Humans differ from other primates in various traits, despite nearly identical protein-coding sequences. Understanding the evolution of these differences requires studying transcriptional regulation. Here, we examine ZEB2, a transcription factor crucial for immune and neural development, to explore its regulatory divergence across great apes. Using B-lymphoblastoid cells, chosen as experimental model system due to the availability of biological replicates for three great ape species, we show that, in addition to conserved ZEB2 targets, human ZEB2 is distinct in regulating a larger repertoire of genes implicated in neuronal development. ZEB2 knock-down in human, chimpanzee, and orangutan B-lymphoblastoid cells followed by transcriptome profiling uncovered human-specific regulatory differences, especially in nervous system-related genes. Additional analysis using single-cell RNA-Seq and brain organoid data identified cell-type-specific differences in ZEB2 expression and regulated genes between humans and other apes, most pronounced in ventral progenitors and neurons. Moreover, human-specific ZEB2 targets are enriched in non-coding genes, suggesting an expanded and possibly rewired regulatory network. Our study demonstrates that species differences in ZEB2 regulation can be detected in a controlled cell system and validated in neural contexts. More broadly, we provide new insights into the functional divergence of TFs across closely related species and how regulatory shifts can contribute to phenotypic evolution.

Transitions toward simplified life cycles can reshape evolutionary trajectories, yet their impact on the rate of molecular evolution remains poorly understood. In aphids, host alternation (heteroecy) entails obligate seasonal migration between highly distinct plant hosts - typically woody and herbaceous species - and has been repeatedly lost, giving rise to monoecious species with simplified life cycles. Using comparative genomics across 46 aphid species, we tested whether transitions from heteroecy to monoecy alter evolutionary dynamics at the gene level. We identified 9,304 orthologs and estimated evolutionary rates (dN/dS) and shifts in selection regimes in the diverse Aphidinae subfamily. We found that 715 orthologs evolved faster in monoecious species, primarily due to relaxed selection, while heteroecious species showed signatures of intensified selection. Genes under relaxed selection in monoecious species were enriched for functions related to environmental sensing, signaling, nutritional adjustments, morph determination and migration related - traits likely central for host alternation. These results suggest that the loss of a complex life cycle leads to reduced selective constraints as a consequence of ecological simplification. This study provides a robust evolutionary framework for understanding how life cycle transitions shape molecular evolution and drive gene decay following trait loss.

The testicular descent leading to the exteriorization of male gonads is a complex sexual dimorphic process observed in numerous mammals, whereas some species, such as elephants and cetaceans, retain the lifelong ascrotal testes. Despite the implication of Wnt signaling in testicular development and descent, the evolutionary mechanisms underlying ascrotal testes have not been adequately addressed. Here, we examined selection signatures and unique amino-acid substitutions in genes of the Wnt signaling pathway. We identified an ascrotal mammal-specific substitution (S406G) in ZNRF3 located within the DVL-interaction region. Functional assays showed that this substitution enhances the affinity of ascrotal ZNRF3 for DVLs and suppresses Wnt3a-induced Wnt signaling. Comparative transcriptomics of the gubernaculum between male fetal rats from wild-type and spontaneous cryptorchid (orl) strains revealed upregulation of Ctnnb1 and Gsk3b in orl rats, along with ascrotal-specific evolutionary changes in regulatory elements. Collectively, these findings suggest that Wnt signaling may be dampened in ascrotal mammals. This study provides insights into the pathogenesis of cryptorchidism in humans and domestic animals.

The testicular descent leading to the exteriorization of male gonads is a complex sexual dimorphic process observed in numerous mammals, whereas some species, such as elephants and cetaceans, retain the lifelong ascrotal testes. Despite the implication of Wnt signaling in testicular development and descent, the evolutionary mechanisms underlying ascrotal testes have not been adequately addressed. Here, we examined selection signatures and unique amino-acid substitutions in genes of the Wnt signaling pathway. We identified an ascrotal mammal-specific substitution (S406G) in ZNRF3 located within the DVL-interaction region. Functional assays showed that this substitution enhances the affinity of ascrotal ZNRF3 for DVLs and suppresses Wnt3a-induced Wnt signaling. Comparative transcriptomics of the gubernaculum between male fetal rats from wild-type and spontaneous cryptorchid (orl) strains revealed upregulation of Ctnnb1 and Gsk3b in orl rats, along with ascrotal-specific evolutionary changes in regulatory elements. Collectively, these findings suggest that Wnt signaling may be dampened in ascrotal mammals. This study provides insights into the pathogenesis of cryptorchidism in humans and domestic animals.

