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Female song elicits increased vocal display effort in both sexes of Alston's singing mouse

Acoustic displays are conspicuous behaviors common across diverse animal taxa. They have long been studied in behavioral ecology, evolutionary biology, and neuroscience. Most of these investigations, however, have focused on male display. For species in which both sexes display, correcting this bias will lead to a fuller understanding of the evolution and function of these behaviors. In this study, we investigated the role of vocal advertisement display in female Alstons singing mice (Scotinomys teguina). Singing mice are small muroid rodents of the family Cricetidae, native to high altitude cloud forests of Central America. Females and males both produce elaborate advertisement songs used in mate attraction and intra-sexual competition. Prior studies have largely focused on male behavior, though we recently found that both sexes dramatically increase their rate of singing and song duration in response to playback of conspecific male song. Here, we tested how mice of both sexes adjust their song effort in response to female song playback. Our results show that, like male song, female song elicits robust increases in song effort from both female and male mice. This study reveals additional social contexts that promote high song effort in this species, while raising additional questions about the role of song in communication within and between the sexes.

animal behavior and cognition↗

NJGPT: A Large Language Model-Driven, User-Friendly Solution for Phylogenetic Tree Construction

MotivationPhylogenetic reconstruction plays an integral part in much of the research in evolutionary biology. Currently, a newly minted phylogeneticist must choose amongst a relatively large array of phylogenetic software, each often with its own analytical routines, inputs and outputs. Our overarching aim is to construct a user-friendly pipeline with the most recent generative AI tool, ChatGPT-4 (at the time of writing) released by OpenAI, that is able to understand queries written in natural language, to build a phylogenetic tree using sequence data. By doing this, we demonstrate how generative AI may be used in phylogenetics, as a proof-of-concept. We also demonstrate the steps needed, presently, to ensure that ChatGPT can build phylogenetic trees accurately. ResultsWe present NJGPT, a phylogenetic tool built using ChatGPT, a Large Language Model (LLM) Generative Pre-trained Transformer (GPT),which employs the Neighbor-Joining method to construct phylogenetic trees. NJGPT simplifies phylogenetic tree construction by allowing users to generate and visualize trees using natural language queries. It supports multiple sequence file formats, matrix calculation models, and gap-deletion methods. To evaluate the performance of NJGPT, we compared output and runtimes with the widely-used phylogenetic software, MEGA. Our results show that NJGPT produces identical trees over a range of sequence lengths and simple models of evolution. However, NJGPT faces visualization issues with datasets over 50 taxa and operational failures with larger datasets due to token limits. NJGPT runtimes were also substantially slower than MEGA; however, NJGPTs user-friendly interface makes it ideal for beginners. AvailabilityThis plugin is available for free at https://chatgpt.com/g/g-1OzP3Qviw-njgpt, the source code is available on GitHub (https://github.com/ZWan622/NJGPT1.0.git) and is implemented using Python Contactzwan622@aucklanduni.ac.nz Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

Sexual reproduction is controlled by successive transcriptomic waves in Podospora anserina

Despite the inherent challenge of finding suitable mating partners, most eukaryotes use sexual reproduction to produce offspring endowed with increase genetic diversity and fitness. The persistence of this mode of reproduction is a key question in evolutionary biology. Fungi offer valuable insights into this question, due to their diversity and short lifecycle. This study focuses on Podospora anserina, a pseudohomothallic ascomycete fungus that bypasses self-sterility by maintaining two compatible nuclei in one mycelium. We performed genome-wide gene expression profiling during ten stages of P. anserina sexual reproduction and identified five major expression patterns. Our expert annotation approaches identified differentially expressed genes related to secondary metabolite production, fungal vegetative incompatibility, programmed cell death, and epigenetic regulation. In addition, master transcriptional regulators and their target networks were uncovered. This study provides a comprehensive database for future functional genomics experiments and novel pathway characterization during sexual reproduction.

genomics↗

Unveiling the evolutionary history of European vipers and their venoms from a multi-omic approach

