Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity.
Vyšlo v časopise: Genome-Wide Fine-Scale Recombination Rate Variation in. PLoS Genet 8(12): e32767. doi:10.1371/journal.pgen.1003090 Kategorie: Research Article prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003090
1. HernandezRD, KelleyJL, ElyashivE, MeltonSC, AutonA, et al. (2011) Classic selective sweeps were rare in recent human evolution. Science 331 : 920–924.
2. SattathS, ElyashivE, KolodnyO, RinottY, SellaG (2011) Pervasive adaptive protein evolution apparent in diversity patterns around amino acid substitutions in Drosophila simulans. PLoS Genet 7: e1001302 doi:10.1371/journal.pgen.1001302.
3. PriceAL, TandonA, PattersonN, BarnesKC, RafaelsN, et al. (2009) Sensitive detection of chromosomal segments of distinct ancestry in admixed populations. PLoS Genet 5: e1000519 doi:10.1371/journal.pgen.1000519.
4. The International HapMap Consortium (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449 : 851–861.
5. Ortiz-BarrientosD, ChangAS, NoorMAF (2006) A recombinational portrait of the Drosophila pseudoobscura genome. Genetics Research Cambridge 87 : 23–31.
6. MyersS, BowdenR, TumianA, BontropR, FreemanC, et al. (2010) Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic recombination. Science 327 : 876–879.
7. AutonA, Fledel-AlonA, PfeiferS, VennO, SégurelL, et al. (2012) A fine-scale chimpanzee genetic map from population sequencing. Science 336 : 193–198.
8. The 1000 Genomes Project Consortium (2010) A map of human genome variation from population-scale sequencing. Nature 467 : 1061–1073.
9. KongA, ThorleifssonG, GudbjartssonDF, MassonG, SigurdssonA, et al. (2010) Fine-scale recombination rate differences between sexes, populations and individuals. Nature 467 : 1099–1103.
10. BaudatF, BuardJ, GreyC, Fledel-AlonA, OberC, et al. (2010) PRDM9 is a major deter-minant of meiotic recombination hotspots in humans and mice. Science 327 : 836–840.
11. BergIL, NeumannR, LamKG, SarbajnaS, Odenthal-HesseL, et al. (2010) PRDM9 variation strongly influences recombination hot-spot activity and meiotic instability in humans. Nature Genetics 42 : 859–863.
12. CoopG, WenX, OberC, PritchardJK, PrzeworskiM (2008) High-resolution mapping of crossovers reveals extensive variation in fine-scale recombination patterns among humans. Science 319 : 1395–1398.
13. MyersS, BottoloL, FreemanC, McVeanG, DonnellyP (2005) A fine-scale map of recombi-nation rates and hotspots across the human genome. Science 310 : 321–324.
14. McVeanGAT, MyersSR, HuntS, DeloukasP, BentleyDR, et al. (2004) The fine-scale structure of recombination rate variation in the human genome. Science 304 : 581–584.
15. DrouaudJ, CamilleriC, BourguignonPY, CanaguierA, BérardA, et al. (2006) Variation in crossing-over rates across chromosome 4 of Arabidopsis thaliana reveals the presence of meiotic recombination “hot spots”. Genome Research 16 : 106–114.
16. TsaiIJ, BurtA, KoufopanouV (2010) Conservation of recombination hotspots in yeast. Proc Nat Acad Sci 107 : 7847–7852.
17. Fiston-LavierAS, SinghND, LipatovM, PetrovDA (2010) Drosophila melanogaster recom-bination rate calculator. Gene 463 : 18–20.
18. MackayTFC, RichardsS, StoneEA, BarbadillaA, AyrolesJF, et al. (2012) The Drosophila melanogaster genetic reference panel. Nature 482 : 173–178.
19. LangleyCH, LazzaroBP, PhillipsW, HeikkinenE, BravermanJM (2000) Linkage dise-quilibria and the site frequency spectra in the su(s) and su(wa) regions of the Drosophila melanogaster X chromosome. Genetics 156 : 1837–1852.
20. SinghND, AquadroCF, ClarkAG (2009) Estimation of fine-scale recombination intensity variation in the white-echinus interval of D. melanogaster. Journal of Molecular Evolution 69 : 42–53.
21. StevisonLS, NoorMAF (2010) Genetic and evolutionary correlates of fine-scale recombina-tion rate variation in Drosophila persimilis. Journal of Molecular Evolution 71 : 332–345.