Whole-genome duplication (WGD), a widespread macromutation across eukaryotes, is predicted to affect the tempo and modes of evolutionary processes. By theory, the additional set(s) of chromosomes present in polyploid organisms may reduce the efficiency of selection while, simultaneously, increasing heterozygosity and buffering deleterious mutations. Despite the theoretical significance of WGD, empirical genomic evidence from natural polyploid populations is scarce and direct comparisons of selection footprints between autopolyploids and closely related diploids remains completely unexplored. We therefore combined locally sampled soil data with resequenced genomes of 76 populations of diploid-autotetraploid Arabidopsis arenosa and tested whether the genomic signatures of adaptation to distinct siliceous and calcareous soils differ between the ploidies. Leveraging multiple independent transitions between these soil types in each ploidy, we identified a set of genes associated with ion transport and homeostasis that were repeatedly selected for across the species' range. Notably, polyploid populations have consistently retained greater variation at candidate loci compared to diploids, reflecting lower fixation rates. In tetraploids, positive selection predominantly acts on such a large pool of standing genetic variation, rather than targeting de novo mutations. Finally, selection in tetraploids targets genes that are more central within the protein-protein interaction network, potentially impacting a greater number of downstream fitness-related traits. In conclusion, both ploidies thrive across a broad gradient of substrate conditions, but WGD fundamentally alters the ploidies adaptive strategies: tetraploids leverage their greater genetic variation and redundancy to compensate for the predicted constraints on the efficacy of positive selection.

Chaperonins are essential protein-folding machines, classified into three structural and phylogenetic groups: Group I (bacterial GroEL), Group II (archaeal thermosome and eukaryotic CCT), and Group III (bacterial thermosome-like). Using ancestral sequence reconstruction (ASR) and protein resurrection, we inferred and experimentally characterized the last common ancestors of these groups (Ancestral Chaperonins ACI, ACII, and ACIII). The resurrected proteins exhibited ATPase activity (except ACII) and protected client proteins from heat-induced inactivation. Structural analyses by electron microscopy and Cryo-EM revealed that ACI forms single 7-mer rings, whereas ACII adopts a mixed population of single/double 8-mer rings, representing the first experimental observation of intermediate oligomeric states. ACII also features a unique cochaperonin-independent closure mechanism, distinct from modern Group I and II chaperonins. Together, these findings provide the experimental structural reconstruction of the most ancient and complex multimeric proteins so far, uncover novel intermediate states in chaperonin evolution, and offer a direct empirical framework for studying the emergence of multimeric complexity in early cellular life.

Estimating selection from genetic time-series data is fundamental to understanding evolutionary dynamics. Accurate selection inference is confounded by multiple noise sources, including limited sampling of populations and genetic drift. To characterize how these uncertainties collectively affect estimator performance, we analyze a mathematically tractable selection coefficient estimator derived under the marginal path likelihood (MPL) framework. We identify a parameter, the integrated mutant allele variance, as a key quantity determining estimator precision. Our analysis reveals that variance integration mitigates sampling and genetic drift errors at different rates, with drift typically becoming the dominant source of error in longer trajectories. The increased robustness of MPL-based estimation to sampling is surprising, since MPL is derived from a model that neglects this effect. Our findings offer insights into how incorporating temporal information reduces multiple sources of noise when estimating selection coefficients.

