize. Genetics 178: 539–551 doi:10.1534/genetics.107.074245

14. BucklerES, HollandJB, BradburyPJ, AcharyaCB, BrownPJ, et al. (2009) The Genetic Architecture of Maize Flowering Time. Science 325: 714–718 doi:10.1126/science.1174276

15. McMullenMD, KresovichS, Sanchez VilledaH, BradburyP, LiH, et al. (2009) Genetic Properties of the Maize Nested Association Mapping Population. Science 325: 737–740 doi:10.1126/science.1174320

16. LiH, BradburyP, ErsozE, BucklerES, WangJ (2011) Joint QTL Linkage Mapping for Multiple-Cross Mating Design Sharing One Common Parent. PLOS ONE 6: e17573 doi:10.1371/journal.pone.0017573

17. KingEG, MerkesCM, McNeilCL, HooferSR, SenS, et al. (2012) Genetic dissection of a model complex trait using the Drosophila Synthetic Population Resource. Genome Res 22: 1558–1566 doi:10.1101/gr.134031.111

18. KingEG, MacdonaldSJ, LongAD (2012) Properties and power of the Drosophila Synthetic Population Resource for the routine dissection of complex traits. Genetics 191: 935–949 doi:10.1534/genetics.112.138537

19. Mackay TFC, Richards S, Gibbs RA (2008) Proposal to Sequence a Drosophila Genetic Reference Panel: A Community Resource for the Study of Genotypic and Phenotypic Variation: 1–32. Available at https://www.genome.gov/Pages/Research/Sequencing/SeqProposals/DrosophilaSeq.pdf

20. MackayTFC, RichardsS, StoneEA, BarbadillaA, AyrolesJF, et al. (2012) The Drosophila melanogaster Genetic Reference Panel. Nature 482: 173–178 doi:10.1038/nature10811

21. BloomJS, EhrenreichIM, LooWT, LiteT-LV, KruglyakL (2013) Finding the sources of missing heritability in a yeast cross. Nature 494: 234–237 doi:10.1038/nature11867

22. BaudA, HermsenR, GuryevV, StridhP, GrahamD, et al. (2013) Combined sequence-based and genetic mapping analysis of complex traits in outbred rats. Nat Genet 45: 767–775 doi:10.1038/ng.2644

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

24. GibsonG, WeirB (2005) The quantitative genetics of transcription. Trends Genet 21: 616–623 doi:10.1016/j.tig.2005.08.010

25. SunG, SchliekelmanP (2011) A Genetical Genomics Approach to Genome Scans Increases Power for QTL Mapping. Genetics 187: 939–953 doi:10.1534/genetics.110.123968

26. GiladY, RifkinSA, PritchardJK (2008) Revealing the architecture of gene regulation: the promise of eQTL studies. Trends Genet 24: 408–415 doi:10.1016/j.tig.2008.06.001

27. EhrenreichIM, GerkeJP, KruglyakL (2010) Genetic Dissection of Complex Traits in Yeast: Insights from Studies of Gene Expression and Other Phenotypes in the BYxRM Cross. Cold Spring Harbor Symposia on Quantitative Biology 74: 145–153 doi:10.1101/sqb.2009.74.013

28. 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.s023

29. GaffneyDJ, VeyrierasJ-B, DegnerJF, Pique-RegiR, PaiAA, et al. (2012) Dissecting the regulatory architecture of gene expression QTLs. Genome Biol 13: R7 doi:10.1186/gb-2012-13-1-r7

30. 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

31. LappalainenT, SammethM, FriedländerMR, HoenPACT, MonlongJ, et al. (2013) Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501: 506–511 doi:10.1038/nature12531

32. HuangG-J, ShifmanS, ValdarW, JohannessonM, YalcinB, et al. (2009) High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues. Genome Res 19: 1133–1140 doi:10.1101/gr.088120.108

33. YangJ, FerreiraT, MorrisAP, MedlandSE, MaddenPAF, et al. (2012) Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies addtional variants influencing comlex traits. Nat Genet 44: 369–375 doi:10.1038/ng.2213

