Genomic Selection for Aquaculture: Principles and Procedures

2010 ◽  
pp. 151-163 ◽  
Author(s):  
Anna K. Sonesson
Keyword(s):  
Genomic Selection ◽  
Selection For

scholarly journals Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 210
Author(s):  
Sang V. Vu ◽  
Cedric Gondro ◽  
Ngoc T. H. Nguyen ◽  
Arthur R. Gilmour ◽  
Rick Tearle ◽  
...  
Keyword(s):  
Moisture Content ◽  
Genomic Selection ◽  
Shell Length ◽  
Prediction Accuracy ◽  
Genomic Information ◽  
Morphometric Traits ◽  
Shell Weight ◽  
Shell Width ◽  
Crassostrea Angulata ◽  
Selection For

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

Genomic Selection for the Traits Expressed after Pollination in Allogamous Plants

Crop Science ◽  
2014 ◽  
Vol 54 (4) ◽  
pp. 1448-1457 ◽  
Author(s):  
Shiori Yabe ◽  
Ryo Ohsawa ◽  
Hiroyoshi Iwata
Keyword(s):  
Genomic Selection ◽  
Selection For

scholarly journals Why and How to Switch to Genomic Selection: Lessons From Plant and Animal Breeding Experience

2021 ◽  
Vol 12 ◽  
Author(s):  
◽  
Aline Fugeray-Scarbel ◽  
Catherine Bastien ◽  
Mathilde Dupont-Nivet ◽  
Stéphane Lemarié
Keyword(s):  
Genetic Diversity ◽  
Genomic Selection ◽  
Plant Species ◽  
Animal Species ◽  
Animal Breeding ◽  
Breeding Cycle ◽  
Breeding Programs ◽  
The Third ◽  
Wide Range ◽  
Selection For

The present study is a transversal analysis of the interest in genomic selection for plant and animal species. It focuses on the arguments that may convince breeders to switch to genomic selection. The arguments are classified into three different “bricks.” The first brick considers the addition of genotyping to improve the accuracy of the prediction of breeding values. The second consists of saving costs and/or shortening the breeding cycle by replacing all or a portion of the phenotyping effort with genotyping. The third concerns population management to improve the choice of parents to either optimize crossbreeding or maintain genetic diversity. We analyse the relevance of these different bricks for a wide range of animal and plant species and sought to explain the differences between species according to their biological specificities and the organization of breeding programs.

Genomic Selection for Yield and Seed Protein Content in Soybean: A Study of Breeding Program Data and Assessment of Prediction Accuracy

Crop Science ◽  
2017 ◽  
Vol 57 (3) ◽  
pp. 1325-1337 ◽  
Author(s):  
Alexandra Duhnen ◽  
Amandine Gras ◽  
Simon Teyssèdre ◽  
Michel Romestant ◽  
Bruno Claustres ◽  
...  
Keyword(s):  
Protein Content ◽  
Genomic Selection ◽  
Prediction Accuracy ◽  
Seed Protein ◽  
Breeding Program ◽  
Seed Protein Content ◽  
Selection For ◽  
Program Data

Genomic Selection for Biomass Yield of Perennial and Annual Legumes

2018 ◽  
pp. 259-264 ◽  
Author(s):  
P. Annicchiarico ◽  
N. Nazzicari ◽  
L. Pecetti ◽  
M. Romani
Keyword(s):  
Genomic Selection ◽  
Biomass Yield ◽  
Annual Legumes ◽  
Selection For

Performance of multi-trait genomic selection for Eucalyptus robusta breeding program

2018 ◽  
Vol 14 (5) ◽  
Author(s):  
Tahina Rambolarimanana ◽  
Lolona Ramamonjisoa ◽  
Daniel Verhaegen ◽  
Jean-Michel Leong Pock Tsy ◽  
Laval Jacquin ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Breeding Program ◽  
Selection For

scholarly journals Effectiveness of Genomic Selection by Response to Selection for Winter Wheat Variety Improvement

2019 ◽  
Vol 12 (3) ◽  
pp. 180090 ◽  
Author(s):  
Xiaowei Hu ◽  
Brett F. Carver ◽  
Carol Powers ◽  
Liuling Yan ◽  
Lan Zhu ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Genomic Selection ◽  
Wheat Variety ◽  
Response To Selection ◽  
Winter Wheat Variety ◽  
Selection For

High-throughput phenotyping platforms enhance genomic selection for wheat grain yield across populations and cycles in early stage

2019 ◽  
Vol 132 (6) ◽  
pp. 1705-1720 ◽  
Author(s):  
Jin Sun ◽  
Jesse A. Poland ◽  
Suchismita Mondal ◽  
José Crossa ◽  
Philomin Juliana ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genomic Selection ◽  
High Throughput ◽  
Early Stage ◽  
Wheat Grain ◽  
High Throughput Phenotyping ◽  
Selection For

scholarly journals Genomic Selection for Quantitative Adult Plant Stem Rust Resistance in Wheat

2014 ◽  
Vol 7 (3) ◽  
Author(s):  
Jessica E. Rutkoski ◽  
Jesse A. Poland ◽  
Ravi P. Singh ◽  
Julio Huerta‐Espino ◽  
Sridhar Bhavani ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Stem Rust ◽  
Rust Resistance ◽  
Stem Rust Resistance ◽  
Adult Plant ◽  
Plant Stem ◽  
Selection For
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