Snake genomes attract significant attention from multiple disciplines, including medicine, drug bioprospection, and evolutionary biology, due to the unique features found in snakes, especially, the evolution of venom. However, genomic research within the family Viperidae has mostly focused to date on the subfamily Crotalinae, while overlooking Viperinae, the Old World vipers. Among Viperinae, European vipers (Vipera) have been the subject of extensive research because of their venoms, phylogeographic, and ecological diversification. Nevertheless, venom research in this group has been conducted using mostly proteomes alone, while phylogeography and systematics in the genus have relied on biased information from mitochondrial phylogenies. Here, we generated chromosome-level genome assemblies for three Vipera species and whole-genome sequencing data for 94 samples representing 15 Vipera taxa. This comprehensive dataset has enabled us to disentangle the phylogenomic relationships of this genus, affected by mito-nuclear discordance and pervaded by ancestral introgression. Population-level analyses in the Iberian Peninsula, where the three oldest lineages within Vipera meet, revealed signals of recent adaptive introgression between ecologically dissimilar species, whereas chromosomal rearrangements isolate species occupying similar niches. Finally, using transcriptomic and proteomic data, we characterized the Vipera toxin-encoding genes, in which opposing selective forces were unveiled as common drivers of the evolution of venom as an integrated phenotype.

genomics↗

A High-quality Genome Assembly of Annona squamosa (Custard Apple) Provides Functional Insights into an Emerging Fruit Crop

Annona squamosa, also known as custard apple, is an emerging fruit crop with medicinal significance. We constructed a high-quality genome of A. squamosa along with transcriptome data to gain insights into its phylogeny, evolution and demographic history. The genome has an N50 value of 93.2 Mb assembled into seven pseudochromosomes. The demographic history showed a continuous decline in the effective population size of A. squamosa. Phylogenetic analysis revealed that magnoliids were sister to eudicots, whereas ASTRAL gene trees showed discordance due to incomplete lineage sorting (ILS). Genome syntenic and Ks distribution analyses confirmed the absence of a recent whole genome duplication event in the A. squamosa. Gene families related to photosynthesis, oxidative phosphorylation and plant thermogenesis were found to be highly expanded in the genome. Comparative analysis with other magnoliids revealed the adaptative evolution in the genes of flavonoid biosynthesis pathway, amino sugar, nucleotide sugar and sucrose metabolism, conferring medicinal value and enhanced hexose sugar accumulation. In addition, we performed genome-wide identification of SWEET genes. Our high-quality genome and evolutionary insights of this emerging fruit crop, thus, serve as a valuable resource for advancing studies in functional genomics, evolutionary biology, and crop improvement.

genomics↗

Cis-regulatory Mutations Drive Tissue-specific Subfunctionalization of sRNA loci Regulating Soybean Seed Color During Domestication

Gene duplication and structural rearrangements have played a pivotal role in plant genome evolution, enabling functional divergence and the development of novel traits. In soybeans (Glycine max), the I locus, which regulates seed color through tissue-specific subfunctionalization of sRNA loci, offers an example of these mechanisms. Using long-read sequencing, we investigated structural variations underlying four major alleles (I, ii, ik, and i) at the I locus. Our study revealed that large-scale rearrangements, including duplications, inversions, and deletions, within a 180-kb CHS repeat-rich region drive allele-specific RNA silencing through small interfering RNAs (siRNAs). The dominant I allele contains a cis-regulatory region of DnaJ upstream of CHS genes, while the ii and ik alleles feature subtilisin- and P450-driven siRNA loci, respectively. The recessive i allele lacks siRNA production due to deletions or inversions disrupting CHS gene clusters. Phenotypic analyses and RNA-seq confirmed allele-specific, tissue-dependent expression of siRNAs correlating with seed coat pigmentation patterns. This study highlights the evolutionary role of repeat-rich regions in generating regulatory innovations and phenotypic diversity. Our findings underscore the importance of structural rearrangements in domestication traits and demonstrate the power of long-read sequencing for resolving complex genomic regions, advancing both evolutionary biology and crop improvement. SIGNIFICANCE{square} Naturally occurring mutations in the soybean seed coat have revealed the evolution of sRNA genes and their subfunctionalization, resulting in tissue-specific gene expression. {square}Non-homologous recombination of repetitive sequences drives cis-regulatory region rearrangements, leading to the subfunctionalization of sRNA loci that regulates one of domestication traits.

