#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Evidence for Widespread Positive and Negative Selection in Coding and Conserved Noncoding Regions of


Selection affects patterns of genomic variation, but it is unclear how much the effects of selection vary across plant genomes, particularly in noncoding regions. To determine the strength and extent of selective signatures across the genome, we sequenced and analyzed genomes from 13 Capsella grandiflora individuals. Because C. grandiflora has experienced a large, stable effective population size, we expect that selection signatures will not be overly distorted by demographic effects. Our analysis shows that positive and negative selection acting on new mutations have broadly shaped patterns of genomic diversity in coding regions but not in most noncoding regions. However, when we focus only on noncoding regions that show evidence of constraint across species, we see evidence for strong positive and negative selection. In addition, we find that genes with high expression experience stronger negative selection than genes with low expression, but the extent of positive selection appears to be equivalent across expression categories.


Vyšlo v časopise: Evidence for Widespread Positive and Negative Selection in Coding and Conserved Noncoding Regions of. PLoS Genet 10(9): e32767. doi:10.1371/journal.pgen.1004622
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004622

Souhrn

Selection affects patterns of genomic variation, but it is unclear how much the effects of selection vary across plant genomes, particularly in noncoding regions. To determine the strength and extent of selective signatures across the genome, we sequenced and analyzed genomes from 13 Capsella grandiflora individuals. Because C. grandiflora has experienced a large, stable effective population size, we expect that selection signatures will not be overly distorted by demographic effects. Our analysis shows that positive and negative selection acting on new mutations have broadly shaped patterns of genomic diversity in coding regions but not in most noncoding regions. However, when we focus only on noncoding regions that show evidence of constraint across species, we see evidence for strong positive and negative selection. In addition, we find that genes with high expression experience stronger negative selection than genes with low expression, but the extent of positive selection appears to be equivalent across expression categories.


Zdroje

1. KeightleyPD, Eyre-WalkerA (2010) What can we learn about the distribution of fitness effects of new mutations from DNA sequence data? Philos Trans R Soc Lond B Biol Sci 365: 1187–1193 doi:10.1098/rstb.2009.0266

2. AndolfattoP (2005) Adaptive evolution of non-coding DNA in Drosophila. Nature 437: 1149–1152 doi:10.1038/nature04107

3. TorgersonDG, BoykoAR, HernandezRD, IndapA, HuX, et al. (2009) Evolutionary processes acting on candidate cis-regulatory regions in humans inferred from patterns of polymorphism and divergence. PLoS Genet 5: e1000592 doi:10.1371/journal.pgen.1000592

4. Lindblad-TohK, GarberM, ZukO, LinMF, ParkerBJ, et al. (2011) A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478: 476–482 doi:10.1038/nature10530

5. 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

6. HoughJ, WilliamsonRJ, WrightSI (2013) Patterns of selection in plant genomes. Annu Rev Ecol Evol Syst 44: 3.1–3.19 doi:10.1146/annurev-ecolsys-110512-135851

7. Zhen Y, Andolfatto P (2012) Methods to detect selection on noncoding DNA. Methods in Molecular Biology. Totowa, NJ: Humana Press, Vol. 856. pp. 141–159. doi:10.1007/978-1-61779-585-5_6.

8. HalliganDL, KousathanasA, NessRW, HarrB, EőryL, et al. (2013) Contributions of protein-coding and regulatory change to adaptive molecular evolution in murid rodents. PLoS Genet 9: e1003995 doi:10.1371/journal.pgen.1003995

9. WrayGA (2007) The evolutionary significance of cis-regulatory mutations. Nat Rev Genet 8: 206–216 doi:10.1038/nrg2063

10. CarrollSB (2005) Evolution at two levels: on genes and form. PLoS Biol 3: e245 doi:10.1371/journal.pbio.0030245

11. HoekstraHE, CoyneJA (2007) The locus of evolution: evo devo and the genetics of adaptation. Evolution 61: 995–1016 doi:10.1111/j.1558-5646.2007.00105.x

