Genetic and genomic evaluation for resistance to white spot syndrome virus in post-larvae of Pacific white shrimp (Litopenaeus vannamei)

Campos-Montes, Gabriel R.; García, Baltasar F.; Medrano-Mendoza, Thania; Caballero-Zamora, Alejandra; Montoya‐Rodríguez, Leobardo; Quintana-Casares, Juan C.; Yáñez, José M.

doi:10.1016/j.aquaculture.2023.739745

Cited by 4 publications

(4 citation statements)

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“…In summary, genomic selection for penaeid shrimps consistently demonstrates increased prediction accuracy compared to conventional pedigree selection across a range of traits. Studies report a median increase in prediction accuracy of 21.4% for growth traits, 9.9% for disease resistance, and 12% for salinity tolerance 71,82-84 . Moreover, these increases in prediction accuracy hold true across different species, genome evaluation models, and genotyping platforms, including both SNP arrays and GBS genotyping technology.…”

Section: Application Of Genomic Selectionmentioning

confidence: 99%

100 years domestication of penaeid shrimp and meta-analysis of breeding traits

Ren,

Yáñez,

Perez-Enriquez

et al. 2024

Preprint

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Penaeid shrimp farming plays a pivotal role in ensuring future food security and promoting economic sustainability. Compared to the extensive long history of domestication observed in terrestrial agriculture species, the domestication and selective breeding of penaeids are relatively recent endeavors. Selective breeding aimed at improving production traits holds significant promise for enhancing efficiency and reducing the environmental impact of shrimp farming, thereby contributing to its long-term sustainability. Assessing genotype-by-environment (G-by-E) interactions is essential in breeding programs to ensure that improved penaeid shrimp strains perform consistently across different production environments, with genomic selection proving more effective than sib-testing alone in mitigating environmental sensitivity. Genome editing tools like CRISPR/Cas9 offer significant potential to accelerate genetic gains in penaeid shrimp by enabling rapid introduction of desired genetic changes, with recent advancements showing promising results in achieving high transfection efficiency in shrimp embryos. Additionally, artificial intelligence and machine learning are being leveraged to streamline phenotyping and enhance decision-making in shrimp breeding and farming, improving efficiency and accuracy in managing traits and predicting disease outbreaks. Herein, we provide an overview and update on the domestication of penaeid shrimp, including the current status of domestication for principal farmed species, key milestones in domestication history, targeted breeding traits in selective breeding programs, the advantages of integrating genomeic selection for enhancing production traits, and future directions for selective breeding of penaeid shrimp.

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Section: Application Of Genomic Selectionmentioning

confidence: 99%

100 years domestication of penaeid shrimp and meta-analysis of breeding traits

Ren,

Yáñez,

Perez-Enriquez

et al. 2024

Preprint

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“…Precise dose calculation and normalisation for per os inoculation can be further challenged by inconsistent viral particle distribution within the tissue and variable feeding behaviour of the experimental shrimp (also see Section 3.3.3 ‘Inoculation method’). Maceration or homogenisation of tissue samples for per os challenge can minimise the influence of heterogeneous viral particle distribution on dosage 182–184 . Additionally, implementing a starving period for experimental animals before per os challenge can increase shrimp receptivity to the inoculum feed, improving dose consistency 57,159,185 …”

Section: Essential Components Of Viral Pathogen Challenge Experiments...mentioning

confidence: 99%

“…Maceration or homogenisation of tissue samples for per os challenge can minimise the influence of heterogeneous viral particle distribution on dosage. [182][183][184] Additionally, implementing a starving period for experimental animals before per os challenge can increase shrimp receptivity to the inoculum feed, improving dose consistency. 57,159,185 Regardless of inoculation method, and the approach used and reported for normalisation of dosage, standardisation and reporting of dosage necessitates accurate quantification of viral copy number within the inoculum.…”

Section: Inoculum Concentration/dosementioning

confidence: 99%

Towards a ‘systems’ approach for viral challenge experiments in shrimp: Reporting guidelines for publication

