Plant & Animal Genomes XI Conference

January 11-15, 2003
Town & Country Convention Center
San Diego, CA

Workshop: Cattle/Sheep
            

GENOPROB: COMPUTATION OF GENOTYPE AND GRANDPARENTAL ORIGIN PROBABILITIES IN COMPLEX PEDIGREES WITH MISSING MARKER DATA.

U.S. Meat Animal Research Center, USDA-ARS, P.O. Box 166, Clay Center, NE 68933

GenoProb is a computer program that analyzes genetic marker data in complex pedigrees with missing marker data using an iterative allelic peeling algorithm. The algorithm is approximate in pedigrees that contain loops, but the degree of approximation may be minimal in many of them, such as those in which sires’ genotypes are unambiguous. GenoProb’s output has been used for QTL detection, marker assisted selection, and identification and correction of errors in marker data and pedigrees. It computes the approximate genotypic distribution of marker loci using an incomplete penetrance model to account for the possibility of scoring errors in marker data and computes the probabilities of scoring errors. It handles microsatellite, SNP, and other types of genetic markers and accounts for recessive alleles such as unamplified microsatellite alleles. GenoProb computes approximate grandparental origin probabilities (marginal probabilities of segregation indicators), which can be used in QTL analyses. A multilocus extension to GenoProb is under development. A method to use probabilities computed by GenoProb in a random QTL effects analysis for arbitrary pedigrees is also under development. Computational requirements are proportional to the numbers of individuals, loci, and possible genotypes per locus and are minimally influenced by the percentage of missing marker data. Analysis of 3959 individuals in a complex pedigree with 21 microsatellite loci on BTA7 with 69% missing marker data required 6.7 min on a 1.7 GHz Pentium 4. GenoProb is available at no cost and runs on Windows operating systems.