Craniometric similarities within and between human populations in comparison with neutral genetic data.
The statement that pairs of individuals from different populations are often more genetically similar than pairs from the same population is a widespread idea inside and outside the scientific community. Witherspoon et al. ["Genetic similarities within and between human populations," Genetics 176:351-359 (2007)] proposed an index called the dissimilarity fraction (omega) to access in a quantitative way the validity of this statement for genetic systems. Witherspoon demonstrated that, as the number of loci increases, omega decreases to a point where, when enough sampling is available, the statement is false. In this study, we applied the dissimilarity fraction to Howells's craniometric database to establish whether or not similar results are obtained for cranial morphological traits. Although in genetic studies thousands of loci are available, Howells's database provides no more than 55 metric traits, making the contribution of each variable important. To cope with this limitation, we developed a routine that takes this effect into consideration when calculating omega. Contrary to what was observed for the genetic data, our results show that cranial morphology asymptotically approaches a mean omega of 0.3 and therefore supports the initial statement--that is, that individuals from the same geographic region do not form clear and discrete clusters--further questioning the idea of the existence of discrete biological clusters in the human species. Finally, by assuming that cranial morphology is under an additive polygenetic model, we can say that the population history signal of human craniometric traits presents the same resolution as a neutral genetic system dependent on no more than 20 loci.
Strauss
André
A
Departamento de Genética e Biologia Evolutiva, Institute de Biociências, Universidade de São Paulo, Rua do Matão 277, 05508-090 São Paulo, Brazil.
Hubbe
Mark
M
D000349:Africa; D001208:Asia; D002508:Cephalometry / Q000379:methods / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D016208:Databases, Factual; D005060:Europe; D005260:Female; D005819:Genetic Markers; D014644:Genetic Variation; D005828:Genetics, Population / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012016:Reference Values
D005819:Genetic Markers