History, geography and population structure influence the distribution and heritability of blood and anthropometric quantitative traits in nine Sardinian genetic isolates.
Portas L., Murgia F., Biino G., Concas MP., Casula L., Milia S., Whalen MB., Vaccargiu S., Cosso M., Parracciani D., Frongia B., Pirastu M.
Isolated founder populations which exhibit great genetic and environmental homogeneity provide an attractive setting for the study of quantitative traits (QTs). Geneticists have repeatedly turned to population isolates and the past successes have prompted increased interest among medical researchers. We studied nine small isolated villages of a secluded area of Sardinia (Ogliastra), all of them characterized by a few founders, high endogamy rates, slow population expansion and a distinct genetic makeup. Anthropometric and blood parameters, 43 QTs in all, were analysed in about 9000 voluntary subjects for whom extended genealogical information was available. We explored the distribution and examined mean differences of each trait among villages by analysis of variance (ANOVA). A heritability analysis with the variance component (VC) method was performed. Results show significant differences in the distribution of most traits between groups of villages located in two distinct geographical areas already identified by a previous population structure analysis, thus supporting the existence of differentiation among sub-populations in the same region. Heritability estimates range between 30 and 89%, demonstrating that genetic effects substantially contribute to phenotypic variation of all investigated traits and that this population provides excellent research conditions for gene-mapping projects. Results suggest that history, geographic location and population structure may have influenced the genetic and phenotypic features of these isolates. Our findings may be useful for the ongoing linkage and association studies in these isolates and suggest that a thorough characterization of population is valuable to better identify genes or variants that may be rare in the population at large and peculiar to single villages.