Multipoint estimation of genetic maps for human trisomies with one parent or other partial data.

Abstract

Centromeric-mapping methods have been used to investigate the association between altered recombination and meiotic nondisjunction in humans. For trisomies, current methods are based on the genotypes from a trisomic offspring and both parents. Because it is sometimes difficult to obtain samples from both parents and because the ability to use sources of DNA previously not available (e.g., stored paraffin-embedded pathological samples) has increased, we have been interested in creating similar maps for trisomic populations in which one of the parents of the trisomic individual is unavailable for genotyping. In this paper, we derive multipoint likelihoods for both missing-parent data and conventional two-parent data. We find that likelihoods for two-parent data and for data generated without a sample from the correctly disjoining parent can be maximized in exactly the same way but also that missing-parent data has a high frequency of partial data of the same sort produced by intercross matings. Previously published centromeric-mapping methods use incorrect likelihoods for intercross matings and thus can perform poorly on missing-parent data. We wrote a FORTRAN program to maximize our multipoint likelihoods and used it in simulation studies to demonstrate the biases in the previous methods.