POPULATION SUBDIVISION
Population subdivision is a means to test the amount of genetic variation amongst subpopulations within a species. This concept was developed by American evolutionary geneticist Sewall Wright (1978). Populations, which have undergone significant adaptation to local conditions, differ in population dynamic history, and limited gene flow between them should differ in allele frequencies at a number of loci. The population subdivision statistic (FST) compares the allelic diversity of each of the subpopulations against a pooled total population. Since Wright's invention of F coefficients, which examine the proportioning of genetic variation between different levels within a species, population geneticists have utilized a minimum value of differentiation between subpopulations and the total species as the threshold for identifying the existence of biological races (FST> 0.250). Wright chose this value to maximize the probability that the subgroups were actually fixed for alternative different alleles at various loci.
Four nucleotides can be found in DNA, adenosine (A), Thymine (T), Guanine (G), and Cytosine (C). In coding regions of the genetic code three nucleotides in succession determine which amino acid should be placed in the resultant protein. The code is redundant, but a change in a position can result in a different amino acid being specified. When we examine the coding and non-coding regions of DNA in a population, most people will have the same nucleotide at the vast majority of the positions within the code. However, at some positions, a variant will be found in some individuals. Such a variant is called a SNP. One study examined 4,833 single nucleotide polymorphisms (SNPs) in 538 clusters across the human genome in Europeans (N = 30), African Americans (N = 30), and Asians (N = 40).
In the study the mean frequency for FST at each locus was 0.083, with only 10 percent of the loci exceeding FST of 0.18 and about 6.5 percent exceeding FST of 0.250. This is consistent with the general finding that, averaged across the genome, FST in humans does not approach Wright's threshold (and is generally FST = 0.110). Utilizing eleven genes that have been reputedly associated with general intelligence (ASPM, OXTR, CCKAR, ADRB2, DTNBP1, ALDH5A1, IGF2R, CHRM2, MCPH1, DRD4, and CTSD; Deary, Johnson, & Houlihan, 2009) I calculated FST from the SNP's currently reported within these genes. The data on SNP's FST values was retrieved from the Allele Frequency Database (ALFRED, maintained by the Kidd Laboratory at Yale University). I calculated FST values for SNP's found within genes and for all SNP's found within these eleven genes. Table 1 reports the mean and standard deviation for FST within each gene. Of the eleven, nine have mean values well below Wright's threshold, OXTR barely exceeds it (0.251) and ASPM is well differentiated at 0.322. The FST values for each SNP were calculated from populations worldwide. The range of populations sampled varied between 4 and 87.
However the vast majority of the SNP's frequencies in these genes were sampled from around 50 populations varying from regions identified as Africa (sub-Saharan Africa), Europe, Asia (Middle East and Eurasia), East Asia, Oceania, and the Americas. Generally, there were more populations sampled in Europe and East Asia, compared to Africa. This discrepancy in sampling makes all world-wide calculations of genetic variability suspect, simply because the data we have at present is not representative of the entire spectrum of human populations. The mean FST for all SNP's from these seven genes is 0.150, with a S. D. of 0.075. Only 12.5% exceeded Wright's threshold of 0.250, see Figure 1. This is to be expected in this sample, since nine of the eleven genes examined had mean FST values for all SNP's within them below Wright's threshold. Despite the limitations of sampling across world populations, the analysis presented above does not support the notion that there should be "racially"; differentiated genetic variation for genetic variants associated for intelligence.
Source: Race, Genomics, and IQ: Slight Return for Intelligence Quotient: Testing, Role of Genetics and the Environment and Social Outcomes, Ed. Joseph Kush, Nova Scientific Publishers, pp. 69 –86 (2013)