Adaptation to high-altitude hypoxia is characterized by systemic and organ-specific metabolic changes. This study investigates whether intestinal metabolic rewiring is a contributing factor to hypoxia adaptation. We conducted a longitudinal analysis over 108 days, with seven time points, examining fecal metabolomic data from a cohort of 46 healthy male adults traveling from Chongqing (a.s.l. 243 m) to Lhasa (a.s.l. 3,658 m) and back. Our findings reveal that short-term hypoxia exposure significantly alters intestinal metabolic pathways, particularly those involving purines, pyrimidines, and amino acids. A notable observation was the significantly reduced level of intestinal uric acid, the end product of purine metabolism, during acclimatization (also called acclimation) and additional two long-term exposed cohorts (Han Chinese and Tibetans) residing in Shigatse, Xizang (a.s.l. 4,700 m), suggesting that low intestinal uric acid levels facilitate adaptation to high-altitude hypoxia. Integrative analyses with gut metagenomic data showed consistent trends in intestinal uric acid levels and the abundance of key uric acid-degrading bacteria, predominantly from the Lachnospiraceae family. The sustained high abundance of these bacteria in the long-term resident cohorts underscores their essential role in maintaining low intestinal uric acid levels. Collectively, these findings suggest that the rewiring of intestinal uric acid metabolism, potentially orchestrated by gut bacteria, is crucial for enhancing human resilience and adaptability in extreme environments.

Malate dehydrogenases (MalDH) (EC.1.1.1.37), which are involved in the conversion of oxaloacetate to pyruvate in the tricarboxylic acid cycle, are a relevant model for the study of enzyme evolution and adaptation. Likewise, a recent study showed that Methanococcales, a major lineage of Archaea, is a good model to study the molecular processes of proteome thermoadaptation in prokaryotes. Here, we use ancestral sequence reconstruction and paleoenzymology to characterize both ancient and extant MalDHs. We observe a good correlation between inferred optimal growth temperatures (OGTs) and experimental optimal temperatures for activity (A-Topt). In particular, we show that the MalDH present in the ancestor of Methanococcales was hyperthermostable and had an A-Topt of 80°C, consistent with a hyperthermophilic lifestyle. This ancestor gave rise to two lineages with different thermal constraints, one remaining hyperthermophilic while the other underwent several independent adaptations to colder environments. Surprisingly, the enzymes of the first lineage have retained a thermoresistant behavior (i.e., strong thermostability and high A-Topt), whereas the ancestor of the second lineage shows a strong thermostability, but a reduced A-Topt. Using mutants, we mimic the adaptation trajectory towards mesophily and show that it is possible to significantly reduce the A-Topt without altering the thermostability of the enzyme by introducing a few mutations. Finally, we reveal an unexpected link between thermostability and the ability to resist γ-irradiation-induced unfolding.

Phylodynamics is central to understanding infectious disease dynamics through the integration of genomic and epidemiological data. Despite advancements, including the application of deep learning to overcome computational limitations, significant challenges persist due to data inadequacies and statistical unidentifiability of key parameters. These issues are particularly pronounced in poorly resolved phylogenies, commonly observed in outbreaks such as SARS-CoV-2. In this study, we conducted a thorough evaluation of PhyloDeep, a deep learning inference tool for phylodynamics, assessing its performance on poorly resolved phylogenies. Our findings reveal the limited predictive accuracy of PhyloDeep (and other state-of-the-art approaches) in these scenarios. However, models trained on poorly resolved, realistically simulated trees demonstrate improved predictive power, despite not being infallible, especially in scenarios with superspreading dynamics, whose parameters are challenging to capture accurately. Notably, we observe markedly improved performance through the integration of minimal contact tracing data, which refines poorly resolved trees. Applying this approach to a sample of SARS-CoV-2 sequences partially matched to contact tracing from Hong Kong yields informative estimates of superspreading potential, extending beyond the scope of contact tracing data alone. Our findings demonstrate the potential for enhancing phylodynamic analysis through complementary data integration, ultimately increasing the precision of epidemiological predictions crucial for public health decision-making and outbreak control.

