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Advances in genome sequencing have improved our understanding of the genetic basis of human diseases, and thousands of human genes have been associated with different diseases. Recent genomic adaptation at disease genes has not been well characterized. Here, we compare the rate of strong recent adaptation in the form of selective sweeps between mendelian, non-infectious disease genes and non-disease genes across distinct human populations from the 1000 Genomes Project. We find that mendelian disease genes have experienced far less selective sweeps compared to non-disease genes especially in Africa. Investigating further the possible causes of the sweep deficit at disease genes, we find that this deficit is very strong at disease genes with both low recombination rates and with high numbers of associated disease variants, but is almost non-existent at disease genes with higher recombination rates or lower numbers of associated disease variants. Because segregating recessive deleterious variants have the ability to interfere with adaptive ones, these observations strongly suggest that adaptation has been slowed down by the presence of interfering recessive deleterious variants at disease genes. These results suggest that disease genes suffer from a transient inability to adapt as fast as the rest of the genome.

The diversity of life is shaped by rates of speciation and extinction, and so estimating these rates correctly is crucial for understanding diversity patterns among clades, regions, and habitats. In 2011, Morlon and collaborators developed a promising likelihood-based approach to estimate speciation and extinction and to infer the model describing how these rates change over time based on AICc. This approach is now implemented in an R package (RPANDA). Here, we test the accuracy of this approach under simulated conditions, to evaluate its ability to correctly estimate rates of speciation, extinction, and diversification (speciation—extinction) and to choose the correct underlying model of diversification (e.g. constant or changing rates of speciation and extinction over time). We found that this likelihood-based approach frequently picked the incorrect model. For example, with changing speciation rates over time, the correct model was chosen in only ∼10 per cent of replicates. There were significant relationships between true and estimated speciation rates using this approach, but relationships were weak when speciation rates were constant within clades. Relationships were consistently weak between true and estimated rates of extinction and of diversification. Overall, we suggest that results from this approach should be interpreted with considerable caution.