Estimation of genomic breeding values for residual feed intake in a multibreed cattle population1

Khansefid, Majid; Pryce, J.E.; Bolormaa, Sunduimijid; Miller, Stephen; Wang, Z.; Li, C.; Goddard, Michael E.

doi:10.2527/jas.2014-7375

Cited by 39 publications

(43 citation statements)

References 30 publications

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“…The finding of Khansefid et al . () is consistent with this finding. They used BLUP for genomic selection of residual feed intake and found half the variance was due to SNPs and half due to SNP by breed interactions.…”

Section: Discussionsupporting

confidence: 92%

“…BAYESR may utilize a number of SNPs to predict the effect of the QTL, and this combination may work in Holsteins but is misleading in Jerseys. The finding of Khansefid et al (2014) is consistent with this finding. They used BLUP for genomic selection of residual feed intake and found half the variance was due to SNPs and half due to SNP by breed interactions.…”

Section: Discussionsupporting

confidence: 91%

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How old are quantitative trait loci and how widely do they segregate?

Kemper

Hayes

Daetwyler

et al. 2015

J Animal Breeding Genetics

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The mutations that cause genetic variation in quantitative traits could be old and segregate across many breeds or they could be young and segregate only within one breed. This has implications for our understanding of the evolution of quantitative traits and for genomic prediction to improve livestock. We investigated the age of quantitative trait loci (QTL) for milk production traits identified as segregating in Holstein dairy cattle. We use a multitrait method and found that six of 11 QTL also segregate in Jerseys. Variants identified as Holstein-only QTL were fixed or rare [minor allele frequency (MAF) < 0.05] in Jersey. The age of the QTL mutations appears to vary from perhaps 2000 to 50,000 generations old. The older QTL tend to have high derived allele frequencies and often segregate across both breeds. Holstein-only QTL were often embedded within longer haplotypes, supporting the conclusion that they are typically younger mutations that have occurred more recently than QTL that segregate in both breeds. A reference population for genomic prediction using both Holsteins and Jersey cattle incorrectly predicted a QTL in Jersey cattle when the QTL only segregates in Holsteins. Overcoming this error should help to make genomic prediction more accurate in smaller breeds.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 91%

How old are quantitative trait loci and how widely do they segregate?

Kemper

Hayes

Daetwyler

et al. 2015

J Animal Breeding Genetics

View full text Add to dashboard Cite

show abstract

“…Variants with effects in the same direction in both breeds resulted in increased across-breed reliabilities of genomic predictions and high genomic correlations, while variants with opposite effects decreased reliabilities and resulted in negative genomic correlations. By fitting separate within- and multi-breed genomic relationship matrices, Khansefid et al [36] reported increases in accuracy for some traits compared to a model using only within-breed relationships.…”

Section: Discussionmentioning

confidence: 99%

Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle

2016

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BackgroundSequence data can potentially increase the reliability of genomic predictions, because such data include causative mutations instead of relying on linkage disequilibrium (LD) between causative mutations and prediction variants. However, the location of the causative mutations is not known, and the presence of many variants that are in low LD with the causative mutations may reduce prediction reliability. Our objective was to investigate whether the use of variants at quantitative trait loci (QTL) that are identified in a multi-breed genome-wide association study (GWAS) for milk, fat and protein yield would increase the reliability of within- and multi-breed genomic predictions in Holstein, Jersey and Danish Red cattle. A wide range of scenarios that test different strategies to select prediction markers, for both within-breed and multi-breed prediction, were compared.ResultsFor all breeds and traits, the use of variants selected from a multi-breed GWAS resulted in substantial increases in prediction reliabilities compared to within-breed prediction using a 50 K SNP array. Reliabilities depended highly on the choice of the prediction markers, and the scenario that led to the highest reliability varied between breeds and traits. While genomic correlations across breeds were low for genome-wide sequence variants, the effects of the QTL variants that yielded the highest reliabilities were highly correlated across breeds.ConclusionsOur results show that the use of sequence variants, which are located near peaks of QTL that are detected in a multi-breed GWAS, can increase reliability of genomic predictions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0259-0) contains supplementary material, which is available to authorized users.

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“…Four subsets were used as training populations (≈946) and the fifth subset as a validation sample (≈237). The animals for the various subsets were selected randomly, except that paternal half-sibs were always placed in the same subset [42]. Cross-validation was replicated 10 times.…”

Section: Methodsmentioning

confidence: 99%

Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture

et al. 2017

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BackgroundHanwoo beef is known for its marbled fat, tenderness, juiciness and characteristic flavor, as well as for its low cholesterol and high omega 3 fatty acid contents. As yet, there has been no comprehensive investigation to estimate genomic selection accuracy for carcass traits in Hanwoo cattle using dense markers. This study aimed at evaluating the accuracy of alternative statistical methods that differed in assumptions about the underlying genetic model for various carcass traits: backfat thickness (BT), carcass weight (CW), eye muscle area (EMA), and marbling score (MS).MethodsAccuracies of direct genomic breeding values (DGV) for carcass traits were estimated by applying fivefold cross-validation to a dataset including 1183 animals and approximately 34,000 single nucleotide polymorphisms (SNPs).ResultsAccuracies of BayesC, Bayesian LASSO (BayesL) and genomic best linear unbiased prediction (GBLUP) methods were similar for BT, EMA and MS. However, for CW, DGV accuracy was 7% higher with BayesC than with BayesL and GBLUP. The increased accuracy of BayesC, compared to GBLUP and BayesL, was maintained for CW, regardless of the training sample size, but not for BT, EMA, and MS. Genome-wide association studies detected consistent large effects for SNPs on chromosomes 6 and 14 for CW.ConclusionsThe predictive performance of the models depended on the trait analyzed. For CW, the results showed a clear superiority of BayesC compared to GBLUP and BayesL. These findings indicate the importance of using a proper variable selection method for genomic selection of traits and also suggest that the genetic architecture that underlies CW differs from that of the other carcass traits analyzed. Thus, our study provides significant new insights into the carcass traits of Hanwoo cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0283-0) contains supplementary material, which is available to authorized users.

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Estimation of genomic breeding values for residual feed intake in a multibreed cattle population1

Cited by 39 publications

References 30 publications

How old are quantitative trait loci and how widely do they segregate?

How old are quantitative trait loci and how widely do they segregate?

Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle

Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture

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