Ancient DNA and archaeological studies indicate the Central Plain's pivotal role in the cultural and genetic evolution of ancient China. However, limited genome-wide data have constrained our understanding of this region's population history during the Bronze Age Shang Dynasty (around 1600-1046 BCE). Here, we present genome-wide data from 11 individuals from the Xisima Cemetery in Central Plain, a site exhibiting clear burial evidence of social stratification dating to the late Shang Dynasty (around 1300 to 1046 BCE). Genetic analyses reveal that all Xisima individuals can be modelled as direct, unadmixed descendants of Late Neolithic Central Plain-related people. We found no systematic genetic differentiation between individuals buried in high-grade (south-to-north) and low-grade (east-to-west) tombs, indicating genetic homogeneity across social strata. These results demonstrate that social stratification at Xisima occurred without corresponding genetic distinction, supporting the decoupling of social hierarchy from significant genetic differentiation in this Shang community.

The evolution of non-coding genome size remains poorly understood. While part of non-coding DNA arguably plays a regulatory role, a significant portion does not appear to have a detectable phenotypic effect. The abundance of non-functional DNA in genomes, observed across the Tree of Life, challenges purely adaptationist explanations. Several non-adaptive theories have been proposed to explain its presence and identify its determinants, emphasizing either the mutational processes or the mutational hazard entailed by non-coding and non-functional DNA. However, those theories have not yet been integrated into a common framework, and the exact nature of the mutational hazard is not yet fully understood. In this work, we introduce a simple mathematical model of genome size evolution. Our model shows that the non-coding fraction of the genome is shaped by two fundamental forces: (i) inherent biases in mutational neutrality ‒ adding base pairs being more likely to be neutral than removing some, and (ii) robustness selection arising from the mere existence of structural mutations ‒ larger genomes being more prone to double-strand breaks that generate such mutations, thereby imposing a second-order selection on robustness. Together, these forces establish an equilibrium non-coding fraction that depends solely on mutation biases and the product of population size and mutation rate.

Peptide deformylases (PDFs) are enzymes that are essential for bacterial viability and attractive targets for antibiotic development. Yet, despite their conserved function, many bacteria encode multiple PDFs, a genomic feature whose prevalence and implications remain largely unexplored. Here, we reveal that nearly half of all bacterial genomes carry more than one PDF gene, frequently embedded within mobile genetic elements such as plasmids and integrons. In Vibrio cholerae, the accessory PDF (Def2VCH) confers reduced susceptibility to actinonin (ACT), the most studied PDF inhibitor, while still supporting bacterial growth in absence of the canonical PDF copies (Def1VCH). Crystallographic analysis shows that this reduced susceptibility stems from an arginine-to-tyrosine substitution that probably reduces ACT binding. Strikingly, this resistance signature is shared by integron-encoded PDFs, and transfer of an integron-encoded PDF cassette from Pseudoxanthomonas into a susceptible V. cholerae is sufficient to abolish ACT susceptibility. These findings reveal a hidden reservoir of resistance within the bacterial mobilome and shed light on potential mechanisms of bacterial resilience to environmental PDF inhibitors.

Ancient DNA extracted from the sediments of archaeological sites (sedaDNA) can provide fine-grained information about the composition of past ecosystems and human site use, even in the absence of visible remains. However, the growing amount of available sequencing data and the nature of the data obtained from archaeological sediments pose several computational challenges; among these, the rapid and accurate taxonomic classification of sequences. While alignment-based taxonomic classifiers remain the standard in sedaDNA analysis pipelines, they are too computationally expensive for the processing of large numbers of sedaDNA sequences. In contrast, alignment-free methods offer fast classification but suffer from higher false-positive rates. To address these limits, we developed quicksand, an open-source Nextflow pipeline designed for rapid and accurate taxonomic classification of mammalian mitochondrial DNA (mtDNA) in sedaDNA samples. quicksand combines fast alignment-free classification using KrakenUniq with post-classification mapping, filtering, and ancient DNA authentication. Based on simulations and reanalyses of published datasets, we demonstrate that quicksand achieves accuracy and sensitivity comparable to or better than existing methods, while significantly reducing runtime. quicksand offers an easy workflow for large-scale screening of sedaDNA samples for archaeological research and is freely available at https://github.com/mpieva/quicksand.

