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The evolutionary divergence of freshwater and marine fish reflects their adaptation to distinct ecological environments, with differences evident in their morphological traits, physiological functions, and genomic structures. Traditional molecular methods often fail to uncover the intricate regulatory relationships among genes under environmental stress. This study proposes the weighted attention gene analysis (WAGA) model, a novel approach that integrates natural language processing (NLP) for protein-coding gene feature representation with deep learning and self-attention (SA) mechanisms. WAGA effectively identifies key genes associated with sensory functions, osmoregulation, and growth and development on the basis of attention weights. The experimental results highlight its effectiveness in revealing genes crucial for ecological adaptation and evolution. This approach is essential for elucidating the mechanisms of ecological adaptability and evolutionary processes, while also offering novel insights and tools to support targeted breeding in aquaculture and fish genomics research.

High-quality, chromosome-scale genomes are essential for genomic analyses. Analyses, including 3D genomics, epigenetics, and comparative genomics rely on a high-quality genome assembly, which is often accomplished with the assistance of Hi-C data. Curation of genomes reveal that current Hi-C-assisted scaffolding algorithms either generate ordering and orientation errors or fail to assemble high-quality chromosome-level scaffolds. Here, we offer the software Puzzle Hi-C, which uses Hi-C reads to accurately assign contigs or scaffolds to chromosomes. Puzzle Hi-C uses the triangle region instead of the square region to count interactions in a Hi-C heatmap. This strategy dramatically diminishes scaffolding interference caused by long-range interactions. This software also introduces a dynamic, triangle window strategy during assembly. Initially small, the window expands with interactions to produce more effective clustering. Puzzle Hi-C outperforms available scaffolding tools.

Genomic islands (GIs) are mobile genetic elements that integrate site-specifically into bacterial chromosomes, bearing genes that affect phenotypes such as pathogenicity and metabolism. GIs typically occur sporadically among related bacterial strains, enabling comparative genomic approaches to GI identification. For a candidate GI in a query genome, the number of reference genomes with a precise deletion of the GI serves as a support value for the GI. Our comparative software for GI identification was slowed by our original use of large reference genome databases (DBs). Here we explore smaller species-focused DBs. With increasing DB size, recovery of our reliable prophage GI calls reached a plateau, while recovery of less reliable GI calls (FPs) increased rapidly as DB sizes exceeded ~500 genomes; i.e., overlarge DBs can increase FP rates. Paradoxically, relative to prophages, FPs were both more frequently supported only by genomes outside the species and more frequently supported only by genomes inside the species; this may be due to their generally lower support values. Setting a DB size limit for our SMAll Ranked Tailored (SMART) DB design speeded runtime ~65-fold. Strictly intra-species DBs would tend to lower yields of prophages for small species (with few genomes available); simulations with large species showed that this could be partially overcome by reaching outside the species to closely related taxa, without an FP burden. Employing such taxonomic outreach in DB design generated redundancy in the DB set; as few as 2984 DBs were needed to cover all 47894 prokaryotic species. Runtime decreased dramatically with SMART DB design, with only minor losses of prophages. We also describe potential utility in other comparative genomics projects.

Aquaculture represents the fastest-growing global food production sector, as it has become an essential component of the global food supply. China has the world’s largest aquaculture industry in terms of production volume. However, the sustainable development of fish culture is hindered by several concerns, including germplasm degradation and disease outbreaks. The practice of genomic breeding, which relies heavily on genome information and genotypephenotype relationships, has significant potential for increasing the efficiency of aquaculture production. In 2014, the completion of the genome sequencing and annotation of the Chinese tongue sole signified the beginning of the fish genomics era in China. Since then, domestic researchers have made dramatic progress in functional genomic studies. To date, the genomes of more than 60 species of fish in China have been assembled and annotated. Based on these reference genomes, evolutionary, comparative, and functional genomic studies have revolutionized our understanding of a wide range of biologically and economically important traits of fishes, including growth and development, sex determination, disease resistance, metamorphosis, and pigmentation. Furthermore, genomic tools and breeding techniques such as SNP arrays, genomic selection, and genome editing have greatly accelerated genetic improvement through the incorporation of functional genomic information into breeding activities. This review aims to summarize the current status, advances, and perspectives of the genome resources, genomic study of important traits, and genomic breeding techniques of fish in China. The review will provide aquaculture researchers, fish breeders, and farmers with updated information concerning fish genomic research and breeding technology. The summary will help to promote the genetic improvement of production traits and thus will support the sustainable development of fish aquaculture.

