Genic distribution modelling predicts adaptation of the bank vole to climate change

. 2022 Sep 16 ; 5 (1) : 981. [epub] 20220916

Jazyk angličtina Země Anglie, Velká Británie Médium electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid36114276
Odkazy

PubMed 36114276
PubMed Central PMC9481625
DOI 10.1038/s42003-022-03935-3
PII: 10.1038/s42003-022-03935-3
Knihovny.cz E-zdroje

The most likely pathway for many species to survive future climate change is by pre-existing trait variation providing a fitness advantage under the new climate. Here we evaluate the potential role of haemoglobin (Hb) variation in bank voles under future climate change. We model gene-climate relationships for two functionally distinct Hb types, HbS and HbF, which have a north-south distribution in Britain presenting an unusually tractable system linking genetic variation in physiology to geographical and temporal variation in climate. Projections to future climatic conditions suggest a change in relative climatic suitability that would result in HbS being displaced by HbF in northern Britain. This would facilitate local adaptation to future climate-without Hb displacement, populations in northern Britain would likely be suboptimally adapted because their Hb would not match local climatic conditions. Our study shows how pre-existing physiological differences can influence the adaptive capacity of species to climate change.

Zobrazit více v PubMed

Davis MB, Shaw RG. Range shifts and adaptive responses to Quaternary climate change. Science. 2001;292:673–679. doi: 10.1126/science.292.5517.673. PubMed DOI

Parmesan C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst. 2006;37:637–669. doi: 10.1146/annurev.ecolsys.37.091305.110100. DOI

Hewitt G. The genetic legacy of the Quaternary ice ages. Nature. 2000;405:907–913. doi: 10.1038/35016000. PubMed DOI

Williams JE, Blois JL. Range shifts in response to past and future climate change: can climate velocities and species’ dispersal capabilities explain variation in mammalian range shifts? J. Biogeogr. 2018;45:2175–2189. doi: 10.1111/jbi.13395. DOI

Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 2003;421:37–42. doi: 10.1038/nature01286. PubMed DOI

Thomas CD. Climate, climate change and range boundaries. Divers. Distrib. 2010;16:488–495. doi: 10.1111/j.1472-4642.2010.00642.x. DOI

Bradshaw AD, McNeilly T. Evolutionary response to global climatic change. Ann. Bot. 1991;67:5–14. doi: 10.1093/oxfordjournals.aob.a088209. DOI

Harter DEV, et al. Impacts of global climate change on the floras of oceanic islands—projections, implications and current knowledge. Perspect. Plant Ecol. Evol. Syst. 2015;17:160–183. doi: 10.1016/j.ppees.2015.01.003. DOI

Veron S, Haevermans T, Govaerts R, Mouchet M, Pellens R. Distribution and relative age of endemism across islands worldwide. Sci. Rep. 2019;9:1–12. doi: 10.1038/s41598-018-37186-2. PubMed DOI PMC

Román-Palacios C, Wiens JJ. Recent responses to climate change reveal the drivers of species extinction and survival. Proc. Natl Acad. Sci. USA. 2020;117:4211–4217. doi: 10.1073/pnas.1913007117. PubMed DOI PMC

Jump AS, Peñuelas J. Running to stand still: adaptation and the response of plants to rapid climate change. Ecol. Lett. 2005;8:1010–1020. doi: 10.1111/j.1461-0248.2005.00796.x. PubMed DOI

Freeman BG, Scholer MN, Ruiz-Gutierrez V, Fitzpatrick JW. Climate change causes upslope shifts and mountaintop extirpations in a tropical bird community. Proc. Natl Acad. Sci. USA. 2018;115:11982–11987. doi: 10.1073/pnas.1804224115. PubMed DOI PMC

Gilbert KJ, Whitlock MC. The genetics of adaptation to discrete heterogeneous environments: frequent mutation or large-effect alleles can allow range expansion. J. Evol. Biol. 2017;30:591–602. doi: 10.1111/jeb.13029. PubMed DOI

Christmas MJ, Breed MF, Lowe AJ. Constraints to and conservation implications for climate change adaptation in plants. Conserv. Genet. 2015;17:305–320. doi: 10.1007/s10592-015-0782-5. DOI

Barrett RDH, Schluter D. Adaptation from standing genetic variation. Trends Ecol. Evol. 2008;23:38–44. doi: 10.1016/j.tree.2007.09.008. PubMed DOI

Lai YT, et al. Standing genetic variation as the predominant source for adaptation of a songbird. Proc. Natl Acad. Sci. USA. 2019;116:2152–2157. doi: 10.1073/pnas.1813597116. PubMed DOI PMC

Hoban S, et al. Finding the genomic basis of local adaptation: Pitfalls, practical solutions, and future directions. Am. Nat. 2016;188:379–397. doi: 10.1086/688018. PubMed DOI PMC

