Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.0
2.4
Journals
Fishes
Special Issues
Functional Gene Analysis and Genomic Technologies in Aquatic Animals
share announcement

Functional Gene Analysis and Genomic Technologies in Aquatic Animals

A special issue of Fishes (ISSN 2410-3888). This special issue belongs to the section "Genetics and Biotechnology".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1663

Special Issue Editor

Dr. Hailiang Song

E-Mail Website
Guest Editor
Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100068, China
Interests: genomic selection; genome-wide association study (GWAS); selection signature; candidate gene identification; multi-omics integration; quantitative genetics

Special Issue Information

Dear Colleagues,

Unraveling the genetic architecture and functional basis of economically important traits in aquatic animals is vital for the advancement of genetic improvement and sustainable aquaculture. Recent developments in sequencing, genomic technologies and bioinformatics have greatly enhanced our ability to identify functional genes and elucidate molecular mechanisms underlying traits such as growth, reproduction, stress tolerance, and disease resistance.

This Special Issue focuses on recent advances and innovative approaches in functional gene analysis and genomic technologies across marine and freshwater organisms, including fish, shellfish, and other aquatic species. Topics of interest include genome-wide association studies (GWAS), genomic selection, selection signature detection, candidate gene discovery, gene editing, and functional validation, as well as multi-omics data integration.

We welcome original research articles, short communications, and comprehensive reviews that provide novel insights into gene function and regulatory mechanisms and that promote the application of advanced genomic technologies to support sustainable and precise aquaculture practices.

Dr. Hailiang Song
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fishes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • genomic selection
  • genome-wide association study (GWAS)
  • selection signature
  • candidate gene identification
  • genome editing
  • functional gene validation
  • multi-omics integration
  • quantitative genetics
  • molecular breeding
  • aquatic genomics
  • sustainable aquaculture

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 854 KB  
Article
A Unified Comparative Evaluation of Genomic Prediction Models Across Four Aquaculture Species
by Jinxin Zhang, Xiaofei Yang, Wei Wang, Hongxia Hu, Shaogang Xu and Hailiang Song
Fishes 2026, 11(2), 115; https://doi.org/10.3390/fishes11020115 - 12 Feb 2026
Viewed by 712
Abstract
Genomic prediction has been increasingly applied in aquaculture selective breeding; however, systematic evaluations of prediction accuracy across multiple aquaculture species and analytical methods under a unified and comparable framework remain limited. In this study, we conducted a comprehensive comparative assessment of genomic prediction [...] Read more.
Genomic prediction has been increasingly applied in aquaculture selective breeding; however, systematic evaluations of prediction accuracy across multiple aquaculture species and analytical methods under a unified and comparable framework remain limited. In this study, we conducted a comprehensive comparative assessment of genomic prediction performance across four representative aquaculture species, including Atlantic salmon (Salmo salar), gilthead sea bream (Sparus aurata), common carp (Cyprinus carpio), and rainbow trout (Oncorhynchus mykiss), using ten genomic prediction models including GBLUP, Bayesian and machine learning methods. Prediction accuracy varied widely among species and models, ranging from 0.49 to 0.85, and was strongly associated with trait heritability. High-heritability traits consistently achieved higher prediction accuracies, with rainbow trout and common carp exhibiting the best overall performance (0.75–0.83 and 0.73–0.85, respectively), whereas Atlantic salmon and gilthead sea bream showed lower and more variable accuracies (0.49–0.61 and 0.49–0.66). No single model performed optimally across all species. Machine learning-based approaches achieved the highest prediction accuracy in specific cases but exhibited pronounced species-dependent variability, while GBLUP provided stable and well-calibrated predictions with consistently low bias. Incremental SNP feature selection further improved prediction accuracy by 2.8–4.2% in three species using only 0.54–9.64% of the available markers, whereas no improvement was observed for a low-heritability trait. These results show that genomic prediction performance is highly context-dependent and underscores the importance of jointly considering trait genetic architecture, population characteristics, model choice, and marker selection when optimizing genomic selection strategies in aquaculture breeding programs. Full article
(This article belongs to the Special Issue Functional Gene Analysis and Genomic Technologies in Aquatic Animals)
►▼ Show Figures

Figure 1

18 pages, 5441 KB  
Article
De Novo Transcriptome Analysis Reveals the Primary Metabolic Capacity of the Sponge Xestospongia sp. from Vietnam
by Le Bich Hang Pham, Hai Quynh Do, Chi Mai Nguyen, Tuong Van Nguyen, Hai Ha Nguyen, Huu Hong Thu Nguyen, Khanh Linh Nguyen, Thi Hoe Pham, Quang Hung Nguyen, Quang Trung Le, My Linh Tran and Thi Thu Hien Le
Fishes 2026, 11(1), 23; https://doi.org/10.3390/fishes11010023 - 31 Dec 2025
Viewed by 527
Abstract
Marine sponges possess complex metabolic systems that support their growth, physiology, and ecological interactions. However, the primary metabolic capacity of the sponge hosts remains incompletely characterized at the molecular level. In this study, we performed de novo transcriptome sequencing of a pooled sample [...] Read more.
Marine sponges possess complex metabolic systems that support their growth, physiology, and ecological interactions. However, the primary metabolic capacity of the sponge hosts remains incompletely characterized at the molecular level. In this study, we performed de novo transcriptome sequencing of a pooled sample of three individuals of Xestospongia sp. collected in Vietnam, using a high-throughput Illumina sequencing system, to characterize the host-derived metabolic pathways. A total of 43,278 unigenes were assembled, of which 69.15% were functionally annotated using multiple public databases. Functional annotation revealed a broad repertoire of genes associated with core metabolic pathways, including carbohydrate, lipid, and sterol metabolisms, as well as cofactor-related processes. Specifically, complete pathways involved in folate biosynthesis, terpenoid backbone biosynthesis, ubiquinone (Coenzyme Q) metabolism, and steroid biosynthesis were identified, reflecting the independent metabolic framework of the sponge host. Several highly expressed genes related to these pathways, including COQ7, ERG6, NUDX1, QDPR, and PCBD, were detected, and their expression patterns were confirmed by quantitative RT-PCR. Furthermore, protein-based phylogenetic analyses indicated that these genes are closely related to homologous proteins from other sponge species, supporting their host origin. This study provides the first comprehensive transcriptomic resource for Xestospongia sp. from Vietnam, and offers baseline molecular insights into the primary metabolic capacity of the sponge host. These data establish a foundation for future investigations of sponge physiology and host–microbe metabolic partitioning. Full article
(This article belongs to the Special Issue Functional Gene Analysis and Genomic Technologies in Aquatic Animals)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop