Integrative zoology最新文献

Cetaceans possess thick blubber, a specialized adipose tissue essential for thermal insulation, a streamlined body form, energy storage, and buoyancy. However, the mechanisms that underpin this adaptation are not yet fully understood. Here, we found that uncoupling protein 1 (UCP1) of cetaceans has undergone significant evolutionary relaxation. A transgenic mouse model with cetacean-like UCP1 inactivation revealed a pronounced obesity phenotype, including expanded brown adipose tissue (BAT) and increased white adipose tissue (WAT) adipocyte hyperplasia. Histological, metabolic, and physiological assessments showed reduced lipolysis, impaired glucose metabolism, and upregulated lipid metabolism pathways in BAT. Additionally, gut microbiome analysis indicated an increased Firmicutes/Bacteroidetes ratio, suggesting enhanced energy absorption and weight gain. Comparison with traditional UCP1-KO mice further revealed that the unique mutations in cetacean UCP1 could be the molecular basis for observed fat accumulation phenotype. Our findings provide novel insights into the evolutionary mechanisms underlying blubber thickening in the secondary aquatic adaptation of cetaceans.

Elongated tails are exaggerated ornaments observed in various bird species, and their functional and evolutionary dynamics have attracted considerable attention. Empirical studies consistently show that sexual selection is a major drive of tail elongation. However, the genetic basis of this trait remains poorly understood. To address this gap, we performed comparative genomic analyses of 23 bird species, including 7 with extremely long tails and 16 with relative short tails. Genes related to feather development exhibited amino acid convergence replacement (e.g., APC) or displayed faster evolutionary rates (e.g., LEF1, WISP3) in the long-tailed species. Importantly, we identified convergence replacements of amino acids and rapid evolution in genes related to reproductive functions (e.g., PAQR7) and immunity (e.g., ADA), suggesting that elongated tails may serve as honest signals of genetic quality. In conclusion, this study provides genomic evidence supporting the role of sexual selection in the evolution of elongated tails, revealing an intricate interplay between sexually selected traits, fitness, and immune competence.

Haemoproteus Kruse, 1890 (Haemosporida: Haemoproteiidae) parasites are known for their high genetic diversity, avian host-specificity, and wide geographical distribution. Currently, 2019 lineages are registered as Haemoproteus species, but only 160 of them have been linked to morphospecies. Two main open access and independent databases are used to compile genetic, geographical, and host information on Haemoproteus parasites: GenBank and MalAvi. However, the data registered are not integrated, representing an obstacle in investigating Haemoproteus parasites. Here, we review all reported avian Haemoproteus lineages convincingly linked to morphospecies. First, we collected all records from GenBank and MalAvi and extracted Haemoproteus parasites identified from wild birds using the cytochrome b gene, with clear evidence of gametocytes being present in blood smears. This led to 135 lineages that were phylogenetically analyzed and compared regarding their distribution across bird species, families, orders, and geographic regions. Most lineages were identified from Passeriformes (68.8%, 95 lineages) and Columbiformes (13.8%, 19 lineages). Phylogenetic analysis shows the relation between bird host families and parasite lineages, confirming that Haemoproteus parasites are highly host-specific and that morphospecies tend to cluster phylogenetically. The global patterns of host-bird specificity and distributions show that lineages linked with morphospecies were skewed toward Europe and South America. Additionally, there are discrepancies between the two databases, as well as lineages in MalAvi linked to morphospecies without clear evidence of morphological identification. In conclusion, the research on Haemoproteus parasites would benefit from establishing a clear protocol for data registration and integrating the morphological and molecular methods for parasite screening.

The framework of integrating passive acoustic monitoring (PAM) and deep learning algorithms with social network analysis (SNA) presents a groundbreaking approach to understanding the complex dynamics of animal societies, especially studying the social behavior and communication of elusive species or those living in inaccessible habitats. By leveraging the non-invasive nature of PAM, we could collect long-term, high-resolution audio data of animal vocalizations, which are essential for understanding social interactions. Applying deep learning algorithms to these data has significantly enhanced our ability to identify, classify, and extract subtle patterns within vocalizations, revealing social subgroups and communication networks that were once undetectable. Furthermore, this technological advancement enables the efficient processing of vast amounts of data and the integration of multi-layered information, such as movement and environmental data, to create a comprehensive view of animal social networks. The framework proposed in this review also facilitates the comparison of social networks across different species and ecological contexts, contributing to a deeper understanding of the principles governing social behavior. As technology continues to evolve, the potential of this framework to transform our capacity to study and protect animal societies is immense, offering a promising future for behavioral ecology and conservation biology.

