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Al-Saffar, S. I.

Publications and source records attributed to Al-Saffar, S. I..

2 recordsLinked to original sources

Evaluating methods for estimating the proportion of adaptive amino acid substitutions

A long-standing debate in molecular evolution concerns the role of adaptation in shaping divergence between species. A number of approaches have been developed to estimate the proportion of amino acid substitutions between species () that are driven by adaptive natural selection. These methods vary in the type of data they use and in the modeling strategies they employ in their inference. In this study, we evaluate the accuracy of nine different methods for estimating , using data simulated in the presence of linked selection. We find that methods that model the distribution of fitness effect (DFE) of both deleterious (as a gamma distribution) and beneficial mutations (as a gamma or exponential distribution) are the most accurate. We applied these methods to whole-genome data, finding that the most accurate methods gave average values of =0.25 in Arabidopsis thaliana, 0.5 in Drosophila melanogaster, and 0.1 in Homo sapiens. We also applied these methods to analyze subsets of tissue-specific genes in A. thaliana that are believed to be under different selective pressures and on genes found on the X vs. autosomes in D. melanogaster. We find estimates of to be higher in the seeds than in other specialized organs, supporting inferences of conflict-driven adaptive evolution in genes expressed in the seed; we also find to be higher on the X chromosome, supporting previous inferences of faster-X evolution. Overall, our results suggest that there are multiple methods that provide accurate estimates of , providing a guide for future estimates of adaptive evolution.

evolutionary biology↗

Human generation times across the past 250,000 years

The generation times of our recent ancestors can tell us about both the biology and social organization of prehistoric humans, placing human evolution on an absolute timescale. We present a method for predicting historic male and female generation times based on changes in the mutation spectrum. Our analyses of whole-genome data reveal an average generation time of 26.9 years across the past 250,000 years, with fathers consistently older (30.7 years) than mothers (23.2 years). Shifts in sex-averaged generation times have been driven primarily by changes to the age of paternity rather than maternity, though we report a disproportionate increase in female generation times over the past several thousand years. We also find a large difference in generation times among populations, with samples from current African populations showing longer ancestral generation times than non-Africans for over a hundred thousand years, reaching back to a time when all humans occupied Africa.

evolutionary biology↗