Although synonymous mutations are commonly assumed neutral or nearly so, recent years have seen reports of fitness effects of synonymous mutations detected under laboratory conditions. In a previous study, we used genome editing to construct thousands of yeast mutants each carrying a synonymous or nonsynonymous mutation in one of 21 genes, and discovered that most synonymous and most nonsynonymous mutations are deleterious. A concern was raised that this observation could be caused by the fitness effects of potential CRISPR/Cas9 off-target edits and/or secondary mutations, and an experiment that would be refractory to such effects was proposed. Using genome sequencing, we here show that no CRISPR/Cas9 off-target editing occurred, although some mutants did carry secondary mutations. Analysis of mutants with negligible effects from secondary mutations and new data collected from the proposed experiment confirms the original conclusion. These findings, along with other reports of fitness effects of synonymous mutations from both case and systematic studies, necessitate a paradigm shift from assuming (near) neutrality of synonymous mutations.

Genes encoded within organelle genomes often evolve at rates different from those in the nuclear genome. Here, we analyzed the relative rates of nucleotide substitution in the mitochondrial, apicoplast and nuclear genomes in four different lineages of Plasmodium species (malaria parasites) infecting mammals. The rates of substitution in the three genomes exhibit substantial variation among lineages, with the relative rates of nuclear and mitochondrial DNA being particularly divergent between the Laverania (including Plasmodium falciparum) and Vivax lineages (including Plasmodium vivax). Consideration of synonymous and nonsynonymous substitution rates suggests that their variation is largely due to changes in mutation rates, with constraints on amino acid replacements remaining more similar among lineages. Mitochondrial DNA mutation rate variations among lineages may reflect differences in the long-term average lengths of the sexual and asexual stages of the life cycle. These rate variations have far-reaching implications for the use of molecular clocks to date Plasmodium evolution.

The evolution of sex chromosomes can involve recombination suppression sometimes involving structural changes, such as inversions, allowing subsequent rearrangements, including inversions and gene transpositions. In the two major genus Salix clades, Salix and Vetrix, almost all species are dioecious, and sex-linked regions have evolved on chromosome 7 and 15, with either male or female heterogamety. We used chromosome conformation capture (Hi-C) and PacBio HiFi (high-fidelity) reads to assemble chromosome-level, gap-free X and Y chromosomes from both clades, S. triandra (15XY system), a basal species in the Vetrix clade, and the Salix clade species S. mesnyi (7XY system). Combining these with other available genome assemblies, we found inversions within the sex-linked regions, which are likely to be pericentromeric and probably recombined rarely in the ancestral species, before sex-linkage evolved. The Y-linked regions in all 15XY and 7XY species include partial duplicates containing exon 1 of an ARR17-like gene similar to male-determining factors in other Salicaceae species. We also found duplicates of a Y-specific gene, which we named MSF. The derived Salix clade 7XY chromosome systems appear to have evolved when these two genes transposed from the 15Y to the 7Y. Additionally, the 7Y chromosomes in S. dunnii and S. chaenomeloides probably evolved from the ancestral 7X of the Salix clade, involving a similar transposition, and loss of the ancestral 7Y. We suggest that pericentromeric regions that recombine infrequently may facilitate the evolution of sex linkage.

Mollusk-hunting (molluscivorous) cone snails belong to a monophyletic group in Conus, a genus of venomous marine snails. The molluscivorous lineage evolved from ancestral worm-hunting (vermivorous) snails ∼18 Ma. To enable the shift to a molluscivorous lifestyle, molluscivorous cone snails must solve biological problems encountered when hunting other gastropods, namely: (i) preventing prey escape and (ii) overcoming the formidable defense of the prey in the form of the molluscan shell, a problem unique to molluscivorous Conus. Here, we show that χ-conotoxins, peptides exclusively expressed in the venoms of molluscivorous Conus, provide solutions to the above problems. Injecting χ-conotoxins into the gastropod mollusk Aplysia californica results in impaired locomotion and uncoordinated hyperactivity. Impaired locomotion impedes escape, and a hyperactive snail will likely emerge from its shell, negating the protection the shell provides. Thus, χ-conotoxins are an evolutionary innovation that accompanied the emergence of molluscivory in Conus and provide solutions to problems posed by hunting other snails.