plant biology↗

First whole genome assembly of Python regius (ball python), a model of extreme physiological and metabolic plasticity

The study of nontraditional model organisms, particularly those exhibiting extreme phenotypes, offers unique insights into adaptive mechanisms of stress response and survival. Snakes, with their remarkable physiological, metabolic, and morphological adaptations, serve as powerful models for investigating these processes. Pythons are a unique model organism that have been studied for their extreme metabolic and physiological plasticity. To date, the Burmese python (Python bivittatus) is the only member of the Pythonidae family to have been sequenced. The low contiguity of this genome and rising challenges in obtaining Burmese pythons for study prompted us to sequence, assemble, and annotate the genome of the closely related ball python (Python regius). Using a hybrid sequencing approach, we generated a 1.45 Gb genome assembly with a contig N50 greater than 18 Mb and a BUSCO score of 98%, representing the highest quality genome to date for a member of the Pythonidae family. This assembly provides a valuable resource for studying snake-specific traits and evolutionary biology. Furthermore, it enables exploration of the molecular mechanisms underlying the remarkable cardiac and muscular adaptations in pythons, such as their ability to rapidly remodel organs following feeding and resist muscular atrophy during prolonged fasting. These insights have potential applications in human health, particularly in the development of therapies targeting cardiac hypertrophy and muscular atrophy.

genomics↗

Draft Genome of the Endangered Visayan Spotted Deer (Rusa alfredi)

The Visayan Spotted Deer (Rusa alfredi) is an endangered and endemic species in the Philippines facing significant threats from habitat loss and hunting. It is considered as the worlds most threatened deer species by the International Union for Conservation of Nature (IUCN) thus its conservation has been a top priority. Despite its status, there is a notable lack of genomic information available for R. alfredi and the genus Rusa in general. This study presents the first draft genome assembly of the Visayan Spotted Deer (VSD), Rusa alfredi, using Illumina short-read sequencing technology. The RusAlf_1.1 assembly has a 2.52 Gb total length with a contig N50 of 46 Kb and scaffold N50 size of 75 Mb. The assembly has a BUSCO complete score of 95.5%, demonstrating the genomes completeness, and includes the annotation of 24,531 genes. Phylogenetic analysis based on single-copy orthologs reveals a close evolutionary relationship between the R. alfredi and the genus Cervus. The availability of the RusAlf_1.1 genome assembly represents a significant advancement in our understanding of the VSD. It opens opportunities for further research in population genetics and evolutionary biology, which could contribute to more effective conservation and management strategies for this endangered species. This genomic resource can help in assuring the survival of Rusa alfredi in the country.

genomics↗

Water parameters and hydrodynamics in rivers and caves hosting Astyanax mexicanus populations reveal macro-, meso- and micro-habitat characteristics

The Mexican tetra (Astyanax mexicanus) has emerged as a leading model for evolutionary biology and the study of adaptation to extreme subterranean environments. The river-dwelling morph of the species is distributed in Mexico and Texas, while the blind and cave-adapted morph inhabits the karstic caves of the Sierra Madre Oriental in northeastern Mexico. The molecular, cellular and genetic underpinnings of Astyanax cavefish evolution are increasingly studied, but our understanding of its habitat and environment is incomplete, limiting the interpretations of its morphological, physiological, and behavioral adaptations. In particular, the physico-chemical parameters of the water and the hydrological regimes to which cavefish are subjected are largely unexplored. From 2009 to 2025, we have recorded the physico-chemical parameters of the water at localities hosting Astyanax mexicanus cavefish and surface fish in the Sierra de El Abra and Sierra La Colmena regions of the states of San Luis Potosi and Tamaulipas, Mexico. We sampled 13 caves out of the 33 known Astyanax caves and 30 surface stations (rivers, springs, ponds). Data were collected using a variety of devices and probes, including both point measurements (at the end of winter) and longitudinal measurements (throughout the year). The comparison of epigean and hypogean waters showed strong signatures of the two macro-habitats. As compared to surface, on average cave water was cooler, much less conductive and highly anoxic. Moreover, a comparison between different caves (i.e., meso-habitat level) revealed significant differences in both specific water parameters and hydrological regimes. One- or two-year longitudinal recordings demonstrated that some caves exhibit relatively stable hydrological regimes, while others experience multiple, sudden and significant fluctuations. Finally, distinct pools within a single cave showed notable differences, displaying a reproducible increasing gradient in water temperature as a function of distance from the cave entrance, and revealing specificities at the micro-habitat level. We interpret our comprehensive dataset on cave water quality and hydrodynamics in the context of an integrated view of cave biology and the evolution of cave organisms.

