Gene geography of human population: computer-generated regional genogeographic atlas

Gene geography is considered in this work as the instrument for analysis of population's gene pool. To be effective in this analysis, gene geography should move from mapping of gene frequencies for each gene (and phenes) to construction of genogeographical atlas, as a collection of maps generated by computer, following some strongly defined principles and methods, and joined together, according to general task and the programme of investigation. Brief version of regional genogeographical atlas of Mongolians and the other peoples of Central Asia is presented in the article. This atlas includes computer-generated maps of AB0, Hp, Gc, G'3, Tf, GLO, EstD and PGM1 gene frequencies as well as computer-generalized maps of Mongolian gene pool.     

Ethnic genetics: ethnogeographic diversity of the gene pool of human populations around the world]

The study was undertaken to estimate a degree of genetic differentiation in human all-world population at the ethnic level of its structure. The genetic information for this work came from well-known A. Mourant's et al. world-wide survey on human genetic polymorphisms and from regional survey on the same polymorphisms of the USSR peoples. The data were grouped into 9 regional populations studied for 49 alleles and haplotypes belonging to 20 polymorphic loci. Average genetic distances from the all-world human gene pool to each of regional one, and from these to gene pools of ethnic groups within regions were estimated and compared. An unexpected result of this within-between-region comparative analysis is the shortest genetic distance between gene pools of the USSR peoples as a whole on the one hand, and all-world peoples on the other. At the same time, a considerable part of the total human genetic polymorphism is persisted in the USSR region.     

Population-genetic structure of Chuvashia (from data on eight DNA loci in the nuclear genome)

Population-genetic study of indigenous populations representing three ethnic Chuvash group: highland (Cheboksarsk and Morgaush district), lowland (Kanash district) and mid-lowland (Marposad district). Eight polymorphic DNA loci of the nuclear genome (VNTR/PAH, STR/PAH, VNTR/ApoB, VNTR/DAT1, APF, VNTR/eNOS, IVS6aGATT, and KM.19/PstI) were examined in the population of each district. For each of the four population, we estimated the allele and genotype frequency distributions at each polymorphic system, heterozygosities HS and between-population differences FST. In the combined Chuvash sample, HS = 0.464 and FST = 0.006. Loci VNTR(DAT) and VNTR(ApoB) showed highest between-population differentiation (0.009 < or = FST < or = 0.012), and loci IVS6aGATT, APF, VNTR/eNOS, and D7S23 (KM.19), lowest differentiation (0.001 < or = FST < or = 0.003). Analysis of genetic distances revealed somewhat higher genetic similarity between the Cheboksarsk and Morgaush populations belonging to the highland Chuvash group, whereas the highland Chuvash population from the Marposad district, which belong to the mid-lowland group, was more distant from the former populations.     

The gene pool of the Belgorod oblast population: II. "Family name portraits" in groups of districts with different degrees of subdivision and the role of migrations in their formation

The frequencies and spectra of surnames have been analyzed in groups of raions (districts) of the Belgorod oblast (region) with different degrees of population subdivision. The "family name portraits" of districts with low (0.00003 less sign f* < 0.00022, f*(r) = 0.00015) and moderate (0.00023 < f*(r) < 0.00042, f*(r) = 0.00029) inbreeding levels are similar both to each other and to the "family name portrait" of the Belgorod oblast as a whole. Districts with high subdivision levels (0.00043 < f*(r) < 0.00125, f*(r) = 0.00072) had very distinctive surname spectra and the highest surname frequencies. Intense immigration to the Belgorod oblast significantly affects its population genetic structure, decreasing the population subdivision.     

Russian genofond. Genogeography of surnames

Surnames are traditionally used in population genetics as "quasi-genetic" markers (i.e., analogs of genes) when studying the structure of the gene pool and the factors of its microevolution. In this study, spatial variation of Russian surnames was analyzed with the use of computer-based gene geography. Gene geography of surnames was demonstrated to be promising for population studies on the total Russian gene pool. Frequencies of surnames were studied in 64 sel'sovets (rural communities; a total of 33 thousand persons) of 52 raions (districts) of 22 oblasts (regions) of the European part of Russia. For each of 75 widespread surnames, an electronic map of its frequency was constructed. Summary maps of principal components were drawn based on all maps of individual surnames. The first 5 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 northwestern to the eastern regions of the area studied. The trend of the second 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 three sets of data (genetic, anthropological, and dermatoglyphical). 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 and quasi-genetic markers demonstrates the effectiveness of the use of surnames for analysis of the Russian gene pool. In view of the dispute between R. Sokal and L.L. Cavalli-Sforza about the effects of false correlations, the maps of principal components of Russian surnames were constructed by two methods: through analysis of maps and through direct analysis of original data on the frequencies of surnames. An almost complete coincidence of these maps (correlation coefficient rho = 0.96) indicates that, taking into account the reliability of the data, the resultant maps of principal components have no errors of false correlations.     

