Review: How to improve genomic predictions in small dairy cattle populations

Animal : an International Journal of Animal Bioscience
M S LundG Su

Abstract

This paper reviews strategies and methods to improve accuracies of genomic predictions from the perspective of a numerically small population. Improvements are realized by influencing one or both of the main factors: (1) improve or increase genomic connections to phenotypic records in training data. (2) Models and strategies to focus genomic predictions on markers closer to the causative variants. Combining populations into a joint reference population results in high improvements when combining populations of the same breed and diminishes as the genetic distance between populations increases. For distantly related breeds sophisticated Bayesian variable selection models in combination with denser markers sets or functional subsets of markers is needed. This is expected to be further improved by the efficient use of sequence information. In addition predictions can be improved by the use of phenotypes of genotyped and non-genotyped cows directly. For a small population the optimal approach will combine the above components.

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Citations

Dec 3, 2016·Genetics, Selection, Evolution : GSE·Roel F VeerkampMario P L Calus
Aug 28, 2017·Journal of Dairy Science·J I WellerM Ron
May 18, 2016·Animal : an International Journal of Animal Bioscience·M P L Calus
Sep 25, 2017·Genetics, Selection, Evolution : GSE·Irene van den BergMike E Goddard
Feb 13, 2017·Journal of Dairy Science·A Reiner-BenaimJ I Weller
Apr 26, 2020·Journal of Dairy Science·I van den BergJ E Pryce
Oct 12, 2020·Journal of Animal Breeding and Genetics = Zeitschrift Für Tierzüchtung Und Züchtungsbiologie·Jovana Marjanovic, Mario P L Calus
Jan 1, 2021·Frontiers in Genetics·Majid KhansefidIona M MacLeod
Oct 16, 2021·The Plant Genome·Sebastian MichelHermann Bürstmayr

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