ecology↗

Comparative pangenome and mobilome analysis of clostridial species clusters reveals different levels of host adaptation and novel conserved biosynthetic potential

To thrive in diverse ecological niches, bacteria adopt various lifestyles, that range from living freely in the soil to forming close associations with human and animal hosts. However, the impact of these adaptation processes on their genomes and metabolisms remains largely unexplored beyond the genus level. Investigating these evolutionary dynamics at higher taxonomic levels can enhance our understanding of the relationship between host adaptation and their functional capabilities. Here, we examine the evolutionary trajectories and metabolic capabilities of the Clostridia class, which displays a variety of lifestyles and is of high importance for industry, medicine and microbiome research. First, we uncover that the clostridial orders have significantly different adaptation rates. Second, we show that the Oscillospirales order has undergone extensive genomic and functional specialisation toward a host-associated lifestyle, while the Lachnospirales order tends to be at a lower level of host association, retaining a remarkably high number of free-living trait genes and a high degree of metabolic versatility. Third, we reveal substantial differences in genomic architecture and metabolic versatility between the clostridial orders and link these to the progressing stages of host adaptation. Additionally, we identify widely conserved biosynthetic gene clusters, highlighting untapped biosynthetic potential of evolutionary significance. Hence, the beyond-genus level analyses in this study provide valuable new insights into bacterial adaptation with broad implications for evolutionary biology, microbiome research and biotechnology.

bioinformatics↗

High-Throughput Conjugation Reveals Strain Specific Recombination Patterns Enabling Precise Trait Mapping in Escherichia coli

Genetic exchange is a cornerstone of evolutionary biology and genomics, driving adaptation and enabling the identification of genetic determinants underlying phenotypic traits. In Escherichia coli, horizontal gene transfer via conjugation and transduction not only promotes diversification and adaptation but has also been instrumental in mapping genetic traits. However, the dynamics and variability of bacterial recombination remain poorly understood, particularly concerning the patterns of recombined DNA fragments. To elucidate these patterns and simultaneously develop a tool for trait mapping, we designed a high-throughput conjugation method to generate recombinant libraries. Recombination profiles were inferred through whole-genome sequencing of individual clones and populations after selection of a marker from the donor strain in the recipient. This analysis revealed an extraordinary range of recombined fragment sizes, spanning less than ten kilobases to over a megabase--a pattern that varied across the three tested strains. Mathematical modelling indicated that this diversity in recombined fragment size enables precise identification of selected loci following genetic crosses. Consistently, population sequencing pinpointed a selected marker at kilobase-scale accuracy, offering a robust tool for identifying subtle genetic determinants that could include point mutations in core genes. These findings challenge the conventional view that conjugation always transfers large fragments, suggesting that even short recombined segments, traditionally attributed to transduction, may originate from conjugation.

microbiology↗

Hi-reComb: constructing recombination maps from bulk gamete Hi-C sequencing

Recombination is central to genetics and to evolution of sexually reproducing organisms. However, obtaining accurate estimates of recombination rates, and of how they vary along chromosomes, continues to be challenging. To advance our ability to estimate recombination rates, we present Hi-reComb, a new method and software for estimation of recombination maps from bulk gamete chromosome conformation capture sequencing (Hi-C). Simulations show that Hi-reComb produces robust, accurate recombination landscapes. With empirical data from sperm of five fish species we show the advantages of this approach, including joint assessment of recombination maps and large structural variants, map comparisons using bootstrap, and workflows with trio phasing vs. Hi-C phasing. With off-the-shelf library construction and a straightforward rapid workflow, our approach will facilitate routine recombination landscape estimation for a broad range of studies and model organisms in genetics and evolutionary biology. Hi-reComb is open-source and freely available at https://github.com/millanek/Hi-reComb.

