Experimental evolution of adaptive divergence under varying degrees of gene flow.


Journal

Nature ecology & evolution
ISSN: 2397-334X
Titre abrégé: Nat Ecol Evol
Pays: England
ID NLM: 101698577

Informations de publication

Date de publication:
03 2021
Historique:
received: 21 04 2020
accepted: 12 11 2020
pubmed: 13 1 2021
medline: 20 3 2021
entrez: 12 1 2021
Statut: ppublish

Résumé

Adaptive divergence is the key evolutionary process generating biodiversity by means of natural selection. Yet, the conditions under which it can arise in the presence of gene flow remain contentious. To address this question, we subjected 132 sexually reproducing fission yeast populations, sourced from two independent genetic backgrounds, to disruptive ecological selection and manipulated the level of migration between environments. Contrary to theoretical expectations, adaptive divergence was most pronounced when migration was either absent (allopatry) or maximal (sympatry), but was much reduced at intermediate rates (parapatry and local mating). This effect was apparent across central life-history components (survival, asexual growth and mating) but differed in magnitude between ancestral genetic backgrounds. The evolution of some fitness components was constrained by pervasive negative correlations (trade-off between asexual growth and mating), while others changed direction under the influence of migration (for example, survival and mating). In allopatry, adaptive divergence was mainly conferred by standing genetic variation and resulted in ecological specialization. In sympatry, divergence was mainly mediated by novel mutations enriched in a subset of genes and was characterized by the repeated emergence of two strategies: an ecological generalist and an asexual growth specialist. Multiple loci showed consistent evidence for antagonistic pleiotropy across migration treatments providing a conceptual link between adaptation and divergence. This evolve-and-resequence experiment shows that rapid ecological differentiation can arise even under high rates of gene flow. It further highlights that adaptive trajectories are governed by complex interactions of gene flow, ancestral variation and genetic correlations.

Identifiants

pubmed: 33432131
doi: 10.1038/s41559-020-01363-2
pii: 10.1038/s41559-020-01363-2
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

