The 81st Annual Meeting of the American Association of Physical Anthropologists (2012)


An examination of the agreement between genetic and dental reconstructions of biological distance among regional populations

AMELIA R. HUBBARD1, DEBBIE GUATELLI-STEINBERG1, PAUL W. SCIULLI1 and PAUL A. FUERST2.

1Anthropology, The Ohio State University, 2Evolution, Ecology, and Organismal Biology, The Ohio State University

Friday 11:15-11:30, Parlors Add to calendar

This study examines the agreement among estimates of biological distance (biodistance) using microsatellite genotype and non-metric dental trait data from four coastal Kenyan populations. The major premise of biodistance analysis is that variation in visible, phenotypic traits reflects genetic variability in human populations. Therefore, the goals of the project are to determine whether non-metric dental characters and genetic data provide comparable reconstructions of biodistance and, if not, whether there are certain conditions under which these datasets can produce similar results. This study approaches these questions using genetic and dental materials from the same individuals and examines populations within a restricted regional context, which is commonly the focus of archaeological investigations.

Thirty-three non-metric dental traits were scored from dental casts and fifty microsatellite loci were genotyped from saliva samples from 350 individuals. Biodistance matrices were constructed using a variety of statistics commonly used with dental (e.g., Mean Measure of Divergence) and microsatellite (e.g., Delta Mu) data. The general expectation was that genetic and dental reconstructions would agree.

Initial reconstructions found a weak and non-significant correlation between genetic distance matrices (based on microsatellite data) and biodistance matrices (based on dental data). In general, genetic distances followed expectations based on known population history, while dental-based distances did not. Interestingly, when older statistical measures were used (Sanghvi's distance), dental-based distances improved. As such, this presentation will review the suitability of available methods, models, and statistics used to assess variation in genetic and non-metric dental characters, including the potential applications of population structure analysis.

This study was funded by the U.S. Department of Education through a Fulbright-Hays Doctoral Dissertation Research Abroad Grant (P022A090029), a Wenner-Gren Foundation Dissertation Improvement Grant (7962), and the Ohio State University Graduate School.

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