Adaptive differentiation of Festuca rubra along a climate gradient revealed by molecular markers and quantitative traits
Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
29617461
PubMed Central
PMC5884518
DOI
10.1371/journal.pone.0194670
PII: PONE-D-17-42801
Knihovny.cz E-zdroje
- MeSH
- fenotyp MeSH
- Festuca fyziologie MeSH
- fyziologická adaptace MeSH
- genotyp MeSH
- klimatické změny * MeSH
- kvantitativní znak dědičný * MeSH
- mikrosatelitní repetice genetika MeSH
- populační genetika MeSH
- selekce (genetika) MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Species response to climate change is influenced by predictable (selective) and unpredictable (random) evolutionary processes. To understand how climate change will affect present-day species, it is necessary to assess their adaptive potential and distinguish it from the effects of random processes. This will allow predicting how different genotypes will respond to forecasted environmental change. Space for time substitution experiments are an elegant way to test the response of present day populations to climate variation in real time. Here we assess neutral and putatively adaptive variation in 11 populations of Festuca rubra situated along crossed gradients of temperature and moisture using molecular markers and phenotypic measurements, respectively. By comparing population differentiation in putatively neutral molecular markers and phenotypic traits (QST-FST comparisons), we show the existence of adaptive differentiation in phenotypic traits and their plasticity across the climatic gradient. The observed patterns of differentiation are due to the high genotypic and phenotypic differentiation of the populations from the coldest (and wettest) environment. Finally, we observe statistically significant covariation between markers and phenotypic traits, which is likely caused by isolation by adaptation. These results contribute to a better understanding of the current adaptation and evolutionary potential to face climate change of a widespread species. They can also be extrapolated to understand how the studied populations will adjust to upcoming climate change without going through the lengthy process of phenotyping.
Department of Biology and Ecology Faculty of Science University of Ostrava Ostrava Czech Republic
Department of Botany Faculty of Science Charles University Prague Czech Republic
Institute of Botany Academy of Sciences of the Czech Republic Průhonice Czech Republic
Zobrazit více v PubMed
Drake JM. Population effects of increased climate variation. Proc Biol Sci. 2005;272: 1823–1827. doi: 10.1098/rspb.2005.3148 PubMed DOI PMC
McCarty JP. Ecological Consequences of Recent Climate Change. Conserv Biol. 2001;15: 320–331. doi: 10.1046/j.1523-1739.2001.015002320.x DOI
Hoffmann AA, Sgrò CM. Climate change and evolutionary adaptation. Nature. 2011;470: 479–485. doi: 10.1038/nature09670 PubMed DOI
Chen I-C, Hill JK, Ohlemüller R, Roy DB, Thomas CD. Rapid range shifts of species associated with high levels of climate warming. Science. 2011;333: 1024–1026. doi: 10.1126/science.1206432 PubMed DOI
Franks SJ, Weber JJ, Aitken SN. Evolutionary and plastic responses to climate change in terrestrial plant populations. Evol Appl. 2014;7: 123–139. doi: 10.1111/eva.12112 PubMed DOI PMC
Loarie SR, Duffy PB, Hamilton H, Asner GP, Field CB, Ackerly DD. The velocity of climate change. Nature. 2009;462: 1052–1055. doi: 10.1038/nature08649 PubMed DOI
Kawecki TJ, Ebert D. Conceptual issues in local adaptation. Ecol Lett. 2004;7: 1225–1241.
Pauls SU, Nowak C, Bálint M, Pfenninger M. The impact of global climate change on genetic diversity within populations and species. Mol Ecol. 2013;22: 925–946. doi: 10.1111/mec.12152 PubMed DOI
Sultan SE. Phenotypic plasticity and plant adaptation. Acta Bot Neerlandica. 1995;44: 363–383.
