title: Ant colony optimization as a method for strategic genotype sampling.
abstract: A simulation study was carried out to develop an alternative method of selecting animals to be genotyped. Simulated pedigrees included 5000 animals, each assigned genotypes for a bi-allelic single nucleotide polymorphism (SNP) based on assumed allelic frequencies of 0.7/0.3 and 0.5/0.5. In addition to simulated pedigrees, two beef cattle pedigrees, one from field data and the other from a research population, were used to test selected methods using simulated genotypes. The proposed method of ant colony optimization (ACO) was evaluated based on the number of alleles correctly assigned to ungenotyped animals (AK(P)), the probability of assigning true alleles (AK(G)) and the probability of correctly assigning genotypes (APTG). The proposed animal selection method of ant colony optimization was compared to selection using the diagonal elements of the inverse of the relationship matrix (A(-1)). Comparisons of these two methods showed that ACO yielded an increase in AK(P) ranging from 4.98% to 5.16% and an increase in APTG from 1.6% to 1.8% using simulated pedigrees. Gains in field data and research pedigrees were slightly lower. These results suggest that ACO can provide a better genotyping strategy, when compared to A(-1), with different pedigree sizes and structures.
authors.affiliation: Animal and Dairy Science Department, University of Georgia, Athens, GA 30602-2771, USA.
authors.forename: M L
authors.initials: ML
authors.lastname: Spangler
authors.forename: K R
authors.initials: KR
authors.lastname: Robbins
authors.forename: J K
authors.initials: JK
authors.lastname: Bertrand
authors.forename: M
authors.initials: M
authors.lastname: Macneil
authors.forename: R
authors.initials: R
authors.lastname: Rekaya
mesh_terms: D000465:Algorithms; D000818:Animals; D002417:Cattle; D003198:Computer Simulation; D005260:Female; D005838:Genotype; D008297:Male; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D018401:Sample Size