22. CirulliET, KlimanRM, NoorMAF (2007) Fine-scale crossover rate heterogeneity in Drosophila pseudoobscura. Journal of Molecular Evolution 64 : 129–135.
23. KulathinalRJ, BennettSM, FitzpatrickCL, NoorMAF (2008) Fine-scale mapping of re-combination rate in Drosophila refines its correlation to diversity and divergence. Proc Nat Acad Sci 105 : 10051–10056.
24. LangleyCH, StevensK, CardenoC, LeeYCG, SchriderDR, et al. (2012) Genomic variation in natural populations of Drosophila melanogaster. Genetics in press.
25. AutonA, McVeanG (2007) Recombination rate estimation in the presence of hotspots. Genome Research 17 : 1219–1227.
26. LiN, StephensM (2003) Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics 165 : 2213–2233.
27. WangY, RannalaB (2008) Bayesian inference of fine-scale recombination rates using popu-lation genomic data. Philosophical Transactions of the Royal Society B 363 : 3921–3930.
28. FearnheadP, SmithNGC (2005) A novel method with improved power to detect recombina-tion hotspots from polymorphism data reveals multiple hotspots in human genes. American Journal of Human Genetics 77 : 781–794.
29. FearnheadP (2006) SequenceLDhot: detecting recombination hotspots. Bioinformatics 22 : 3061–3066.
30. McVeanG, AwadallaP, FearnheadP (2002) A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics 160 : 1231–1241.
31. AxelssonE, WebsterMT, RatnakumarA (2012) The LUPA Consortium (2012) PontingCP, et al. (2012) Death of PRDM9 coincides with stabilization of the recombination landscape in the dog genome. Genome Research 22 : 51–63.
32. JohnsonP, SlatkinM (2009) Inference of microbial recombination rates from metagenomic data. PLoS Genet 5: e1000674 doi:10.1371/journal.pgen.1000674.
33. SellaG, PetrovDA, PrzeworskiM, AndolfattoP (2009) Pervasive natural selection in the Drosophila genome? PLoS Genet 5: e1000495 doi:10.1371/journal.pgen.1000495.
34. ReedFA, TishkoffSA (2006) Positive selection can create false hotspots of recombination. Genetics 172 : 2011–2014.
35. StephanW, SongYS, LangleyCH (2006) The hitchhiking effect on linkage disequilibrium between linked neutral loci. Genetics 172 : 2647–2663.
36. JenkinsPA, SongYS (2009) Closed-form two-locus sampling distributions: accuracy and universality. Genetics 183 : 1087–1103.
37. JenkinsPA, SongYS (2010) An asymptotic sampling formula for the coalescent with recom-bination. Annals of Applied Probability 20 : 1005–1028.
38. JenkinsPA, SongYS (2012) Padé approximants and exact two-locus sampling distributions. Annals of Applied Probability 22 : 576–607.
39. BhaskarA, SongYS (2012) Closed-form asymptotic sampling distributions under the coa-lescent with recombination for an arbitrary number of loci. Advances in Applied Probability 44 : 391–407.
40. JenkinsPA, SongYS (2011) The effect of recurrent mutation on the frequency spectrum of a segregating site and the age of an allele. Theor Popul Biol 80 : 158–173.
41. BhaskarA, KammJA, SongYS (2012) Approximate sampling formulas for general finite-alleles models of mutation. Advances in Applied Probability 44 : 408–428.
42. KimY, NielsenR (2004) Linkage disequilibrium as a signature of selective sweeps. Genetics 167 : 1513–1524.
43. McVeanG (2007) The structure of linkage disequilibrium around a selective sweep. Genetics 175 : 1395–1406.
44. AndolfattoP (2007) Hitchhiking effects of recurrent beneficial amino acid substitutions in the Drosophila melanogaster genome. Genome Research 17 : 1755–1762.
45. JensenJD, ThorntonKR, AndolfattoP (2008) An approximate Bayesian estimator suggests strong, recurrent selective sweeps in Drosophila. PLoS Genet 4: e1000198 doi:10.1371/journal.pgen.1000198.
46. HaddrillPR, ThorntonKR, CharlesworthB, AndolfattoP (2005) Multi-locus patterns of nucleotide variability and the demographic and selection history of Drosophila melanogaster populations. Genome Research 15 : 790–799.
47. ThorntonK, AndolfattoP (2006) Approximate Bayesian inference reveals evidence for a recent, severe bottleneck in a Netherlands population of Drosophila melanogaster. Genetics 172 : 1607–1619.