Bats possess a range of distinctive characteristics, including flight, echolocation, impressive longevity, and the ability to harbor various zoonotic pathogens. Additionally, they account for the second-highest species diversity among mammalian orders, yet their phylogenetic relationships and demographic history remain underexplored. Here, we generated de novo assembled genomes for 17 bat species and two of their mammalian relatives (the Amur hedgehog and Chinese mole shrew), with 12 genomes reaching chromosome-level assembly. Comparative genomics and ChIP-seq assays identified newly gained genomic regions in bats potentially linked to the regulation of gene activity and expression. Notably, some antiviral infection related gene under positive selection exhibited the activity of suppressing cancer, evidencing the linkage between virus tolerance and cancer resistance in bats. By integrating published bat genome assemblies, phylogenetic reconstruction established the proximity of noctilionoid bats to vesper bats. Interestingly, we found two distinct patterns of ancient population dynamics in bats and population changes since the last-glacial maximum do not reflect species phylogenetic relationships. These findings enriched our understanding of adaptive mechanisms and demographic history of bats.

Limbs are a defining characteristic of tetrapods, yet numerous taxa, primarily among amphibians and reptiles, have independently lost limbs as an adaptation to new ecological niches. To elucidate the genetic factors contributing to this convergent limb loss, we present a 12 Gb chromosome-level assembly of the Banna caecilian (Ichthyophis bannanicus), a limbless amphibian. Our comparative analysis, which includes the reconstruction of amphibian karyotype evolution, reveals constrained gene length evolution in a subset of developmental genes across 3 large genomes. Investigation of limb development genes uncovered the loss of Grem1 in caecilians and Tulp3 in snakes. Interestingly, caecilians and snakes share a significantly larger number of convergent degenerated conserved noncoding elements than limbless lizards, which have a shorter evolutionary history of limb loss. These convergent degenerated conserved noncoding elements overlap significantly with active genomic regions during mouse limb development and are conserved in limbed species, suggesting their essential role in limb patterning in the tetrapod common ancestor. While most convergent degenerated conserved noncoding elements emerged in the jawed vertebrate ancestor, coinciding with the origin of paired appendage, more recent degenerated conserved noncoding elements also contribute to limb development, as demonstrated through functional experiments. Our study provides novel insights into the regulatory elements associated with limb development and loss, offering an evolutionary perspective on the genetic basis of morphological specialization.

The transcriptional regulatory network (TRN) in bacteria is thought to rapidly evolve in response to selection pressures, modulating transcription factor (TF) activities and interactions. In order to probe the limits and mechanisms surrounding the short-term adaptability of the TRN, we generated, evolved, and characterized knockout (KO) strains in Escherichia coli for 11 regulators selected based on measured growth impact on glucose minimal media. All but one knockout strain (Δlrp) were able to recover growth and did so requiring few convergent mutations. We found that the TF knockout adaptations could be divided into four categories: (i) Strains (ΔargR, ΔbasR, Δlon, ΔzntR, and Δzur) that recovered growth without any regulator-specific adaptations, likely due to minimal activity of the regulator on the growth condition, (ii) Strains (ΔcytR, ΔmlrA, and ΔybaO) that recovered growth without TF-specific mutations but with differential expression of regulators with overlapping regulons to the KO'ed TF, (iii) Strains (Δcrp and Δfur) that recovered growth using convergent mutations within their regulatory networks, including regulated promoters and connected regulators, and (iv) Strains (Δlrp) that were unable to fully recover growth, seemingly due to the broad connectivity of the TF within the TRN. Analyzing growth capabilities in evolved and unevolved strains indicated that growth adaptation can restore fitness to diverse substrates often despite a lack of TF-specific mutations. This work reveals the breadth of TRN adaptive mechanisms and suggests these mechanisms can be anticipated based on the network and functional context of the perturbed TFs.

