Estimating pairwise relatedness between individuals with different levels of ploidy.

Abstract

Estimates of relatedness coefficients, based on genetic marker data, are often necessary for studies of genetics and ecology. Whilst many estimates based on method-of-moment or maximum-likelihood methods exist for diploid organisms, no such estimators exist for organisms with multiple ploidy levels, which occur in some insect and plant species. Here, we extend five estimators to account for different levels of ploidy: one relatedness coefficient estimator, three coefficients of coancestry estimators and one maximum-likelihood estimator. We use arrhenotoky (when unfertilized eggs develop into haploid males) as an example in evaluations of estimator performance by Monte Carlo simulation. Also, three virtual sex-determination systems are simulated to evaluate their performances for higher levels of ploidy. Additionally, we used two real data sets to test the robustness of these estimators under actual conditions. We make available a software package, PolyRelatedness, for other researchers to apply to organisms that have various levels of ploidy.