Introduction
The farming of Penaeus vannamei is one of the cornerstones of the global aquaculture, particularly in countries such as Ecuador, where it is one of the main exports. However, diseases remain one of the factors limiting the sector's sustainability and profitability. Among these, the White Spot Syndrome Virus (WSSV) stands out for its high virulence and mortality rate, whilst acute hepatopancreatic necrosis disease (AHPND), caused by Vibrio parahaemolyticus, results in significant economic losses in intensive systems (Negm, 2024; Mart��nez Soler et al., 2025). Furthermore, the Infectious Hypodermal and Hematopoietic Necrosis Virus (IHHNV), although less lethal, affects growth and the commercial quality of the product (Shin et al., 2025). In this context, genetic improvement programmes have proven to be an effective tool for increasing disease resistance. However, the relationship between resistance and production traits may vary depending on the pathogen.
Given the impact of infectious diseases on shrimp aquaculture, the aim of this study is to compare the genetic parameters for resistance to WSSV, AHPND and IHHNV, as well as their correlations with growth traits, using data from the PMG–BIOGEMAR�� programme, with a view to providing information that can be applied to the design of selection strategies for these traits under industrial conditions.
Materials and Methods
Data from various trials conducted on different generations of Penaus vannamei within the PMG-BOGEMAR�� breeding program in Ecuador were used. The growth-oriented selection scheme based on weight is founded on BLUP methodology and the optimal contribution selection (OCS) (Meuwissen, 1997). For WSSV, approximately 4,700 individuals weighing approximately 2 g, from 220 families of generation 7 (G7), were analysed. These were subjected to an experimental challenge via oral infection with two viral strains (pBIO and pCENA) under differente salinity conditions (5 ppt and 35 ppt), with survival and viral loas assessed using qPCR (Negm, 2024). In the case of AHPND, two challenges were carried out via inmersion (Test 1) and oral (Test 2) infection with Vibrio parahaemolyticus. Approximately 3,350 shrimps weighing approximately 0.8 g and 3.5 g, from 159 families of generation 5 (G5), were used; growth parameters, survival rates and infection levels were recorded (Martinez Soler et al., 2025). For IHHNV, data on natural infection were analysed for around 11,500 individuals at harvest size (approximately 25 g) under industrial farming conditions. These animals were originated from 120 families of generation 4 (G4), and growth, survival and viral load were assessed using qPCR (Shin et al., 2025).
The variance components and genetic parameters (heritabilities and genetic correlations) were estimated using mixed models based on BLUP and restricted maximum likelihood (Neumaier and Groeneveld, 1998; Groeneveld et al., 2010; Misztal, 2022).
Results and discussion
The results showed differences in the genetic architecture of resistance to the three diseases studied. Resistance to WSSV exhibited low heritability and a negative genetic correlation with growth traits (-0.43 REML, -0.44 BAYESIAN), indicating a trade-off between resistance and production (Negm, 2024). In contrast, resistance to AHPND showed low to moderate heritabilities and positive genetic correlations with growth traits, reaching values above 0.55 under experimental conditions (Mart��nez Soler et al., 2025), suggesting that indirect selection for weight could improve resistance. IHHNV showed low to moderate heritabilities, and its genetic correlations with growth traits were virtually zero with the viral load (0.01–0.05), and low with survival (0.22–0.29) (Shin et al., 2025), indicating a limited impact on production performance.
Overall, the results show that the relationship between disease resistance traits and growth is pathogen-dependent; therefore, there is no single selection strategy. These findings have direct implications for the industry, as they enable the design of specific selection strategies based on the predominant health risk in each production system. In this context, the need to develop multi-trait selection indexes that integrate disease resistance and growth traits is reinforced, thereby enabling the simultaneous optimization of robustness and productivity.
Acknowledgment
The authors would like to thank BIOGEMAR S.A. (Grupo ALMAR) for providing the data and the population used in this study, as well as for its support in the development of the PMG-BOGEMAR�� genetic improvement program. We would also like to thank CENAIM-ESPOL for its collaboration in carrying out the experimental trials. The support provided by the University of Las Palmas through the award of a predoctoral research contract (File No.: 50290/2025) is gratefully acknowledged.
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