48. AulardS, DavidJ, LemeunierF, et al. (2002) Chromosomal inversion polymorphism in afrotropical populations of Drosophila melanogaster. Genetical Research 79 : 49–63.
49. Corbett-DetigRB, CardenoC, LangleyCH (2012) Sequence-based detection and breakpoint assembly of polymorphic inversions. Genetics in press.
50. McQuiltonP, PierreSES, ThurmondJ (2012) the FlyBase Consortium (2012) FlyBase 101—the basics of navigating FlyBase. Nucleic Acids Research 40: D706–D714.
51. AndersonJA, SongYS, LangleyCH (2008) Molecular population genetics of Drosophila subtelomeric DNA. Genetics 178 : 477–487.
52. BrunschwigH, LeviL, Ben-DavidE, WilliamsRW, YakirB, et al. (2012) Fine-scale maps of recombination rates and hotspots in the mouse genome. Genetics 191 : 757–764.
53. SpencerCCA, DeloukasP, HuntS, MullikinJ, MyersS, et al. (2006) The influence of recombination on human genetic diversity. PLoS Genet 2: e148 doi:10.1371/journal.pgen.0020148.
54. TorrenceC, CompoGP (1998) A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79 : 61–78.
55. FargeM (1992) Wavelet transforms and their applications to turbulence. Annual Review of Fluid Mechanics 24 : 395–457.
56. BegunDJ, AquadroCF (1992) Levels of naturally occurring DNA polymorphism correlate with recombination rates in D. melanogaster. Nature 356 : 519–520.
57. BegunDJ, HollowayAK, StevensK, HillierLW, PohYP, et al. (2007) Population genomics: whole-genome analysis of polymorphism and divergence in Drosophila simulans. PLoS Biol 5: e310 doi:10.1371/journal.pbio.0050310.
58. MillerDE, TakeoS, NandananK, PaulsonA, GogolMM, et al. (2012) A whole-chromosome analysis of meiotic recombination in Drosophila melanogaster. G3: Genes—Genomes—Genetics 2 : 249–260.
59. WallJD, AndolfattoP, PrzeworskiM (2002) Testing models of selection and demography in Drosophila simulans. Genetics 162 : 203–216.
60. PoolJE, NielsenR (2007) Population size changes reshape genomic patterns of diversity. Evolution 61 : 3001–3006.
61. LucchesiJ, SuzukiD (1968) The interchromosomal control of recombination. Annual Review of Genetics 2 : 53–86.
62. PortinP, RantanenM (1990) Further studies on the interchromosomal effect on crossing over in Drosophila melanogaster affecting the preconditions of exchange. Genetica 82 : 203–207.
63. CharlesworthB (2012) The effects of deleterious mutation on evolution at linked sites. Ge-netics 190 : 5–22.
64. CharlesworthB (2012) The role of background selection in shaping patterns of molecular evolution and variation: evidence from variability on the Drosophila X chromosome. Genetics 191 : 233–246.
65. GreenP (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82 : 711–732.
66. HudsonRR (2001) Two-locus sampling distributions and their application. Genetics 159 : 1805–1817.
67. FearnheadP, DonnellyP (2001) Estimating recombination rates from population genetic data. Genetics 159 : 1299–1318.
68. GoldingGB (1984) The sampling distribution of linkage disequilibrium. Genetics 108 : 257–274.
69. EthierSN, GriffithsRC (1990) On the two-locus sampling distribution. Journal of Mathe-matical Biology 29 : 131–159.
70. GriffithsRC, TavaréS (1994) Simulating probability distributions in the coalescent. Theor Popul Biol 46 : 131–159.
71. LiH, DurbinR (2011) Inference of human population history from individual whole-genome sequences. Nature 475 : 493–496.
72. ChenG, MarjoramP, WallJ (2009) Fast and flexible simulation of DNA sequence data. Genome Research 19 : 136–142.
73. TeshimaKM, InnanH (2009) mbs: modifying Hudson's ms software to generate samples of DNA sequences with a biallelic site under selection. BMC Bioinformatics 10 : 166.
74. HellenthalG, StephensM (2007) msHOT: modifying Hudson's ms simulator to incorporate crossover and gene conversion hotspots. Bioinformatics 23 : 520–521.
75. GrinstedA, MooreJC, JevrejevaS (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics 11 : 561–566.
Zvýšte si kvalifikáciu online z pohodlia domova
Nemáte účet? Registrujte sa
Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.
