Acute nitrite exposure causes gut microbiota dysbacteriosis and proliferation of pathogenic Photobacterium in shrimp.

Nitrite exposure has become a significant concern in the aquaculture industry, posing a severe threat to aquatic animals such as shrimp. While studies have reported the adverse effects of nitrite on shrimp growth, the part played by the gut microbiota in shrimp mortality resulting from nitrite exposure is poorly understood. Here, the effects of nitrite on shrimp gut bacterial community were investigated using 16S rRNA amplicon sequencing, bacterial isolation, genomic analysis, and infection experiments. Compared to the control_healthy group, changes in the bacterial composition of the nitrite_dead group were associated with reduced abundance of specific beneficial bacteria and increased abundance of certain pathogenic bacteria. Notably, members of the Photobacterium genus were found to be significantly enriched in the nitrite_dead group. Genomic analysis of a representative Photobacterium strain (LvS-8n3) revealed a variety of genes encoding bacterial toxins, including hemolysin, adhesin, and phospholipase. Furthermore, it was also found that LvS-8n3 exhibits strong pathogenicity, probably due to its high production of pathogenic factors and the ability to utilize nitrite for proliferation. Therefore, the proliferation of pathogenic Photobacterium species appears pivotal for driving shrimp mortality caused by nitrite exposure. These findings provide novel insights into the disease mechanism in shrimp under conditions of environmental change.

Genome-wide association analysis reveals the genetic basis of thermal tolerance in dwarf surf clam Mulinia lateralis.

Recently, elevated seawater temperatures have resulted numerous adverse effects, including significant mortality among bivalves. The dwarf surf clam, Mulinia lateralis, is considered a valuable model species for bivalve research due to its rapid growth and short generation time. The successful cultivation in laboratory setting throughout its entire life cycle makes it an ideal candidate for exploring the potential mechanisms underlying bivalve responses to thermal stress. In this study, a total of 600 clams were subjected to a 17-day thermal stress experiment at a temperature of 30 °C which is the semi-lethal temperature for this species. Ninety individuals who perished initially were classified as heat-sensitive populations (HSP), while 89 individuals who survived the experiment were classified as heat-tolerant populations (HTP). Subsequently, 179 individuals were then sequenced, and 21,292 single nucleotide polymorphisms (SNPs) were genotyped for downstream analysis. The heritability estimate for survival status was found to be 0.375 ± 0.127 suggesting a genetic basis for thermal tolerance trait. Furthermore, a genome-wide association study (GWAS) identified three SNPs and 10 candidate genes associated with thermal tolerance trait in M. lateralis. These candidate genes were involved in the ETHR/EHF signaling pathway and played pivotal role in signal sensory, cell adhesion, oxidative stress, DNA damage repair, etc. Additionally, qPCR results indicated that, excluding MGAT4A, ZAN, and RFC1 genes, all others exhibited significantly higher expression in the HTP (p < 0.05), underscoring the critical involvement of the ETHR/EHF signaling pathway in M. lateralis' thermal tolerance. These results unveil the presence of standing genetic variations associated with thermal tolerance in M. lateralis, highlighting the regulatory role of the ETHR/EHF signaling pathway in the bivalve's response to thermal stress, which contribute to comprehension of the genetic basis of thermal tolerance in bivalves.

Deciphering the population structure and genetic basis of growth traits from whole-genome resequencing of the leopard coral grouper ( Plectropomus leopardus).

The leopard coral grouper ( Plectropomus leopardus) is a species of significant economic importance. Although artificial cultivation of P. leopardus has thrived in recent decades, the advancement of selective breeding has been hindered by the lack of comprehensive population genomic data. In this study, we identified over 8.73 million single nucleotide polymorphisms (SNPs) through whole-genome resequencing of 326 individuals spanning six distinct groups. Furthermore, we categorized 226 individuals with high-coverage sequencing depth (≥14×) into eight clusters based on their genetic profiles and phylogenetic relationships. Notably, four of these clusters exhibited pronounced genetic differentiation compared with the other populations. To identify potentially advantageous loci for P. leopardus, we examined genomic regions exhibiting selective sweeps by analyzing the nucleotide diversity ( θπ) and fixation index ( F ST) in these four clusters. Using these high-coverage resequencing data, we successfully constructed the first haplotype reference panel specific to P. leopardus. This achievement holds promise for enabling high-quality, cost-effective imputation methods. Additionally, we combined low-coverage sequencing data with imputation techniques for a genome-wide association study, aiming to identify candidate SNP loci and genes associated with growth traits. A significant concentration of these genes was observed on chromosome 17, which is primarily involved in skeletal muscle and embryonic development and cell proliferation. Notably, our detailed investigation of growth-related SNPs across the eight clusters revealed that cluster 5 harbored the most promising candidate SNPs, showing potential for genetic selective breeding efforts. These findings provide a robust toolkit and valuable insights into the management of germplasm resources and genome-driven breeding initiatives targeting P. leopardus.

Proteome analysis of outer membrane vesicles from Vibrio parahaemolyticus causing acute hepatopancreatic necrosis disease.

