RT Journal Article SR Electronic T1 Full-genome evolutionary histories of selfing, splitting and selection in Caenorhabditis JF bioRxiv FD Cold Spring Harbor Laboratory SP 011502 DO 10.1101/011502 A1 Cristel G. Thomas A1 Wei Wang A1 Richard Jovelin A1 Rajarshi Ghosh A1 Tatiana Lomasko A1 Quang Trinh A1 Leonid Kruglyak A1 Lincoln D. Stein A1 Asher D. Cutter YR 2014 UL http://biorxiv.org/content/early/2014/11/18/011502.abstract AB The nematode Caenorhabditis briggsae is a model for comparative developmental evolution with C. elegans. Worldwide collections of C. briggsae have implicated an intriguing history of divergence among genetic groups separated by latitude, or by restricted geography, that is being exploited to dissect the genetic basis to adaptive evolution and reproductive incompatibility. And yet, the genomic scope and timing of population divergence is unclear. We performed high-coverage whole-genome sequencing of 37 wild isolates of the nematode C. briggsae and applied a pairwise sequentially Markovian coalescent (PSMC) model to 703 combinations of genomic haplotypes to draw inferences about population history, the genomic scope of natural selection, and to compare with 40 wild isolates of C. elegans. We estimate that a diaspora of at least 6 distinct C. briggsae lineages separated from one another approximately 200 thousand generations ago, including the ‘Temperate’ and ‘Tropical’ phylogeographic groups that dominate most samples from around the world. Moreover, an ancient population split in its history 2 million generations ago, coupled with only rare gene flow among lineage groups, validates this system as a model for incipient speciation. Low versus high recombination regions of the genome give distinct signatures of population size change through time, indicative of widespread effects of selection on highly linked portions of the genome owing to extreme inbreeding by self-fertilization. Analysis of functional mutations indicates that genomic context, owing to selection that acts on long linkage blocks, is a more important driver of population variation than are the functional attributes of the individually encoded genes.