338-349

Références

Darwin, C. & Wallace, A. R. On the tendency of species to form varieties; and on the perpetuation of varieties and species by natural means of selection. Zool. J. Linn. Soc. 3, 45–62 (1858).
doi: 10.1111/j.1096-3642.1858.tb02500.x
Schluter, D. Evidence for ecological speciation and its alternative. Science 323, 737–741 (2009).
pubmed: 19197053 doi: 10.1126/science.1160006
Dobzhansky, T. Genetics and the Origin of Species Vol. 11 (Columbia Univ. Press, 1937).
Mayr, E. Animal Species and Evolution (Harvard Univ. Press, 1963).
Coyne, J. A. & Orr, H. A. Speciation (Sinauer, 2004).
Dettman, J. R., Sirjusingh, C., Kohn, L. M. & Anderson, J. B. Incipient speciation by divergent adaptation and antagonistic epistasis in yeast. Nature 447, 585–588 (2007).
pubmed: 17538619 doi: 10.1038/nature05856
Haldane, J. B. S. A mathematical theory of natural and artificial selection. (Part VI, Isolation.). Math. Proc. Camb. Phil. Soc. 26, 220–230 (1930).
doi: 10.1017/S0305004100015450
Räsänen, K. & Hendry, A. P. Disentangling interactions between adaptive divergence and gene flow when ecology drives diversification. Ecol. Lett. 11, 624–636 (2008).
pubmed: 18384363 doi: 10.1111/j.1461-0248.2008.01176.x
Smadja, C. M. & Butlin, R. K. A framework for comparing processes of speciation in the presence of gene flow. Mol. Ecol. 20, 5123–5140 (2011).
pubmed: 22066935 doi: 10.1111/j.1365-294X.2011.05350.x
Ronce, O. & Kirkpatrick, M. When sources become sinks: migrational meltdown in heterogeneous habitats. Evolution 55, 1520–1531 (2001).
pubmed: 11580012
Spichtig, M. & Kawecki, T. J. The maintenance (or not) of polygenic variation by soft selection in heterogeneous environments. Am. Nat. 164, 70–84 (2004).
pubmed: 15266372 doi: 10.1086/421335
Guillaume, F. & Whitlock, M. C. Effects of migration on the genetic covariance matrix. Evolution 61, 2398–2409 (2007).
pubmed: 17711463 doi: 10.1111/j.1558-5646.2007.00193.x
Arnold, S. J., Bürger, R., Hohenlohe, P. A., Ajie, B. C. & Jones, A. G. Understanding the evolution and stability of the G-matrix. Evolution 62, 2451–2461 (2008).
pubmed: 18973631 pmcid: 3229175 doi: 10.1111/j.1558-5646.2008.00472.x
Garant, D., Forde, S. E. & Hendry, A. P.The multifarious effects of dispersal and gene flow on contemporary adaptation. Funct. Ecol. 21, 434–443 (2006).
doi: 10.1111/j.1365-2435.2006.01228.x
Nosil, P. Speciation with gene flow could be common. Mol. Ecol. 17, 2103–2106 (2008).
pubmed: 18410295 doi: 10.1111/j.1365-294X.2008.03715.x
Dieckmann, U., Doebeli, M., Metz, J. A. J. & Tautz, D. Adaptive Speciation (Cambridge Univ. Press, 2012).
Shafer, A. B. A. & Wolf, J. B. W. Widespread evidence for incipient ecological speciation: a meta-analysis of isolation-by-ecology. Ecol. Lett. 16, 940–950 (2013).
pubmed: 23627762 doi: 10.1111/ele.12120
Hendry, A. P., Bolnick, D. I., Berner, D. & Peichel, C. L. Along the speciation continuum in sticklebacks. J. Fish. Biol. 75, 2000–2036 (2009).
pubmed: 20738669 doi: 10.1111/j.1095-8649.2009.02419.x
Nosil, P. Ecological Speciation (Oxford Univ. Press, 2012).
Arnegard, M. E. et al. Genetics of ecological divergence during speciation. Nature 511, 307–311 (2014).
pubmed: 24909991 pmcid: 4149549 doi: 10.1038/nature13301
Seehausen, O. et al. Genomics and the origin of species. Nat. Rev. Genet. 15, 176–192 (2014).
pubmed: 24535286 doi: 10.1038/nrg3644
Wolf, J. B. W. & Ellegren, H. Making sense of genomic islands of differentiation in light of speciation. Nat. Rev. Genet. 18, 87–100 (2017).
pubmed: 27840429 doi: 10.1038/nrg.2016.133
Gray, J. C. & Goddard, M. R. Gene-flow between niches facilitates local adaptation in sexual populations. Ecol. Lett. 15, 955–962 (2012).
pubmed: 22690742 doi: 10.1111/j.1461-0248.2012.01814.x
Soria-Carrasco, V. et al. Stick insect genomes reveal natural selection’s role in parallel speciation. Science 344, 738–742 (2014).
pubmed: 24833390 doi: 10.1126/science.1252136
Schluter, D.Adaptive radiation along genetic lines of least resistance. Evolution 50, 1766–1774 (1996).
pubmed: 28565589 doi: 10.2307/2410734
Reznick, D. The structure of guppy life histories: the tradeoff between growth and reproduction. Ecology 64, 862–873 (1983).
