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Forward genetic screens
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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Genomic Selection in Aquaculture Species.

François Allal1, Nguyen Hong Nguyen2

  • 1MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France. francois.allal@ifremer.fr.

Methods in Molecular Biology (Clifton, N.J.)
|April 22, 2022
PubMed
Summary

Genomic selection (GS) significantly improves breeding accuracy for aquaculture species, enhancing growth and disease resistance. Its wider adoption, aided by cost-effective imputation, is crucial for sustainable aquaculture and climate change adaptation.

Keywords:
AccuracyAquacultureCrustaceansFinfishGenomic selectionGenotype-by-environmentMolluscs

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Area of Science:

  • Aquaculture genomics
  • Animal breeding
  • Quantitative genetics

Background:

  • Genomic prediction (GP) is applied in approximately 20 aquaculture species, primarily using intra-family genomic selection (GS).
  • Classical pedigree-based breeding value estimation is often outperformed by genomic estimated breeding values (GEBVs) in aquaculture.
  • Significant accuracy gains for growth (15–89%) and disease resistance (0–567%) are observed with GS.

Purpose of the Study:

  • To synthesize the literature on the application of genomic selection (GS) in aquaculture.
  • To highlight the benefits of GS for various aquaculture species, including finfish, crustaceans, and molluscs.
  • To discuss the future potential of GS in aquaculture breeding programs, considering climate change.

Main Methods:

  • Literature review of genomic prediction applications in aquaculture.
  • Analysis of accuracy improvements from genomic estimated breeding values (GEBVs) versus pedigree-based methods.
  • Synthesis of current and future roles of GS in finfish, crustacean, and mollusc breeding.

Main Results:

  • GS offers substantial accuracy increases for key aquaculture traits.
  • The implementation of GS requires minimal additional investment in existing breeding programs.
  • Cost-effective imputation from low-density panels can facilitate broader GS deployment.
  • GS can enhance sustainability traits like yield, feed efficiency, and disease resistance.
  • GS improves tolerance to environmental variations, crucial for climate change adaptation.

Conclusions:

  • Genomic selection is a powerful tool for accelerating genetic gain in aquaculture.
  • Wider adoption of GS, supported by imputation strategies, is recommended for aquaculture breeding programs.
  • GS is vital for developing resilient and sustainable aquaculture systems in the face of environmental challenges.