Literature DB >> 26330119

Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey.

G Su1, P Ma1, U S Nielsen2, G P Aamand3, G Wiggans4, B Guldbrandtsen1, M S Lund1.   

Abstract

Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such like Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing size of reference population in Danish Jersey. The first approach was to include North American Jersey bulls in Danish Jersey reference population. The second was to genotype cows and use them as reference animals. The validation of genomic prediction was carried out on bulls and cows, respectively. In validation on bulls, about 300 Danish bulls (depending on traits) born in 2005 and later were used as validation data, and the reference populations were: (1) about 1050 Danish bulls, (2) about 1050 Danish bulls and about 1150 US bulls. In validation on cows, about 3000 Danish cows from 87 young half-sib families were used as validation data, and the reference populations were: (1) about 1250 Danish bulls, (2) about 1250 Danish bulls and about 1150 US bulls, (3) about 1250 Danish bulls and about 4800 cows, (4) about 1250 Danish bulls, 1150 US bulls and 4800 Danish cows. Genomic best linear unbiased prediction model was used to predict breeding values. De-regressed proofs were used as response variables. In the validation on bulls for eight traits, the joint DK-US bull reference population led to higher reliability of genomic prediction than the DK bull reference population for six traits, but not for fertility and longevity. Averaged over the eight traits, the gain was 3 percentage points. In the validation on cows for six traits (fertility and longevity were not available), the gain from inclusion of US bull in reference population was 6.6 percentage points in average over the six traits, and the gain from inclusion of cows was 8.2 percentage points. However, the gains from cows and US bulls were not accumulative. The total gain of including both US bulls and Danish cows was 10.5 percentage points. The results indicate that sharing reference data and including cows in reference population are efficient approaches to increase reliability of genomic prediction. Therefore, genomic selection is promising for numerically small population.

Entities:  

Keywords:  Jersey cattle; genomic selection; reference population; reliability

Mesh:

Year:  2015        PMID: 26330119     DOI: 10.1017/S1751731115001792

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  6 in total

1.  Genomic Estimated Breeding Value of Milk Performance and Fertility Traits in the Russian Black-and-White Cattle Population.

Authors:  F S Sharko; A Khatib; E B Prokhortchouk
Journal:  Acta Naturae       Date:  2022 Jan-Mar       Impact factor: 2.204

2.  Using a very low-density SNP panel for genomic selection in a breeding program for sheep.

Authors:  Jérôme Raoul; Andrew A Swan; Jean-Michel Elsen
Journal:  Genet Sel Evol       Date:  2017-10-24       Impact factor: 4.297

3.  Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome.

Authors:  Emre Karaman; Mogens S Lund; Mahlet T Anche; Luc Janss; Guosheng Su
Journal:  G3 (Bethesda)       Date:  2018-11-06       Impact factor: 3.154

4.  Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data.

Authors:  Aoxing Liu; Mogens Sandø Lund; Didier Boichard; Emre Karaman; Sebastien Fritz; Gert Pedersen Aamand; Ulrik Sander Nielsen; Yachun Wang; Guosheng Su
Journal:  Heredity (Edinb)       Date:  2019-07-05       Impact factor: 3.821

5.  Systematic genotyping of groups of cows to improve genomic estimated breeding values of selection candidates.

Authors:  Laura Plieschke; Christian Edel; Eduardo C G Pimentel; Reiner Emmerling; Jörn Bennewitz; Kay-Uwe Götz
Journal:  Genet Sel Evol       Date:  2016-09-28       Impact factor: 4.297

6.  Genomic Selection for Milk Production Traits in Xinjiang Brown Cattle.

Authors:  Menghua Zhang; Hanpeng Luo; Lei Xu; Yuangang Shi; Jinghang Zhou; Dan Wang; Xiaoxue Zhang; Xixia Huang; Yachun Wang
Journal:  Animals (Basel)       Date:  2022-01-07       Impact factor: 2.752

  6 in total

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