The transition from terrestrial to marine environments represents one of the most fundamental evolutionary shifts in vertebrate history, requiring radical physiological and genomic remodeling. We investigated the genomic signatures of saltwater adaptation in the green sea turtle (Chelonia mydas), the leatherback turtle (Dermochelys coriacea), and the independently evolved estuarine diamondback terrapin (Malaclemys terrapin). Our analyses reveal that the marine transition is characterized by rapid evolution and expansion in gene families linked to iron metabolism, organ morphogenesis, and sensory perception-patterns that mirror those seen in other secondarily marine tetrapods. Notably, while we identified shared targets of positive selection across these independent lineages, we found no evidence of repeated evolution at the nucleotide level, reinforcing that functional convergence often arises through distinct molecular trajectories. Furthermore, demographic reconstructions reveal that saltwater-adapted turtles share a history of deep-time population declines; however, the delayed recovery of M. terrapin underscores the specific susceptibility of estuarine specialists to Pleistocene sea-level volatility. By bridging comparative genomics and historical demography, this study provides new insights into the genomic basis of marine adaptations in turtles and a comprehensive framework for understanding the molecular and ecological mechanisms that facilitate major vertebrate transitions into the marine realm.

The amniote digits have undergone recurrent modifications, with the diversified molecular mechanisms more studied among mammals than reptiles. Here we focus on the emu wings and ostrich feet, both of which experienced species-specific digit changes driven respectively by secondary flight loss and adaptation to running. By comparing their digit transcriptomes to those of chicken and alligator, we identified different gene networks in skeleton/muscle development responsible for the degenerated digits in archosaur ancestors and emu, but those in epidermal development for the load-bearing digit of ostrich. These results provide new clues for developmental programs of different cell types between different digits, on which natural selection can convergently operate.

Pairwise sequence comparisons are at the center of molecular evolutionary analyses. However, viral pairwise comparisons are challenging because extreme mutation rates and evolutionary pressure cause genomes to diverge rapidly, limiting detectable sequence similarity to fewer than 3% of virus pairs. To overcome these limitations, we compared viruses based on structural similarity, using predicted protein structures from ColabFold and Foldseek to define protein fold clusters. We represented each virus genome by its protein structural content. Pairwise similarities between viruses were then quantified using the Jaccard index based on the presence or absence of protein fold clusters. Using a recently established viral protein fold database, we compared all pairs of eukaryotic viruses in RefSeq. This approach increased the proportion of comparable viral genome pairs from 2.4% to 16.5%. Using this protein-fold representation of viruses, we were able to accurately predict viral families with an average sensitivity of 85.9%. Investigation of viral families showing limited sensitivity with this approach uncovered a laterally transferred structural cluster (Rep/NS1) broadly shared across diverse viral families and found in the avian lineage of adenoviruses. Sequence homology suggests that this Rep was acquired from Parvoviridae, but the protein is mutant in the ATPase active site, indicating possible exaptation toward a purely DNA-binding function. In Gammapapillomaviruses, several E4 clusters were associated with human tropism. In summary, by representing viruses with structural protein clusters, we can classify highly divergent viruses, trace lateral gene transfer, and uncover features associated with viral host range.

Genomic prediction leverages all available markers, irrespective of their statistical significance in genome-wide association studies (GWAS). Recent advancements in marker density, sample sizes, and sophisticated statistical GWAS methods have demonstrated that integrating GWAS results can potentially boost the accuracy of genomic predictions. The Genomic Association and Prediction Tool (GAPIT) has recently begun incorporating GWAS findings into its prediction framework, streamlining this approach, referred to as GWAS-Assisted Genomic Best Linear Unbiased Prediction (GAGBLUP). A sufficient simulation study revealed that the benefits of GAGBLUP depend on the GWAS model used. Multiple-locus models, such as Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK), outperformed single-locus models, such as the mixed linear model. Specifically, when BLINK GWAS results in a real trait were incorporated into Genomic Best Linear Unbiased Prediction (GBLUP), prediction accuracy improved by over 20% compared to GBLUP alone. This approach integrates the trait-specific insights from GWAS with the polygenic modeling capacity of GBLUP, resulting in more stable prediction across varying genetic backgrounds. This broader applicability enhances the utility of genomic selection in breeding programs, enabling its deployment across a wider range of crops and trait architectures.

Copy number variants (CNVs) are DNA duplications and deletions that cause genetic variation, underlying rapid adaptive evolution. CNVs often confer selective advantages but can also incur fitness costs. Evolution of Saccharomyces cerevisiae in nutrient-limited chemostats recurrently selects for amplifications of nutrient transporter genes. However, their fate upon return to a non-selective environment remains unknown. To investigate CNV fitness and stability upon removing the original selection pressure, we studied 15 CNV lineages (11 segmental and 4 whole-chromosomal amplifications) selected in nitrogen-limited chemostats. CNV stability was monitored using fluorescent reporters during propagation in nutrient-rich batch cultures for 110 to 220 generations. All aneuploid lineages showed rapid CNV loss and reversion to a single-copy genotype, whereas segmental amplifications were remarkably stable; one of the 11 strains reverted. Pairwise fitness competitions in rich media revealed strong fitness defects associated solely with CNVs that reverted; reversion led to increased fitness. Using simulation-based inference to estimate reversion rates and fitness effects, we determined negative selection as the primary driver of CNV loss. Whole-genome sequencing revealed that reversion of aneuploids and a segmental amplification left no evidence of prior CNV existence, rendering revertant genomes indistinguishable from the single-copy ancestor. Detailed characterization of a partial revertant identified chromosomal translocation, suggesting that extant CNVs can undergo structural diversification. Our findings provide novel evidence that most segmental CNVs adapted to nitrogen limitation are stable upon removal of selection, but costly gene amplifications are readily reversible. Together, these highlight the importance of CNVs in both long-term genome evolution and rapid, reversible adaptation to transient selection.

