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Published VersionCC BY V4.0, Open Access
Journal article
Genetics and Genomics of Infectious Diseases in Key Aquaculture Species
Biology , Vol.13(1), pp.1-19
2024
PMID: 38248460
Abstract
Diseases pose a significant challenge for aquaculture, exacerbated by changing weather conditions. The sector has explored various strategies, including maintaining a clean environment and employing vaccines, to combat these diseases. However, these solutions are effective only against specific diseases and species. In our recent research, we investigated the use of genetics to enhance disease resistance in three crucial species: white leg shrimp, striped catfish, and yellowtail kingfish. Our findings indicate that the studied populations of these species possess genes that can be inherited, imparting greater resistance to diseases such as White Spot Syndrome Virus, Bacterial Necrotic Pancreatitis, and skin fluke. By selectively breeding animals with these resistant genes, we successfully increased resistance within the population, promoting overall fish health and boosting production. Additionally, we examined these genes and utilized computer models to predict the most resistant individuals for breeding to combat diseases. Looking ahead, our focus is on omics technologies, precision farming systems, and advanced algorithms to further enhance the disease resistance of these species, thereby making aquaculture more sustainable and resilient against threats.
Details
- Title
- Genetics and Genomics of Infectious Diseases in Key Aquaculture Species
- Authors
- Nguyen Hong Nguyen (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Biology , Vol.13(1), pp.1-19
- Publisher
- MDPI AG
- Date published
- 2024
- DOI
- 10.3390/biology13010029
- ISSN
- 2079-7737
- PMID
- 38248460
- Copyright note
- © 2024 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- All the data are included in tables and figures of this article.
- Organisation Unit
- School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99999995502621
- Output Type
- Journal article
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