Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals
Autoři:
Marjolaine Rousselle aff001; Paul Simion aff001; Marie-Ka Tilak aff001; Emeric Figuet aff001; Benoit Nabholz aff001; Nicolas Galtier aff001
Působiště autorů:
ISEM, Univ. Montpellier, CNRS, EPHE, IRD, Montpellier, France
aff001; LEGE, Department of Biology, University of Namur, Namur, Belgium
aff002
Vyšlo v časopise:
Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals. PLoS Genet 16(4): e32767. doi:10.1371/journal.pgen.1008668
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1008668
Souhrn
Whether adaptation is limited by the beneficial mutation supply is a long-standing question of evolutionary genetics, which is more generally related to the determination of the adaptive substitution rate and its relationship with species effective population size (Ne) and genetic diversity. Empirical evidence reported so far is equivocal, with some but not all studies supporting a higher adaptive substitution rate in large-Ne than in small-Ne species. We gathered coding sequence polymorphism data and estimated the adaptive amino-acid substitution rate ωa, in 50 species from ten distant groups of animals with markedly different population mutation rate θ. We reveal the existence of a complex, timescale dependent relationship between species adaptive substitution rate and genetic diversity. We find a positive relationship between ωa and θ among closely related species, indicating that adaptation is indeed limited by the mutation supply, but this was only true in relatively low-θ taxa. In contrast, we uncover no significant correlation between ωa and θ at a larger taxonomic scale, suggesting that the proportion of beneficial mutations scales negatively with species' long-term Ne.
Klíčová slova:
Ants – Evolutionary adaptation – Moths and butterflies – Mussels – Population genetics – Primates – Substitution mutation – Taxonomy
Zdroje
1. Bell G. Evolutionary rescue and the limits of adaptation. Philos Trans R Soc B Biol Sci. 2013;368(1610):20120080.
2. Lanfear R, Kokko H, Eyre-Walker A. Population size and the rate of evolution. Trends Ecol Evol. 2014 Jan;29(1):33–41. doi: 10.1016/j.tree.2013.09.009 24148292
3. Smith JM. What Determines the eate of evolution? Am Nat. 1976 May 1;110(973):331–8.
4. Nam K, Munch K, Mailund T, Nater A, Greminger MP, Krützen M, et al. Evidence that the rate of strong selective sweeps increases with population size in the great apes. Proc Natl Acad Sci. 2017 Feb 14;114(7):1613–8. doi: 10.1073/pnas.1605660114 28137852
5. Bürger R, Lynch M. Evolution and extinction in a changing environment: a quantitative‐genetic analysis. Evolution. 1995;49(1):151–63. doi: 10.1111/j.1558-5646.1995.tb05967.x 28593664
6. Barton N, Partridge L. Limits to natural selection. BioEssays. 2000;22(12):1075–84. doi: 10.1002/1521-1878(200012)22:12<1075::AID-BIES5>3.0.CO;2-M 11084623
7. Lourenço JM, Glémin S, Galtier N. The rate of molecular adaptation in a changing environment. Mol Biol Evol. 2013;30(6):1292–301. doi: 10.1093/molbev/mst026 23412912
8. Kopp M, Hermisson J. The genetic basis of phenotypic adaptation II: the distribution of adaptive substitutions in the moving optimum model. Genetics. 2009;183(4):1453–76. doi: 10.1534/genetics.109.106195 19805820
9. Karasov T, Messer PW, Petrov DA. Evidence that Adaptation in Drosophila is not limited by mutation at single sites. PLOS Genet. 2010 Jun 17;6(6):e1000924. doi: 10.1371/journal.pgen.1000924 20585551
10. Weissman DB, Barton NH. Limits to the Rate of Adaptive Substitution in Sexual Populations. PLOS Genet. 2012 Jun 7;8(6):e1002740. doi: 10.1371/journal.pgen.1002740 22685419