Phylogenomic data are indispensable for establishing reliable relationships to build a robust Tree of Life. The superalignment approach concatenates hundreds or thousands of genomic segments, providing a straightforward, computationally efficient, and effective means of inferring phylogenies. However, the standard bootstrap method can produce overly confident support for incorrect inferences based on superalignments, as it fails to account for the heterogeneity in phylogenetic signals across the data, which is caused by incomplete lineage sorting (ILS), data errors, and other biological processes. To detect such erroneous inferences, researchers need to produce and deliberate on the concordance of inferences derived from many complex and computationally demanding analyses that require knowledge of data partitions. This study demonstrates that analyzing phylogenomic subsamples with bootstrap upsampling overcomes the overconfidence drawback of the super-alignment approach. We found that bootstrapping multiple small, randomly selected site subsets revealed the presence of phylogeny variation signals across the dataset, similar to that detected using biological data partitions. We present Net Bootstrap Support (NBS) that accounts for this phylogenetic variation. NBS values showed comparable performance to multispecies coalescent analyses in the presence of ILS and surpassed it for datasets simulated with gene tree estimation errors. NBS analyses of phylogenomic data from rodents, fungi, and carnivorous plants corroborated the performance observed in simulated datasets and even mitigated overconfidence resulting from some data errors. NBS calculations are computationally efficient, with low memory consumption and high computational time savings, making NBS well-suited for big data molecular phylogenetics on both desktops and high-performance computing systems.

Adaptive introgression is an important evolutionary process, which can be identified with widely used summary statistics, such as the number of uniquely shared sites and the quantile of the derived allele frequencies in such sites. However, these as well as more recently developed statistics such as D+ and Danc, still lack accessible implementations. Here, we present SAI, a Python package for computing these statistics along with a new statistic, DD, and demonstrate its application on two datasets. First, using the 1000 Genomes Project data, we replicated previously reported candidate regions and identified additional ones, including a region detected by studies using supervised deep learning. Second, we investigated bonobo introgression into central chimpanzees and identified candidate genes, finding one region that overlaps a high-frequency Denisovan-introgressed haplotype block reported in modern Papuans. This is an intriguing co-occurrence across divergent lineages, underscoring the role of adaptive introgression in evolution.

Evolutionary simulations of multiple chromosomes, even up to the scale of full-genome simulations, are becoming increasingly important in population genetics and evolutionary ecology. Unfortunately, the popular simulation framework SLiM has always been intrinsically limited to simulations of a single diploid chromosome. Modeling multiple chromosomes of different types, such as sex chromosomes, has always been cumbersome even with scripting, presenting a substantial barrier to the development of full-genome simulations. Here we present SLiM 5, a major extension of SLiM's capabilities for simulating multiple chromosomes. Modeling up to 256 chromosomes is now possible, and each chromosome may belong to any of a wide variety of types - not just autosomes (diploid and haploid), but also sex chromosomes (X, Y, Z, and W), haploid mitochondrial and chloroplast DNA, and more. This new functionality is integrated across all of SLiM, including not only the mechanics of reproduction and inheritance, but also input and output of multi-chromosome data in formats like VCF, and tree-sequence recording across multiple chromosomes. New recipes in the SLiM manual demonstrate these new features, and SLiM's graphical modeling environment, SLiMgui, has been extended in many ways for the visualization of multi-chromosome models. These new features will open new horizons and enable a heightened level of realism for full-genome simulations.

Ultraconserved elements are segments of DNA that are identical or nearly identical in distantly related species. Finding 100% identity over long evolutionary times is unexpected, but pioneering research in human-mouse pairwise alignment uncovered something even more puzzling: these elements are not as rare as previously suspected. Furthermore, their sizes are distributed as a power-law, a feature that cannot be explained by standard models of genome evolution where conservation is expected to decay exponentially. Despite the power-law behavior having been reported and investigated in a wide variety of biological and physical contexts, from cell-division to protein family evolution, why it appears in the size distribution of ultraconserved elements remains elusive. To address this question, I propose a model of DNA sequence evolution by mutations of arbitrary length based on a classical integro-differential equation that arises in various applications in biology. The model captures the ultraconserved size distribution observed in pairwise alignments between human and 40 other vertebrates, encompassing more than 400 million years of evolution, from chimpanzee to zebrafish. I also show that the model can be used to predict other important aspects of genome evolution, such as indel rates and conservation in functional classes.