genetics↗

Quartformer: An Accurate Deep LearningFramework for Phylogenetic TreeConstruction

The construction of phylogenetic trees is a fundamental task in evolutionary biology, with the inference of tree topologies being particularly challenging due to the super-exponential growth in the number of possible topologies as the number of species increases. Recent advances in deep learning have offered promising solutions to this challenge, especially approaches that first infer the topologies of all quartets using deep neural networks, and then assemble these quartets into a complete phylogenetic tree using quartet combination algorithms. Building upon these methods, we propose Quartformer, a novel framework that incorporates a sparse attention mechanism to enhance information interaction among quartets derived from the same tree. This allows each quartet to be inferred with richer contextual information, leading to more accurate topology predictions. Experimental results demonstrate that Quartformer outperforms both the original framework and the traditional maximum likelihood method RAxML on simulated datasets. We further validate its improvements on real-biological datasets and theoretically analyze the underlying reasons for its performance gains, which also inform future research directions. Additionally, we systematically evaluate optimization strategies for inference speed and their impact on overall performance. Overall, this work advances the application of deep learning in phylogenetic tree Construction and provides theoretical and practical insights for future methodological developments in the field.

bioinformatics↗

Second-order elasticities for Ecology and Evolution: Unravelling nonlinear fitness responses to perturbations

In ecology and evolutionary biology, understanding the relationship between vital rates (e.g., survival, development, reproduction) and population growth is essential to elucidate how life history strategies are shaped by natural selection. However, the established demographic methods to decipher the relationship between vital rates and population growth often analyse only the linear changes in population fitness as a result of changes in vital rates, thus simplifying the complexities of said relationships. To overcome the widespread linearity simplification, here we introduce the second-order elasticities of mean population fitness, the S-elasticity. The S-elasticity quantifies how changes in one or more vital rates can produce a second-order change in mean fitness. We provide a systematic mathematical framework behind the S-elasticity, revealing its ability to identify the convex and concave responses of mean fitness to perturbations of vital rates. Through structured population models, we demonstrate the distinct roles of linear and nonlinear mean fitness responses, and their combination, enabling to characterise local concavity/convexity of the mean population fitness function. We illustrate the application and the differences of S-elasticities and their biological meanings using matrix population models of the armadillo (Dasupys novemcinctus) and Pynes plum (Astragallus bibullatus). These two case studies showcase how the S-elasticity provides key insights into mean fitness responses to perturbations on demographic process and their correlations. We discuss the improvements that the S-elasticity provides for species management and our understanding of how natural populations cope with environmental change.

ecology↗

Cryptic and Ecologically Relevant Locomotor Activity Patterns in Lake Malawi Cichlids Revealed Through Computer Vision Pipeline

Cichlid fishes have long been a popular model for ecology and evolutionary biology. Not only do they exhibit nearly unparalleled taxonomic diversity, but their community structures are both complex and extremely dense. Niche partitioning along dietary axes has been credited in maintaining cichlid biodiversity in a broad sense; however, it is common for cichlid species with overlapping diets to co-exist, leading to the search for other mechanisms to explain the maintenance of cichlid biodiversity. Behavioral variation has the potential to lead to fine-scale (i.e., micro-) habitat partitioning, but analyzing complex animal behavior poses several challenges, including time, cost and reproducibility. Modern tools, such as Machine Learning (ML), ease the burden of behavioral analyses, and are increasingly used in the field. Here, we present the application of tools from a well-developed sub-field of ML, Computer Vision (CV), to extract locomotor behavioral data from four Lake Malawi cichlid species. Our dataset consisted of low-resolution (320x240), twenty-four-hour infrared videos of activity in 4 cichlid species. We first analyzed a pair of species with divergent behaviors, diets and habitats (i.e., Abactochromis labrosus versus Tropheops kumwera), representing a proof-of-concept comparison. Next we analyzed activity in two closely related species with broadly similar behaviors and overlapping diets and habitats (i.e., Maylandia sp. Daktari versus Maylandia faiaziberi). In both comparisons, our analysis involved the quantification of tank usage patterns and stop/rest activity. Not only did our data align with the known ecologies and behaviors of the species in our proof-of-concept comparison, but they revealed novel behavioral differences between all species, especially as related to variation in tank usage from day to night. Our approach provides a window into potential cryptic behavioral niche partitioning, as well as a foundation for future, high-throughput analyses to study the genetic basis and evolution of behavior.

