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Open Access Research article

The effects of linkage on comparative estimators of selection

Carmen HS Chan12*, Steven Hamblin12 and Mark M Tanaka12

Author Affiliations

1 School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia

2 Evolution and Ecology Research Centre, University of New South Wales, Sydney, NSW, Australia

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BMC Evolutionary Biology 2013, 13:244  doi:10.1186/1471-2148-13-244

Published: 7 November 2013

Abstract

Background

A major goal of molecular evolution is to determine how natural selection has shaped the evolution of a gene. One approach taken by methods such as KA/KS and the McDonald-Kreitman (MK) test is to compare the frequency of non-synonymous and synonymous changes. These methods, however, rely on the assumption that a change in frequency of one mutation will not affect changes in frequency of other mutations.

Results

We demonstrate that linkage between sites can bias measures of selection based on synonymous and non-synonymous changes. Using forward simulation of a Wright-Fisher process, we show that hitch-hiking of deleterious mutations with advantageous mutations can lead to overestimation of the number of adaptive substitutions, while background selection and clonal interference can distort the site frequency spectrum to obscure the signal for positive selection. We present three diagnostics for detecting these effects of linked selection and apply them to the human influenza (H3N2) hemagglutinin gene.

Conclusion

Various forms of linked selection have characteristic effects on MK-type statistics. The extent of background selection, hitch-hiking and clonal interference can be evaluated using the diagnostic statistics presented here. The diagnostics can also be used to determine how well we expect the MK statistics to perform and whether one form of the statistic may be preferable to another.

Keywords:
KA/KS; McDonald-Kreitman; Linkage; Background selection; Hitch-hiking; Clonal interference