Nicotra AB, Atkin OK, Bonser SP, Davidson AM, Finnegan EJ, Mathesius U, et al. Plant phenotypic plasticity in a changing climate. Trends Plant Sci. 2010;15: 684–692. doi: 10.1016/j.tplants.2010.09.008 PubMed DOI
Schlichting CD. The Evolution of Phenotypic Plasticity in Plants. Annu Rev Ecol Syst. 1986;17: 667–693. doi: 10.1146/annurev.es.17.110186.003315 DOI
Via S. Adaptive phenotypic plasticity: target or by-product of selection in a variable environment? Am Nat. 1993;142: 352–365. doi: 10.1086/285542 PubMed DOI
Springate DA, Scarcelli N, Rowntree J, Kover PX. Correlated response in plasticity to selection for early flowering in Arabidopsis thaliana. J Evol Biol. 2011;24: 2280–2288. doi: 10.1111/j.1420-9101.2011.02360.x PubMed DOI
Davis MB, Shaw RG, Etterson JR. Evolutionary Responses to Changing Climate. Ecology. 2005;86: 1704–1714. doi: 10.1890/03-0788 DOI
Pickett STA. Space-for-Time Substitution as an Alternative to Long-Term Studies Long-Term Studies in Ecology. Springer, New York, NY; 1989. pp. 110–135. doi: 10.1007/978-1-4615-7358-6_5 DOI
Blois JL, Williams JW, Fitzpatrick MC, Jackson ST, Ferrier S. Space can substitute for time in predicting climate-change effects on biodiversity. Proc Natl Acad Sci. 2013;110: 9374–9379. doi: 10.1073/pnas.1220228110 PubMed DOI PMC
Lester RE, Close PG, Barton JL, Pope AJ, Brown SC. Predicting the likely response of data-poor ecosystems to climate change using space-for-time substitution across domains. Glob Change Biol. 2014;20: 3471–3481. PubMed
Meerhoff M. Environmental Warming in Shallow Lakes. A Review of Potential Changes in Community Structure as Evidenced from Space-for-Time Substitution Approaches. 2012;
Merilä J, Hendry AP. Climate change, adaptation, and phenotypic plasticity: the problem and the evidence. Evol Appl. 2014;7: 1–14. doi: 10.1111/eva.12137 PubMed DOI PMC
Merilä J, Crnokrak P. Comparison of genetic differentiation at marker loci and quantitative traits. J Evol Biol. 2001;14: 892–903.
Leinonen T, McCairns RS, O’Hara RB, Merilä J. QST–FST comparisons: evolutionary and ecological insights from genomic heterogeneity. Nat Rev Genet. 2013;14: 179–190. doi: 10.1038/nrg3395 PubMed DOI
Karhunen M, Ovaskainen O, Herczeg G, Merilä J. Bringing habitat information into statistical tests of local adaptation in quantitative traits: a case study of nine-spined sticklebacks. Evolution. 2014;68: 559–568. doi: 10.1111/evo.12268 PubMed DOI
Li S-L, Vasemägi A, Ramula S. Genetic variation facilitates seedling establishment but not population growth rate of a perennial invader. Ann Bot. 2015; mcv145. PubMed PMC
Luo Y, Widmer A, Karrenberg S. The roles of genetic drift and natural selection in quantitative trait divergence along an altitudinal gradient in Arabidopsis thaliana. Heredity. 2015;114: 220–228. doi: 10.1038/hdy.2014.89 PubMed DOI PMC
Skálová H, Pecháčková S, Suzuki J, Herben T, Hara T, Hadincová V, et al. Within population genetic differentiation in traits affecting clonal growth: Festuca rubra in a mountain grassland. J Evol Biol. 1997;10: 383–406. doi: 10.1046/j.1420-9101.1997.10030383.x DOI
Herben T, Krahulec F, Hadincová V, Pecháčková S. Clone-specific response of Festuca rubra to natural variation in biomass and species composition of neighbours. Oikos. 2001;95: 43–52.