Pathogenic multidrug-resistant bacteria with hybrid chromosomes have emerged as a significant global healthcare threat. These include the pandemic Escherichia coli ST1193, the product of homologous recombination events involving two phylogenetically distant strains of E. coli, in which mutant alleles of the widely separated genes, gyrA and parC, generating high-level fluoroquinolone resistance were acquired. The mechanisms and frequency of hybrid formation are poorly understood. We developed a robust hybrid selection procedure and applied it to 118 clinical UTI isolates of E. coli mixed with suitable recipient strains. Hybrids were selected from 39% of isolates. All hybrids were recombinants of donor and recipient chromosomal DNA (median length of donor DNA 367 kb), with 90% also acquiring conjugative mobile genetic elements (MGE) from the donor. We showed that individual conjugative plasmids, and integrative conjugative elements (ICE), from donors were sufficient to drive hybrid formation. These observations strongly support conjugative chromosomal DNA transfer as the major mechanism underlying hybrid formation. ICE are genome-integrated and passively propagated but when transferring to recipients they normally do so by excising and producing their own conjugation machinery. We found that ICE were responsible for the highest frequencies of hybrid chromosome formation. They could mobilize DNA around the full length of the chromosome, including the simultaneous acquisition of mutant variants of gyrA and parC, separated by ∼826 kb, generating highly fluoroquinolone-resistant bacteria in a single event. Bacterial hybrid chromosome formation driven by conjugative MGE may be an important and widespread mechanism in the emergence and evolution of high-risk bacterial pathogens.

Ants, Formicidae, are a group of small social insects that inhabit nearly all terrestrial environments. Three competing hypotheses of ant relationships have been proposed, differing in the placement of Martialinae, a subfamily of cryptic, endogean ants. We used BUSCO genes to investigate the signals in individual and concatenated gene datasets. We found that gene trees support all three hypotheses. After concatenation, the three signals persist but their relative strength is model-dependent. The CAT-posterior mean site frequencies approach (which our model adequacy tests show best explains the across-site compositional heterogeneity of the data) finds Martialinae as the sister of all ants but Leptanillinae. We tested the effect of across-lineage compositional heterogeneity using data-recoding and excluding highly heterogeneous taxa. These tests did not lead to the emergence of significant support for alternative tree topologies. However, we identified strong gene- and site-discordance in the data and evidence that signals representing incongruent evolutionary processes exist in ant genomes supporting all three hypotheses. Incomplete lineage sorting and/or introgression seem to have significantly affected early ant evolution, which might make it impossible to establish whether Leptanillinae, Leptanillinae plus Martialinae, or Martialinae represents the sister of all the other ants.

Hybridization between species can occur along repeated zones of contact, providing a natural laboratory for studying the interplay between migration and selection, and identifying loci involved in adaptation and reproductive isolation. However, interpreting how evolutionary processes shape genomic patterns can be challenging: repeatability of genotype-environment association alone is not strong evidence for selection, as hybrid zones derived from the same parental species are not evolutionarily independent. Conversely, processes that operate within the middle of each hybrid zone, such as selection driving directional introgression, may be more evolutionarily independent, and therefore provide stronger evidence of selection. Here, we compared hybridization and local adaptation patterns between 2 replicated regions within the western Canada interior spruce hybrid zone: a broad latitudinal transect with gradual environmental variation and a narrow elevational transect with substantial topographical and environmental variation. We discovered a complex pattern of introgression, with strong differences in ancestry maintained even across small spatial scales at several locations along the elevational transect. Despite differences in their spatial scales, the elevational and latitudinal transects revealed strikingly similar genome-wide patterns of differentiation and adaptation, and consistent patterns of directional introgression. We explore the extent to which the evolutionary nonindependence of these hybrid zones allows inferences about the role of natural selection and drift in shaping these patterns. Consistent with theory, we found longer genomic tracts in the elevational transect, likely because the steeper environmental gradients over shorter distances limit the rate of mixing by migration and recombination relative to drift and selection.

Statistical methods to identify Neanderthal ancestry in modern human genomes rest on varying assumptions and inputs. Nonetheless, most studies of introgression use only a single method to define Neanderthal ancestry. Due to a lack of "ground truth," we have a limited understanding of the accuracy, comparative strengths and weaknesses, and the sensitivity of downstream conclusions for these methods. Here, we performed large-scale comparisons of 14 genome-wide introgression maps computed by 11 representative Neanderthal introgression detection algorithms: admixfrog, ArchaicSeeker2, ArchIE, ARGweaver-D, CRF, DICAL-ADMIX, hmmix, IBDmix, SARGE, Sprime, and S*. These algorithms span statistical approaches based on summary statistics, probabilistic modeling, and machine learning, and vary in their use of archaic, modern, and simulated genomes as input. Our results highlight a core set of regions predicted by nearly all methods, as well as substantial heterogeneity in commonly used Neanderthal introgression maps, especially at the individual genome level. Furthermore, we find that downstream analyses may result in different conclusions depending on the map used. Thus, we recommend careful consideration of map(s) chosen for downstream analysis and support the use of multiple maps to ensure robustness of conclusions. We make integrated prediction sets available, enabling further understanding of Neanderthal introgression's legacy on modern humans.