Literature DB >> 20494185

Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information.

K L Verbyla1, M P L Calus, H A Mulder, Y de Haas, R F Veerkamp.   

Abstract

The objective of this study was to investigate the genetic basis of energy balance (EB) and the potential use of genomic selection to enable EB to be incorporated into selection programs. Energy balance provides an essential link between production and nonproduction traits because both depend on a common source of energy. A small number (527) of Dutch Holstein-Friesian heifers with phenotypes for EB were genotyped. Direct genomic values were predicted for these heifers using a model that included the genotypic information. A polygenic model was also applied to predict estimated breeding values using only pedigree information. A 10-fold cross-validation approach was employed to assess the accuracies of the 2 sets of predicted breeding values by correlating them with phenotypes. Because of the small number of phenotypes, accuracies were relatively low (0.29 for the direct genomic values and 0.21 for the estimated breeding values), where the maximum possible accuracy was the square root of heritability (0.57). Despite this, the genomic model produced breeding values with reliability double that of the breeding values produced by the polygenic model. To increase the accuracy of the genomic breeding values and make it possible to select for EB, measurement and recording of EB would need to improve. The study suggests that it may be possible to select for minimally recorded traits; for instance, those measured on experimental farms, using genomic selection. Overall, the study demonstrated that genomic selection could be used to select for EB, confirming its genetic background. 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20494185     DOI: 10.3168/jds.2009-2928

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  5 in total

1.  The effect of linkage disequilibrium and family relationships on the reliability of genomic prediction.

Authors:  Yvonne C J Wientjes; Roel F Veerkamp; Mario P L Calus
Journal:  Genetics       Date:  2012-12-24       Impact factor: 4.562

2.  Identification of Mendelian inconsistencies between SNP and pedigree information of sibs.

Authors:  Mario P L Calus; Han A Mulder; John W M Bastiaansen
Journal:  Genet Sel Evol       Date:  2011-10-11       Impact factor: 4.297

3.  Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.).

Authors:  M F R Resende; P Muñoz; M D V Resende; D J Garrick; R L Fernando; J M Davis; E J Jokela; T A Martin; G F Peter; M Kirst
Journal:  Genetics       Date:  2012-01-23       Impact factor: 4.562

4.  Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency.

Authors:  Sunduimijid Bolormaa; Iona M MacLeod; Majid Khansefid; Leah C Marett; William J Wales; Filippo Miglior; Christine F Baes; Flavio S Schenkel; Erin E Connor; Coralia I V Manzanilla-Pech; Paul Stothard; Emily Herman; Gert J Nieuwhof; Michael E Goddard; Jennie E Pryce
Journal:  Genet Sel Evol       Date:  2022-09-06       Impact factor: 5.100

5.  Increasing selection gain and accuracy of harvest prediction models in Jatropha through genome-wide selection.

Authors:  Adriano Dos Santos; Erina Vitório Rodrigues; Bruno Galvêas Laviola; Larissa Pereira Ribeiro Teodoro; Paulo Eduardo Teodoro; Leonardo Lopes Bhering
Journal:  Sci Rep       Date:  2021-06-30       Impact factor: 4.379

  5 in total

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