34. XuS (2003) Theoretical basis of the Beavis effect. Genetics 165: 2259–2268.

35. EdgarR, DomrachevM, LashAE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Research 30: 207–210.

36. BoyleEI, WengS, GollubJ, JinH, BOTSTEIND, et al. (2004) GO::TermFinder–open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes. Bioinformatics 20: 3710–3715 doi:10.1093/bioinformatics/bth456

37. RobinsonSW, HerzykP, DowJAT, LeaderDP (2012) FlyAtlas: database of gene expression in the tissues of Drosophila melanogaster. Nucleic Acids Research 41: D744–D750 doi:10.1093/nar/gks1141

38. KohK, EvansJM, HendricksJC, SehgalA (2006) A Drosophila model for age-associated changes in sleep:wake cycles. P Natl Acad Sci Usa 103: 13843–13847 doi:10.1073/pnas.0605903103

39. MarygoldSJ, LeylandPC, SealRL, GoodmanJL, ThurmondJ, et al. (2012) FlyBase: improvements to the bibliography. Nucleic Acids Research 41: D751–D757 doi:10.1093/nar/gks1024

40. ZinkeI, SchützCS, KatzenbergerJD, BauerM, PankratzMJ (2002) Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response. EMBO J 21: 6162–6173.

41. VargheseJ, LimSF, CohenSM (2010) Drosophila miR-14 regulates insulin production and metabolism through its target, sugarbabe. Genes & Development 24: 2748–2753 doi:10.1101/gad.1995910

42. ZhangX, CalAJ, BorevitzJO (2011) Genetic architecture of regulatory variation in Arabidopsis thaliana. Genome Res 21: 725–733 doi:10.1101/gr.115337.110

43. KangHM, YeC, EskinE (2008) Accurate Discovery of Expression Quantitative Trait Loci Under Confounding From Spurious and Genuine Regulatory Hotspots. Genetics 180: 1909–1925 doi:10.1534/genetics.108.094201

44. SmithEN, KruglyakL (2008) Gene–Environment Interaction in Yeast Gene Expression. PLoS Biol 6: e83 doi:10.1371/journal.pbio.0060083.st004

45. LeekJT, StoreyJD (2007) Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet 3: 1724–1735 doi:10.1371/journal.pgen.0030161

46. 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

47. GruberJD, LongAD (2008) Cis-regulatory Variation Is Typically Polyallelic in Drosophila. Genetics 181: 661–670 Available: http://www.genetics.org/cgi/doi/10.1534/genetics.108.098459.

48. PowellJE, HendersAK, McRaeAF, KimJ, HemaniG, et al. (2013) Congruence of Additive and Non-Additive Effects on Gene Expression Estimated from Pedigree and SNP Data. PLoS Genet 9: e1003502 doi:10.1371/journal.pgen.1003502.s016

49. NuzhdinSV, PasyukovaE, DildaC, ZengZ, MackayTFC (1997) Sex-specific quantitative trait loci affecting longevity in Drosophila melanogaster. P Natl Acad Sci Usa 94: 9734–9739.

50. KislukhinG, KingEG, WaltersKN, MacdonaldSJ, LongAD (2013) The Genetic Architecture of Methotrexate Toxicity Is Similar in Drosophila melanogaster and Humans. G3 (Bethesda) 3: 1301–1310 doi:10.1534/g3.113.006619

51. McClellanJ, KingM-C (2010) Genetic Heterogeneity in Human Disease. Cell 141: 210–217 doi:10.1016/j.cell.2010.03.032

52. KleinRJ (2005) Complement Factor H Polymorphism in Age-Related Macular Degeneration. Science 308: 385–389 doi:10.1126/science.1109557

53. HughesAE, OrrN, EsfandiaryH, Diaz-TorresM, GoodshipT, et al. (2006) A common CFH haplotype, with deletion of CFHR1 and CFHR3, is associated with lower risk of age-related macular degeneration. Nat Genet 38: 1173–1177 doi:10.1038/ng1890

54. LiM, Atmaca-SonmezP, OthmanM, BranhamKEH, KhannaR, et al. (2006) CFH haplotypes without the Y402H coding variant show strong association with susceptibility to age-related macular degeneration. Nat Genet 38: 1049–1054 doi:10.1038/ng1871

55. MallerJ, GeorgeS, PurcellS, FagernessJ, AltshulerD, et al. (2006) Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration. Nat Genet 38: 1055–1059 doi:10.1038/ng1873

56. SwaroopA, BranhamKE, ChenW, AbecasisG (2007) Genetic susceptibility to age-related macular degeneration: a paradigm for dissecting complex disease traits. Human Molecular Genetics 16: R174–R182 doi:10.1093/hmg/ddm212

57. R Core Team (2013) R: a language and environment for statistical computing. Available: http://www.R-project.org/.

58. BolstadBM, IrizarryRA, AstrandM, SpeedTP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19: 185–193.

59. IrizarryRA, BolstadBM, CollinF, CopeLM, HobbsB, et al. (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Research 31: e15.

