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Multiple trait genetic evaluation of ewe traits in Icelandic sheep
Author(s) -
Árnason T.,
Jónmundsson J.V.
Publication year - 2008
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/j.1439-0388.2008.00734.x
Subject(s) - heritability , restricted maximum likelihood , best linear unbiased prediction , biology , bivariate analysis , genetic correlation , trait , zoology , statistics , veterinary medicine , selection (genetic algorithm) , maximum likelihood , genetic variation , mathematics , genetics , medicine , artificial intelligence , computer science , gene , programming language
Summary The prolificacy of the ewes was measured as the number of lambs born per ewe mated (NLB) when the ewes were 1–4 years of age. The ewe productivity related to the same age interval was measured by special ewe production indices (EPI). The genetic parameters for these traits were estimated by a series of bivariate REML analyses using animal models. The material used for the genetic analysis contained records on 193 213 ewes. The heritability estimates for NLB were h 2 = 0.17, 0.13, 0.11, 0.10 for the four respective age classes. Corresponding estimates for EPI were h 2 = 0.16, 0.17, 0.17, 0.15. The genetic correlations among NLB at different ages ranged from 0.63 to 0.98 and among EPI from 0.82 to 0.99. The genetic correlations between NLB and EPI were generally low. The material used for estimating the breeding values by the MT‐BLUP Animal Model consisted of 1.5 million individuals in the pedigree file. In total 815 782 ewes had records for the NLB and 763 491 ewes had production index (at least 1 year). The records were registered in the years 1990–2006. All possible missing patterns were present in the data. In the iteration process expected values for missing traits were generated and solutions were obtained on canonical transformed scale. The genetic evaluations were run independently for NLB and EPI for computational convenience given the correlations between these traits were negligible.