12. KeightleyPD, GaffneyDJ (2003) Functional constraints and frequency of deleterious mutations in noncoding DNA of rodents. Proc Natl Acad Sci USA 100: 13402–13406 doi:10.1073/pnas.2233252100

13. LocktonS, GautBS (2005) Plant conserved non-coding sequences and paralogue evolution. Trends Genet 21: 60–65 doi:10.1016/j.tig.2004.11.013

14. HaudryA, PlattsAE, VelloE, HoenDR, LeclercqM, et al. (2013) An atlas of over 90,000 conserved noncoding sequences provides insight into crucifer regulatory regions. Nat Genet 45: 891–898 doi:10.1038/ng.2684

15. PálC, PappB, HurstLD (2001) Highly expressed genes in yeast evolve slowly. Genetics 158: 927–931.

16. SubramanianS, KumarS (2004) Gene expression intensity shapes evolutionary rates of the proteins encoded by the vertebrate genome. Genetics 168: 373–381 doi:10.1534/genetics.104.028944

17. DrummondDA, RavalA, WilkeCO (2006) A single determinant dominates the rate of yeast protein evolution. Mol Biol Evol 23: 327–337 doi:10.1093/molbev/msj038

18. YangL, GautBS (2011) Factors that contribute to variation in evolutionary rate among Arabidopsis genes. Mol Biol Evol 28: 2359–2369 doi:10.1093/molbev/msr058

19. SlotteT, BataillonT, HansenTT, St OngeK, WrightSI, et al. (2011) Genomic determinants of protein evolution and polymorphism in Arabidopsis. Genome Biol Evol 3: 1210–1219 doi:10.1093/gbe/evr094

20. PaapeT, BataillonT, ZhouP, J Y KonoT, BriskineR, et al. (2013) Selection, genome-wide fitness effects and evolutionary rates in the model legume Medicago truncatula. Mol Ecol 22: 3525–3538 doi:10.1111/mec.12329

21. RenautS, GrassaCJ, MoyersBT, KaneNC, RiesebergLH (2012) The population genomics of sunflowers and genomic determinants of protein evolution revealed by RNAseq. Biology (Basel) 1: 575–596 doi:10.3390/biology1030575

22. GautB, YangL, TakunoS, EguiarteLE (2011) The patterns and causes of variation in plant nucleotide substitution rates. Annu Rev Ecol Evol Syst 42: 245–266 doi:10.1146/annurev-ecolsys-102710-145119

23. ParkC, ChenX, YangJ-R, ZhangJ (2013) Differential requirements for mRNA folding partially explain why highly expressed proteins evolve slowly. Proc Natl Acad Sci USA 110: E678–E686 doi:10.1073/pnas.1218066110

24. YangJ-R, LiaoB-Y, ZhuangS-M, ZhangJ (2012) Protein misinteraction avoidance causes highly expressed proteins to evolve slowly. Proc Natl Acad Sci USA 109: E831–E840 doi:10.1073/pnas.1117408109

25. DrummondDA, WilkeCO (2008) Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell 134: 341–352 doi:10.1016/j.cell.2008.05.042

26. GossmannTI, SongB-H, WindsorAJ, Mitchell-OldsT, DixonCJ, et al. (2010) Genome wide analyses reveal little evidence for adaptive evolution in many plant species. Mol Biol Evol 27: 1822–1832.

27. St OngeKR, KällmanT, SlotteT, LascouxM, PalméAE (2011) Contrasting demographic history and population structure in Capsella rubella and Capsella grandiflora, two closely related species with different mating systems. Mol Ecol 20: 3306–3320 doi:10.1111/j.1365-294X.2011.05189.x

28. Eyre-WalkerA, KeightleyPD (2009) Estimating the rate of adaptive molecular evolution in the presence of slightly deleterious mutations and population size change. Mol Biol Evol 26: 2097–2108 doi:10.1093/molbev/msp119

29. SellaG, PetrovDA, PrzeworskiM, AndolfattoP (2009) Pervasive natural selection in the Drosophila genome? PLoS Genet 5: e1000495 doi:10.1371/journal.pgen.1000495