60. IrizarryRA, HobbsB, CollinF, Beazer-BarclayYD, AntonellisKJ, et al. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4: 249–264 doi:10.1093/biostatistics/4.2.249

61. CarvalhoBS, IrizarryRA (2010) A framework for oligonucleotide microarray preprocessing. Bioinformatics 26: 2363–2367 doi:10.1093/bioinformatics/btq431

62. AltschulSF, GishW, MillerW, MyersEW, LipmanDJ (1990) Basic local alignment search tool. J Mol Biol 215: 403–410 doi:10.1016/S0022-2836(05)80360-2

63. CamachoC, CoulourisG, AvagyanV, MaN, PapadopoulosJ, et al. (2009) BLAST+: architecture and applications. BMC Bioinformatics 10: 421 doi:10.1186/1471-2105-10-421

64. AlbertsR, TerpstraP, LiY, BreitlingR, NapJ-P, et al. (2007) Sequence polymorphisms cause many false cis eQTLs. PLOS ONE 2: e622 doi:10.1371/journal.pone.0000622

65. BenovoyD, KwanT, MajewskiJ (2008) Effect of polymorphisms within probe-target sequences on olignonucleotide microarray experiments. Nucleic Acids Research 36: 4417–4423 doi:10.1093/nar/gkn409

66. ChenL, PageGP, MehtaT, FengR, CuiX (2009) Single nucleotide polymorphisms affect both cis- and trans-eQTLs. Genomics 93: 501–508 doi:10.1016/j.ygeno.2009.01.011

67. CiobanuDC, LuL, MozhuiK, WangX, JagalurM, et al. (2010) Detection, validation, and downstream analysis of allelic variation in gene expression. Genetics 184: 119–128 doi:10.1534/genetics.109.107474

68. RamasamyA, TrabzuniD, GibbsJR, DillmanA, HernandezDG, et al. (2013) Resolving the polymorphism-in-probe problem is critical for correct interpretation of expression QTL studies. Nucleic Acids Research 41: e88 doi:10.1093/nar/gkt069

69. LiH, DurbinR (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25: 1754–1760 doi:10.1093/bioinformatics/btp324

70. LiH, HandsakerB, WysokerA, FennellT, RuanJ, et al. (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078–2079 doi:10.1093/bioinformatics/btp352

71. AulchenkoYS, de KoningD-J, HaleyC (2007) Genomewide rapid association using mixed model and regression: A fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics 177: 577–585 doi:10.1534/genetics.107.075614

72. ChurchillGA, DoergeRW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138: 963–971.

73. ManichaikulA, DupuisJ, SenS, BromanKW (2006) Poor performance of bootstrap confidence intervals for the location of a quantitative trait locus. Genetics 174: 481–489 Available: http://www.genetics.org/cgi/doi/10.1534/genetics.106.061549.

74. Broman KW, Sen S (2009) A Guide to QTL Mapping with R/qtl. Springer New York.

75. LyckegaardEM, ClarkAG (1989) Ribosomal DNA and Stellate gene copy number variation on the Y chromosome of Drosophila melanogaster. P Natl Acad Sci Usa 86: 1944–1948.

76. YalcinB (2005) Using Progenitor Strain Information to Identify Quantitative Trait Nucleotides in Outbred Mice. Genetics 171: 673–681 doi:10.1534/genetics.104.028902

Štítky
Genetika Reprodukčná medicína

Článok vyšiel v časopise

PLOS Genetics


2014 Číslo 5
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Získaná hemofilie - Povědomí o nemoci a její diagnostika
nový kurz

Eozinofilní granulomatóza s polyangiitidou
Autori: doc. MUDr. Martina Doubková, Ph.D.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#