Bayesian phylodynamic models have become essential for reconstructing population history from genetic data, yet their accuracy depends crucially on choosing appropriate demographic models. To address uncertainty in model choice, we introduce a Bayesian Model Averaging (BMA) framework that integrates multiple parametric coalescent models‒including constant, exponential, logistic, and Gompertz growth‒along with their ``expansion'' variants that account for non-zero ancestral populations. Implemented in a Bayesian setting with Metropolis-coupled MCMC, this approach allows the sampler to switch among candidate growth functions, thereby capturing demographic histories without having to pre-specify a single model. Simulation studies verify that the logistic and Gompertz models may require specialised sampling strategies such as adaptive multivariate proposals to achieve robust mixing. We demonstrate the performance of these models on datasets simulated under different substitution models, and show that joint inference of genealogy and population parameters is well-calibrated when properly incorporating correlated-move operators and BMA. We then apply this method to two real-world datasets. Analysis of Egyptian Hepatitis C virus (HCV) sequences indicates that models with a founder population followed by a rapid expansion are well supported, with a slight preference for Gompertz-like expansions. Our analysis of a metastatic colorectal cancer (CRC) single-cell dataset suggests that exponential-like growth is plausible even for an advanced stage cancer patient. We believe this highlights that tumour subclones may retain substantial proliferative capacity into the later stages of the disease. Overall, our unified BMA framework reduces the need for restrictive model selection procedures and can also provide deeper biological insights into epidemic spread and tumour evolution. By systematically integrating multiple growth hypotheses within a standard Bayesian setting, this approach naturally avoids overfitting and offers a powerful tool for inferring population histories across diverse biological domains.

The increasing scale of population genomic datasets presents computational challenges in estimating summary statistics such as nucleotide diversity (π) and divergence (dxy). Accurate estimates of diversity require knowledge of missing data and existing tools require all-sites VCFs. However, generating these files is computationally expensive for large datasets. Here, we introduce Callable Loci And More (clam), a tool that leverages callable loci-determined from depth information-to estimate population genetic statistics using a variant-only VCF. This approach offers improvements in storage footprint and computational performance compared to contemporary methods. We validate clam's accuracy using simulated data, demonstrating that it produces estimates of π, dxy, and FST identical to those from all-sites VCF approaches. We then benchmark clam using a large muskox dataset and demonstrate that it produces accurate estimates of π while substantially reducing runtime requirements compared to current best-practice methods. clam provides an efficient and scalable alternative for population genomic analyses, facilitating the study of increasingly large and diverse datasets. clam is available as a standalone program and integrated into snpArcher for efficient reproducible population genomic analysis.

Due to their remarkable diversity and rapid evolution, conotoxins - peptide toxins from predatory marine cone snails - provide a powerful system for exploring how gene diversification may contribute to the development of lineage-specific adaptations. We previously demonstrated that 2-loop Tau conotoxins represent an evolutionary innovation associated with mollusk-hunting behaviors in cone snails. Here, we investigate the evolutionary history of these toxins as a model to understand the mechanism of ancestral gene neofunctionalization, which may have contributed to the emergence of mollusk-hunting in cone snails. Using ancestral sequence reconstruction, we present a model in which ancestral T-superfamily conotoxins neofunctionalized into the 2-loop Tau conotoxins. Predicted ancestral sequences reveal an intermediate structure between the classic T-superfamily conotoxins and the derived 2-loop Tau forms. Notably, these ancestral intermediates acquired a new cysteine scaffold that facilitated a structural transition from a globular to a ribbon fold. This conformational shift was followed by sequence-level changes that presumably enhanced activity against molecular targets in mollusks. We propose that the emergence of 2-loop Tau conotoxins may have been one factor that contributed to the emergence of molluscivory, providing insight into how gene innovation may underlie ecological diversification.

