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Data from: Determining the null model for detecting adaptive convergence from genomic data: a case study using echolocating mammals

Citation

Thomas, Gregg W. C.; Hahn, Matthew W. (2016), Data from: Determining the null model for detecting adaptive convergence from genomic data: a case study using echolocating mammals, Dryad, Dataset, https://doi.org/10.5061/dryad.16qc5

Abstract

Convergent evolution occurs when the same trait arises independently in multiple lineages. In most cases of phenotypic convergence such transitions are adaptive, so finding the underlying molecular causes of convergence can provide insight into the process of adaptation. Convergent evolution at the genomic level also lends itself to study by comparative methods, though molecular convergence can also occur by chance, adding noise to this process. Parker et al. (2013) studied convergence across the genomes of several mammals, including echolocating bats and dolphins. Based on a null distribution of site-specific likelihood support (SSLS) generated using simulated topologies, they concluded that there was evidence for genome-wide adaptive convergence between echolocating taxa. Here we demonstrate that methods based on SSLS do not adequately measure convergence, and reiterate the use of an empirical null model that directly compares convergent substitutions between all pairs of species. We find that when the proper comparisons are made there is no surprising excess of convergence between echolocating mammals, even in sensory genes.

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