Abstract Fins are major functional appendages of fish that have been repeatedly modified in different lineages. To search for genomic changes underlying natural fin diversity, we compared the genomes of 36 percomorph fish species that span over 100 million years of evolution and either have complete or reduced pelvic and caudal fins. We identify 1,614 genomic regions that are well-conserved in fin-complete species but missing from multiple fin-reduced lineages. Recurrent deletions of conserved sequences in wild fin-reduced species are enriched for functions related to appendage development, suggesting that convergent fin reduction at the organismal level is associated with repeated genomic deletions near fin-appendage development genes. We used sequencing and functional enhancer assays to confirm that PelA, a Pitx1 enhancer previously linked to recurrent pelvic loss in sticklebacks, has also been independently deleted and may have contributed to the fin morphology in distantly related pelvic-reduced species. We also identify a novel enhancer that is conserved in the majority of percomorphs, drives caudal fin expression in transgenic stickleback, is missing in tetraodontiform, syngnathid, and synbranchid species with caudal fin reduction, and alters caudal fin development when targeted by genome editing. Our study illustrates a broadly applicable strategy for mapping phenotypes to genotypes across a tree of vertebrate species and highlights notable new examples of regulatory genomic hotspots that have been used to evolve recurrent phenotypes across 100 million years of fish evolution.

A comparative analysis of five teleostean genomes, namely zebrafish, medaka, three-spine stickleback, fugu and pufferfish was performed with the aim to highlight the nature of the forces driving both length and base composition of introns (i.e., bpi and GCi). An inter-genome approach using orthologous intronic sequences was carried out, analyzing independently both variables in pairwise comparisons. An average length shortening of introns was observed at increasing average GCi values. The result was not affected by masking transposable and repetitive elements harbored in the intronic sequences. The routine metabolic rate (mass specific temperature-corrected using the Boltzmann's factor) was measured for each species. A significant correlation held between average differences of metabolic rate, length and GC content, while environmental temperature of fish habitat was not correlated with bpi and GCi. Analyzing the concomitant effect of both variables, i.e., bpi and GCi, at increasing genomic GC content, a decrease of bpi and an increase of GCi was observed for the significant majority of the intronic sequences (from ∼ 40% to ∼ 90%, in each pairwise comparison). The opposite event, concomitant increase of bpi and decrease of GCi, was counter selected (from <1% to ∼ 10%, in each pairwise comparison). The results further support the hypothesis that the metabolic rate plays a key role in shaping genome architecture and evolution of vertebrate genomes.

Bacteria of the genus Salmonella comprise a large and evolutionary related population of zoonotic pathogens that can infect mammals, including humans and domestic animals, birds, reptiles and amphibians. Salmonella carries a plethora of virulence genes, including fimbrial adhesins, some of them known to participate in mammalian or avian host colonization. Each type of fimbria has its structural subunit and biogenesis genes encoded by one fimbrial gene cluster (FGC). The accumulation of new genomic information offered a timely opportunity to better evaluate the number and types of FGCs in the Salmonella pangenome, to test the use of current classifications based on phylogeny, and to infer potential correlations between FGC evolution in various Salmonella serovars and host niches. This study focused on the FGCs of the currently deciphered 90 genomes and 60 plasmids of Salmonella. The analysis highlighted a fimbriome consisting of 35 different FGCs, of which 16 were new, each strain carrying between 5 and 14 FGCs. The Salmonella fimbriome was extremely diverse with FGC representatives in 8 out of 9 previously categorized fimbrial clades and subclades. Phylogenetic analysis of Salmonella suggested macroevolutionary shifts detectable by extensive FGC deletion and acquisition. In addition, microevolutionary drifts were best depicted by the high level of allelic variation in predicted or known adhesins, such as the type 1 fimbrial adhesin FimH for which 67 different natural alleles were identified in S. enterica subsp. I. Together with strain-specific collections of FGCs, allelic variation among adhesins attested to the pathoadaptive evolution of Salmonella towards specific hosts and tissues, potentially modulating host range, strain virulence, disease progression, and transmission efficiency. Further understanding of how each Salmonella strain utilizes its panel of FGCs and specific adhesin alleles for survival and infection will support the development of new approaches for the control of Salmonellosis.

