Selection Of Genetically Diverse Recombinant Inbreds With An Ordered Gene Evolutionary Algorithm

Abstract

Recombinant inbreds are created by crossing two genetically distinct inbred lines and then inbreeding the resulting progeny multiple times. They are used to estimate associations of genes by co-inheritance of alleles from the two parent inbred types in the recombinant inbreds derived from the cross in a process called genetic mapping. Typically the recombinant inbred lines used in a genetic mapping study are relatively well studied and so they are natural choices for microarray, proteomic, and metabolomic studies. These are quite costly and so typically use fewer individuals than are used in most genetic mapping studies. An evolutionary algorithm for selecting a subset of a collection of recombinant inbred lines with maximum genetic diversity in their mapping characters is described. The evolutionary algorithm is an ordered-gene algorithm with the first k genes in the ordered selection taken to be the subset. Ordered genes are a convenient representation for subset selection. It is found that the problem is not difficult and that in a well mixed mapping population of recombinant inbreds the marginal increase in diversity obtained by evolutionary optimization is small but significant. In order to better understand the problem, synthetic data are also examined and suggest that the problem is easy in general, not only in the specific biological cases used. Recombinant inbreds are created by crossing two genetically distinct inbred lines and then inbreeding the resulting progeny multiple times.