30. SlotteT, HazzouriKM, AgrenJA, KoenigD, MaumusF, et al. (2013) The Capsella rubella genome and the genomic consequences of rapid mating system evolution. Nat Genet 45: 831–835 doi:10.1038/ng.2669

31. McKennaA, HannaM, BanksE, SivachenkoA, CibulskisK, et al. (2010) The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20: 1297–1303 doi:10.1101/gr.107524.110

32. SlotteT, FoxeJP, HazzouriKM, WrightSI (2010) Genome-wide evidence for efficient positive and purifying selection in Capsella grandiflora, a plant species with a large effective population size. Mol Biol Evol 27: 1813–1821.

33. ClarkRM, SchweikertG, ToomajianC, OssowskiS, ZellerG, et al. (2007) Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science 317: 338–342 doi:10.1126/science.1138632

34. WrightSI, FoxeJP, DeRose-WilsonL, KawabeA, LooseleyM, et al. (2006) Testing for effects of recombination rate on nucleotide diversity in natural populations of Arabidopsis lyrata. Genetics 174: 1421–1430 doi:10.1534/genetics.106.062588

35. KawabeA, ForrestA, WrightSI, CharlesworthD (2008) High DNA sequence diversity in pericentromeric genes of the plant Arabidopsis lyrata. Genetics 179: 985–995 doi:10.1534/genetics.107.085282

36. BrancaA, PaapeTD, ZhouP, BriskineR, FarmerAD, et al. (2011) Whole-genome nucleotide diversity, recombination, and linkage disequilibrium in the model legume Medicago truncatula. Proc Natl Acad Sci USA 108: E864–E870 doi:10.1073/pnas.1104032108

37. SlotteT (2014) The impact of linked selection on plant genomic variation. Brief Funct Genomics 13: 268–275 doi:10.1093/bfgp/elu009

38. EhrenreichIM, PuruggananMD (2008) Sequence variation of MicroRNAs and their binding sites in Arabidopsis. Plant Physiol 146: 1974–1982 doi:10.1104/pp.108.116582

39. SattathS, ElyashivE, KolodnyO, RinottY, SellaG (2011) Pervasive adaptive protein evolution and diversity patterns around amino acid substitutions in Drosophila simulans. PLoS Genet 7: e1001302.

40. SmithJM, HaighJ (1974) The hitch-hiking effect of a favourable gene. Genet Res 23: 23–35 doi:10.1017/S0016672308009579

41. KimY, LeeG, JeonE, SohnEJ, LeeY, et al. (2013) The immediate upstream region of the 5′-UTR from the AUG start codon has a pronounced effect on the translational efficiency in Arabidopsis thaliana. Nucleic Acids Res 42: 485–498 doi:10.1093/nar/gkt864

42. HanMV, DemuthJP, McGrathCL, CasolaC, HahnMW (2009) Adaptive evolution of young gene duplicates in mammals. Genome Res 19: 859–867 doi:10.1101/gr.085951.108

43. QiuS, ZengK, SlotteT, WrightS, CharlesworthD (2011) Reduced efficacy of natural selection on codon usage bias in selfing Arabidopsis and Capsella species. Genome Biol Evol 3: 868–880 doi:10.1093/gbe/evr085

44. WrightSI, YauCBK, LooseleyM, MeyersBC (2004) Effects of gene expression on molecular evolution in Arabidopsis thaliana and Arabidopsis lyrata. Mol Biol Evol 21: 1719–1726 doi:10.1093/molbev/msh191

45. DuretL, MouchiroudD (1999) Expression pattern and, surprisingly, gene length shape codon usage in Caenorhabditis, Drosophila, and Arabidopsis. Proc Natl Acad Sci USA 96: 4482–4487.

46. MaraisG, MouchiroudD, DuretL (2001) Does recombination improve selection on codon usage? Lessons from nematode and fly complete genomes. Proc Natl Acad Sci USA 98: 5688–5692.

