Abstract The estimation of evolutionary parameters provides essential information for designing public health policies. In short time intervals, however, nucleotide substitutions are ineffective to record all complexities of virus population dynamics. In this sense, the current SARS-CoV-2 pandemic poses a challenge for evolutionary analysis. We used computer simulation to evolve populations in scenarios of varying temporal intervals to evaluate the impact of the age of an epidemic on estimates of time and geography. Before estimating virus timescales, the shape of tree topologies can be used as a proxy to assess the effectiveness of the virus phylogeny in providing accurate estimates of evolutionary parameters. In short timescales, estimates have larger uncertainty. We compared the predictions from simulations with empirical data. The tree shape of SARS-CoV-2 was closer to shorter timescales scenarios, which yielded parametric estimates with larger uncertainty, suggesting that estimates from these datasets should be evaluated cautiously. To increase the accuracy of the estimates of virus transmission times between populations, the uncertainties associated with the age estimates of both the crown and stem nodes should be communicated. We place the age of the common ancestor of the current SARS-CoV-2 pandemic in late September 2019, corroborating an earlier emergence of the virus.

Abstract Tsetse flies are responsible for the transmission of Trypanossoma sp. to vertebrate animals in Africa causing huge health issues and economic loss. The availability of the genome sequence of Glossina morsitans enabled the discovery of several genes related to medically important phenotypes and novel physiological features. However, a genome-wide scan for coding regions that underwent positive selection is still missing, which is surprising given the evolution of traits associated with the hematophagy in this lineage. In this study, we employed an experimental design that controlled for the rate of false positives and we performed a scan of 3,318 G. morsitans genes. We found 145 genes with significant historical signal of positive selection. These genes were categorized into 18 functional classes after careful manual annotation. Based on their attributed functions, we identified candidate genes related with feeding habits and embryonic development. When our results were contrasted with gene expression data, we confirmed that most genes that underwent adaptive molecular evolution were frequently expressed in organs associated with key physiological evolutionary innovations in the G. morsitans lineage, namely, the salivary gland, the midgut, fat body tissue, and in the spermatophore.