doi: 10.2307/1937209
Roff, D. A. Trade-offs between growth and reproduction: an analysis of the quantitative genetic evidence. J. Evol. Biol. 13, 434–445 (2000).
doi: 10.1046/j.1420-9101.2000.00186.x
Haselhorst, M. S. H., Edwards, C. E., Rubin, M. J. & Weinig, C. Genetic architecture of life history traits and environment-specific trade-offs. Mol. Ecol. 20, 4042–4058 (2011).
pubmed: 21902746 doi: 10.1111/j.1365-294X.2011.05227.x
Silva, F. F. G., Slotte, A., Johannessen, A., Kennedy, J. & Kjesbu, O. S. Strategies for partition between body growth and reproductive investment in migratory and stationary populations of spring-spawning Atlantic herring (Clupea harengus L.). Fish. Res. 138, 71–79 (2013).
doi: 10.1016/j.fishres.2012.07.013
Lande, R. Quantitative genetic analysis of multivariate evolution, applied to brain: body size allometry. Evolution 33, 402–416 (1979).
pubmed: 28568194
Arnold, S. J. Constraints on phenotypic evolution. Am. Nat. 140, S85–S107 (1992).
pubmed: 19426028 doi: 10.1086/285398
Kryazhimskiy, S., Rice, D. P., Jerison, E. R. & Desai, M. M. Microbial evolution. Global epistasis makes adaptation predictable despite sequence-level stochasticity. Science 344, 1519–1522 (2014).
pubmed: 24970088 pmcid: 4314286 doi: 10.1126/science.1250939
Butlin, R. K. Recombination and speciation. Mol. Ecol. 14, 2621–2635 (2005).
pubmed: 16029465 doi: 10.1111/j.1365-294X.2005.02617.x
Kassen, R. The experimental evolution of specialists, generalists, and the maintenance of diversity. J. Evol. Biol. 15, 173–190 (2002).
doi: 10.1046/j.1420-9101.2002.00377.x
Levene, H. Genetic equilibrium when more than one ecological niche is available. Am. Nat. 87, 331–333 (1953).
doi: 10.1086/281792
Débarre, F. & Gandon, S. Evolution in heterogeneous environments: between soft and hard selection. Am. Nat. 177, E84–E97 (2011).
pubmed: 21460536 doi: 10.1086/658178
Nei, M. Molecular Evolutionary Genetics (Columbia Univ. Press, 1987).
Ratcliff, W. C., Denison, R. F., Borrello, M. & Travisano, M. Experimental evolution of multicellularity. Proc. Natl Acad. Sci. USA 109, 1595–1600 (2012).
pubmed: 22307617 pmcid: 3277146 doi: 10.1073/pnas.1115323109
Burke, M. K., Liti, G. & Long, A. D. Standing genetic variation drives repeatable experimental evolution in outcrossing populations of Saccharomyces cerevisiae. Mol. Biol. Evol. 31, 3228–3239 (2014).
pubmed: 25172959 pmcid: 4245818 doi: 10.1093/molbev/msu256
Franssen, S. U., Kofler, R. & Schlötterer, C. Uncovering the genetic signature of quantitative trait evolution with replicated time series data. Heredity 118, 42–51 (2017).
pubmed: 27848948 doi: 10.1038/hdy.2016.98
Behe, M. J. Experimental evolution, loss-of-function mutations, and “the first rule of adaptive evolution”. Q. Rev. Biol. 85, 419–445 (2010).
pubmed: 21243963 doi: 10.1086/656902
Anderson, J. T., Lee, C.-R., Rushworth, C. A., Colautti, R. I. & Mitchell-Olds, T. Genetic trade-offs and conditional neutrality contribute to local adaptation: genetic basis of local adaptation. Mol. Ecol. 22, 699–708 (2013).
pubmed: 22420446 doi: 10.1111/j.1365-294X.2012.05522.x
Maclean, R. C. Adaptive radiation in microbial microcosms: microbial diversification. J. Evol. Biol. 18, 1376–1386 (2005).
pubmed: 16313450 doi: 10.1111/j.1420-9101.2005.00931.x
Samani, P. & Bell, G. Experimental evolution of the grain of metabolic specialization in yeast. Ecol. Evol. 6, 3912–3922 (2016).
pubmed: 27516854 pmcid: 4972220 doi: 10.1002/ece3.2151
Savolainen, O., Lascoux, M. & Merilä, J. Ecological genomics of local adaptation. Nat. Rev. Genet. 14, 807–820 (2013).
pubmed: 24136507 doi: 10.1038/nrg3522
Barton, N. H. & Cara, M. A. R. D. The evolution of strong reproductive isolation. Evolution 63, 1171–1190 (2009).
pubmed: 19154394 doi: 10.1111/j.1558-5646.2009.00622.x
Flaxman, S. M., Wacholder, A. C., Feder, J. L. & Nosil, P. Theoretical models of the influence of genomic architecture on the dynamics of speciation. Mol. Ecol. 23, 4074–4088 (2014).
pubmed: 24724861 doi: 10.1111/mec.12750
