A genetic algorithm to investigate genotyping in groups

Abstract

Innovative strategies are required to reduce the cost of DNA testing for both commercial use and research in agricultural species. Previous research has focused on maximising the utility of genotyping by prioritising animals for genotyping according to the whole-herd information gained by that genotyping. This is done under the assumption that animals are genotyped one at a time, with segregation analysis carried out after each genotyping. For logistic reasons, animals may have to be genotyped in groups rather than individually, and the best group of animals chosen will be expected to differ from the same sized group chosen when animals are genotyped singly. A genetic algorithm is used to investigate the problem of group genotypings in individual herds, with the focus on finding patterns in the evolved solutions from which to draw guidelines for group genotyping in practice.