HGM2002 Poster Abstracts: 11. Genome Diversity
POSTER NO: 534
Study of Russian gene pool based on surname frequencies: genetic, dermatoglyphic, and surname data result in similar synthetic maps
1Oleg P. Balanovsky, 2Alexandra P. Buzhilova, 3Natalia A. Dolinova, 4Nikolai N. Abolmasov, 1Dariya S. Subbota, 1Elena V. Balanovska
Surnames are traditionally used in population genetics as analogues of genes when studying the structure of the gene pool. Russian surnames distributions were studied in 58 districts (a total of 33 thousand persons) of 22 regions of the European part of Russia. The 'ONOMA' database containing frequencies of Russian surnames in these and others populations was developed. For each of 75 wide-spread surnames, a computer gene geographic map of its frequency was constructed and synthetic maps of principal components were drawn. The first five of 75 principal components accounted for half of the total variance, which indicates high resolving power of surnames. The map of the first principal component exhibits a trend directed from the north-western to the eastern regions of the area studied. The trend of the second principal component was directed from the southwestern to the northern regions of the area studied, i.e. it was close to latitudinal. This trend almost coincided with the latitudinal trend of principal components for genetic and dermatoglyphical data. Therefore, the latitudinal trend may be considered the main direction of variation of the Russian gene pool. The similarity between the main scenarios for the genetic markers and surnames demonstrates the effectiveness of the use of surnames for analysis of the gene pool. In view of the dispute between R. Sokal and L.L. Cavalli-Sforza about the effects of false correlations, the synthetic maps of Russian surnames were constructed by two methods: through analysis of maps and through direct analysis of original data. An almost complete coincidence of these maps (correlation coefficient p=0.96) indicates that the maps have no errors of the false correlations. This work was supported by RFBR 01-07-90041 and RGNF 01-06-00146 grants.
Other abstracts in same session