Lowry, D. B., Rockwood, R. C. & Willis, J. H. Ecological reproductive isolation of coast and inland races of Mimulus guttatus. Evolution 62, 2196–2214 (2008).
pubmed: 18637837 doi: 10.1111/j.1558-5646.2008.00457.x
Barton, N. & Bengtsson, B. O.The barrier to genetic exchange between hybridising populations. Heredity 57, 357–376 (1986).
pubmed: 3804765 doi: 10.1038/hdy.1986.135
Nicolaus, M. & Edelaar, P. Comparing the consequences of natural selection, adaptive phenotypic plasticity, and matching habitat choice for phenotype–environment matching, population genetic structure, and reproductive isolation in meta-populations. Ecol. Evol. 8, 3815–3827 (2018).
pubmed: 29721259 pmcid: 5916293 doi: 10.1002/ece3.3816
Smith, J. M. Sympatric speciation. Am. Nat. 100, 637–650 (1966).
doi: 10.1086/282457
Filchak, K. E., Roethele, J. B. & Feder, J. L. Natural selection and sympatric divergence in the apple maggot Rhagoletis pomonella. Nature 407, 739–742 (2000).
pubmed: 11048719 doi: 10.1038/35037578
Flaxman, S. M., Feder, J. L. & Nosil, P. Genetic hitchhiking and the dynamic buildup of genomic divergence during speciation with gene flow. Evolution 67, 2577–2591 (2013).
pubmed: 24033168 doi: 10.1111/evo.12055
Sexton, J. P., Hangartner, S. B. & Hoffmann, A. A. Genetic isolation by environment or distance: which pattern of gene flow is most common? Evolution 68, 1–15 (2014).
pubmed: 24111567 doi: 10.1111/evo.12258
Powell, T. H. Q. et al. Genetic divergence along the speciation continuum: the transition from host race to species in Rhagoletis (diptera: Tephritidae). Evolution 67, 2561–2576 (2013).
pubmed: 24033167 doi: 10.1111/evo.12209
Roux, C. et al. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biol. 14, e2000234 (2016).
pubmed: 28027292 pmcid: 5189939 doi: 10.1371/journal.pbio.2000234
Wright, S. Evolution in Mendelian populations. Genetics 16, 97–159 (1931).
pubmed: 17246615 pmcid: 1201091 doi: 10.1093/genetics/16.2.97
Mayr, E. in Evolution as a Process (eds Huxley, J. S. et al.) 157–180 (Allen & Unwin, 1954).
Bulmer, M. G. Multiple niche polymorphism. Am. Nat. 106, 254–257 (1972).
doi: 10.1086/282765
Fry, J. D. Multilocus models of sympatric speciation: Bush versus Rice versus Felsenstein. Evolution 57, 1735–1746 (2003).
pubmed: 14503616
Nieuwenhuis, B. P. S. et al. Repeated evolution of self-compatibility for reproductive assurance. Nat. Commun. 9, 1639 (2018).
pubmed: 29691402 pmcid: 5915400 doi: 10.1038/s41467-018-04054-6
Curtsinger, J. W., Service, P. M. & Prout, T. Antagonistic pleiotropy, reversal of dominance, and genetic polymorphism. Am. Nat. 144, 210–228 (1994).
doi: 10.1086/285671
Charlesworth, B. & Hughes, K. A. in Evolutionary Genetics: from Molecules to Morphology Vol. 1 (eds Singh, R. S. & Krimbas, C. B.) 369–391 (Cambridge Univ. Press, 2000).
Phillips, P. C. Epistasis—the essential role of gene interactions in the structure and evolution of genetic systems. Nat. Rev. Genet. 9, 855–867 (2008).
pubmed: 18852697 pmcid: 2689140 doi: 10.1038/nrg2452
Carter, A. J. & Nguyen, A. Q. Antagonistic pleiotropy as a widespread mechanism for the maintenance of polymorphic disease alleles. BMC Med. Genet. 12, 160 (2011).
pubmed: 22151998 pmcid: 3254080 doi: 10.1186/1471-2350-12-160
Hedrick, P. W., Ginevan, M. E. & Ewing, E. P. Genetic polymorphism in heterogeneous environments. Annu. Rev. Ecol. Syst. 7, 1–32 (1976).
doi: 10.1146/annurev.es.07.110176.000245
Macnair, M. R. Why the evolution of resistance to anthropogenic toxins normally involves major gene changes: the limits to natural selection. Genetica 84, 213–219 (1991).
doi: 10.1007/BF00127250
Ono, J., Gerstein, A. C. & Otto, S. P. Widespread genetic incompatibilities between first-step mutations during parallel adaptation of Saccharomyces cerevisiae to a common environment. PLoS Biol. 15, e1002591 (2017).
pubmed: 28114370 pmcid: 5256870 doi: 10.1371/journal.pbio.1002591
Blount, Z. D., Lenski, R. E. & Losos, J. B. Contingency and determinism in evolution: replaying life’s tape. Science 362, eaam5979 (2018).
pubmed: 30409860 doi: 10.1126/science.aam5979
Jeffares, D. C. The natural diversity and ecology of fission yeast. Yeast 35, 253–260 (2018).
pubmed: 29084364 doi: 10.1002/yea.3293
