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Title: VALIDATION OF A GENETIC ALOGORITHM FOR IDENTIFICATION OF LIVESTOCK FOR GERMPLASM PRESERVATION

Author
item MELTON, L - UNIVERSITY OF MISSOURI
item LAMBERSON, P - COLUMBIA UNIVERSITY
item BRENNEMAN, R - OMAHA'S DOORLY ZOO
item Chase, Chadwick - Chad
item LAMBERSON, W - UNIVERSITY OF MISSOURI

Submitted to: Journal of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: 9/18/2003
Publication Date: 10/1/2003
Citation: Melton, L.L., Lamberson, P.J., Brenneman, R.A., Chase, C.C., Lamberson, W.R. 2003. Validation of a genetic alogorithm for identification of livestock for germplasm preservation. Journal of Animal Science Vol. 81 (Suppl.2)p 39.

Interpretive Summary:

Technical Abstract: As livestock production intensifies, a loss of genetic diversity has been observed because of increased use of a few breeds to the exclusion of many others. To preserve diversity the USDA has initiated a program of germplasm preservation through freezing semen. An algorithm to identify least-related animals using pedigree relationships has been developed. Preliminary testing of the algorithm showed that mean relationships between selected animals increased as the proportion of animals preselected increased. In order to test the efficacy of the alogorithm in maintaining genetic diversity, data from a pedigreed population of Romosinuano cattle genotyped for 28 microsatellite markers was evaluated. The proportion of total alleles in the population that were maintained in the samples identified for preservation was calculated and comparisons made among methods of identification. An index calculated by summing the inverse of frequencies of all alleles for each individual was determined and animals were ranked on the index. When initiated with a single random seed and 25% of the population was identified by the algorithm for selection, 85% of the alleles in the population were captured in the selection sample. When 40% of the population was selected, the proportion of alleles captured increased to 89%. However, when identifying 25% and the single seed used to initiate the algorithm was the highest indexing animal, 88% of the alleles in the population were captured. When identifying 40% and the single seed used to initiate the algorithm was the highest indexing animal, 93% of the alleles in the population were captured. Additional testing is needed to establish how the algorithm performs with multiple seeds. The algorithm has been used to evaluate the Hereford Swine Association Registry to identify boars for germplasm preservation.