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Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response

Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on...

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Autor principal: Oh, S.-H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4092951/
https://www.ncbi.nlm.nih.gov/pubmed/25049566
http://dx.doi.org/10.5713/ajas.2011.11315
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author Oh, S.-H.
author_facet Oh, S.-H.
author_sort Oh, S.-H.
collection PubMed
description Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ( [Formula: see text]) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, [Formula: see text]. iv) Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.
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spelling pubmed-40929512014-07-21 Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response Oh, S.-H. Asian-Australas J Anim Sci Article Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ( [Formula: see text]) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, [Formula: see text]. iv) Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs. Asian-Australasian Association of Animal Production Societies (AAAP) and Korean Society of Animal Science and Technology (KSAST) 2012-03 /pmc/articles/PMC4092951/ /pubmed/25049566 http://dx.doi.org/10.5713/ajas.2011.11315 Text en Copyright © 2012 by Asian-Australasian Journal of Animal Sciences This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License http://creativecommons.org/licenses/by-nc/3.0/ which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Oh, S.-H.
Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response
title Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response
title_full Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response
title_fullStr Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response
title_full_unstemmed Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response
title_short Evaluation of Optimum Genetic Contribution Theory to Control Inbreeding While Maximizing Genetic Response
title_sort evaluation of optimum genetic contribution theory to control inbreeding while maximizing genetic response
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4092951/
https://www.ncbi.nlm.nih.gov/pubmed/25049566
http://dx.doi.org/10.5713/ajas.2011.11315
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