Fish dentition exhibits substantial variability that reflects ecological niches and dietary specialization within the Red Sea ecosystem, highlighting adaptive evolutionary responses to different feeding strategies. This study investigated tooth morphology using scanning electron microscopy and explored the evolutionary basis of dental diversity through comparative genomic analyses. Ultrastructural examination of six representative fish families revealed distinct dentition patterns. Herbivorous (Scaridae and Siganidae) displayed incisiform, villiform, and molariform teeth, whereas carnivorous (Sphyraenidae, Holocentridae, Serranidae, Lethrinidae, and Lutjanidae) exhibited sharp conical and canine-like dentition adapted for prey capture. In parallel, 130 tooth-associated genes were analyzed across 25 teleost genomes representing herbivorous and carnivorous lineages. Phylogenetic analyses recovered well-supported family-level clades and suggested independent origins of herbivory consistent with convergent evolution. Selection analyses detected widespread episodic positive selection, with 70 genes remaining significant after correction. Branch-level analyses further identified reciprocal selection patterns between herbivorous and carnivorous lineages. Site-level analyses detected adaptive codons overlapping predicted functional regions in lrp5 and pam. Comparative tests further revealed contrasting selection pressures between trophic groups, with genes related to odontogenesis and skeletal development intensified in herbivores, whereas genes associated with growth factor signaling and neural processes were intensified in carnivores. Together, these findings highlight the interplay between dietary ecology, tooth morphology, and molecular evolution in teleost fishes. Functional validation will be required to confirm these genomic predictions.
To aid in the empirical evaluation of species hypotheses / concepts we present a strategy that uses NGS whole nuclear genome assemblies to identify novel single-copy universal PCR targets whose sequences discriminate species-scale clades. Our approach begins by identifying UCEs within partial Illumina genome assemblies across a strategically-chosen taxa set and culminates with experimental validation of appropriate single-copy nuclear DNA regions for PCR/Sanger sequencing. The highly diverse ( 35 K species) group of eupulmonate gastropods was used as proof-of-concept. Among the 24 K ultraconserved elements identified across 14 de novo and publicly-available genome assemblies spanning eupulmonate phylogeny, 61 informative universal PCR targets were ultimately identified. These allow for targeted sequence recovery from loci known to contain useful phylogenetic signal and permit efficient scaling to larger sample sizes, something that is immensely important when working with issues as complex as evolution and biodiversity.
This study re-evaluates the Pleistocene history of the European hedgehog (Erinaceus europaeus) and the Northern white-breasted hedgehog (E. roumanicus), by integrating genetically verified occurrence records, complementary allopatric GBIF records and ecological niche modelling (ENM). We assessed differences in broad-scale environmental associations, identified climatic predictors associated with their distributions, and reconstructed potential past climatic suitability during the Last Glacial Maximum. Niche overlap, equivalency and similarity analyses were applied across allopatric regions and areas of sympatry. Human Footprint showed a strong signal in exploratory models for both species, with a stronger effect in the Northern white-breasted hedgehog. Climatic predictors differed between the species: predicted suitability for the Northern white-breasted hedgehog was more strongly associated with temperature-related variables, whereas the European hedgehog models were mainly influenced by annual temperature range and precipitation-related variables. Niche comparisons across the Central European (CE) and Russian–Baltic (RB) contact zones revealed contrasting patterns, with stronger realized climatic niche differentiation in the CE zone and apparently greater, but less clearly resolved, niche overlap in the RB zone. The location of the CE contact zone may partly coincide with the transition between oceanic and continental climates, consistent with the trapping hypothesis of hybrid zones. Palaeoclimatic projections indicated suitable areas beyond the classical Mediterranean peninsulas, supporting the possibility of northern or extra-Mediterranean refugial areas. Our results suggest that broad-scale environmental gradients may contribute to the spatial structuring of contact zones and may interact with species-boundary dynamics despite ongoing hybridization, while palaeoclimatic reconstructions support a more complex Pleistocene history than implied by the classical southern-refugia paradigm. These findings highlight the importance of considering both ecological and historical processes when interpreting the evolutionary history of European temperate taxa.
Mobile genetic elements drive horizontal gene transfer (HGT), which may have contributed to the functional diversity of termite gut microbiomes, although the environmental determinants of these processes remain poorly understood. Our proposed model integrates spatially resolved physicochemical gradients and mobile genetic element (MGE) dynamics to quantitatively predict HGT patterns in termite guts. The framework integrates high-resolution metabolomic and transcriptomic profiling data from gut compartments, sourced from published experimental studies, with a generalized additive model to forecast the rate of MGE transfer as a function of local environmental conditions, and goes beyond static cataloguing of HGT events. Moreover, metabolic network alignments have been used to predict MGE-host interactions based on functional complementarity, and a heterogeneous graph neural network is used to dynamically predict HGT hotspots using environmental, MGE, and microbial host data. Unlike traditional methods, our framework explicitly links microenvironmental variability with gene flow mediated by MGEs using taxonomic, metagenomic, and metabolic features. The framework incorporates state-of-the-art computational methods, such as nanoscale secondary ion mass spectrometry for spatial metabolite mapping and graph attention networks (GAT) for transfer-likelihood prediction. The study of physicochemical gradients in the context of MGE-host interactions offers a mechanistic framework for investigating HGT dynamics in complex microbial communities, with broader implications for understanding gene flow in other host-associated ecosystems.