Multiple rounds of whole-genome duplication (WGD) followed by diploidization have occurred throughout the evolutionary history of angiosperms. Much work has been done to model the genomic consequences and evolutionary significance of WGD. While researchers have historically modeled polyploids as either allopolyploids or autopolyploids, the variety of natural polyploids span a continuum of differentiation across multiple parameters, such as the extent of polysomic vs. disomic inheritance, and the degree of genetic differentiation between the ancestral lineages. Here we present a forward-time polyploid genome evolution simulator called SpecKS. SpecKS models polyploid speciation as originating from a 2D continuum, whose dimensions account for both the level of genetic differentiation between the ancestral parental genomes, as well the time lag between ancestral speciation and their subsequent reunion in the derived polyploid. Using extensive simulations, we demonstrate that changes in initial conditions along either dimension of the 2D continuum deterministically affect the shape of the Ks histogram. Our findings indicate that the error in the common method of estimating WGD time from the Ks histogram peak scales with the degree of allopolyploidy, and we present an alternative, accurate estimation method that is independent of the degree of allopolyploidy. Lastly, we use SpecKS to derive tests that infer both the lag time between parental divergence and WGD time, and the diversity of the ancestral species, from an input Ks histogram. We apply the latter test to transcriptomic data from over 200 species across the plant kingdom, the results of which are concordant with the prevailing theory that the majority of angiosperm lineages are derived from diverse parental genomes and may be of allopolyploid origin.

In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data is limited, the ease at which simulated data can now be generated has led to the recent development of approaches that take in image representations of haplotype alignments and automatically extract important features using convolutional neural networks. Digital image processing methods termed α-molecules are a class of techniques for multi-scale representation of objects that can extract a diverse set of features from images. One such α-molecule method, termed wavelet decomposition, lends greater control over high-frequency components of images. Another α-molecule method, termed curvelet decomposition, is an extension of the wavelet concept that considers events occurring along curves within images. We show that application of these α-molecule techniques to extract features from image representations of haplotype alignments yield high true positive rate and accuracy to detect hard and soft selective sweep signatures from genomic data with both linear and nonlinear machine learning classifiers. Moreover, we find that such models are easy to visualize and interpret, with performance rivaling those of contemporary deep learning approaches for detecting sweeps.

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence-function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ∼400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

Felsenstein's bootstrap is the most commonly used method to measure branch support in phylogenetics. Current sequencing technologies can result in massive sampling of taxa (e.g. SARS-CoV-2). In this case, the sequences are very similar, the trees are short, and the branches correspond to a small number of mutations (possibly 0). Nevertheless, these trees contain a strong signal, with unresolved parts but a low rate of false branches. With such data, Felsenstein's bootstrap is not satisfactory. Due to the frequentist nature of bootstrap sampling, the expected support of a branch corresponding to a single mutation is ∼63%, even though it is highly likely to be correct. Here, we propose a Bayesian version of the phylogenetic bootstrap in which sites are assigned uninformative prior probabilities. The branch support can then be interpreted as a posterior probability. We do not view the alignment as a small subsample of a large sample of sites, but rather as containing all available information (e.g. as with complete viral genomes, which are becoming routine). We give formulas for expected supports under the assumption of perfect phylogeny, in both the frequentist and Bayesian frameworks, where a branch corresponding to a single mutation now has an expected support of ∼90%. Simulations show that these theoretical results are robust to realistic data. Analyses on low-homoplasy viral and nonviral datasets show that Bayesian bootstrap support is easier to interpret, with high supports for branches very likely to be correct. As homoplasy increases, the two supports become closer and strongly correlated.