Münzbergová Z, Hadincová V, Skálová H, Vandvik V. Genetic differentiation and plasticity interact along temperature and precipitation gradients to determine plant performance under climate change. J Ecol. 2017; doi: 10.1111/1365-2745.12762 DOI
Meineri E, Skarpaas O, Spindelböck J, Bargmann T, Vandvik V. Direct and size-dependent effects of climate on flowering performance in alpine and lowland herbaceous species. J Veg Sci. 2014;25: 275–286. doi: 10.1111/jvs.12062 DOI
Ellstrand NC, Roose ML. Patterns of genotypic diversity in clonal plant species. Am J Bot. 1987;74: 123–131. doi: 10.2307/2444338 DOI
Klanderud K, Vandvik V, Goldberg D. The importance of biotic vs. abiotic drivers of local plant community composition along regional bioclimatic gradients. PloS One. 2015;10: e0130205 doi: 10.1371/journal.pone.0130205 PubMed DOI PMC
Castro S, Münzbergová Z, Raabová J, Loureiro J. Breeding barriers at a diploid–hexaploid contact zone in Aster amellus. Evol Ecol. 2010;25: 795–814. doi: 10.1007/s10682-010-9439-5 PubMed DOI
Govindjee SA. On the relation between the Kautsky effect (Chlorophyll a fluorescence induction) and photosystem II: Basic and applications of the OJIP fluorescence transient. J Photoch Photobio B. 2011;104: 236–257. PubMed
Valladares F, Martinez-Ferri E, Balaguer L, Perez-Corona E, Manrique E. Low leaf-level response to light and nutrients in Mediterranean evergreen oaks: a conservative resource-use strategy? New Phytol. 2000;148: 79–91. PubMed
Valladares F, Sanchez-Gomez D, Zavala MA. Quantitative estimation of phenotypic plasticity: bridging the gap between the evolutionary concept and its ecological applications. J Ecol. 2006;94: 1103–1116. doi: 10.1111/j.1365-2745.2006.01176.x DOI
FU Y-B, Qiu J, Peterson GW, Willms WD, Wilmshurst JF. Characterization of microsatellite markers for rough fescue species (Festuca spp.). Mol Ecol Resour. 2006;6: 894–896.
Lauvergeat V, Barre P, Bonnet M, Ghesquiere M. Sixty simple sequence repeat markers for use in the Festuca–Lolium complex of grasses. Mol Ecol Resour. 2005;5: 401–405.
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria: 2014;2014 Available: http://www.R-project.org/.
Porth I, Klapste J, McKown AD, La Mantia J, Guy RD, Ingvarsson PK, et al. Evolutionary Quantitative Genomics of Populus trichocarpa. Plos One. 2015;10: e0142864 doi: 10.1371/journal.pone.0142864 PubMed DOI PMC
Henderson CR. Applications of Linear Models in Animal Breeding. University of Guelph; 1984.
Butler DG, Cullis BR, Gilmour AR, Gogel BJ. ASReml-R reference manual. State Qld Dep Prim Ind Fish Brisb. 2009; Available: http://discoveryfoundation.org.uk/downloads/asreml/release3/asreml-R.pdf
Loiselle BA, Sork VL, Nason J, Graham C. Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). Am J Bot. 1995; 1420–1425.
Hardy OJ, Vekemans X. SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Resour. 2002;2: 618–620.
Leinonen T, Cano JM, Mäkinen H, Merilä J. Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks. J Evol Biol. 2006;19: 1803–1812. doi: 10.1111/j.1420-9101.2006.01182.x PubMed DOI
Brommer JE. Whither PST? The approximation of QST by PST in evolutionary and conservation biology. J Evol Biol. 2011;24: 1160–1168. doi: 10.1111/j.1420-9101.2011.02268.x PubMed DOI
Whitlock MC, Guillaume F. Testing for Spatially Divergent Selection: Comparing QST to FST. Genetics. 2009;183: 1055–1063. doi: 10.1534/genetics.108.099812 PubMed DOI PMC
Lind MI, Ingvarsson PK, Johansson H, Hall D, Johansson F. Gene Flow and Selection on Phenotypic Plasticity in an Island System of Rana Temporaria. Evolution. 2011;65: 684–697. doi: 10.1111/j.1558-5646.2010.01122.x PubMed DOI
Lewontin RC, Krakauer J. Distribution of Gene Frequency as a Test of the Theory of the Selective Neutrality of Polymorphisms. Genetics. 1973;74: 175–195. PubMed PMC
Michalakis Y, Excoffier L. A generic estimation of population subdivision using distances between alleles with special reference for microsatellite loci. Genetics. 1996;142: 1061–1064. PubMed PMC
Edelaar PIM, Burraco P, GOMEZ-MESTRE I. Comparisons between QST and FST—how wrong have we been? Mol Ecol. 2011;20: 4830–4839. doi: 10.1111/j.1365-294X.2011.05333.x PubMed DOI
Ellegren H. Microsatellites: simple sequences with complex evolution. Nat Rev Genet. 2004;5: 435–445. doi: 10.1038/nrg1348 PubMed DOI
Dolédec S, Chessel D. Co-inertia analysis: an alternative method for studying species–environment relationships. Freshw Biol. 1994;31: 277–294.