The gene pool of Belgorod oblast population: the distribution of immunological and biochemical gene markers

The frequencies of 33 alleles of 12 loci of immunological and biochemical gene markers (ABO, RH, HP, GC, TF, PI, C'3, ACP1, GLO1, PGM1, ESD, and 6-PGD) have been estimated in the indigenous Russian and Ukrainian populations of Belgorod oblast. Differences of the Belgorod population from other populations of Russia with respect to the genetic structure have been determined. It has been found that the frequency distributions of all alleles studied in the Belgorod population are similar to those typical of the genetic structure of Caucasoid populations.     

Ethnogenetics: adaptive structure of the gene pool of the mankind from the data on human polymorphic genetic markers

The mean FST value as a characteristic of gene frequency changes in a random sample of polymorphic genes from population gene pool provides the best indirect estimation of selectively neutral level of genetic variability. The set of test criteria, including chi 2, F and t, can be used in order to compare F1 with F and subdivide gene sample into three subgroups, or classes of genes which are differing from each other by the degree of variation of allelic frequencies. These three classes comprise the adaptive structure of gene pool and consist of the genes which are, respectively, under stabilizing and differentiating selection pressures or neutral ones. Adaptive structures of gene pools of aboriginal human populations at the main 9 geographical regions of the World, taken together, reveal statistically significantly correlation with adaptive structure of the total gene pool of the Mankind. But the correlation is rather small and therefore, the adaptive structure of human gene pool reveals between adaptive structures, the highest is for the USSR and the lowest are for the East-Asiatic and Australian regions. The proportion of neutral to non-neutral genes is about 50% in the average, with the range of variation 40-60% in different regions. But none of the polymorphic genes so far studied reveals constant neutrality in all regional conditions of environment and at different times of evolution history of human gene pool. Its adaptive structure underwent essential transformation from the Palaeolithic till the Postpalaeolithic times, but nevertheless, among the main features of contemporary adaptive structure of human gene pool, those predominate which are of the Palaeolithic origin.     

Analysis of polymorphism at nine nuclear genome DNA loci in maris

Population genetic survey of the indigenous populations of the Marii El Republic, represented by the two major ethnographic groups of Maris, Meadow (five samples from Morkinsk, Orshansk, Semursk, Sovetsk, and Zvenigovsk districts) and Mountain (one sample from Gornomariisk district) Maris, was carried out. All Mari groups were examined at nine polymorphic DNA loci of nuclear genome, VNTR(PAH) (N = 422), STR(PAH) (N = 152), VNTR(ApoB) (N= 294), VNTR(DAT1) (N = 363), VNTR(eNOS) (N = 373), ACE (N = 412), IVS6aGATT (N = 513), D7S23(KM.19) (N = 494), and D7S8 (N = 366). Allele and genotype frequency distribution patterns were obtained for individual samples and ethnographic groups, as well as for the ethnic group overall. In each of six Mari samples examined, the deficit of heterozygotes was observed, i.e., the mean observed heterozygosity was lower than the expected one. The indices of mean heterozygosity, Hs = 0.455, and interpopulation differentiation, FST = 0.0024, for the Mari gene pool were obtained using a set of DNA markers analyzed. Analysis of the genetic distances and between population differentiation (FST) showed that the main part of genetic diversity in Maris was determined by the differentiation between the populations of Meadow Maris. The contribution of the differences between the ethnographic groups of Mountain and Meadow Maris to the ethnic gene pool was small. It is suggested that the main role in the formation of the Mari gene pool is played by the geographic factor.     

The Russian gene pool. Genogeography of serum genetic markers (HP, GC, PI, TF)

The study continues the series of works on the Russian gene pool. Gene geographic analysis of four serum gene markers best studied in the Russian population (HP, GC, PI, and TF) has been performed. Gene-geographic electronic maps have been constructed for 14 alleles of these loci and their correlations with geographic latitude and longitude. For all maps, statistical characteristics are presented, including the variation range and mean gene frequencies, partial and multiple correlations with latitude and longitude, and parameters of heterozygosity and interpopulation diversity. The maps of five alleles (HP*1, GC*2, GC*1S, PI*M2, and TF*C2) are shown and analyzed in detail. The genetic relief and structural elements of the maps are compared with the ecumenical trends, main variation patterns of these genes in northern Eurasia, and genetic characteristics of the indigenous populations of the Urals and Europe.     

The Russian gene pool. Genogeography of erythrocyte genetic markers (ACP1, PGM1, ESD, GLO1, 6-PGD)

The study continues the series of works on the Russian gene pool. Gene geographic analysis of five erythrocytic gene markers best studied in the Russian population (ACP1, PGM1, ESD, GLO1, and 6-PGD) has been performed. Gene-geographic electronic maps have been constructed for 13 alleles of these loci and their correlations with geographic latitude and longitude. For all maps, statistical characteristics are presented, including the variation range and mean gene frequencies, partial and multiple correlations with latitude and longitude, and parameters of heterozygosity and interpopulation diversity. The maps of eight alleles (ACP1*A, ACP1*C, PGM1*2+, PGM1*2-, PGM1*1-, ESD*1, GLO1*1, and PGD*C) are shown and analyzed in detail. The genetic relief and structural elements of the maps are compared with the ecumenical trends, main variation patterns of these genes in northern Eurasia, and genetic characteristics of the indigenous populations of the Urals and Europe.