Comparative genomic studies of social insects suggest that changes in gene regulation are associated with evolutionary transitions in social behavior, but the activity of predicted regulatory regions has not been tested empirically. We used self-transcribing active regulatory region sequencing, a high-throughput enhancer discovery tool, to identify and measure the activity of enhancers in the socially variable sweat bee, Lasioglossum albipes. We identified over 36,000 enhancers in the L. albipes genome from 3 social and 3 solitary populations. Many enhancers were identified in only a subset of L. albipes populations, revealing rapid divergence in regulatory regions within this species. Population-specific enhancers were often proximal to the same genes across populations, suggesting compensatory gains and losses of regulatory regions may preserve gene activity. We also identified 1,182 enhancers with significant differences in activity between social and solitary populations, some of which are conserved regulatory regions across species of bees. These results indicate that social trait variation in L. albipes is associated with the fine-tuning of ancient enhancers as well as lineage-specific regulatory changes. Combining enhancer activity with population genetic data revealed variants associated with differences in enhancer activity and identified a subset of differential enhancers with signatures of selection associated with social behavior. Together, these results provide the first empirical map of enhancers in a socially flexible bee and highlight links between cis-regulatory variation and the evolution of social behavior.

While whole-genome sequencing has been applied extensively to investigate the genetic diversity of global populations, ethnic minority groups in Pakistan are generally underrepresented. In particular, little is known about the genetic origin and highland adaptation of the Pamirian Wakhi people. According to Chinese historical records, the geographical location and language usage of Wakhi may be closely related to Xinjiang Tajiks (XJT). In this study, based on high-coverage (∼30×) whole-genome sequencing of eight Wakhi and 25 XJT individuals, we performed data analyses together with worldwide populations to gain insights into their genetic composition, demography, and adaptive evolution to the highland environment. The Wakhi derived more than 85% of their ancestry from West Eurasian populations (European ∼44.5%, South Asian ∼42.2%) and 10% from East Eurasian populations (Siberian ∼6.0%, East Asian ∼4.3%). Modeling the admixture history of the Wakhi indicated that the early West-East admixture occurred approximately 3,875-2,250 years ago and that the recent admixture occurred 750-375 years ago. We identified selection signatures across EGLN3, in particular, a distinctive evolutionary signature was observed, and a certain underlying selected haplotype showed higher frequency (87.5%) in the Wakhi than in nearby XJT and other highlanders. Interestingly, we found high-frequency archaic sequences in the Wakhi genome, which overlapped with several genes related to cellular signaling transduction, including MAGI2, previously associated with high-altitude adaptation. Our analysis indicates that the Wakhi are distinct from the XJTs and Tajikistan Tajiks, and shed light on the Wakhi's ancestral origin and genetic basis of high-altitude adaptation.

Transposable elements (TEs) compose a substantial proportion of the largest eukaryotic genomes. TE diversity has been hypothesized to be negatively correlated with genome size, yet empirical demonstrations of such a relationship in a phylogenetic context are largely lacking. Furthermore, the most abundant type of TEs in genomes varies across groups, and it is not clear if there are patterns of TE activity consistent with genome size among different taxa with large genome sizes. We use low-coverage sequencing of 16 species of Neotropical salamanders, which vary ∼7-fold in genome size, to estimate TE relative abundance and diversity for each species. We also compare the divergence of copies of each TE superfamily to estimate patterns of TE activity in each species. We find a negative relationship between TE diversity and genome size, which is consistent with the hypothesis that either competition among TEs or reduced selection against ectopic recombination may result in lower diversity in the largest genomes. We also find divergent activity patterns in the largest versus the smallest genomes, suggesting that the history of TE activity may explain differences in genome size. Our results suggest that both TE diversity and relative abundance may be predictable, at least within taxonomic groups.