Dray S, Chessel D, Thioulouse J. Co-inertia analysis and the linking of ecological data tables. Ecology. 2003;84: 3078–3089.
Jarraud S, Mougel C, Thioulouse J, Lina G, Meugnier H, Forey F, et al. Relationships between Staphylococcus aureus Genetic Background, Virulence Factors, agr Groups (Alleles), and Human Disease. Infect Immun. 2002;70: 631–641. doi: 10.1128/IAI.70.2.631-641.2002 PubMed DOI PMC
Dray S, Dufour A-B, others. The ade4 package: implementing the duality diagram for ecologists. J Stat Softw. 2007;22: 1–20.
Jombart T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008;24: 1403–1405. doi: 10.1093/bioinformatics/btn129 PubMed DOI
Clark LV, Jasieniuk M. POLYSAT: an R package for polyploid microsatellite analysis. Mol Ecol Resour. 2011;11: 562–566. doi: 10.1111/j.1755-0998.2011.02985.x PubMed DOI
Esselink GD, Nybom H, Vosman B. Assignment of allelic configuration in polyploids using the MAC-PR (microsatellite DNA allele counting-peak ratios) method. TAG Theor Appl Genet Theor Angew Genet. 2004;109: 402–408. doi: 10.1007/s00122-004-1645-5 PubMed DOI
Dufresne F, Stift M, Vergilino R, Mable BK. Recent progress and challenges in population genetics of polyploid organisms: an overview of current state-of-the-art molecular and statistical tools. Mol Ecol. 2014;23: 40–69. doi: 10.1111/mec.12581 PubMed DOI
Pons O, Petit RJ. Measwring and testing genetic differentiation with ordered versus unordered alleles. Genetics. 1996;144: 1237–1245. PubMed PMC
Motro U, Thomson G. On heterozygosity and the effective size of populations subject to size changes. Evolution. 1982;36: 1059–1066. doi: 10.1111/j.1558-5646.1982.tb05474.x PubMed DOI
Ohta T, Kimura M. A model of mutation appropriate to estimate the number of electrophoretically detectable alleles in a finite population. Genet Res. 1973;22: 201–204. PubMed
Hetherington AM, Woodward FI. The role of stomata in sensing and driving environmental change. Nature. 2003;424: 901 doi: 10.1038/nature01843 PubMed DOI
Zhang L, Niu H, Wang S, Zhu X, Luo C, Li Y, et al. Gene or environment? Species-specific control of stomatal density and length. Ecol Evol. 2012;2: 1065–1070. doi: 10.1002/ece3.233 PubMed DOI PMC
Raven JA. Selection pressures on stomatal evolution. New Phytol. 2002;153: 371–386. doi: 10.1046/j.0028-646X.2001.00334.x PubMed DOI
Beerling DJ, Chaloner WG, Huntley B, Pearson JA, Tooley MJ. Stomatal density responds to the glacial cycle of environmental change. Proc R Soc Lond B. 1993;251: 133–138. doi: 10.1098/rspb.1993.0019 DOI
Aykanat T, Johnston SE, Orell P, Niemelä E, Erkinaro J, Primmer CR. Low but significant genetic differentiation underlies biologically meaningful phenotypic divergence in a large Atlantic salmon population. Mol Ecol. 2015;24: 5158–5174. doi: 10.1111/mec.13383 PubMed DOI
García-Navas V, Ferrer ES, Sanz JJ, Ortego J. The role of immigration and local adaptation on fine-scale genotypic and phenotypic population divergence in a less mobile passerine. J Evol Biol. 2014;27: 1590–1603. doi: 10.1111/jeb.12412 PubMed DOI
Gömöry D, Ditmarová L, Hrivnák M, Jamnická G, Kmet’ J, Krajmerová D, et al. Differentiation in phenological and physiological traits in European beech (Fagus sylvatica L.). Eur J For Res. 2015;134: 1075–1085.