Arbon,

Andrade Martinez,

Jerry

et al. 2023

Reviews in Aquaculture

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The success of contemporary disease management strategies in shrimp aquaculture, such as the ‘systems’ approach, is predicated on robust knowledge of the conditions and interactions between the host, pathogen and environment that promote disease. Pathogen challenge experiments (PCEs) are a power tool for investigating these conditions and interactions. However, absence of accurately reported experimental detail in published PCEs limits scientific transparency, reproducibility, and the potential for the research to make progressive advancements contributing to contemporary shrimp disease management strategies. This review identifies and discusses key factors relating to the host (shrimp), pathogen (virus), and environment that should be carefully considered during the design and publication of PCEs. We offer substantial evidence of their impact on viral disease outcomes, drawn from the existing body of literature, to supporting their consideration. The prevalence of reported experimental details for these factors across 186 viral PCEs in shrimp were evaluated. The review highlights a concerning paucity of experimental detail reported in published shrimp PCEs. We propose a checklist for the minimum reportable information in the publication of shrimp viral PCEs, hereafter referred to as the Shrimp PCE Reporting Guidelines (SPERG). The guidelines aim to enhance the transparency and standardisation of reporting in published PCEs, ensuring that key factors pertaining to the shrimp, pathogen, and environment are adequately considered and documented. Adoption of SPERG is envisaged to empower researchers, reviewers, and readers to assess the internal and external validity of PCEs, facilitating critical evaluation and improved utility of PCE findings for contemporary disease management.

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“…The precise estimation of genetic parameters for objective traits is fundamental to breeding programs, particularly in guiding the formulation of selection indices, breeding stock retention, and mating strategies. Numerous studies have documented the heritability levels of shrimp resistance to WSSV, ranging from 0.03 to 0.53 [ 3 , 11 , 12 , 13 , 14 ]. The genetic correlations between growth and WSSV resistance in different populations ranged from negative to no significant association [ 15 , 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Genetic Parameters for Growth and WSSV Resistance Traits in Litopenaeus vannamei

Sui,

Sun,

Kong

et al. 2024

Animals

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The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the analysis of phenotypic values of five traits: body weight (BW), overall length (OL), body length (BL), tail length (TL), and survival hour post-infection (HPI). The analysis included test data from a total of 1017 individuals belonging to 20 families, of which 293 individuals underwent whole-genome resequencing, resulting in 18,137,179 high-quality SNP loci being obtained. Three methods, including pedigree-based best linear unbiased prediction (pBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic BLUP (ssGBLUP) were utilized. Compared to the pBLUP model, the heritability of growth-related traits obtained from GBLUP and ssGBLUP was lower, whereas the heritability of WSSV resistance was higher. Both the GBLUP and ssGBLUP models significantly enhanced prediction accuracy. Specifically, the GBLUP model improved the prediction accuracy of BW, OL, BL, TL, and HPI by 4.77%, 21.93%, 19.73%, 19.34%, and 63.44%, respectively. Similarly, the ssGBLUP model improved prediction accuracy by 10.07%, 25.44%, 25.72%, 19.34%, and 122.58%, respectively. The WSSV resistance trait demonstrated the most substantial enhancement using both genomic prediction models, followed by body size traits (e.g., OL, BL, and TL), with BW showing the least improvement. Furthermore, the choice of models minimally impacted the assessment of genetic and phenotypic correlations. Genetic correlations among growth traits ranged from 0.767 to 0.999 across models, indicating high levels of positive correlations. Genetic correlations between growth and WSSV resistance traits ranged from (−0.198) to (−0.019), indicating low levels of negative correlations. This study assured significant advantages of the GBLUP and ssGBLUP models over the pBLUP model in the genetic parameter estimation of growth and WSSV resistance in L. vannamei, providing a foundation for further breeding programs.

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Genetic and genomic evaluation for resistance to white spot syndrome virus in post-larvae of Pacific white shrimp (Litopenaeus vannamei)

Cited by 4 publications

References 43 publications

100 years domestication of penaeid shrimp and meta-analysis of breeding traits

100 years domestication of penaeid shrimp and meta-analysis of breeding traits

Towards a ‘systems’ approach for viral challenge experiments in shrimp: Reporting guidelines for publication

Estimation of Genetic Parameters for Growth and WSSV Resistance Traits in Litopenaeus vannamei

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