Genomic prediction for latent variables related to milk fatty acid composition in Holstein, Simmental and Brown Swiss dairy cattle breeds.
dairy cattle
genomic selection
milk fatty acids
multivariate factor analysis
Journal
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
ISSN: 1439-0388
Titre abrégé: J Anim Breed Genet
Pays: Germany
ID NLM: 100955807
Informations de publication
Date de publication:
May 2021
May 2021
Historique:
revised:
27
11
2020
received:
17
07
2020
accepted:
02
12
2020
pubmed:
18
12
2020
medline:
23
9
2021
entrez:
17
12
2020
Statut:
ppublish
Résumé
Genomic selection (GS) reports on milk fatty acid (FA) profiles have been published quite recently and are still few despite this trait represents the most important aspect of milk nutritional and sensory quality. Reasons for this can be found in the high costs of phenotype recording but also in issues related to its nature of complex trait constituted by multiple genetically correlated variables with low heritabilities. One possible strategy to deal with such constraint is represented by the use of dimension reduction methods. We analysed 40 individual FAs from Italian Brown Swiss, Holstein and Simmental milk through multivariate factor analysis (MFA) to study the genetics of milk FA-related latent variables (factors) and assess their potential use in breeding. A total of nine factors were obtained, and their genetic parameters were inferred under a Bayesian framework using two statistical approaches: the classical pedigree best linear unbiased prediction (ABLUP) and the single-step genomic BLUP (ssGBLUP). The resulting factorial solutions were able to represent groups of FAs with common origin and function and can be considered concise pathway-level phenotypes. The heritability (h
Substances chimiques
Fatty Acids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
389-402Informations de copyright
© 2020 John Wiley & Sons Ltd.
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