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Genetics, Vol. 168, 265-279, September 2004, Copyright © 2004
doi:10.1534/genetics.103.025494
Identification of a Locus Under Complex Positive Selection in Drosophila simulans by Haplotype Mapping and Composite-Likelihood Estimation
Colin D. Meiklejohn*,1,
Yuseob Kim
,2,
Daniel L. Hartl* and
John Parsch
* Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853
Department of Biology II, Section of Evolutionary Biology, University of Munich (LMU), 80333 Munich, Germany
1 Corresponding author: Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Ave., Cambridge, MA 02138.
E-mail: cmeiklejohn{at}oeb.harvard.edu
The recent action of positive selection is expected to influence patterns of intraspecific DNA sequence variation in chromosomal regions linked to the selected locus. These effects include decreased polymorphism, increased linkage disequilibrium, and an increased frequency of derived variants. These effects are all expected to dissipate with distance from the selected locus due to recombination. Therefore, in regions of high recombination, it should be possible to localize a target of selection to a relatively small interval. Previously described patterns of intraspecific variation in three tandemly arranged, testes-expressed genes (janusA, janusB, and ocnus) in Drosophila simulans included all three of these features. Here we expand the original sample and also survey nucleotide polymorphism at three neighboring loci. On the basis of recombination events between derived and ancestral alleles, we localize the target of selection to a 1.5-kb region surrounding janusB. A composite-likelihood-ratio test based on the spatial distribution and frequency of derived polymorphic variants corroborates this result and provides an estimate of the strength of selection. However, the data are difficult to reconcile with the simplest model of positive selection, whereas a new composite-likelihood method suggests that the data are better described by a model in which the selected allele has not yet gone to fixation.
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