Hoffmann AA, Sgrò CM. Climate change and evolutionary adaptation. Nature. 2011;470:479–485. doi: 10.1038/nature09670. PubMed DOI

Catullo RA, Llewelyn J, Phillips BL, Moritz CC. The potential for rapid evolution under anthropogenic climate change. Curr. Biol. 2019;29:R996–R1007. doi: 10.1016/j.cub.2019.08.028. PubMed DOI

Botkin DB, et al. Forecasting the effects of global warming on biodiversity. BioScience. 2007;57:227–236. doi: 10.1641/B570306. DOI

Wiens JA, Stralberg D, Jongsomjit D, Howell CA, Snyder MA. Niches, models, and climate change: assessing the assumptions and uncertainties. Proc. Natl Acad. Sci. USA. 2009;106:19729–19736. doi: 10.1073/pnas.0901639106. PubMed DOI PMC

Smith AB, Godsoe W, Rodríguez-Sánchez F, Wang HH, Warren D. Niche estimation above and below the species level. Trends Ecol. Evol. 2019;34:260–273. doi: 10.1016/j.tree.2018.10.012. PubMed DOI

Waldvogel A-M, et al. Evolutionary genomics can improve prediction of species’ responses to climate change. Evol. Lett. 2020;4:4–18. doi: 10.1002/evl3.154. PubMed DOI PMC

Razgour O, et al. An integrated framework to identify wildlife populations under threat from climate change. Mol. Ecol. Resour. 2018;18:18–31. doi: 10.1111/1755-0998.12694. PubMed DOI PMC

Razgour O, et al. Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections. Proc. Natl Acad. Sci. USA. 2019;116:10418–10423. doi: 10.1073/pnas.1820663116. PubMed DOI PMC

Aguirre-Liguori JA, Ramírez-Barahona S, Tiffin P, Eguiarte LE. Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize. Proc. R. Soc. B. 2019;286:20190486. doi: 10.1098/rspb.2019.0486. PubMed DOI PMC

Evans TG, Diamond SE, Kelly MW. Mechanistic species distribution modelling as a link between physiology and conservation. Conserv. Physiol. 2015;3:cov056. doi: 10.1093/conphys/cov056. PubMed DOI PMC

Hall SJG. Haemoglobin polymorphism in the bank vole, Clethrionomys glareolus, in Britain. J. Zool. 1979;187:153–160. doi: 10.1111/j.1469-7998.1979.tb03939.x. DOI

Kotlík P, et al. Adaptive phylogeography: functional divergence between haemoglobins derived from different glacial refugia in the bank vole. Proc. R. Soc. B. 2014;281:20140021. doi: 10.1098/rspb.2014.0021. PubMed DOI PMC

Searle JB, et al. The Celtic fringe of Britain: Insights from small mammal phylogeography. Proc. R. Soc. B. 2009;276:4287–4294. doi: 10.1098/rspb.2009.1422. PubMed DOI PMC

Escalante MA, Horníková M, Marková S, Kotlík P. Niche differentiation in a postglacial colonizer, the bank vole Clethrionomys glareolus. Ecol. Evol. 2021;11:8054–8070. doi: 10.1002/ece3.7637. PubMed DOI PMC

Reischl E, Dafre AL, Franco JL, Wilhelm Filho D. Distribution, adaptation and physiological meaning of thiols from vertebrate hemoglobins. Comp. Biochem. Physiol. Part C. Toxicol. Pharmacol. 2007;146:22–53. doi: 10.1016/j.cbpc.2006.07.015. PubMed DOI

Storz JF, Wheat CW. Integrating evolutionary and functional approaches to infer adaptation at specific loci. Evolution. 2010;64:2489–2509. doi: 10.1111/j.1558-5646.2010.01044.x. PubMed DOI PMC

Rossi R, et al. Different metabolizing ability of thiol reactants in human and rat blood. Biochemical and pharmacological implications. J. Biol. Chem. 2001;276:7004–7010. doi: 10.1074/jbc.M005156200. PubMed DOI

Vitturi DA, et al. Antioxidant functions for the hemoglobin β93 cysteine residue in erythrocytes and in the vascular compartment in vivo. Free Radic. Biol. Med. 2013;55:119–129. doi: 10.1016/j.freeradbiomed.2012.11.003. PubMed DOI PMC

Petersen AG, et al. Hemoglobin polymerization via disulfide bond formation in the hypoxia-tolerant turtle Trachemys scripta: Implications for antioxidant defense and O2 transport. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2018;314:R84–R93. doi: 10.1152/ajpregu.00024.2017. PubMed DOI

Paital B, et al. Longevity of animals under reactive oxygen species stress and disease susceptibility due to global warming. World J. Biol. Chem. 2016;7:110–127. doi: 10.4331/wjbc.v7.i1.110. PubMed DOI PMC

