Reconstructing Kinship from Genetic Samples

1. CACACACA 5’ Alleles CACACACA #1 CACACACACACA #2 #3 CACACACACACACA Cowbird (Molothrusater) nestling with a song sparrow nestmate Reconstructing Kinship from Genetic Samples Tanya Berger-Wolf and BhaskarDasGupta, Computer Science, UIC; Mary Ashley, Biology, UIC; WanprachaChaovalitwongse, Industrial Engineering, Rutgers Microsatellites • Falcons and other birds of prey are extremely secretive about their lives. Sharks are hard to catch in the open ocean. Cowbirds leave eggs in other birds’ nests and let them raise the cowbird chicks. One of the things common to all these species is that it is difficult to study their mating system. It is even difficult to identify which animals are siblings. Yet, this simple fact is necessary for conservation, animal management, and understanding of evolutionary mechanisms. • New technologies for collecting genotypic data from natural populations open the possibilities of investigating many fundamental biological phenomena. Yet full utilization of the genotypic data is only possible if statistical and computational approaches keep pace with our ability to sample organisms and obtain their genotypes. • Our goal is to develop robust computational methods for reconstructing kinship relationships from microsatellite data. Genotypes Reconstruct 1/1 2/2 1/2 1/3 2/3 3/3 Young Lemon sharks (Negaprionbrevirostris) during sampling in Bimini, Bahamas • Use Mendelianconstraintsto form potential feasible family groups • Use the combinatorial optimization of the covering problem with various parsimony objectives to find the best sets of family groups containing all individuals. Typically there is more than one optimal or near optimal solution. • Use consensus techniques to combine solutions that are optimal, coming from different methods, or resulting from perturbations allowing for errors in data into one robust error-tolerant solution. • All resulting optimization problems are NP-hard and provably hard to approximate. We use commercial optimization package CPLEX to find optimal solutions. • http://kinalyzer.cs.uic.edu • The following methods are or becoming available as a web-based service: • Reconstruction of sibling groups + error identification • Reconstruction of parental genotype • Reconstruction of half-sibling relationships • Future: • Incorporation of partial information • Multi generation pedigree reconstruction • Non-diploid species