Literature DB >> 20723056

Perspectives on the use of landscape genetics to detect genetic adaptive variation in the field.

Stéphanie Manel1, Stéphane Joost, Bryan K Epperson, Rolf Holderegger, Andrew Storfer, Michael S Rosenberg, Kim T Scribner, Aurélie Bonin, Marie-Josée Fortin.   

Abstract

Understanding the genetic basis of species adaptation in the context of global change poses one of the greatest challenges of this century. Although we have begun to understand the molecular basis of adaptation in those species for which whole genome sequences are available, the molecular basis of adaptation is still poorly understood for most non-model species. In this paper, we outline major challenges and future research directions for correlating environmental factors with molecular markers to identify adaptive genetic variation, and point to research gaps in the application of landscape genetics to real-world problems arising from global change, such as the ability of organisms to adapt over rapid time scales. High throughput sequencing generates vast quantities of molecular data to address the challenge of studying adaptive genetic variation in non-model species. Here, we suggest that improvements in the sampling design should consider spatial dependence among sampled individuals. Then, we describe available statistical approaches for integrating spatial dependence into landscape analyses of adaptive genetic variation.

Mesh:

Year:  2010        PMID: 20723056     DOI: 10.1111/j.1365-294X.2010.04717.x

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  44 in total

1.  Environmental patterns are imposed on the population structure of Escherichia coli after fecal deposition.

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2.  Harnessing genomics for delineating conservation units.

Authors:  W Chris Funk; John K McKay; Paul A Hohenlohe; Fred W Allendorf
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3.  A new eigenfunction spatial analysis describing population genetic structure.

Authors:  José Alexandre Felizola Diniz-Filho; João Vitor Barnez P L Diniz; Thiago Fernando Rangel; Thannya Nascimento Soares; Mariana Pires de Campos Telles; Rosane Garcia Collevatti; Luis Mauricio Bini
Journal:  Genetica       Date:  2013-10-27       Impact factor: 1.082

4.  Altitudinal and climatic adaptation is mediated by flowering traits and FRI, FLC, and PHYC genes in Arabidopsis.

Authors:  Belén Méndez-Vigo; F Xavier Picó; Mercedes Ramiro; José M Martínez-Zapater; Carlos Alonso-Blanco
Journal:  Plant Physiol       Date:  2011-10-11       Impact factor: 8.340

5.  Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations.

Authors:  K Mdladla; E F Dzomba; F C Muchadeyi
Journal:  Heredity (Edinb)       Date:  2018-02-09       Impact factor: 3.821

6.  Disease swamps molecular signatures of genetic-environmental associations to abiotic factors in Tasmanian devil (Sarcophilus harrisii) populations.

Authors:  Alexandra K Fraik; Mark J Margres; Brendan Epstein; Soraia Barbosa; Menna Jones; Sarah Hendricks; Barbara Schönfeld; Amanda R Stahlke; Anne Veillet; Rodrigo Hamede; Hamish McCallum; Elisa Lopez-Contreras; Samantha J Kallinen; Paul A Hohenlohe; Joanna L Kelley; Andrew Storfer
Journal:  Evolution       Date:  2020-06-03       Impact factor: 3.694

7.  Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Authors:  Stéphanie Manel; Felix Gugerli; Wilfried Thuiller; Nadir Alvarez; Pierre Legendre; Rolf Holderegger; Ludovic Gielly; Pierre Taberlet
Journal:  Mol Ecol       Date:  2012-06-10       Impact factor: 6.185

Review 8.  Evolutionary genetics of plant adaptation.

Authors:  Jill T Anderson; John H Willis; Thomas Mitchell-Olds
Journal:  Trends Genet       Date:  2011-07       Impact factor: 11.639

9.  Multi-Approach Analysis Reveals Local Adaptation in a Widespread Forest Tree of Reunion Island.

Authors:  Edith Garot; Stephane Dussert; Fr D Ric Domergue; Thierry Jo T; Isabelle Fock-Bastide; Marie-Christine Combes; Philippe Lashermes
Journal:  Plant Cell Physiol       Date:  2021-05-11       Impact factor: 4.927

10.  Testing for associations between loci and environmental gradients using latent factor mixed models.

Authors:  Eric Frichot; Sean D Schoville; Guillaume Bouchard; Olivier François
Journal:  Mol Biol Evol       Date:  2013-03-29       Impact factor: 16.240

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