Heim, L. Construction of an h
pubmed: 2311128 doi: 10.1007/BF00313243
Forsburg, S. L. Schizosaccharomyces pombe strain maintenance and media. Curr. Protoc. Mol. Biol. 64, 13.15.1–13.15.5 (2003).
doi: 10.1002/0471142727.mb1315s64
Ellis, B. et al. flowCore: flowCore: Basic structures for flow cytometry data. R package version 1.52.1 (2019).
Kassambara, A. & Mundt, F. factoextra: Extract and visualize the results of multivariate data analyses. R package version 3.4.4 https://rdrr.io/cran/factoextra/ (2017).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10 (2011).
doi: 10.14806/ej.17.1.200
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
pubmed: 24695404 pmcid: 4103590 doi: 10.1093/bioinformatics/btu170
Wood, V. et al. The genome sequence of Schizosaccharomyces pombe. Nature 415, 871–880 (2002).
pubmed: 11859360 doi: 10.1038/nature724
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
pubmed: 19451168 pmcid: 2705234 doi: 10.1093/bioinformatics/btp324
McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
pubmed: 20644199 pmcid: 2928508 doi: 10.1101/gr.107524.110
Koboldt, D. C. et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics 25, 2283–2285 (2009).
pubmed: 19542151 pmcid: 2734323 doi: 10.1093/bioinformatics/btp373
Li, H. Toward better understanding of artefacts in variant calling from high-coverage samples. Bioinformatics 30, 2843–2851 (2014).
pubmed: 24974202 pmcid: 4271055 doi: 10.1093/bioinformatics/btu356
Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w
pubmed: 22728672 pmcid: 3679285 doi: 10.4161/fly.19695
Lock, A. et al. PomBase 2018: user-driven reimplementation of the fission yeast database provides rapid and intuitive access to diverse, interconnected information. Nucleic Acids Res. 47, D821–D827 (2019).
pubmed: 30321395 doi: 10.1093/nar/gky961
Nei, M. & Li, W. H. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl Acad. Sci. USA 76, 5269–5273 (1979).
pubmed: 291943 pmcid: 413122 doi: 10.1073/pnas.76.10.5269
Weir, B. S. & Cockerham, C. C.Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).
pubmed: 28563791
Haller, B. C. & Messer, P. W. SLIM 3: forward genetic simulations beyond the Wright–Fisher model. Mol. Biol. Evol. 36, 632–637 (2019).
pubmed: 30517680 pmcid: 6389312 doi: 10.1093/molbev/msy228
Farlow, A. et al. The spontaneous mutation rate in the fission yeast Schizosaccharomyces pombe. Genetics 201, 737–744 (2015).
pubmed: 26265703 pmcid: 4596680 doi: 10.1534/genetics.115.177329
Munz, P., Wolf, K., Kohli, J. & Leupold, U. in Molecular Biology of the Fission Yeast 1–30 (Academic Press, 1989).
Tusso, S., Nieuwenhuis, B. P. S., Weissensteiner, B., Immler, S. & Wolf, J. B. W. Data from: Experimental evolution of adaptive divergence under varying degrees of gene flow. (Zenodo, 2020); https://doi.org/10.5281/ZENODO.4133489

Auteurs

Sergio Tusso (S)

Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany. situssog@gmail.com.
Science for Life Laboratory, Uppsala University, Uppsala, Sweden. situssog@gmail.com.
Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden. situssog@gmail.com.

Bart P S Nieuwenhuis (BPS)

Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany.

Bernadette Weissensteiner (B)

Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany.

Simone Immler (S)

Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden.
School of Biological Sciences, University of East Anglia, Norwich, UK.

Jochen B W Wolf (JBW)

Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilians-Universität Munich, Munich, Germany. j.wolf@bio.lmu.de.
Science for Life Laboratory, Uppsala University, Uppsala, Sweden. j.wolf@bio.lmu.de.
Department of Evolutionary Biology, Uppsala University, Uppsala, Sweden. j.wolf@bio.lmu.de.

Articles similaires

A scenario for an evolutionary selection of ageing.

Tristan Roget, Claire Macmurray, Pierre Jolivet et al.
1.00
Aging Selection, Genetic Biological Evolution Animals Fertility
Biological Evolution History, 20th Century Selection, Genetic History, 19th Century Biology
Animals Lung India Sheep Transcriptome
Lakes Salinity Archaea Bacteria Microbiota

Classifications MeSH