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Human activity is an important driver of ecological and evolutionary change on our planet. In particular, domestication and biological introductions have important and long-lasting effects on species’ genomic architecture and diversity. However, genome-wide analysis of independent domestication and introduction events within a single species has not previously been performed. The Pacific kelp Undaria pinnatifida provides such an opportunity because it has been cultivated in its native range in Northeast Asia but also introduced to four other continents in the past 50 years. Here we present the results of a genome-wide analysis of natural, cultivated and introduced populations of U. pinnatifida to elucidate human-driven evolutionary change. We demonstrate that these three categories of origin can be distinguished at the genome level, reflecting the combined influence of neutral (demography and migration) and non-neutral (selection) processes. Human-driven evolutionary changes are captured by comparison of the genomes of natural, cultivated and introduced populations of a globally distributed Pacific kelp.

Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

Red sea bream, a popular fish resource in Korea and Japan, is being bred in fish farms of the two countries. It is hypothesized that the genomes of red sea bream are influenced by decades of artificial selection. This study investigates the impact of artificial selection on genomes of red sea bream. Whole genome sequencing was conducted for 40 samples of red sea bream either from Ehime, Nagasaki and Tongyeong fish farms or from the wild. Population stratification based on whole genome data was investigated and the genomic regions of fish farm populations under selection were identified using XP-EHH and relative nucleotide diversity. Gene ontology analysis revealed that different functions were enriched in different fish farms. In conclusion, this study highlights the difference between independently cultured red sea bream populations by showing that influence of artificial selection acted upon completely different genes related to different functions including metabolic and developmental processes.

Vibrio parahaemolyticus, a significant cause of gastroenteritis and a growing public health concern, has become increasingly prevalent owing to the rise in ocean temperatures driven by climate change. This study aimed to characterize the genetic diversity, pathogenic potential, and antimicrobial resistance (AMR) profiles of V. parahaemolyticus strains isolated from the southern coastal region of Korea. Using whole genome sequencing (WGS) and advanced bioinformatics tools, we identified novel sequence types through multilocus sequence typing and serotyped isolates using the VPsero database. Pathogenic genes, such as tdh and trh, were detected in only a few isolates, suggesting the involvement of alternative virulence mechanisms in the pathogenicity of these strains. An in silico analysis revealed widespread AMR, particularly against beta-lactams, chloramphenicol, and tetracycline antibiotics, underscoring the public health threats posed by these strains. A phylogenetic analysis revealed no significant clustering by geographic origin, year, or strain source, although most clinical and environmental strains were not closely related at lower phylogenetic branches. These findings highlight the importance of continued genomic surveillance and strict regulations regarding antibiotic use in marine environments. Moreover, this study suggests that integrating WGS data with epidemiological models could enhance the prediction of the emerging virulent strains and support effective outbreak management strategies.

Summer mortality, caused by thermal conditions, is the biggest threat to abalone aquaculture production industries. Various measures have been taken to mitigate this issue by adjusting the environment; however, the cellular processes of Pacific abalone (Haliotis discus hannai) have been overlooked due to the paucity of genetic information. The draft genome of H. discus hannai has recently been reported, prompting exploration of the genes responsible for thermal regulation in Pacific abalone. In this study, 413 proteins were systematically annotated as members of the heat shock protein (HSP) super families, and among them 26 HSP genes from four Pacific abalone tissues (hemocytes, gill, mantle, and muscle) were differentially expressed under cold and heat stress conditions. The co-expression network revealed that HSP expression patterns were tissue-specific and similar to those of other shellfish inhabiting intertidal zones. Finally, representative HSPs were selected at random and their expression patterns were identified by RNA sequencing and validated by qRT-PCR to assess expression significance. The HSPs expressed in hemocytes were highly similar in both analyses, suggesting that hemocytes could be more reliable samples for validating thermal condition markers compared to other tissues.