animal behavior and cognition↗

Myosin 2 drives actin contractility in fast-crawling species outside of the amorphean lineage

Myosin 2-dependent actin contractility drives essential cell functions including fast crawling motility in animal cells, Dictyostelium amoebae, and other species from the Amorphea lineage. Whether and how species outside this single eukaryotic group can generate contractile actin networks has been largely unexplored. We demonstrate that Naegleria, an amoeba from the Heterolobosea--an evolutionarily distant eukaryotic lineage that includes the fastest known crawling eukaryotes--expresses three distinct Myosin 2 homologs. Using biochemical assays and immunofluorescence, we show that these Myosin 2 proteins bind cellular actin networks and that these networks generate ATP-dependent contractility. By identifying additional Myosin 2 homologs in dozens of additional heterolobosean amoebae (but not obligate flagellates), we find a widespread correlation within this group between crawling behavior and contractile actin networks. This correlation includes the amoeba Vahlkampfia avara, which we demonstrate can crawl at speeds exceeding 180 m/min and has contractile actin networks and Myosin 2 homologs. These findings show that Myosin 2-driven contractility exists beyond Amorphea and is associated with diverse, fast-crawling cell types. Expanding the taxonomic breadth of actin network contractility impacts our basic understanding of cell motility, evolutionary biology, and of the fundamental biology of human pathogens that rely on fast cell migration.

cell biology↗

VAMPIRE: Analyzing variation and motif pattern in tandem repeats

Tandem repeats (TRs) are pervasive in eukaryotic genomes and play key roles in genome organization, evolution, and function, particularly in complex regions such as centromeres and subtelomeres. Although long-read sequencing technologies have improved the resolution of these regions, existing methods remain limited in their ability to systematically and accurately characterize large-scale TRs. Here, we introduce VAMPIRE, a k-mer-based computational tool for comprehensive TR discovery, annotation, and quantification. Unlike previous methods, VAMPIRE enables reference-free, fine-grained decomposition of both simple and complex TRs, capturing motif variation in sequence, length, and structure with high sensitivity and scalability. Applied to complete telomere-to-telomere (T2T) human and nonhuman primate (NHP) genome assemblies, VAMPIRE reveals previously unrecognized high-order repeat inversions within human centromeres--an underappreciated evolutionary mechanism contributing to centromere diversity. Additionally, the tool identifies lineage-specific and expanded TRs, including human-specific STR/VNTR expansions and NHP-specific subtelomeric heterochromatin (e.g., pCht/StSat), underscoring their dynamic turnover and structural complexity. VAMPIRE provides a robust and scalable framework for TR analysis in the era of long-read sequencing, with broad utility across human genetics, evolutionary biology, and the study of complex TRs in non-model organisms.

genomics↗

Bird species with color polymorphism have greater ecological success

The explanation of the variation in ecological success of species is one of the key challenges in ecology, evolutionary biology and conservation biology. Here, we discuss the function of polymorphism in body color which is one of the most conspicuous features of organisms strongly affecting the performance of species. We applied a phylogenetic comparative approach to assess whether body color polymorphisms contribute to species success in birds, reflected in distributional ranges, extinction risk, and current population trends. We compiled and analyzed a comprehensive global dataset that included the distribution, phylogeny, ecology and morphological traits of all extant bird species. Species with body color polymorphism showed larger distributional ranges, larger environmental ranges, lower risk of extinction, and more stable population trends. Our analyses suggest that the presence of color polymorphism contributes to avian species success at the global scale, especially reflected in lower extinction likelihood and better population trends.

ecology↗