Major ampullate (MA) silk, synthesized by spiders, is tougher than most biological and synthetic materials. Orb weavers evolved some of the toughest MA silk, reaching extremes in bark spiders, genus Caerostris (Araneidae). Increased proline content is associated with tougher silk but may increase the metabolic cost. Transitions (phylogenetic/ontogenetic) to larger body sizes are expected to drive coevolution of tougher, costlier silk, because larger prey presents disproportionally higher kinetic energy. Interspecific shifts to tougher MA silk are documented, but intraspecific patterns are unknown, although spiders increase several hundred times in body mass through ontogeny. Small spiderlings prey on small insects and might not face the selection pressure on adults for capturing large prey. Additionally, extreme female-biased sexual size dimorphism in orb-weaving species like bark spiders results in sex-specific selection pressures for small versus large prey. We therefore ask whether species with exceptionally tough silk, like bark spiders, show different patterns in silk toughness between ontogenetic stages and sexes. We posed three hypotheses: H1, constrained silk production hypothesis; H2, sexually decoupled silk production hypothesis; H3, body size selection pressure hypothesis; and tested them by investigating the mechanical properties of MA silk among size classes and sexes in two Caerostris species from Madagascar, C. darwini Kuntner & Agnarsson, 2010 and C. kuntneri Gregorič & Yu, 2025. We found that only large females produce exceptionally tough silk with higher initial stiffness, while juvenile females and all males produce inferior silks. These results imply ontogenetic plasticity in Caerostris silk production and support the third hypothesis.

A cartoon for showing the two steps (regional dispersal and local dispersal) of the proposed theory for biodiversity formation.

This flowchart outlines the comprehensive workflow of the study, integrating diverse bioinformatics tools (e.g., NCBI2GO, SSU-align, bpRNA) and their sequential interactions. Key steps, such as data preprocessing, structural prediction, and evolutionary analysis, are depicted with their respective outputs (e.g., standardized records, consensus templates, domain annotations) listed on the right, connected via directional arrows to illustrate data flow.

The adaptive evolution of Canidae mitochondrial genomes and their mechanistic association with ecological strategies have long been constrained by insufficient cross-lineage integration and unresolved multidimensional interaction networks. Here, complete mitochondrial genomes from all extant canid species (including 11 newly assembled genomes) were analyzed, revealing highly conserved gene arrangements and lineage-specific codon usage patterns. High-altitude species exhibited atypical initiation codons for ND4L, while boreal species exhibited significant termination codon shifts, and polar specialists had distinct codon optimization profiles. Positive selection analyses identified strong selective pressures on arginine- and leucine-encoding sites, with core oxidative phosphorylation genes demonstrating accelerated adaptive evolution in large-bodied canids and specialized predatory lineages. Phylogenomic reconstructions revealed consistency in South American Lycalopex radiation timing with regional orogenic events, while also linking Canis diversification to grassland biome expansion. Further, statistical models confirmed robust correlations between mitochondrial evolutionary rates and both body mass and predatory ecology, wherein body size increases drive metabolic optimization through lineage-specific selection on energy-related genes. Based on these observations, a "functional constraint-geological driver-body size adaptation" tripartite framework is proposed that highlights how mitochondrial genomes maintain metabolic plasticity through mutation-selection equilibrium, how geological events trigger lineage divergence, and how body size-predation strategies shape modular gene evolution. Consequently, this study establishes a novel paradigm for understanding genome-environment interactions in terrestrial carnivore adaptations.

Parasitism can play a key role in shaping species' adaptability to environmental changes. Understanding how intrinsic traits of bird species influence susceptibility to haemosporidian infection is critical for understanding host-parasite dynamics, especially in biodiverse tropical regions. This study aimed to determine the host traits that influence the probability of haemosporidian infection in birds in a tropical country. We compiled published haemosporidian diagnoses of birds from Colombia and data on ecological, morphological, coloration, and sexual selection (dimorphism and dichromatism) traits. We also calculated an index for habitat specialization. Using phylogenetic generalized linear models (phylo-GLMs), we performed a phylogenetically informed comparative analysis of 115 bird species from different families with diverse characteristics. Our analysis revealed that migratory species, birds with larger body sizes, and those with more colorful plumage had a higher probability of infection. Conversely, habitat specialization was negatively associated with infection risk. Our results are explained in the framework of increased exposure to haemosporidian vectors. However, further studies are needed to better understand the relationship between the traits related to sexual selection and infection. These findings provide valuable insights into host-parasite dynamics in tropical bird communities and help to understand susceptibility factors, considering the potential negative consequences for avian communities.

In this study, we introduce Dual-Branch BioTraitNet, a deep-learning model tailored for trait imputation in small-sample ecological and biological datasets. By combining unsupervised and supervised learning strategies, the model jointly leverages quantitative and qualitative trait information. Its dual-branch architecture enables efficient learning under data-sparse conditions and generalizes well across diverse taxa. On the lizard dataset, the model achieved R² values of 0.862 for mean body length and 0.67 for average body weight; on the fish dataset, R² values for maximum body length, minimum spawning temperature, and egg diameter were 0.876, 0.402, and 0.496, respectively. Unlike conventional approaches such as K-nearest neighbors (KNN) and genetic algorithms (and their variants), which are often prone to overfitting or underfitting, BioTraitNet demonstrates strong predictive stability and robustness. This is evident in its consistent avoidance of negative R² values. Notably, it maintains high accuracy even without incorporating phylogenetic information, making it particularly suitable for scenarios where evolutionary data are missing or uncertain. The proposed framework offers a flexible and reliable solution for addressing missing trait data in ecological and evolutionary research. The computational Python code was available from https://github.com/BB-yu/Dual-Branch-BioTraitNet.