Nut weight is one of the most important traits that can affect a chestnut grower’s returns. Due to the long juvenile phase of chestnut trees, the selection of desired characteristics at early developmental stages represents a major challenge for chestnut breeding. In this study, we identified single nucleotide polymorphisms (SNPs) in transcriptomic regions, which were significantly associated with nut weight in chestnuts ( Castanea crenata ), using a genome-wide association study (GWAS). RNA-sequencing (RNA-seq) data were generated from large and small nut-bearing trees, using an Illumina HiSeq. 2000 system, and 3,271,142 SNPs were identified. A total of 21 putative SNPs were significantly associated with chestnut weight (false discovery rate [FDR] < 10 −5 ), based on further analyses. We also applied five machine learning (ML) algorithms, support vector machine (SVM), C5.0, k -nearest neighbour ( k -NN), partial least squares (PLS), and random forest (RF), using the 21 SNPs to predict the nut weights of a second population. The average accuracy of the ML algorithms for the prediction of chestnut weights was greater than 68%. Taken together, we suggest that these SNPs have the potential to be used during marker-assisted selection to facilitate the breeding of large chestnut-bearing varieties.

Antimicrobial peptides (AMPs) are promising agents for treating antibiotic‐resistant bacterial infections. Although discovering novel AMPs is crucial for combating multidrug‐resistant bacteria and biofilm‐related infections, their clinical potential relies on precise, real‐time evaluation of efficacy, toxicity, and mechanisms. Optical diffraction tomography (ODT), a label‐free imaging technology, enables real‐time visualization of bacterial morphological changes, membrane damage, and biofilm formation over time. Here, a computational analysis of the leech transcriptome using an advanced AI‐based peptide screening strategy with ODT to identify potential AMPs is employed. Among the 19 potential AMPs identified, hirunipin 2 demonstrates potent antibacterial activity, low mammalian cytotoxicity, and minimal hemolytic effects. It demonstrates efficacy comparable to melittin, resistance to physiological salts and human serum, and a low likelihood of inducing bacterial resistance. Microscopy and 3D‐ODT confirm its disruption of bacterial membranes and intracellular aggregation, leading to cell death. Notably, hirunipin 2 effectively inhibits biofilm formation, eradicates preformed biofilms, and synergizes with antibiotics against multidrug‐resistant Acinetobacter baumannii (MDRAB) by enhancing membrane permeability. Additionally, hirunipin 2 significantly suppresses pro‐inflammatory cytokine expression in LPS‐stimulated macrophages, highlighting its anti‐inflammatory properties. These findings highlight hirunipin 2 as a strong candidate for developing novel antibacterial, anti‐inflammatory, and antibiofilm therapies, particularly against multidrug‐resistant bacterial infections. Novel antimicrobial peptides (AMPs) are identified from the medicinal leech Hirudo nipponia using transcriptome analysis, AI‐based in silico prediction, and optical diffraction tomography screening. Among the 19 potential AMPs identified, hirunipin 2 demonstrates potent antibacterial activity, antibiofilm and anti‐inflammatory activities. This peptide enhances the efficacy of conventional antibiotics synergistically, making it a promising therapeutic candidate.

Abalone (Haliotis discus hannai) is one of the most valuable marine aquatic species in Korea, Japan and China. Tremendous exposure to bacterial infection is common in aquaculture environment, especially by Vibrio sp. infections. It's therefore necessary and urgent to understand the mechanism of H. discus hannai host defense against Vibrio parahemolyticus infection. However studies on its immune system are hindered by the lack of genomic resources. In the present study, we sequenced the transcriptome of control and bacterial challenged H. discus hannai tissues. Totally, 138 MB of reference transcriptome were obtained from de novo assembly of 34 GB clean bases from ten different libraries and annotated with the biological terms (GO and KEGG). A total of 10,575 transcripts exhibiting the differentially expression at least one pair of comparison and the functional annotations highlight genes related to immune response, cell adhesion, immune regulators, redox molecules and mitochondrial coding genes. Mostly, these groups of genes were dominated in hemocytes compared to other tissues. This work is a prerequisite for the identification of those physiological traits controlling H. discus hannai ability to survive against Vibrio infection.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Onion ( Allium cepa L.) is an economically valuable crop, but its large, repeat-enriched genome makes genome assembly difficult and limits molecular breeding and biological studies. Herein, we present a chromosomal-level reference genome assembly of the double-haploid onion line DHW30006, constructed by combining PacBio, Illumina, and Hi-C sequencing approaches. The assembled genome totaled 12.77 Gb, with 65,730 gene models, and was anchored to eight pseudo-chromosomes covering 12.07 Gb (94.5%), with a scaffold N50 of 1.40 Gb. DHW30006 onion genome contained improved gene models covering approximately 580 Mb (4.54%) of the genic regions with an average gene length of 8,827 bp and 5.48 exons per gene. These gene models represented the most improved annotation among Allium genomes. This onion genome will serve as a valuable resource for breeding and biological research in Allium plants.