Background The Bioinformatics Resource Manager (BRM) is a web-based tool developed to facilitate identifier conversion and data integration for Homo sapiens (human), Mus musculus (mouse), Rattus norvegicus (rat), Danio rerio (zebrafish), and Macaca mulatta (macaque), as well as perform orthologous conversions among the supported species. In addition to providing a robust means of identifier conversion, BRM also incorporates a suite of microRNA (miRNA)-target databases upon which to query target genes or to perform reverse target lookups using gene identifiers. Results BRM has the capability to perform cross-species identifier lookups across common identifier types, directly integrate datasets across platform or species by performing identifier retrievals in the background, and retrieve miRNA targets from multiple databases simultaneously and integrate the resulting gene targets with experimental mRNA data. Here we use workflows provided in BRM to integrate RNA sequencing data across species to identify common biomarkers of exposure after treatment of human lung cells and zebrafish to benzo[ a ]pyrene (BAP). We further use the miRNA Target workflow to experimentally determine the role of miRNAs as regulators of BAP toxicity and identify the predicted functional consequences of miRNA-target regulation in our system. The output from BRM can easily and directly be uploaded to freely available visualization tools for further analysis. From these examples, we were able to identify an important role for several miRNAs as potential regulators of BAP toxicity in human lung cells associated with cell migration, cell communication, cell junction assembly and regulation of cell death. Conclusions Overall, BRM provides bioinformatics tools to assist biologists having minimal programming skills with analysis and integration of high-content omics’ data from various transcriptomic and proteomic platforms. BRM workflows were developed in Java and other open-source technologies and are served publicly using Apache Tomcat at https://cbb.pnnl.gov/brm/ .

Species invading non‐native habitats can cause irreversible environmental damage and economic harm. Yet, how introduced species become widespread invaders remains poorly understood. Adaptation within native‐range habitats and rapid adaptation to new environments may both influence invasion success. Here, we examine these hypotheses using 7058 SNPs from 36 native, 40 introduced and 19 farmed populations of tench, a fish native to Eurasia. We examined genetic structure among these populations and accounted for long‐term evolutionary history within the native range to assess whether introduced populations exhibited lower genetic diversity than native populations. Subsequent to infer genotype–environment correlations within native‐range habitats, we assessed whether adaptation to native environments may have shaped the success of some introduced populations. At the broad scale, two glacial refugia contributed to the ancestry and genomic diversity of tench. However, native, introduced and farmed populations of admixed origin exhibited up to 10‐fold more genetic diversity (i.e., observed heterozygosity, expected heterozygosity and allelic richness) compared to populations with predominantly single‐source ancestry. The effects of introduction to a new location were also apparent as introduced populations exhibited fewer private alleles (mean = 9.9 and 18.9 private alleles in introduced and native populations, respectively) and higher population‐specific Fst compared to native populations, highlighting their distinctiveness relative to the pool of allelic frequencies across tench populations. Finally, introduced populations with varying levels of genetic variation and similar genetic compositions have become established and persisted under strikingly different climatic and ecological conditions. Our results suggest that lack of prior adaptation and low genetic variation may not consistently hinder the success of introduced populations for species with a demonstrated ability to expand their native range.

This chapter describes the classical and novel approaches that help in embarking on the field of marine genomics, which have been categorized under different sections that include: bioinformatics, genomics, transcriptomics, proteomics, metagenomics, metabolomics, nutrigenomics, sponge genomics, and fish genomics. The advent of the “omics” era has generated many datasets from marine organisms which have been deposited in the repositories. Metagenomics‐based techniques show an attractive option which helps to obtain unbiased visibility of community structure of microbial genomes within the niche. Proteomic tactics have been broadly classified as bottom–up, middle–down, and top–down, which are used for identifyingand characterizing protein‐peptides. Two ionization techniques are mainly used in proteomics: the soft ionization methods of nano‐electrospray ionization and matrix‐assisted laser desorption ionization. Transcriptomics is an emerging field in functional genomics which aims at quantifying the mRNA molecules.