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Effect of manipulating recombination rates on response to selection in livestock breeding programs
BACKGROUND: In this work, we performed simulations to explore the potential of manipulating recombination rates to increase response to selection in livestock breeding programs. METHODS: We carried out ten replicates of several scenarios that followed a common overall structure but differed in the a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4917950/ https://www.ncbi.nlm.nih.gov/pubmed/27335010 http://dx.doi.org/10.1186/s12711-016-0221-1 |
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author | Battagin, Mara Gorjanc, Gregor Faux, Anne-Michelle Johnston, Susan E. Hickey, John M. |
author_facet | Battagin, Mara Gorjanc, Gregor Faux, Anne-Michelle Johnston, Susan E. Hickey, John M. |
author_sort | Battagin, Mara |
collection | PubMed |
description | BACKGROUND: In this work, we performed simulations to explore the potential of manipulating recombination rates to increase response to selection in livestock breeding programs. METHODS: We carried out ten replicates of several scenarios that followed a common overall structure but differed in the average rate of recombination along the genome (expressed as the length of a chromosome in Morgan), the genetic architecture of the trait under selection, and the selection intensity under truncation selection (expressed as the proportion of males selected). Recombination rates were defined by simulating nine different chromosome lengths: 0.10, 0.25, 0.50, 1, 2, 5, 10, 15 and 20 Morgan, respectively. One Morgan was considered to be the typical chromosome length for current livestock species. The genetic architecture was defined by the number of quantitative trait variants (QTV) that affected the trait under selection. Either a large (10,000) or a small (1000 or 500) number of QTV was simulated. Finally, the proportions of males selected under truncation selection as sires for the next generation were equal to 1.2, 2.4, 5, or 10 %. RESULTS: Increasing recombination rate increased the overall response to selection and decreased the loss of genetic variance. The difference in cumulative response between low and high recombination rates increased over generations. At low recombination rates, cumulative response to selection tended to asymptote sooner and the genetic variance was completely eroded. If the trait under selection was affected by few QTV, differences between low and high recombination rates still existed, but the selection limit was reached at all rates of recombination. CONCLUSIONS: Higher recombination rates can enhance the efficiency of breeding programs to turn genetic variation into response to selection. However, to increase response to selection significantly, the recombination rate would need to be increased 10- or 20-fold. The biological feasibility and consequences of such large increases in recombination rates are unknown. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-016-0221-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4917950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49179502016-06-24 Effect of manipulating recombination rates on response to selection in livestock breeding programs Battagin, Mara Gorjanc, Gregor Faux, Anne-Michelle Johnston, Susan E. Hickey, John M. Genet Sel Evol Research Article BACKGROUND: In this work, we performed simulations to explore the potential of manipulating recombination rates to increase response to selection in livestock breeding programs. METHODS: We carried out ten replicates of several scenarios that followed a common overall structure but differed in the average rate of recombination along the genome (expressed as the length of a chromosome in Morgan), the genetic architecture of the trait under selection, and the selection intensity under truncation selection (expressed as the proportion of males selected). Recombination rates were defined by simulating nine different chromosome lengths: 0.10, 0.25, 0.50, 1, 2, 5, 10, 15 and 20 Morgan, respectively. One Morgan was considered to be the typical chromosome length for current livestock species. The genetic architecture was defined by the number of quantitative trait variants (QTV) that affected the trait under selection. Either a large (10,000) or a small (1000 or 500) number of QTV was simulated. Finally, the proportions of males selected under truncation selection as sires for the next generation were equal to 1.2, 2.4, 5, or 10 %. RESULTS: Increasing recombination rate increased the overall response to selection and decreased the loss of genetic variance. The difference in cumulative response between low and high recombination rates increased over generations. At low recombination rates, cumulative response to selection tended to asymptote sooner and the genetic variance was completely eroded. If the trait under selection was affected by few QTV, differences between low and high recombination rates still existed, but the selection limit was reached at all rates of recombination. CONCLUSIONS: Higher recombination rates can enhance the efficiency of breeding programs to turn genetic variation into response to selection. However, to increase response to selection significantly, the recombination rate would need to be increased 10- or 20-fold. The biological feasibility and consequences of such large increases in recombination rates are unknown. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-016-0221-1) contains supplementary material, which is available to authorized users. BioMed Central 2016-06-22 /pmc/articles/PMC4917950/ /pubmed/27335010 http://dx.doi.org/10.1186/s12711-016-0221-1 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Battagin, Mara Gorjanc, Gregor Faux, Anne-Michelle Johnston, Susan E. Hickey, John M. Effect of manipulating recombination rates on response to selection in livestock breeding programs |
title | Effect of manipulating recombination rates on response to selection in livestock breeding programs |
title_full | Effect of manipulating recombination rates on response to selection in livestock breeding programs |
title_fullStr | Effect of manipulating recombination rates on response to selection in livestock breeding programs |
title_full_unstemmed | Effect of manipulating recombination rates on response to selection in livestock breeding programs |
title_short | Effect of manipulating recombination rates on response to selection in livestock breeding programs |
title_sort | effect of manipulating recombination rates on response to selection in livestock breeding programs |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4917950/ https://www.ncbi.nlm.nih.gov/pubmed/27335010 http://dx.doi.org/10.1186/s12711-016-0221-1 |
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