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Recent studies suggest that closely related species can accumulate substantial genetic and phenotypic differences despite ongoing gene flow, thus challenging traditional ideas regarding the genetics of speciation. Baboons (genus Papio) are Old World monkeys consisting of six readily distinguishable species. Baboon species hybridize in the wild, and prior data imply a complex history of differentiation and introgression. We produced a reference genome assembly for the olive baboon (Papio anubis) and whole-genome sequence data for all six extant species. We document multiple episodes of admixture and introgression during the radiation of Papio baboons, thus demonstrating their value as a model of complex evolutionary divergence, hybridization, and reticulation. These results help inform our understanding of similar cases, including modern humans, Neanderthals, Denisovans, and other ancient hominins.

The role of balancing selection is a long-standing evolutionary puzzle. Balancing selection is a crucial evolutionary process that maintains genetic variation (polymorphism) over extended periods of time; however, detecting it poses a significant challenge. Building upon the Polymorphism-aware phylogenetic Models (PoMos) framework rooted in the Moran model, we introduce a PoMoBalance model. This novel approach is designed to disentangle the interplay of mutation, genetic drift, and directional selection (GC-biased gene conversion), along with the previously unexplored balancing selection pressures on ultra-long timescales comparable with species divergence times by analyzing multi-individual genomic and phylogenetic divergence data. Implemented in the open-source RevBayes Bayesian framework, PoMoBalance offers a versatile tool for inferring phylogenetic trees as well as quantifying various selective pressures. The novel aspect of our approach in studying balancing selection lies in polymorphism-aware phylogenetic models' ability to account for ancestral polymorphisms and incorporate parameters that measure frequency-dependent selection, allowing us to determine the strength of the effect and exact frequencies under selection. We implemented validation tests and assessed the model on the data simulated with SLiM and a custom Moran model simulator. Real sequence analysis of Drosophila populations reveals insights into the evolutionary dynamics of regions subject to frequency-dependent balancing selection, particularly in the context of sex-limited color dimorphism in Drosophila erecta. [ABSTRACT FROM AUTHOR]

Different frequencies amongst codons that encode the same amino acid (i.e. synonymous codons) have been observed in multiple species. Studies focused on uncovering the forces that drive such codon usage showed that a combined effect of mutational biases and translational selection works to produce different frequencies of synonymous codons. However, only few have been able to measure and distinguish between these forces that may leave similar traces on the coding regions. Here, we have developed a codon model that allows the disentangling of mutation, selection on amino acids and synonymous codons, and GC-biased gene conversion (gBGC) which we employed on an extensive dataset of 415 chordates and 191 arthropods. We found that chordates need 15 more synonymous codon categories than arthropods to explain the empirical codon frequencies, which suggests that the extent of codon usage can vary greatly between animal phyla. Moreover, methylation at CpG sites seems to partially explain these patterns of codon usage in chordates but not in arthropods. Despite the differences between the two phyla, our findings demonstrate that in both, GC-rich codons are disfavored when mutations are GC-biased, and the opposite is true when mutations are AT-biased. This indicates that selection on the genomic coding regions might act primarily to stabilize its GC/AT content on a genome-wide level. Our study shows that the degree of synonymous codon usage varies considerably among animals, but is likely governed by a common underlying dynamic. [ABSTRACT FROM AUTHOR]

Genome-wide scans for positively selected genes (PSGs) in mammals have provided insight into the dynamics of genome evolution, the genetic basis of differences between species, and the functions of individual genes. However, previous scans have been limited in power and accuracy owing to small numbers of available genomes. Here we present the most comprehensive examination of mammalian PSGs to date, using the six high-coverage genome assemblies now available for eutherian mammals. The increased phylogenetic depth of this dataset results in substantially improved statistical power, and permits several new lineage- and clade-specific tests to be applied. Of approximately 16,500 human genes with high-confidence orthologs in at least two other species, 400 genes showed significant evidence of positive selection (FDR