Michalski SG, Durka W. Separation in flowering time contributes to the maintenance of sympatric cryptic plant lineages. Ecol Evol. 2015;5: 2172–2184. doi: 10.1002/ece3.1481 PubMed DOI PMC
Pujol B, Wilson AJ, Ross RIC, Pannell JR. Are QST–FST comparisons for natural populations meaningful? Mol Ecol. 2008;17: 4782–4785. doi: 10.1111/j.1365-294X.2008.03958.x PubMed DOI
Münzbergová Z, Hadincová V. Transgenerational plasticity as an important mechanism affecting response of clonal species to changing climate. Ecol Evol. 2017; Available: http://onlinelibrary.wiley.com/doi/10.1002/ece3.3105/full PubMed DOI PMC
McKay JK, Latta RG. Adaptive population divergence: markers, QTL and traits. Trends Ecol Evol. 2002;17: 285–291. doi: 10.1016/S0169-5347(02)02478-3 DOI
Nosil P, Funk DJ, Ortiz-Barrientos D. Divergent selection and heterogeneous genomic divergence. Mol Ecol. 2009;18: 375–402. doi: 10.1111/j.1365-294X.2008.03946.x PubMed DOI
Gonzalo-Turpin H, Hazard L. Local adaptation occurs along altitudinal gradient despite the existence of gene flow in the alpine plant species Festuca eskia. J Ecol. 2009;97: 742–751. doi: 10.1111/j.1365-2745.2009.01509.x DOI
Körner C, Neumayer M, Menendez-Riedl SP, Smeets-Scheel A. Functional morphology of mountain plants. Flora. 1989;182: 353–383.
Stenström A, Jónsdóttir IS, Augner M. Genetic and environmental effects on morphology in clonal sedges in the Eurasian Arctic. Am J Bot. 2002;89: 1410–1421. doi: 10.3732/ajb.89.9.1410 PubMed DOI
Debat V, David P. Mapping phenotypes: canalization, plasticity and developmental stability. Trends Ecol Evol. 2001;16: 555–561.
Nicotra AB, Segal DL, Hoyle GL, Schrey AW, Verhoeven KJF, Richards CL. Adaptive plasticity and epigenetic variation in response to warming in an Alpine plant. Ecol Evol. 2015;5: 634–647. doi: 10.1002/ece3.1329 PubMed DOI PMC
De Witte LC, Stöcklin J. Longevity of clonal plants: why it matters and how to measure it. Ann Bot. 2010;106: 859–870. doi: 10.1093/aob/mcq191 PubMed DOI PMC
Ahmad P, Prasad MNV. Abiotic stress responses in plants: metabolism, productivity and sustainability. Springer Science & Business Media; 2011.
Brommer JE, Merilä J, Sheldon BC, Gustafsson L. Natural selection and genetic variation for reproductive reaction norms in a wild bird population. Evol Int J Org Evol. 2005;59: 1362–1371. PubMed
Rogell B, Dannewitz J, Palm S, Petersson E, Dahl J, Prestegaard T, et al. Strong divergence in trait means but not in plasticity across hatchery and wild populations of sea-run brown trout Salmo trutta. Mol Ecol. 2012;21: 2963–2976. doi: 10.1111/j.1365-294X.2012.05590.x PubMed DOI
De Kort H, Vander Mijnsbrugge K, Vandepitte K, Mergeay J, Ovaskainen O, Honnay O. Evolution, plasticity and evolving plasticity of phenology in the tree species Alnus glutinosa. J Evol Biol. 2016;29: 253–264. doi: 10.1111/jeb.12777 PubMed DOI
De Jong G. Evolution of phenotypic plasticity: patterns of plasticity and the emergence of ecotypes. New Phytol. 2005;166: 101–118. doi: 10.1111/j.1469-8137.2005.01322.x PubMed DOI
Kim Y, Stephan W. Joint Effects of Genetic Hitchhiking and Background Selection on Neutral Variation. Genetics. 2000;155: 1415–1427. PubMed PMC
Barton NH. Genetic hitchhiking. Philos Trans R Soc Lond B Biol Sci. 2000;355: 1553–1562. doi: 10.1098/rstb.2000.0716 PubMed DOI PMC
Mosca E, Eckert AJ, Di Pierro EA, Rocchini D, La Porta N, Belletti P, et al. The geographical and environmental determinants of genetic diversity for four alpine conifers of the European Alps. Mol Ecol. 2012;21: 5530–5545. doi: 10.1111/mec.12043 PubMed DOI
Hanssen-Bauer I, Achberger C, Benestad RE, Chen D, Førland EJ. Statistical downscaling of climate scenarios over Scandinavia. Clim Res. 2005;29: 255–268.
Evolutionary Rescue as a Mechanism Allowing a Clonal Grass to Adapt to Novel Climates