A simple visualization method to reconstruct nest-mate patterns among bumble bees(Hymenoptera: Apidae)using genetic data

概要

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We propose a simple visualization method, Shared Loci Correspondence Analysis (SLCA), to reconstruct nest-mate patterns of bumble bees with co-dominant genetic marker data. The method begins with a similarity matrix based on pairwise comparison of allele-sharing patterns among individuals, which is then sorted using correspondence analysis. The resulting matrix represents visually estimated sibling groups along its diagonal. This method can be applied to all haplodiploid species to estimate full siblingship. In particular, SLCA does not require the estimation of allele frequency in a population. It is difficult to conduct large-scale sampling when studying wild populations, and hence we cannot accurately estimate allele frequency. Therefore, SLCA would solve various problems in estimating social structure, mating behavior, and the dispersal range of wild insect populations, for which the collection of large amounts of data is prohibitive. To illustrate our algorithm, we used two types of actual microsatellite data collected from wild populations of Bombus ardens and Bombus diversus. The result of the data sets shows that SLCA can accurately cluster nest mates.
日本応用動物昆虫学会の論文
2007-02-25