For over a decade, experimental evolution has been combined with high‐throughput sequencing techniques. In so‐called Evolve‐and‐Resequence (E&R) experiments, populations are kept in the laboratory under controlled experimental conditions where their genomes are sampled and allele frequencies monitored. However, identifying signatures of adaptation in E&R datasets is far from trivial, and it is still necessary to develop more efficient and statistically sound methods for detecting selection in genome‐wide data. Here, we present Bait‐ER – a fully Bayesian approach based on the Moran model of allele evolution to estimate selection coefficients from E&R experiments. The model has overlapping generations, a feature that describes several experimental designs found in the literature. We tested our method under several different demographic and experimental conditions to assess its accuracy and precision, and it performs well in most scenarios. Nevertheless, some care must be taken when analysing trajectories where drift largely dominates and starting frequencies are low. We compare our method with other available software and report that ours has generally high accuracy even for trajectories whose complexity goes beyond a classical sweep model. Furthermore, our approach avoids the computational burden of simulating an empirical null distribution, outperforming available software in terms of computational time and facilitating its use on genome‐wide data. We implemented and released our method in a new open‐source software package that can be accessed at https://doi.org/10.5281/zenodo.7351736. [ABSTRACT FROM AUTHOR]

Abstract Background The Wnt genes encode secreted glycoprotein ligands that regulate a wide range of developmental processes, including axis elongation and segmentation. There are thirteen subfamilies of Wnt genes in metazoans and this gene diversity appeared early in animal evolution. The loss of Wnt subfamilies appears to be common in insects, but little is known about the Wnt repertoire in other arthropods, and moreover the expression and function of these genes have only been investigated in a few protostomes outside the relatively Wnt-poor model species Drosophila melanogaster and Caenorhabditis elegans. To investigate the evolution of this important gene family more broadly in protostomes, we surveyed the Wnt gene diversity in the crustacean Daphnia pulex, the chelicerates Ixodes scapularis and Achaearanea tepidariorum, the myriapod Glomeris marginata and the annelid Platynereis dumerilii. We also characterised Wnt gene expression in the latter three species, and further investigated expression of these genes in the beetle Tribolium castaneum. Results We found that Daphnia and Platynereis both contain twelve Wnt subfamilies demonstrating that the common ancestors of arthropods, ecdysozoans and protostomes possessed all members of all Wnt subfamilies except Wnt3. Furthermore, although there is striking loss of Wnt genes in insects, other arthropods have maintained greater Wnt gene diversity. The expression of many Wnt genes overlap in segmentally reiterated patterns and in the segment addition zone, and while these patterns can be relatively conserved among arthropods and the annelid, there have also been changes in the expression of some Wnt genes in the course of protostome evolution. Nevertheless, our results strongly support the parasegment as the primary segmental unit in arthropods, and suggest further similarities between segmental and parasegmental regulation by Wnt genes in annelids and arthropods respectively. Conclusions Despite frequent losses of Wnt gene subfamilies in lineages such as insects, nematodes and leeches, most protostomes have probably maintained much of their ancestral repertoire of twelve Wnt genes. The maintenance of a large set of these ligands could be in part due to their combinatorial activity in various tissues rather than functional redundancy. The activity of such Wnt 'landscapes' as opposed to the function of individual ligands could explain the patterns of conservation and redeployment of these genes in important developmental processes across metazoans. This requires further analysis of the expression and function of these genes in a wider range of taxa.

Abstract Background Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars. Previously, phylo-grammars have required considerable effort to implement, limiting their adoption by computational biologists. Results We have developed an open source software tool, xrate, for working with reversible, irreversible or parametric substitution models combined with stochastic context-free grammars. xrate efficiently estimates maximum-likelihood parameters and phylogenetic trees using a novel "phylo-EM" algorithm that we describe. The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source. We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures. Conclusion Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools.