Stable linkage disequilibrium owing to sexual antagonism

Linkage disequilibrium (LD) is an association between genetic loci that is typically transient. Here, we identify a previously overlooked cause of stable LD that may be pervasive: sexual antagonism. This form of selection produces unequal allele frequencies in males and females each generation, which upon admixture at fertilization give rise to an excess of haplotypes that couple male-beneficial with male-beneficial and female-beneficial with female-beneficial alleles. Under sexual antagonism, LD is obtained for all recombination frequencies in the absence of epistasis. The extent of LD is highest at low recombination and for stronger selection. We provide a partition of the total LD into distinct components and compare our result for sexual antagonism with Li and Nei''s model of LD owing to population subdivision. Given the frequent observation of sexually antagonistic selection in natural populations and the number of traits that are often involved, these results suggest a major contribution of sexual antagonism to genomic structure.     

Molecular evolutionary analysis of seminal receptacle sperm storage organ genes of Drosophila melanogaster

Sperm storage organs are common and broadly distributed among animal taxa. However, little is known about how these organs function at the molecular level. Additionally, there is a paucity of knowledge about the evolution of genes expressed in these organs. This investigation is an evolutionary expressed sequence tag (EST) study of genes expressed in the seminal receptacle, one of the sperm storage organs in Drosophila. The incidence of positive selection is higher for the seminal receptacle genes than Drosophila reproductive genes as a whole, but lower than genes associated with the spermatheca, a second type of Drosophila sperm storage organ. By identifying overrepresented classes of proteins and classes for which sperm storage function is suggested by the nature of the proteins, candidate genes were discovered. These candidates belong to protein classes such as muscle contraction, odorant binding and odorant receptor, protease inhibitor and immunity.     

In defence of model‐based inference in phylogeography

Recent papers have promoted the view that model‐based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model‐based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model‐based inference in population genetics.     

Does reproductive isolation evolve faster in larger populations via sexually antagonistic coevolution?

Sexual conflict over reproductive investment can lead to sexually antagonistic coevolution and reproductive isolation. It has been suggested that, unlike most models of allopatric speciation, the evolution of reproductive isolation through sexually antagonistic coevolution will occur faster in large populations as these harbour greater levels of standing genetic variation, receive larger numbers of mutations and experience more intense sexual selection. We tested this in bruchid beetle populations (Callosobruchus maculatus) by manipulating population size and standing genetic variability in replicated lines derived from founders that had been released from sexual conflict for 90 generations. We found that after 19 generations of reintroduced sexual conflict, none of our treatments had evolved significant overall reproductive isolation among replicate lines. However, as predicted, measures of reproductive isolation tended to be greater among larger populations. We discuss our methodology, arguing that reproductive isolation is best examined by performing a matrix of allopatric and sympatric crosses whereas measurement of divergence requires crosses with a tester line.     

PEAS V1.0: a package for elementary analysis of SNP data

We have developed a software package named PEAS to facilitate analyses of large data sets of single nucleotide polymorphisms (SNPs) for population genetics and molecular phylogenetics studies. PEAS reads SNP data in various formats as input and is versatile in data formatting; using PEAS, it is easy to create input files for many popular packages, such as STRUCTURE, frappe, Arlequin, Haploview, LDhat, PLINK, EIGENSOFT, PHASE, fastPHASE, MEGA and PHYLIP. In addition, PEAS fills up several analysis gaps in currently available computer programs in population genetics and molecular phylogenetics. Notably, (i) It calculates genetic distance matrices with bootstrapping for both individuals and populations from genome-wide high-density SNP data, and the output can be streamlined to MEGA and PHYLIP programs for further processing; (ii) It calculates genetic distances from STRUCTURE output and generates MEGA file to reconstruct component trees; (iii) It provides tools to conduct haplotype sharing analysis for phylogenetic studies based on high-density SNP data. To our knowledge, these analyses are not available in any other computer program. PEAS for Windows is freely available for academic users from http://www.picb.ac.cn/~xushua/index.files/Download_PEAS.htm.