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Abstract / Description of output
Summary: AlphaMate is a flexible program that optimises 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 optimisation 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 optimisation 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 optimisation 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: Executable versions of AlphaMate for Windows, Mac, and Linux platforms are available at http://www.AlphaGenes.roslin.ed.ac.uk/AlphaMate.
Contact: [email protected].
Availability: Executable versions of AlphaMate for Windows, Mac, and Linux platforms are available at http://www.AlphaGenes.roslin.ed.ac.uk/AlphaMate.
Contact: [email protected].
Original language | English |
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Pages (from-to) | 3408-3411 |
Journal | Bioinformatics |
Volume | 34 |
Issue number | 19 |
Early online date | 2 May 2018 |
DOIs | |
Publication status | Published - 1 Oct 2018 |
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Developing next generation genetic improvement tools from next generation sequencing
Hickey, J.
16/06/15 → 15/06/18
Project: Research