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AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs
SUMMARY: AlphaMate is a flexible program that optimizes selection, maintenance of genetic diversity and mate allocation in breeding programs. It can be used in animal and cross- and self-pollinating plant populations. These populations can be subject to selective breeding or conservation management....
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157072/ https://www.ncbi.nlm.nih.gov/pubmed/29722792 http://dx.doi.org/10.1093/bioinformatics/bty375 |
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author | Gorjanc, Gregor Hickey, John M |
author_facet | Gorjanc, Gregor Hickey, John M |
author_sort | Gorjanc, Gregor |
collection | PubMed |
description | SUMMARY: AlphaMate is a flexible program that optimizes selection, maintenance of genetic diversity and mate allocation in breeding programs. It can be used in animal and cross- and self-pollinating plant populations. These populations can be subject to selective breeding or conservation management. The problem is formulated as a multi-objective optimization of a valid mating plan that is solved with an evolutionary algorithm. A valid mating plan is defined by a combination of mating constraints (the number of matings, the maximal number of parents, the minimal/equal/maximal number of contributions per parent, or allowance for selfing) that are gender specific or generic. The optimization can maximize genetic gain, minimize group coancestry, minimize inbreeding of individual matings, or maximize genetic gain for a given increase in group coancestry or inbreeding. Users provide a list of candidate individuals with associated gender and selection criteria information (if applicable) and coancestry matrix. Selection criteria and coancestry matrix can be based on pedigree or genome-wide markers. Additional individual or mating specific information can be included to enrich optimization objectives. An example of rapid recurrent genomic selection in wheat demonstrates how AlphaMate can double the efficiency of converting genetic diversity into genetic gain compared to truncation selection. Another example demonstrates the use of genome editing to expand the gain-diversity frontier. AVAILABILITY AND IMPLEMENTATION: Executable versions of AlphaMate for Windows, Mac and Linux platforms are available at http://www.AlphaGenes.roslin.ed.ac.uk/AlphaMate. |
format | Online Article Text |
id | pubmed-6157072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61570722018-10-01 AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs Gorjanc, Gregor Hickey, John M Bioinformatics Applications Notes SUMMARY: AlphaMate is a flexible program that optimizes selection, maintenance of genetic diversity and mate allocation in breeding programs. It can be used in animal and cross- and self-pollinating plant populations. These populations can be subject to selective breeding or conservation management. The problem is formulated as a multi-objective optimization of a valid mating plan that is solved with an evolutionary algorithm. A valid mating plan is defined by a combination of mating constraints (the number of matings, the maximal number of parents, the minimal/equal/maximal number of contributions per parent, or allowance for selfing) that are gender specific or generic. The optimization can maximize genetic gain, minimize group coancestry, minimize inbreeding of individual matings, or maximize genetic gain for a given increase in group coancestry or inbreeding. Users provide a list of candidate individuals with associated gender and selection criteria information (if applicable) and coancestry matrix. Selection criteria and coancestry matrix can be based on pedigree or genome-wide markers. Additional individual or mating specific information can be included to enrich optimization objectives. An example of rapid recurrent genomic selection in wheat demonstrates how AlphaMate can double the efficiency of converting genetic diversity into genetic gain compared to truncation selection. Another example demonstrates the use of genome editing to expand the gain-diversity frontier. AVAILABILITY AND IMPLEMENTATION: Executable versions of AlphaMate for Windows, Mac and Linux platforms are available at http://www.AlphaGenes.roslin.ed.ac.uk/AlphaMate. Oxford University Press 2018-10-01 2018-05-02 /pmc/articles/PMC6157072/ /pubmed/29722792 http://dx.doi.org/10.1093/bioinformatics/bty375 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Gorjanc, Gregor Hickey, John M AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
title | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
title_full | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
title_fullStr | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
title_full_unstemmed | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
title_short | AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
title_sort | alphamate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157072/ https://www.ncbi.nlm.nih.gov/pubmed/29722792 http://dx.doi.org/10.1093/bioinformatics/bty375 |
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