New data on 21 Alu insertions in 32 populations are analyzed along with three other large, globally dispersed data sets that consist of apparently neutral biallelic nuclear markers, as well as with a beta-global data set possibly subject to selection.
Previous studies have reported that approximately 85 percent of human diversity at short tandem repeat (STR) and restriction fragment length polymorphism (RFLP) autosomal loci is due to differences between individuals of the same population; whereas, differences among continental groups account for only 10 percent of the overall genetic variance. These findings conflict with popular notions of distinct and relatively homogeneous human races and may also challenge the apparent usefulness of ethnic classification. In the current study, discriminant analysis confirms the existence of some degree of geographic structuring in humans. If a set of biallelic loci from an individual's genome is considered in attempting to determine the continent from which that genotype comes, the result will be correct most of the time; however, even when jointly considered, all of the markers that could be used, including those of the Y chromosome, were not able to assign more than 70 percent of the individuals to their continent of origin. This is unexpected if humans were subdivided and deep genetic discontinuities existed among continental groups. The study also shows, albeit in a relatively small sample, that the genetic variances among continents at a locus undergoing selection, beta-globin, are not greater than those estimated at neutral loci. The results suggest that at random biallelic loci, there is little, if any, evidence of a clear subdivision of humans into biologically defined groups. The authors typed 21 Alu insertion polymorphisms in population samples from five continents and analyze published biallelic DNA polymorphisms data at several other nuclear loci, both autosomal and Y linked. 10 tables, 2 figures, and 55 references
Downloads
Similar Publications
- ILIAD: A Suite of Automated Snakemake Workflows for Processing Genomic Data for Downstream Applications
- Environmental Predictors Impact Microbial-based Postmortem Interval (PMI) Estimation Models within Human Decomposition Soils
- Solving Cases of Sudden Unexpected Natural Death in the Young through Comprehensive Postmortem Genetic Testing