Genomic prediction of scale drop disease resistance in barramundi Lates calcarifer under controlled laboratory conditions

Barramundi ( Lates calcarifer ) is a tropical aquaculture species principally farmed across Southeast Asia and Australia. However, outbreaks of scale drop disease virus (SDDV) have caused substantial economic losses due to mass mortalities of 40 % to 90 % on farms in Singapore. While vaccines against SDDV are under development, selective breeding for resistance offers a promising avenue for long term disease management. Although moderate heritability against SDDV has been observed in farm environments, the development of controlled laboratory studies, free of interference from external factors and co-infections, is necessary to provide a clearer understanding of barramundi genetic resistance and accelerate the development of SDDV-resistant barramundi strains. This study established a laboratory infection model for juvenile barramundi to determine the appropriate SDDV dose via intraperitoneal injections required to induce approximately 50 % mortality over 21 days. Subsequently, two challenge trials involving 654 (80.1 ± 16.1 g) and 705 (68.6 ± 12.0 g) juveniles were conducted under controlled conditions in a single 6000 L recirculating aquaculture system, with survival rates of 5.8 % and 34.2 % respectively. Three SDDV resistant traits were assessed: survival time (days survived), survival status (alive or dead at day 21), and survival 50 % (alive or dead on the day closest to 50 % survival). Genomic prediction models were developed using GBLUP and bayesR approaches based on ~48 k SNPs from a 70 K barramundi SNP Array. Heritability estimates ranged from 0.16 to 0.42 for survival time, 0.06 to 0.33 for survival status, and 0.26 to 0.35 for survival 50 %. Prediction accuracies were high across traits, from 0.75 to 0.91 for survival time, 0.51 to 0.63 for survival status, and 0.72 to 0.90 for survival 50 %, confirming the feasibility of genomic selection for developing SDDV-resistant barramundi lines. These findings provide a strong foundation for integrating disease resistance into selective breeding programmes, offering a strategy to mitigate SDDV-related losses and strengthening the resilience of barramundi aquaculture. • Development of a standardised SDDV challenge model for juvenile barramundi • Moderate heritability found for three SDDV resistance traits • High prediction accuracies were achieved with genomic selection models • Genomic selection is a suitable strategy for SDDV resistance

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Journal
Aquaculture
Published
2025-09-27
DOI
https://doi.org/10.1016/j.aquaculture.2025.743250
Primary Topic
Genetics and Plant Breeding
Type
article
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article

Genomic prediction of scale drop disease resistance in barramundi Lates calcarifer under controlled laboratory conditions

Dean R. Jerry, Jose A. Domingos, Maura Carrai, Shubha Vij et al.
Aquaculture
Genetics and Plant Breeding
article

Genomic prediction of scale drop disease resistance in barramundi Lates calcarifer under controlled laboratory conditions

Dean R. Jerry, Jose A. Domingos, Maura Carrai, Shubha Vij, Susan Gibson‐Kueh, Celestine Terence, Zhi Weng Josiah Poon, David B. Jones, Sarah Priyanka Nelson, Sunita Awate, Ha Thanh Dong, Xueyan Shen, Nguyen Thanh Vu, Marie R. Tan, Saengchan Senapin, Yang Tan
article en

Abstract

Barramundi ( Lates calcarifer ) is a tropical aquaculture species principally farmed across Southeast Asia and Australia. However, outbreaks of scale drop disease virus (SDDV) have caused substantial economic losses due to mass mortalities of 40 % to 90 % on farms in Singapore. While vaccines against SDDV are under development, selective breeding for resistance offers a promising avenue for long term disease management. Although moderate heritability against SDDV has been observed in farm environments, the development of controlled laboratory studies, free of interference from external factors and co-infections, is necessary to provide a clearer understanding of barramundi genetic resistance and accelerate the development of SDDV-resistant barramundi strains. This study established a laboratory infection model for juvenile barramundi to determine the appropriate SDDV dose via intraperitoneal injections required to induce approximately 50 % mortality over 21 days. Subsequently, two challenge trials involving 654 (80.1 ± 16.1 g) and 705 (68.6 ± 12.0 g) juveniles were conducted under controlled conditions in a single 6000 L recirculating aquaculture system, with survival rates of 5.8 % and 34.2 % respectively. Three SDDV resistant traits were assessed: survival time (days survived), survival status (alive or dead at day 21), and survival 50 % (alive or dead on the day closest to 50 % survival). Genomic prediction models were developed using GBLUP and bayesR approaches based on ~48 k SNPs from a 70 K barramundi SNP Array. Heritability estimates ranged from 0.16 to 0.42 for survival time, 0.06 to 0.33 for survival status, and 0.26 to 0.35 for survival 50 %. Prediction accuracies were high across traits, from 0.75 to 0.91 for survival time, 0.51 to 0.63 for survival status, and 0.72 to 0.90 for survival 50 %, confirming the feasibility of genomic selection for developing SDDV-resistant barramundi lines. These findings provide a strong foundation for integrating disease resistance into selective breeding programmes, offering a strategy to mitigate SDDV-related losses and strengthening the resilience of barramundi aquaculture. • Development of a standardised SDDV challenge model for juvenile barramundi • Moderate heritability found for three SDDV resistance traits • High prediction accuracies were achieved with genomic selection models • Genomic selection is a suitable strategy for SDDV resistance

AquacultureVol. 612
National Science and Technology Development Agency (TH), Republic Polytechnic (SG), Mahidol University (TH), Henderson Community College (US), Australian Institute of Tropical Health and Medicine (AU), Asian Institute of Technology (TH), James Cook University Singapore (SG), Woodlands Health Campus (SG), James Cook University (AU), National Center for Genetic Engineering and Biotechnology (TH)
Openalex Percentile: Top 81%
Genetics and Plant Breeding
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