Literature DB >> 23317062

Comparison of heritabilities of dairy traits in Australian Holstein-Friesian cattle from genomic and pedigree data and implications for genomic evaluations.

M Haile-Mariam1, G J Nieuwhof, K T Beard, K V Konstatinov, B J Hayes.   

Abstract

The reliability of genomic evaluations depends on the proportion of genetic variation explained by the DNA markers. In this study, we have estimated the proportion of variance in daughter trait deviations (DTDs) of dairy bulls explained by 45 993 genome wide single-nucleotide polymorphism (SNP) markers for 29 traits in Australian Holstein-Friesian dairy cattle. We compare these proportions to the proportion of variance in DTDs explained by the additive relationship matrix derived from the pedigree, as well as the sum of variance explained by both pedigree and marker information when these were fitted simultaneously. The proportion of genetic variance in DTDs relative to the total genetic variance (the total genetic variance explained by the genomic relationships and pedigree relationships when both were fitted simultaneously) varied from 32% for fertility to approximately 80% for milk yield traits. When fitting genomic and pedigree relationships simultaneously, the variance unexplained (i.e. the residual variance) in DTDs of the total variance for most traits was reduced compared to fitting either individually, suggesting that there is not complete overlap between the effects. The proportion of genetic variance accounted by the genomic relationships can be used to modify the blending equations used to calculate genomic estimated breeding value (GEBV) from direct genomic breeding value (DGV) and parent average. Our results, from a validation population of young dairy bulls with DTD, suggest that this modification can improve the reliability of GEBV by up to 5%.
Copyright © 2013 Blackwell Verlag GmbH.

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Year:  2013        PMID: 23317062     DOI: 10.1111/j.1439-0388.2013.01001.x

Source DB:  PubMed          Journal:  J Anim Breed Genet        ISSN: 0931-2668            Impact factor:   2.380


  28 in total

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Journal:  Genetics       Date:  2019-04       Impact factor: 4.562

2.  Explicit Modeling of Ancestry Improves Polygenic Risk Scores and BLUP Prediction.

Authors:  Chia-Yen Chen; Jiali Han; David J Hunter; Peter Kraft; Alkes L Price
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3.  Toward genomic prediction from whole-genome sequence data: impact of sequencing design on genotype imputation and accuracy of predictions.

Authors:  T Druet; I M Macleod; B J Hayes
Journal:  Heredity (Edinb)       Date:  2013-04-03       Impact factor: 3.821

Review 4.  Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture.

Authors:  M E Goddard; K E Kemper; I M MacLeod; A J Chamberlain; B J Hayes
Journal:  Proc Biol Sci       Date:  2016-07-27       Impact factor: 5.349

Review 5.  Pitfalls of predicting complex traits from SNPs.

Authors:  Naomi R Wray; Jian Yang; Ben J Hayes; Alkes L Price; Michael E Goddard; Peter M Visscher
Journal:  Nat Rev Genet       Date:  2013-07       Impact factor: 53.242

6.  Two-Variance-Component Model Improves Genetic Prediction in Family Datasets.

Authors:  George Tucker; Po-Ru Loh; Iona M MacLeod; Ben J Hayes; Michael E Goddard; Bonnie Berger; Alkes L Price
Journal:  Am J Hum Genet       Date:  2015-11-05       Impact factor: 11.025

7.  Combining genomic and genealogical information in a reproducing kernel Hilbert spaces regression model for genome-enabled predictions in dairy cattle.

Authors:  Silvia Teresa Rodríguez-Ramilo; Luis Alberto García-Cortés; Oscar González-Recio
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

8.  Assumptions and properties of limiting pathway models for analysis of epistasis in complex traits.

Authors:  Sven Stringer; Eske M Derks; René S Kahn; William G Hill; Naomi R Wray
Journal:  PLoS One       Date:  2013-07-30       Impact factor: 3.240

9.  Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches.

Authors:  Camillo Bérénos; Philip A Ellis; Jill G Pilkington; Josephine M Pemberton
Journal:  Mol Ecol       Date:  2014-06-26       Impact factor: 6.185

10.  Estimates of missing heritability for complex traits in Brown Swiss cattle.

Authors:  Sergio-Iván Román-Ponce; Antonia B Samoré; Marlies A Dolezal; Alessandro Bagnato; Theo H E Meuwissen
Journal:  Genet Sel Evol       Date:  2014-06-04       Impact factor: 4.297

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