Streptomyces are ubiquitous soil-dwelling bacteria with large, linear genomes that are of special importance as a source of metabolites used in human and veterinary medicine, agronomy, and industry. Conjugative elements (actinomycetes integrative and conjugative elements, AICEs) are the main drivers of Streptomyces Horizontal Gene Transfer. AICE transfer has long been known to be accompanied by mobilization of chromosomal DNA. However, the magnitude of DNA transfer, or the localization of acquired DNA across their linear chromosome, has remained undetermined. We here show that conjugative crossings in sympatric strains of Streptomyces result in the large-scale, genome-wide distributed replacement of up to one-third of the recipient chromosome, a phenomenon for which we propose the name "Streptomyces Chromosomal Transfer" (SCT). Such chromosome blending results in the acquisition, loss, and hybridization of Specialized Metabolite Biosynthetic Gene Clusters, leading to a novel metabolic arsenal in exconjugant offspring. Harnessing conjugation-mediated specialized metabolite biosynthesis gene cluster diversification holds great promise in the discovery of new bioactive compounds including antibiotics.

Rates of molecular evolution vary greatly among even closely related species. Although theory predicts that antagonistic interactions between species increase rates of molecular evolution, predictions for how mutualism affects evolutionary rates are mixed. We compared rates of molecular evolution between 1) mutualistic and non-mutualistic legumes, 2) an independent set of symbiotic rhizobia and their non-symbiotic close relatives, and 3) symbiotic and non-symbiotic clades within Ensifer, a diverse genus of bacteria with various lifestyles. We assembled transcriptomes de novo for 12 legume species and calculated dN/dS ratios at orthologous genes in all species to determine if genes in mutualistic plants evolve faster or slower than in their non-mutualistic relatives. We also calculated dN/dS ratios in genes known to be important for symbiosis. We found that mutualists have higher rates of molecular evolution genome-wide compared to non-mutualist legumes, but this pattern did not hold in symbiosis genes. We next calculated dN/dS ratios in 14 bacteria species across the proteobacteria phylogeny that differ in whether they associate mutualistically with plants, using published data. In most pairs, symbiotic rhizobia show higher dN/dS values compared to their non-symbiotic relatives. Within a bacterial genus with many well-characterized mutualist species (Ensifer), we calculated dN/dS ratios in symbiotic and non-symbiotic clades and found that symbiotic lineages have higher rates of molecular evolution genome-wide, but not at genes on the symbiotic plasmid pSymB. Our results suggest that although mutualism between legumes and rhizobia is associated with elevated rates of molecular evolution genome-wide, symbiosis genes may be evolutionarily stagnant.

Maroons in Suriname and French Guiana descend from enslaved Africans who escaped the plantations during colonial times. Maroon farmers still cultivate a large diversity of rice, their oldest staple crop. The oral history and written records of Maroons by colonial authorities provide contrasting perspectives on the origins of Maroon rice. Here, we analyzed the genomic ancestry of 136 newly sequenced Maroon rice varieties and found seven genomic groups that differ in their geographical associations. We interpreted these findings in light of ethnobotanical and archival investigations to reconstruct the historical contexts associated with the introduction of rice varieties to the Guianas. We found that two rice groups trace to West Africa, which we propose are linked to the transatlantic slave trade (c. 1526 to 1825). We posit that the Maroon rice stock additionally contains varieties that derive from rice introduced by indentured laborers from Java (1890 onwards), USA rice breeders (1932 onwards), and Hmong refugees who fled the Vietnam War (1991). Furthermore, on the Maroon fields, we found rice types never documented before that were derived from crosses. Overall, our results demonstrate that the Maroon farmers prioritize maintenance of a high stock diversity, which we posit reflects the expertise they inherited from their (African) ancestors. Ignored by agricultural modernization initiatives, Maroon farmers today are custodians of a unique cultural heritage. Notably, the genomic findings underline many Maroon stories about their past. We anticipate that a similar study approach can be applied to other heirloom crops of (Indigenous) communities that may have preserved their history on their farms to reconstruct, acknowledge, and honor the past.