Genomic Selection in Aquaculture Breeding Programs

Genomic selection in aquaculture combines dense genome-wide marker information with statistical models to predict the genetic merit of breeding candidates before phenotypic records are available. By capturing both within- and between-family variation, this approach overcomes the limitations of conventional pedigree-based selection and enables accelerated improvement of complex traits such as growth rate, disease resistance and feed conversion efficiency. Implementation typically involves discovery of single nucleotide polymorphisms (SNPs) via array‐based platforms or genotyping by sequencing, estimation of marker effects in a training population with recorded phenotypes, and calculation of genomic estimated breeding values (GEBVs) for selection candidates. Advances in reference genome assemblies, high‐density linkage maps and low-cost sequencing have expanded GS to a wide range of species, including finfish, shrimp and molluscs. Practical applications have demonstrated higher accuracy of selection, reduced generation intervals and lower inbreeding rates, underpinning sustainable productivity gains and resilience in global aquaculture enterprises.

Research from Nature Portfolio

A high-density genetic linkage map for Pacific white shrimp was constructed using next-generation sequencing to identify over 6 000 reliable SNP markers. Integration of these markers with genome scaffolds and BAC clones produced a framework spanning 44 linkage groups, facilitating the detection of quantitative trait loci (QTLs) for body weight and length. This resource provides the scaffold for genomic prediction in penaeid shrimp, enabling the translation of marker-trait associations into breeding decisions and marking a key step towards routine implementation of genomic selection in crustacean aquaculture.

Genomic Selection in Aquaculture Breeding Programs publication trend

The graph below shows the total number of articles in genomic selection in aquaculture breeding programs across all publications each year (not limited to Nature Index journals).

Technical terms

Genomic selection (GS): A breeding approach that uses genome-wide marker data to predict breeding values without direct phenotyping of candidates.

Single nucleotide polymorphism (SNP) array: A platform for genotyping thousands of SNP markers across the genome simultaneously.

Genomic estimated breeding value (GEBV): A prediction of an individual’s genetic merit derived from SNP effects across the entire genome.

Linkage disequilibrium (LD): The non-random association of alleles at different loci, critical for the efficacy of genomic prediction.

Genotyping by sequencing (GBS): A cost-effective method for simultaneous SNP discovery and genotyping, often used in non-model species.

References

1. Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture. Genetics Selection Evolution (2017).
2. Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations. Genetics Selection Evolution (2016).
3. Genome survey and high-density genetic map construction provide genomic and genetic resources for the Pacific White Shrimp Litopenaeus vannamei. Scientific Reports (2015).
4. Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters. Frontiers in Genetics (2019).