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

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 a...

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Bibliographic Details
Published in:Molecular ecology 2010-09, Vol.19 (17), p.3760-3772
Main Authors: Manel, Stephanie, Joost, Stephane, Epperson, Bryan K, Holderegger, Rolf, Storfer, Andrew, Rosenberg, Michael S, Scribner, Kim T, Bonin, Aurelie, Fortin, Marie-Josee
Format: Article
Language:English
Subjects:
Adaptation
Adaptation, Physiological - genetics
Amplified Fragment Length Polymorphism Analysis
computational approach
Ecology - methods
Expressed Sequence Tags
Genetic Variation
Genetics, Population
genome scan
Genomics
Landscape ecology
landscape genomics
local adaptation
Microsatellite Repeats
Models, Statistical
Molecular biology
molecular techniques
Polymorphism, Single Nucleotide
Population genetics
regression analysis
Sampling techniques
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Summary: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.
ISSN:0962-1083
1365-294X
DOI:10.1111/j.1365-294X.2010.04717.x