If you are seeing this message, you may be experiencing temporary network problems. Please wait a few minutes and refresh the page. If the problem persists, you may wish to report it to your local Network Manager.
It is also possible that your web browser is not configured or not able to display style sheets. In this case, although the visual presentation will be degraded, the site should continue to be functional. We recommend using the latest version of Microsoft or Mozilla web browser to help minimise these problems.
Wiley InterScience | |||||||||
![]() Molecular EcologyVolume 14 Issue 3, Pages 671 - 688 Published Online: 14 Jan 2005 © 2010 Blackwell Publishing Ltd
Abstract | References | Full Text: HTML, PDF (Size: 339K) | Related Articles | Citation Tracking INVITED REVIEW Using genome scans of DNA polymorphism to infer adaptive population divergence Copyright © 2005 Blackwell Publishing Ltd KEYWORDS adaptation • genomics • natural selection • neutral theory • population genomics • positive selection • QTL • speciation Abstract
Elucidating the genetic basis of adaptive population divergence is a goal of central importance in evolutionary biology. In principle, it should be possible to identify chromosomal regions involved in adaptive divergence by screening genome-wide patterns of DNA polymorphism to detect the locus-specific signature of positive directional selection. In the case of spatially separated populations that inhabit different environments or sympatric populations that exploit different ecological niches, it is possible to identify loci that underlie divergently selected traits by comparing relative levels of differentiation among large numbers of unlinked markers. In this review I first address the question of whether diversifying selection on polygenic traits can be expected to produce predictable patterns of allelic variation at the underlying quantitative trait loci (QTL), and whether the locus-specific effects of selection can be reliably detected against the genome-wide backdrop of stochastic variability. I then review different approaches that have been developed to identify loci involved in adaptive population divergence and I discuss the relative merits of model-based approaches that rely on assumptions about population structure vs. model-free approaches that are based on empirical distributions of summary statistics. Finally, I consider the evolutionary and functional insights that might be gained by conducting genome scans for loci involved in adaptive population divergence. Received 16 September 2004; revision received 18 November 2004; accepted 18 November 2004 |