11. Yeaman S, Gerstein AC, Hodgins KA, Whitlock MC. Quantifying how constraints limit the diversity of viable routes to adaptation. PLoS Genet. 2018;14(10):e1007717. doi: 10.1371/journal.pgen.1007717 30296265
12. McDonald JH, Kreitman M. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 1991 Jun 20;351(6328):652–4. doi: 10.1038/351652a0 1904993
13. Smith NGC, Eyre-Walker A. Adaptive protein evolution in Drosophila. Nature. 2002 Feb;415(6875):1022–4. doi: 10.1038/4151022a 11875568
14. Keightley PD, Eyre-Walker A. Joint inference of the distribution of fitness effects of deleterious mutations and population demography based on nucleotide polymorphism frequencies. Genetics. 2007;177(4):2251–61. doi: 10.1534/genetics.107.080663 18073430
15. Boyko AR, Williamson SH, Indap AR, Degenhardt JD, Hernandez RD, Lohmueller KE, et al. Assessing the evolutionary impact of amino acid mutations in the human genome. PLoS Genet. 2008;4(5):e1000083. doi: 10.1371/journal.pgen.1000083 18516229
16. Eyre-Walker A, Keightley PD. Estimating the rate of adaptive molecular evolution in the presence of slightly seleterious mutations and population size change. Mol Biol Evol. 2009 Sep 1;26(9):2097–108. doi: 10.1093/molbev/msp119 19535738
17. Messer PW, Petrov DA. Frequent adaptation and the McDonald–Kreitman test. Proc Natl Acad Sci. 2013 May 21;110(21):8615–20. doi: 10.1073/pnas.1220835110 23650353
18. Galtier N. Adaptive protein evolution in animals and the effective population size hypothesis. PLOS Genet. 2016 Jan 11;12(1):e1005774. doi: 10.1371/journal.pgen.1005774 26752180
19. Keightley PD, Campos JL, Booker TR, Charlesworth B. Inferring the frequency spectrum of derived variants to quantify adaptive molecular evolution in protein-coding genes of Drosophila melanogaster. Genetics. 2016 Jun 1;203(2):975–84. doi: 10.1534/genetics.116.188102 27098912
20. Tataru P, Mollion M, Glémin S, Bataillon T. Inference of distribution of fitness effects and proportion of adaptive substitutions from polymorphism data. Genetics. 2017 Nov 1;207(3):1103–19. doi: 10.1534/genetics.117.300323 28951530
21. Loewe L, Charlesworth B. Inferring the distribution of mutational effects on fitness in Drosophila. Biol Lett. 2006 Sep 22;2(3):426–30. doi: 10.1098/rsbl.2006.0481 17148422
22. Stoletzki N, Eyre-Walker A. Estimation of the neutrality index. Mol Biol Evol. 2010;28(1):63–70. doi: 10.1093/molbev/msq249 20837603
23. Rousselle M, Mollion M, Nabholz B, Bataillon T, Galtier N. Overestimation of the adaptive substitution rate in fluctuating populations. Biol Lett. 2018 May 1;14(5):20180055. doi: 10.1098/rsbl.2018.0055 29743267
24. Eyre-Walker A. Changing effective population size and the McDonald-Kreitman test. Genetics. 2002;162(4):2017–24. 12524367
25. Corcoran P, Gossmann TI, Barton HJ, Slate J, Zeng K. Determinants of the efficacy of natural selection on coding and noncoding variability in two passerine species. Genome Biol Evol. 2017 Nov 1;9(11):2987–3007. doi: 10.1093/gbe/evx213 29045655
26. Rousselle M, Laverré A, Figuet E, Nabholz B, Galtier N. Influence of recombination and GC-biased gene conversion on the adaptive and nonadaptive substitution rate in mammals versus birds. Mol Biol Evol. 2019 Mar 1;36(3):458–71. doi: 10.1093/molbev/msy243 30590692
27. Bolívar P, Mugal CF, Rossi M, Nater A, Wang M, Dutoit L, et al. Biased inference of selection due to GC-biased gene conversion and the rate of protein evolution in flycatchers when accounting for it. Mol Biol Evol. 2018;35(10):2475–86. doi: 10.1093/molbev/msy149 30085180