Jacobs PJ, Oosthuizen MK, Mitchell C, Blount JD, Bennett NC. Heat and dehydration induced oxidative damage and antioxidant defenses following incubator heat stress and a simulated heat wave in wild caught four-striped field mice Rhabdomys dilectus. PLoS One. 2020;15:e0242279. doi: 10.1371/journal.pone.0242279. PubMed DOI PMC

Kotlík P, Marková S, Horníková M, Escalante MA, Searle JB. The bank vole (Clethrionomys glareolus) as a model system for adaptive phylogeography in the European theater. Front. Ecol. Evol. 2022;10:866605. doi: 10.3389/fevo.2022.866605. DOI

Strážnická M, Marková S, Searle JB, Kotlík P. Playing hide-and-seek in beta-globin genes: Gene conversion transferring a beneficial mutation between differentially expressed gene guplicates. Genes. 2018;9:492. doi: 10.3390/genes9100492. PubMed DOI PMC

Stocker, T. Climate Change 2013: the Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2013).

Araújo MB, Pearson RG, Thuiller W, Erhard M. Validation of species-climate impact models under climate change. Glob. Chang. Biol. 2005;11:1504–1513. doi: 10.1111/j.1365-2486.2005.01000.x. DOI

Peterson AT, Papeş M, Soberón J. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Modell. 2008;213:63–72. doi: 10.1016/j.ecolmodel.2007.11.008. DOI

Warren DL, Glor RE, Turelli M. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution. 2008;62:2868–2883. doi: 10.1111/j.1558-5646.2008.00482.x. PubMed DOI

Warren DL, et al. ENMTools 1.0: an R package for comparative ecological biogeography. Ecography. 2021;44:504–511. doi: 10.1111/ecog.05485. DOI

Mayes J, Wheeler D. Regional weather and climates of the British Isles—part 1: introduction. Weather. 2013;68:3–8. doi: 10.1002/wea.2041. DOI

Kotlík P, Marková S, Konczal M, Babik W, Searle JB. Genomics of end-Pleistocene population replacement in a small mammal. Proc. R. Soc. B. 2018;285:20172624. doi: 10.1098/rspb.2017.2624. PubMed DOI PMC

Capblancq T, Fitzpatrick MC, Bay RA, Exposito-Alonso M, Keller SR. Genomic prediction of (mal)adaptation across current and future climatic landscapes. Annu. Rev. Ecol. Evol. Syst. 2020;51:245–269. doi: 10.1146/annurev-ecolsys-020720-042553. DOI

Benito Garzón M, Robson TM, Hampe A. ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity. N. Phytol. 2019;222:1757–1765. doi: 10.1111/nph.15716. PubMed DOI

Wisz MS, et al. Effects of sample size on the performance of species distribution models. Divers. Distrib. 2008;14:763–773. doi: 10.1111/j.1472-4642.2008.00482.x. DOI

Phillips, S. J., Dudík, M. & Schapire, R. E. A maximum entropy approach to species distribution modeling. in Twenty-first International Conference on Machine Learning - ICML ’04 9, 83 (ACM Press, 2004).

Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 2005;25:1965–1978. doi: 10.1002/joc.1276. DOI

Zeng Y, Low BW, Yeo DCJ. Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish. Ecol. Modell. 2016;341:5–13. doi: 10.1016/j.ecolmodel.2016.09.019. DOI

Warren DL, Seifert SN. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol. Appl. 2011;21:335–342. doi: 10.1890/10-1171.1. PubMed DOI

Warren DL, Glor RE, Turelli M. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography. 2010;33:607–611. doi: 10.1111/j.1600-0587.2009.06041.x. DOI

Gent PR, et al. The community climate system model version 4. J. Clim. 2011;24:4973–4991. doi: 10.1175/2011JCLI4083.1. DOI

Dufresne JL, et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn. 2013;40:2123–2165. doi: 10.1007/s00382-012-1636-1. DOI

Watanabe S, et al. MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev. 2011;4:845–872. doi: 10.5194/gmd-4-845-2011. DOI

Giorgetta MA, et al. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Model. Earth Syst. 2013;5:572–597. doi: 10.1002/jame.20038. DOI

Schoener TW. The anolis lizards of Bimini: resource partitioning in a complex fauna. Ecology. 1968;49:704–726. doi: 10.2307/1935534. DOI

Nejnovějších 20 citací...

Zobrazit více v
Medvik | PubMed

Genetic admixture drives climate adaptation in the bank vole

. 2024 Jul 15 ; 7 (1) : 863. [epub] 20240715

Local adaptation and future climate vulnerability in a wild rodent

. 2023 Nov 29 ; 14 (1) : 7840. [epub] 20231129

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...