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Interplay between heritability, genetic correlation and economic weighting in a selection index with and without genomic information
Author(s) -
Haberland A.M.,
Pimentel E.C.G.,
Ytournel F.,
Erbe M.,
Simianer H.
Publication year - 2013
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/jbg.12051
Subject(s) - heritability , trait , index (typography) , weighting , selection (genetic algorithm) , statistics , biology , genetic correlation , population , quantitative trait locus , correlation , genomic information , genetics , mathematics , genetic variation , demography , computer science , gene , genome , medicine , geometry , radiology , artificial intelligence , sociology , world wide web , programming language
Summary The availability of genomic information demands proper evaluation on how the kind (phenotypic versus genomic) and the amount of information influences the interplay of heritability ( h 2 ), genetic correlation (rG iG j) and economic weighting of traits with regard to the standard deviation of the index ( σ I ). As σ I is directly proportional to response to selection, it was the chosen parameter for comparing the indices. Three selection indices incorporating conventional and genomic information for a two trait ( i and j ) breeding goal were compared. Information sources were chosen corresponding to pig breeding applications. Index I incorporating an own performance in trait j served as reference scenario. In index II , additional information in both traits was contributed by a varying number of full‐sibs (2, 7, 50). In index III , the conventional own performance in trait j was combined with genomic information for both traits. The number of animals in the reference population ( N P = 1000, 5000, 10 000) and thus the accuracy of GBV s were varied. With more information included in the index, σ I became more independent ofrG iG j,h j2and relative economic weighting. This applied for index II (more full‐sibs) and for index III (more accurate GBV s). Standard deviations of index II with seven full‐sibs and index III with N P = 1000 were similar when both traits had the same heritability. If the heritability of trait j was reduced (h j2 = 0.1), σ I of index III with N P = 1000 was clearly higher than for index II with seven full‐sibs. When enhancing the relative economic weight of trait j , the decrease in σ I of the conventional full‐sib index was much stronger than for index III . Our results imply that N P = 1000 can be considered a minimum size for a reference population in pig breeding. These conclusions also hold for comparing the accuracies of the indices.