Development of Single Nucleotide Polymorphisms Markers Associated with Disease Resistance towards Pseudomonas koreensis in Empurau (Tor tambroides) using T-Plex ARMS PCR Assay

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Abstract

The rapid growth of aquaculture is driven by the increasing demand for fish which provide essential nutrients for balanced health. Empurau is a highly-sought freshwater fish with high market value due to its unique flesh taste, making it one of the most famous species among the aquaculture industry. However, the main challenge of the industry remains as the infectious disease outbreak with Pseudomonas species as one of the most threatening fish pathogens while residing a wide range of environments. Given antibiotics administration as the common solution to disease outbreaks, contributing to the worsening of antimicrobial resistance, the development of disease-resistant broodstock through the identification of SNP markers appeared as one of a promising strategy. In this study, a total of 1,048,576 SNP markers were identified via whole genome pooled sequencing on samples treated with LD 50 , forming resistant and susceptible group. Multiple tests (pairwise F ST test, CMH test and FE test) and visualization had been conducted to screen and select candidate SNP markers for further validation using T-plex ARMS real-time PCR assay. The genotyping results on the selected candidate markers were confirmed using Sanger sequencing. Statistical analysis had been performed to validate the significance of the candidate marker. The successful validation of 19,564 G/C SNP markers is expected to advance research on disease-resistant association SNPs and support their integration into breeding programs, enabling the use of genomic information to optimize artificial selection in empurau breeding.
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Abstract

The rapid growth of aquaculture is driven by the increasing demand for fish which provide essential nutrients for balanced health. Empurau is a highly-sought freshwater fish with high market value due to its unique flesh taste, making it one of the most famous species among the aquaculture industry. However, the main challenge of the industry remains as the infectious disease outbreak with Pseudomonas species as one of the most threatening fish pathogens while residing a wide range of environments. Given antibiotics administration as the common solution to disease outbreaks, contributing to the worsening of antimicrobial resistance, the development of disease-resistant broodstock through the identification of SNP markers appeared as one of a promising strategy. In this study, a total of 1,048,576 SNP markers were identified via whole genome pooled sequencing on samples treated with LD 50, forming resistant and susceptible group. Multiple tests (pairwise F ST test, CMH test and FE test) and visualization had been conducted to screen and select candidate SNP markers for further validation using T-plex ARMS real-time PCR assay. The genotyping results on the selected candidate markers were confirmed using Sanger sequencing. Statistical analysis had been performed to validate the significance of the candidate marker. The successful validation of 19,564 G/C SNP markers is expected to advance research on disease-resistant association SNPs and support their integration into breeding programs, enabling the use of genomic information to optimize artificial selection in empurau breeding. Supplementary Material File (manuscript.docx) - Download - 1.27 MB Information & Authors Information Version history Peer review timeline Published Aquaculture International Version of Record2 Jun 2025Published Copyright This work is licensed under a Non Exclusive No Reuse License.

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Authors Metrics & Citations Metrics Article Usage 157views 67downloads Citations Download citation Melinda Mei Lin Lau, Hung Hui Chung, Cindy Jia Yung Kho, et al. Development of Single Nucleotide Polymorphisms Markers Associated with Disease Resistance towards Pseudomonas koreensis in Empurau (Tor tambroides) using T-Plex ARMS PCR Assay. Authorea. 15 January 2025. DOI: https://doi.org/10.22541/au.173694093.33957612/v1 DOI: https://doi.org/10.22541/au.173694093.33957612/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.

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