28. Ohta T. The nearly neutral theory of molecular evolution. Annu Rev Ecol Syst. 1992;23(1):263–86.
29. Gossmann TI, Keightley PD, Eyre-Walker A. The effect of variation in the effective population size on the rate of adaptive molecular evolution in Eukaryotes. Genome Biol Evol. 2012 Jan 1;4(5):658–67. doi: 10.1093/gbe/evs027 22436998
30. Gossmann TI, Song B-H, Windsor AJ, Mitchell-Olds T, Dixon CJ, Kapralov MV, et al. Genome wide analyses reveal little evidence for adaptive evolution in many plant species. Mol Biol Evol. 2010;27(8):1822–32. doi: 10.1093/molbev/msq079 20299543
31. Strasburg JL, Kane NC, Raduski AR, Bonin A, Michelmore R, Rieseberg LH. Effective population size is positively correlated with levels of adaptive divergence among annual sunflowers. Mol Biol Evol. 2010;28(5):1569–80. doi: 10.1093/molbev/msq270 20952500
32. Huber CD, Kim BY, Marsden CD, Lohmueller KE. Determining the factors driving selective effects of new nonsynonymous mutations. Proc Natl Acad Sci. 2017;114(17):4465–70. doi: 10.1073/pnas.1619508114 28400513
33. Simion P, Belkhir K, François C, Veyssier J, Rink JC, Manuel M, et al. A software tool ‘CroCo’detects pervasive cross-species contamination in next generation sequencing data. BMC Biol. 2018;16(1):28. doi: 10.1186/s12915-018-0486-7 29506533
34. James JE, Piganeau G, Eyre‐Walker A. The rate of adaptive evolution in animal mitochondria. Mol Ecol. 2016;25(1):67–78. doi: 10.1111/mec.13475 26578312
35. Galtier N, Roux C, Rousselle M, Romiguier J, Figuet E, Glémin S, et al. Codon usage bias in animals: disentangling the effects of natural selection, effective population size, and GC-biased gene conversion. Mol Biol Evol. 2018;35(5):1092–103. doi: 10.1093/molbev/msy015 29390090
36. Romiguier J, Gayral P, Ballenghien M, Bernard A, Cahais V, Chenuil A, et al. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature. 2014;515(7526):261. doi: 10.1038/nature13685 25141177
37. Chen J, Glémin S, Lascoux M. Genetic diversity and the efficacy of purifying selection across plant and animal species. Mol Biol Evol. 2017 Jun;34(6):1417–28. doi: 10.1093/molbev/msx088 28333215
38. Zhen Y, Huber CD, Davies RW, Lohmueller KE. Stronger and higher proportion of beneficial amino acid changing mutations in humans compared to mice and flies. bioRxiv. 2018 Sep 26.
39. Eyre-Walker A, Woolfit M, Phelps T. The distribution of fitness effects of new deleterious amino acid mutations in Humans. Genetics. 2006 Jun 1;173(2):891–900. doi: 10.1534/genetics.106.057570 16547091
40. Castellano D, Macià MC, Tataru P, Bataillon T, Munch K. Comparison of the full distribution of fitness effects of new amino acid mutations across great apes. Genetics. 2019 Nov 1;213(3):953–66. doi: 10.1534/genetics.119.302494 31488516
41. Jensen JD, Bachtrog D. Characterizing the influence of effective population size on the rate of adaptation: Gillespie’s Darwin domain. Genome Biol Evol. 2011 Jun 24;3:687–701. doi: 10.1093/gbe/evr063 21705473
42. Gillespie JH. Is the population size of a species relevant to its evolution? Evolution. 2001. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.0014-3820.2001.tb00732.x
43. Gillespie JH. The neutral theory in an infinite population. Gene. 2000;261(1):11–8. doi: 10.1016/s0378-1119(00)00485-6 11164032
44. Coop G. Does linked selection explain the narrow range of genetic diversity across species? bioRxiv. 2016 Mar 7;042598.
45. Barton N. Understanding adaptation in large populations. PLoS Genet. 2010;6(6):e1000987. doi: 10.1371/journal.pgen.1000987 20585547
46. Enard D, Cai L, Gwennap C, Petrov DA. Viruses are a dominant driver of protein adaptation in mammals. eLife. 2016 17;5.
47. Lawrie DS, Messer PW, Hershberg R, Petrov DA. Strong Purifying Selection at Synonymous Sites in D. melanogaster. PLoS Genet. 2013 May 30;9(5).
48. Machado HE, Lawrie DS, Petrov DA. Pervasive Strong Selection at the Level of Codon Usage Bias in Drosophila melanogaster. Genetics. 2019 Dec 23;302542.2019.
49. Matsumoto T, John A, Baeza-Centurion P, Li B, Akashi H. Codon Usage Selection Can Bias Estimation of the Fraction of Adaptive Amino Acid Fixations. Mol Biol Evol. 2016 Jun;33(6):1580–9. doi: 10.1093/molbev/msw027 26873577
50. Hill WG, Robertson A. The effect of linkage on limits to artificial selection. Genet Res. 1966;8(3):269–94. 5980116
51. Razeto-Barry P, Díaz J, Vásquez RA. The nearly neutral and selection theories of molecular evolution under the fisher geometrical framework: substitution rate, population size, and complexity. Genetics. 2012;191(2):523–34. doi: 10.1534/genetics.112.138628 22426879
52. Orr HA. Adaptation and the cost of complexity. Evolution. 2000 Feb 1;54(1):13–20. doi: 10.1111/j.0014-3820.2000.tb00002.x 10937178
53. Fernández A, Lynch M. Non-adaptive origins of interactome complexity. Nature. 2011;474(7352):502. doi: 10.1038/nature09992 21593762
54. Rousselle M, Faivre N, Ballenghien M, Galtier N, Nabholz B. Hemizygosity enhances purifying selection: lack of fast-z evolution in two Satyrine butterflies. Genome Biol Evol. 2016 Oct 1;8(10):3108–19. doi: 10.1093/gbe/evw214 27590089
55. Ballenghien M, Faivre N, Galtier N. Patterns of cross-contamination in a multispecies population genomic project: detection, quantification, impact, and solutions. BMC Biol. 2017 Dec;15(1).
