Quality of breeding value predictions from longitudinal analyses, with application to residual feed intake in pigs.

TitleQuality of breeding value predictions from longitudinal analyses, with application to residual feed intake in pigs.
Publication TypeJournal Article
Year of Publication2022
AuthorsDavid, I, Ricard, A, Huynh-Tran, V-H, Dekkers, JCM, Gilbert, H
JournalGenet Sel Evol
Date Published2022 May 13
KeywordsAnimal Feed, Animals, Body Weight, Eating, Female, Genome, Genomics, Phenotype, Swine

BACKGROUND: An important goal in animal breeding is to improve longitudinal traits. The objective of this study was to explore for longitudinal residual feed intake (RFI) data, which estimated breeding value (EBV), or combination of EBV, to use in a breeding program. Linear combinations of EBV (summarized breeding values, SBV) or phenotypes (summarized phenotypes) derived from the eigenvectors of the genetic covariance matrix over time were considered, and the linear regression method (LR method) was used to facilitate the evaluation of their prediction accuracy.

RESULTS: Weekly feed intake, average daily gain, metabolic body weight, and backfat thickness measured on 2435 growing French Large White pigs over a 10-week period were analysed using a random regression model. In this population, the 544 dams of the phenotyped animals were genotyped. These dams did not have own phenotypes. The quality of the predictions of SBV and breeding values from summarized phenotypes of these females was evaluated. On average, predictions of SBV at the time of selection were unbiased, slightly over-dispersed and less accurate than those obtained with additional phenotypic information. The use of genomic information did not improve the quality of predictions. The use of summarized instead of longitudinal phenotypes resulted in predictions of breeding values of similar quality.

CONCLUSIONS: For practical selection on longitudinal data, the results obtained with this specific design suggest that the use of summarized phenotypes could facilitate routine genetic evaluation of longitudinal traits.

Alternate JournalGenet Sel Evol
PubMed ID35562648
PubMed Central IDPMC9103455
Grant ListEU 633531 / / Horizon 2020 /