A specific strain of Vibrio parahaemolyticus (VpAHPND) causes acute hepatopancreatic necrosis disease (AHPND), leading to significant losses in shrimp aquaculture. Outer membrane vesicles (OMVs) are naturally secreted by Gram-negative bacteria, and their significant roles in host-pathogen interactions and pathogenicity have been recognized. In the present study, OMVs were isolated from VpAHPND by differential-ultracentrifugation and used for proteomics analysis. In the Nano-HPLC-MS/MS analysis, totally 645 proteins were determined, including virulence factors, immunogenic proteins, outer membrane protein, bacterial secretory proteins, ribosomal proteins, protease, and iron regulation proteins. Furthermore, GO and KEGG annotations indicated that proteins identified in VpAHPND-OMVs are involved in metabolism, regulation of multiple biological processes, genetic information processes, immunity and more. Meanwhile, toxin proteins PirAvp and PirBvp, associated with VpAHPND pathogenicity, were also identified in the proteome of VpAHPND-OMVs. Our objective is to identify the protein composition of OMVs released by VpAHPND, analyzing the potential for cytotoxicity and immunomodulatory activity of these granule hosts. This study is crucial for understanding the roles played by bacterial-derived vesicles in the disease process, given that these vesicles carry relevant activities inherent to the bacteria that produce them.

Pan-evolutionary and regulatory genome architecture delineated by an integrated macro- and microsynteny approach.

The forthcoming massive genome data generated by the Earth BioGenome Project will open up a new era of comparative genomics, for which genome synteny analysis provides an important framework. Profiling genome synteny represents an essential step in elucidating genome architecture, regulatory blocks/elements and their evolutionary history. Here we describe PanSyn, ( https://github.com/yhw320/PanSyn ), the most comprehensive and up-to-date genome synteny pipeline, providing step-by-step instructions and application examples to demonstrate its usage. PanSyn inherits both basic and advanced functions from existing popular tools, offering a user-friendly, highly customized approach for genome macrosynteny analysis and integrated pan-evolutionary and regulatory analysis of genome architecture, which are not yet available in public synteny software or tools. The advantages of PanSyn include: (i) advanced microsynteny analysis by functional profiling of microsynteny genes and associated regulatory elements; (ii) comprehensive macrosynteny analysis, including the inference of karyotype evolution from ancestors to extant species; and (iii) functional integration of microsynteny and macrosynteny for pan-evolutionary profiling of genome architecture and regulatory blocks, as well as integration with external functional genomics datasets from three- or four-dimensional genome and ENCODE projects. PanSyn requires basic knowledge of the Linux environment and Perl programming language and the ability to access a computer cluster, especially for large-scale genomic comparisons. Our protocol can be easily implemented by a competent graduate student or postdoc and takes several days to weeks to execute for dozens to hundreds of genomes. PanSyn provides yet the most comprehensive and powerful tool for integrated evolutionary and functional genomics.

Signatures of selection in Mulinia lateralis underpinning its rapid adaptation to laboratory conditions.

The dwarf surf clam, Mulinia lateralis, is considered as a model species for bivalves because of its rapid growth and short generation time. Recently, successful breeding of this species for multiple generations in our laboratory revealed its acquisition of adaptive advantages during artificial breeding. In this study, 310 individuals from five different generations were genotyped with 22,196 single nucleotide polymorphisms (SNPs) with the aim of uncovering the genetic basis of their adaptation to laboratory conditions. Results revealed that M. lateralis consistently maintained high genetic diversity across generations, characterized by high observed heterozygosity (H o: 0.2733-0.2934) and low levels of inbreeding (F is: -0.0244-0.0261). Population analysis indicated low levels of genetic differentiation among generations of M. lateralis during artificial breeding (F st <0.05). In total, 316 genomic regions exhibited divergent selection, with 168 regions under positive selection. Furthermore, 227 candidate genes were identified in the positive selection regions, which have functions including growth, stress resistance, and reproduction. Notably, certain selection signatures with significantly higher F st value were detected in genes associated with male reproduction, such as GAL3ST1, IFT88, and TSSK2, which were significantly upregulated during artificial breeding. This suggests a potential role of sperm-associated genes in the rapid evolutionary response of M. lateralis to selection in laboratory conditions. Overall, our findings highlight the phenotypic and genetic changes, as well as selection signatures, in M. lateralis during artificial breeding. This contributes to understanding their adaptation to laboratory conditions and underscores the potential for using this species to explore the adaptive evolution of bivalves.

Deqformer: high-definition and scalable deep learning probe design method.

Target enrichment sequencing techniques are gaining widespread use in the field of genomics, prized for their economic efficiency and swift processing times. However, their success depends on the performance of probes and the evenness of sequencing depth among each probe. To accurately predict probe coverage depth, a model called Deqformer is proposed in this study. Deqformer utilizes the oligonucleotides sequence of each probe, drawing inspiration from Watson-Crick base pairing and incorporating two BERT encoders to capture the underlying information from the forward and reverse probe strands, respectively. The encoded data are combined with a feed-forward network to make precise predictions of sequencing depth. The performance of Deqformer is evaluated on four different datasets: SNP panel with 38 200 probes, lncRNA panel with 2000 probes, synthetic panel with 5899 probes and HD-Marker panel for Yesso scallop with 11 000 probes. The SNP and synthetic panels achieve impressive factor 3 of accuracy (F3acc) of 96.24% and 99.66% in 5-fold cross-validation. F3acc rates of over 87.33% and 72.56% are obtained when training on the SNP panel and evaluating performance on the lncRNA and HD-Marker datasets, respectively. Our analysis reveals that Deqformer effectively captures hybridization patterns, making it robust for accurate predictions in various scenarios. Deqformer leads to a novel perspective for probe design pipeline, aiming to enhance efficiency and effectiveness in probe design tasks.