Parasitic lifestyles often impose profound evolutionary pressures, affecting molecular evolution through both adaptive and non-adaptive mechanisms. Among barnacles (subclass Cirripedia), the obligate parasitic Rhizocephala differ markedly from their filter-feeding thoracican relatives in morphology, ecology, and life history. However, how the shift to parasitism has shaped mitochondrial genome evolution within Cirripedia remains unclear. Here, we present the first comprehensive comparative analysis of mitochondrial genomes between parasitic and non-parasitic barnacles, including three newly sequenced and one unpublished species of parasitic Rhizocephala, a clade whose mitochondrial genomes had not been characterized until now. Phylogenomic and molecular evolutionary analyses reveal that Rhizocephala species exhibit extremely long branches likely attributed to the clade-specific tempo (high substitution rate) and mode (selection pressure) of mtDNA sequence evolution associated with their parasitic lifestyle. A two-cluster molecular clock test reveals significantly elevated substitution rates across rhizocephalans, consistent with reduced effective population sizes (Ne) linked to their opportunistic, host-dependent life cycles. We also detect signatures of positive selection in protein-coding genes encoding key components of the electron transport chain complexes III and IV. Structural modeling highlights amino acid substitutions at functionally critical sites for electron transfer and proton pumping, suggesting adaptive modifications to mitochondrial bioenergetics under hypoxic conditions within host tissues. Together, our findings underscore that both non-adaptive (genetic drift, relaxed selection) and adaptive (positive selection) processes have driven the rapid sequence divergence of mitochondrial genomes in parasitic Rhizocephala. Further experimental study is needed to elucidate how mitochondrial and nuclear-encoded subunits of oxidative phosphorylation coevolve in this specialized parasitic group.

Transformation occurs when bacteria import exogenous DNA via the competence machinery and integrate it into their genome through homologous recombination (HR). This process may provide an evolutionary advantage to cells through enabling "chromosomal curing": the deletion of integrative mobile genetic elements (MGEs). However, many such MGEs are sensitive to RecA-DNA filaments, triggering activation of a lifecycle that may enable them to evade HR-mediated deletion. Despite >40% of isolates containing prophage integrated at a site that inhibits transformation, 3 representative prophages were identified in naturally competent pneumococci to test this hypothesis. These encompassed representatives with C1-type and ImmAR-type regulatory systems, found in almost all pneumococcal prophages. All 3 prophages were deleted by HR with an efficiency similar to the transfer of base substitutions. Mutations that impaired a C1-regulated prophage increased this deletion rate, reflecting this element being activated by RecA-DNA filaments imported during transformation, likely preferentially killing cells that induce competence. ImmAR-regulated prophage instead responded to transient stimuli by excising as deletion-resistant pseudolysogens, only driving cell lysis in response to sustained stimuli. This was likely a consequence of these prophages reacting to multiple signals, as they differed in their response to both RecA and the DNA-binding protein and competence repressor DprA. One prophage constitutively elevated host DprA levels, thereby reducing transformation by preventing induction of the competence machinery. Hence, these data are consistent with an evolutionary arms race between prophage and the competence machinery, resulting in bacterial diversification though HR being impeded by MGEs preventing their own elimination from the chromosome.

Ribosomes are essential for protein synthesis and require ribosome biogenesis factors for assembly. To uncover the evolutionary diversity of ribosome biogenesis, we analyzed over 30,000 bacterial genomes and revealed that Candidate Phyla Radiation, also known as the phylum Patescibacteria, characterized by reduced genomes and smaller ribosomes, has about half the average number of ribosome biogenesis factors compared with non-Candidate Phyla Radiation bacteria. Notably, key ribosome biogenesis factors such as der, obgE, and rbfA, considered indispensable, are conserved in only around 20%-70% of Candidate Phyla Radiation genomes. Since such repertoires were not observed in reduced genomes of other phyla, Candidate Phyla Radiation presumably diverged early in bacterial evolution. We further confirmed that ribosomal structural changes correlate with reduced ribosome biogenesis factor, evidencing co-evolution between ribosome biogenesis factor and the ribosome. These findings suggest that ribosomal biogenesis is more flexible than recognized, and the small cell and genome sizes of Candidate Phyla Radiation bacteria and their early divergence may influence the unusual repertoires of ribosome biogenesis factors.