Literature DB >> 18096114

Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance.

Han A Mulder1, Piter Bijma, William G Hill.   

Abstract

In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters, breeding goal, number of progeny per sire and breeding scheme on selection responses in mean and variance when applying index selection. Genetic parameters were obtained from the literature. Economic values for the mean and variance were derived for some standard non-linear profit equations, e.g. for traits with an intermediate optimum. The economic value of variance was in most situations negative, indicating that selection for reduced variance increases profit. Predicted responses in residual variance after one generation of selection were large, in some cases when the number of progeny per sire was at least 50, by more than 10% of the current residual variance. Progeny testing schemes were more efficient than sib-testing schemes in decreasing residual variance. With optimum traits, selection pressure shifts gradually from the mean to the variance when approaching the optimum. Genetic improvement of uniformity is particularly interesting for traits where the current population mean is near an intermediate optimum.

Mesh:

Year:  2007        PMID: 18096114      PMCID: PMC2674918          DOI: 10.1186/1297-9686-40-1-37

Source DB:  PubMed          Journal:  Genet Sel Evol        ISSN: 0999-193X            Impact factor:   4.297


  28 in total

1.  Genetic Control of Environmental Variation of Two Quantitative Traits of Drosophila melanogaster Revealed by Whole-Genome Sequencing.

Authors:  Peter Sørensen; Gustavo de los Campos; Fabio Morgante; Trudy F C Mackay; Daniel Sorensen
Journal:  Genetics       Date:  2015-08-12       Impact factor: 4.562

2.  Selection for environmental variation: a statistical analysis and power calculations to detect response.

Authors:  Noelia Ibáñez-Escriche; Daniel Sorensen; Rasmus Waagepetersen; Agustín Blasco
Journal:  Genetics       Date:  2008-10-01       Impact factor: 4.562

3.  Heritable environmental variance causes nonlinear relationships between traits: application to birth weight and stillbirth of pigs.

Authors:  Herman A Mulder; William G Hill; Egbert F Knol
Journal:  Genetics       Date:  2015-01-27       Impact factor: 4.562

4.  Derivation of economic values for production traits in aquaculture species.

Authors:  Kasper Janssen; Paul Berentsen; Mathieu Besson; Hans Komen
Journal:  Genet Sel Evol       Date:  2017-01-05       Impact factor: 4.297

5.  Effects of genetics and early-life mild hypoxia on size variation in farmed gilthead sea bream (Sparus aurata).

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Journal:  Fish Physiol Biochem       Date:  2020-11-13       Impact factor: 2.794

Review 6.  Genetic aspects of piglet survival and related traits: a review.

Authors:  Egbert F Knol; Dianne van der Spek; Louisa J Zak
Journal:  J Anim Sci       Date:  2022-06-01       Impact factor: 3.338

7.  Detecting major genetic loci controlling phenotypic variability in experimental crosses.

Authors:  Lars Rönnegård; William Valdar
Journal:  Genetics       Date:  2011-04-05       Impact factor: 4.562

8.  Genetics of microenvironmental sensitivity of body weight in rainbow trout (Oncorhynchus mykiss) selected for improved growth.

Authors:  Matti Janhunen; Antti Kause; Harri Vehviläinen; Otso Järvisalo
Journal:  PLoS One       Date:  2012-06-11       Impact factor: 3.240

Review 9.  Understanding the unexplained: The magnitude and correlates of individual differences in residual variance.

Authors:  David J Mitchell; Christa Beckmann; Peter A Biro
Journal:  Ecol Evol       Date:  2021-05-03       Impact factor: 2.912

10.  Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle.

Authors:  Camila U Braz; Troy N Rowan; Robert D Schnabel; Jared E Decker
Journal:  Sci Rep       Date:  2021-06-25       Impact factor: 4.379

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