47. HernandezRD, KelleyJL, ElyashivE, MeltonSC, AutonA, et al. (2011) Classic selective sweeps were rare in recent human evolution. Science 331: 920–924 doi:10.1126/science.1198878

48. PenningsPS, HermissonJ (2006) Soft sweeps II–molecular population genetics of adaptation from recurrent mutation or migration. Mol Biol Evol 23: 1076–1084 doi:10.1093/molbev/msj117

49. PenningsPS, HermissonJ (2006) Soft sweeps III: the signature of positive selection from recurrent mutation. PLoS Genet 2: e186 doi:10.1371/journal.pgen.0020186

50. HermissonJ, PenningsPS (2005) Soft sweeps: molecular population genetics of adaptation from standing genetic variation. Genetics 169: 2335–2352 doi:10.1534/genetics.104.036947

51. MesserPW, PetrovDA (2013) Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol Evol 28: 659–669 doi:10.1016/j.tree.2013.08.003

52. PavlidisP, MetzlerD, StephanW (2012) Selective sweeps in multilocus models of quantitative traits. Genetics 192: 225–239 doi:10.1534/genetics.112.142547

53. LemosB, BettencourtBR, MeiklejohnCD, HartlDL (2005) Evolution of proteins and gene expression levels are coupled in Drosophila and are independently associated with mRNA abundance, protein length, and number of protein-protein interactions. Mol Biol Evol 22: 1345–1354 doi:10.1093/molbev/msi122

54. Drosophila 12 Genomes Consortium, ClarkAG, EisenMB, SmithDR, BergmanCM, et al. (2007) Evolution of genes and genomes on the Drosophila phylogeny. Nature 450: 203–218 doi:10.1038/nature06341

55. CarneiroM, AlbertFW, Melo-FerreiraJ, GaltierN, GayralP, et al. (2012) Evidence for widespread positive and purifying selection across the European rabbit (Oryctolagus cuniculus) Genome. Mol Biol Evol 29: 1837–1849 doi:10.1093/molbev/mss025

56. LunterG, GoodsonM (2011) Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Research 21: 936–939 doi:10.1101/gr.111120.110

57. DePristoMA, BanksE, PoplinR, GarimellaKV, MaguireJR, et al. (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genetics 43: 491–498 doi:10.1038/ng.806

58. Harris RS (2007) Improved pairwise alignment of genomic DNA. PhD Thesis, Penn State Univ.

59. OstlundG, SchmittT, ForslundK, KostlerT, MessinaDN, et al. (2009) InParanoid 7: new algorithms and tools for eukaryotic orthology analysis. Nucleic Acids Res 38: D196–D203 doi:10.1093/nar/gkp931

60. AlexeyenkoA, TamasI, LiuG, SonnhammerELL (2006) Automatic clustering of orthologs and inparalogs shared by multiple proteomes. Bioinformatics 22: e9–e15 doi:10.1093/bioinformatics/btl213

61. SubramanianAR, KaufmannM, MorgensternB (2008) DIALIGN-TX: greedy and progressive approaches for segment-based multiple sequence alignment. Algorithms Mol Biol 3: 6 doi:10.1186/1748-7188-3-6

62. YangZ (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24: 1586–1591 doi:10.1093/molbev/msm088

63. BlanchetteM, KentWJ, RiemerC, ElnitskiL, SmitAFA, et al. (2004) Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res 14: 708–715 doi:10.1101/gr.1933104

64. KeightleyPD, Eyre-WalkerA (2007) Joint inference of the distribution of fitness effects of deleterious mutations and population demography based on nucleotide polymorphism frequencies. Genetics 177: 2251–2261 doi:10.1534/genetics.107.080663

65. TrapnellC, PachterL, SalzbergSL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25: 1105–1111 doi:10.1093/bioinformatics/btp120

66. TrapnellC, WilliamsBA, PerteaG, MortazaviA, KwanG, et al. (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28: 511–515 doi:10.1038/nbt.1621

Štítky
Genetika Reprodukčná medicína

Článok vyšiel v časopise

PLOS Genetics


2014 Číslo 9
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#