56. Meyer M, Kircher M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb Protoc. 2010;2010(6):pdb. prot5448.
57. Tilak M-K, Justy F, Debiais-Thibaud M, Botero-Castro F, Delsuc F, Douzery EJP. A cost-effective straightforward protocol for shotgun Illumina libraries designed to assemble complete mitogenomes from non-model species. Conserv Genet Resour. 2015 Mar 1;7(1):37–40.
58. Rohland N, Reich D. Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Genome Res. 2012;
59. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. doi: 10.1093/bioinformatics/btu170 24695404
60. Cahais V, Gayral P, Tsagkogeorga G, Melo‐Ferreira J, Ballenghien M, Weinert L, et al. Reference‐free transcriptome assembly in non‐model animals from next‐generation sequencing data. Mol Ecol Resour. 2012;12(5):834–45. doi: 10.1111/j.1755-0998.2012.03148.x 22540679
61. Simpson JT, Wong K, Jackman SD, Schein JE, Jones SJ, Birol I. ABySS: a parallel assembler for short read sequence data. Genome Res. 2009;19(6):1117–23. doi: 10.1101/gr.089532.108 19251739
62. Huang X, Madan A. CAP3: A DNA sequence assembly program. Genome Res. 1999;9(9):868–77. doi: 10.1101/gr.9.9.868 10508846
63. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29(7):644. doi: 10.1038/nbt.1883 21572440
64. Li H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics. 2009;25(14):1754–60. doi: 10.1093/bioinformatics/btp324 19451168
65. Tsagkogeorga G, Cahais V, Galtier N. The population genomics of a fast evolver: high levels of diversity, functional constraint, and molecular adaptation in the tunicate Ciona intestinalis. Genome Biol Evol. 2012;4(8):852–61.
66. Gayral P, Melo-Ferreira J, Glémin S, Bierne N, Carneiro M, Nabholz B, et al. Reference-free population genomics from next-generation transcriptome data and the vertebrate–invertebrate gap. PLoS Genet. 2013;9(4):e1003457. doi: 10.1371/journal.pgen.1003457 23593039
67. Ranwez V, Delsuc F, Ranwez S, Belkhir K, Tilak M-K, Douzery EJ. OrthoMaM: a database of orthologous genomic markers for placental mammal phylogenetics. BMC Evol Biol. 2007;7(1):241.
68. Douzery EJ, Scornavacca C, Romiguier J, Belkhir K, Galtier N, Delsuc F, et al. OrthoMaM v8: a database of orthologous exons and coding sequences for comparative genomics in mammals. Mol Biol Evol. 2014;31(7):1923–8. doi: 10.1093/molbev/msu132 24723423
69. Emms DM, Kelly S. OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol. 2015;16(1):157.
70. Ranwez V, Harispe S, Delsuc F, Douzery EJ. MACSE: Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons. PloS One. 2011;6(9):e22594. doi: 10.1371/journal.pone.0022594 21949676
71. Guéguen L, Gaillard S, Boussau B, Gouy M, Groussin M, Rochette NC, et al. Bio++: efficient extensible libraries and tools for computational molecular evolution. Mol Biol Evol. 2013;30(8):1745–50. doi: 10.1093/molbev/mst097 23699471
72. Haller BC, Messer PW. SLiM 2: Flexible, Interactive Forward Genetic Simulations. Mol Biol Evol. 2017 Jan 1;34(1):230–40. doi: 10.1093/molbev/msw211 27702775
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 4
- Může hubnutí souviset s vyšším rizikem nádorových onemocnění?
- Raději si zajděte na oční! Jak souvisí citlivost zraku s rozvojem demence?
- Co způsobuje pooperační infekce? Na vině může být i naše vlastní mikrobiota
- Čeká nás průlom v diagnostice karcinomu pankreatu?
- Polibek, který mi „vzal nohy“ aneb vzácný výskyt EBV u 70leté ženy – kazuistika
Nejčtenější v tomto čísle
- Analysis of genes within the schizophrenia-linked 22q11.2 deletion identifies interaction of night owl/LZTR1 and NF1 in GABAergic sleep control
- High expression in maize pollen correlates with genetic contributions to pollen fitness as well as with coordinated transcription from neighboring transposable elements
- Molecular genetics of maternally-controlled cell divisions
- Spastin mutations impair coordination between lipid droplet dispersion and reticulum