TY - JOUR T1 - CLEAR: Composition of Likelihoods for Evolve And Resequence Experiments JF - bioRxiv DO - 10.1101/080085 SP - 080085 AU - Arya Iranmehr AU - Ali Akbari AU - Christian Schlötterer AU - Vineet Bafna Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/10/13/080085.abstract N2 - Experimental evolution (EE) studies are powerful tools for observing molecular evolution “in-action” from populations sampled in controlled and natural environments. The advent of next generation sequencing technologies has made whole-genome and whole-population sampling possible, even for eukaryotic organisms with large genomes, and allowed us to locate the genes and variants responsible for genetic adaptation. While many computational tests have been developed for detecting regions under selection, they are mainly designed for static (single time) data, and work best when the favored allele is close to fixation. Conversely, EE studies provide samples over multiple time points, often at early stages of selective sweep.While more predictive than static data analysis, a majority of the EE studies are constrained by the limited time span since onset of selection, depending upon the generation time of the organism. This constraint curbs the power of adaptation studies, as the population can only be evolved-and-resequenced for a small number of generations relative to the fixation-time of the favored allele. Moreover, coverage in pooled sequencing experiments varies across replicates and time points for every variant.In this article, we directly address these issues while developing tools for identifying selective sweep in pool-sequenced EE of sexual organisms and propose Composition of Likelihoods for Evolve-And-Resequence experiments (Clear). Extensive simulations show that Clear achieves higher power in detecting and localizing selection over a wide range of parameters. In contrast to existing methods, the Clear statistic is robust to variation of coverage. Clear also provides robust estimates of model parameters, including selection strength and overdominance, as byproduct of the statistical testing, while being orders of magnitude faster. Finally, we applied the Clear statistic to data from a study of D. melanogaster adaptation to alternating temperatures. We identified selection in many genes, including Heat Shock Proteins. The genes were enriched in “response to heat”, “cold acclimation” and “defense response to bacterium”, and other relevant biological processes. ER -