Infracranial versus cranial nonmetric traits and mtDNA data in the study of genetic divergence of human populations

Abstract

Although cranial and dental nonmetric traits have proven to be reliable proxies for genetic data, the usefulness of infracranial nonmetric traits as phenetic markers in population affinity studies remains unclear. Our aim was to analyze infracranial and cranial nonmetric trait frequencies in the same samples in comparison with genetic data to determine the value of infracranial nonmetric traits in assessing genetic relationships among populations. We examined the frequencies of 25 cranial and 16 infracranial nonmetric traits in seven adult osteological samples from different regions of northern Eurasia (northern Russians, indigenous populations of Volga-Ural region, Buryats, and Yupik) and the data on mitochondrial DNA polymorphisms in the same ethnic groups. The biological distance between each pair of samples was estimated using the Smith's mean measure of divergence (MMD) for nonmetric traits and Cavalli-Sforza distance measure for mtDNA data. Mantel correlations were calculated between two matrices of mean measures of divergence (MMD) distances, and a multidimensional scaling (MDS) procedure was applied to each matrix. The Mantel test showed a strong correlation between the two nonmetric distance matrices. The three-dimensional spatial representations of each matrix revealed similar patterns of intergroup differences. On both nonmetric MDS maps, the sample locations roughly reflected the geographic separation of the groups, with the exception of northern Russians, who were grouped with Volga-Ural populations.Comparison of our results with those obtained from genetic data confirmed that both sets of nonmetric traits provide reliable genetic affinities among the samples. The association of northern Russians with the Volga-Ural groups can be explained by their genetic background. Our findings show that infracranial nonmetric traits can be successfully used as phenetic markers to define a population's affinity and divergence, particularly in cases where only infracranial bones are available for study.

Biological distances between Late Holocene hunter‐gatherers from the lower Paraná wetland (Argentina)

“…Thirty‐three cranial and mandibular nonmetric traits were recorded (Table 3). These traits were chosen as they were successfully used in several other works to assess biological distances between archaeological samples (e.g., Blom et al, 1998; Movsesian & Vagner‐Sapukhina, 2021; Nikita et al, 2012; Ricaut et al, 2010; Sutter & Mertz, 2004; Tyrell, 2000) and are well described in the literature (Buikstra & Ubelaker, 1994; Hauser & De Stefano, 1989; Mann et al, 2016). Each trait was scored as presence/absence.…”

“…Other researchers also succeeded in correlating nonmetric cranial traits with the size and shape of the cranium, which pointed to the same developmental and growth processes intervening in both nonmetric and metric traits (Cheverud et al, 1979;Hanihara et al, 2003;Herrera et al, 2014), or with dental nonmetric morphology (Prowse & Lovell, 1996;Sutter & Mertz, 2004). Furthermore, biodistances obtained from cranial nonmetric traits correlate with molecular data (Herrera et al, 2014;Movsesian & Vagner-Sapukhina, 2021;Ricaut et al, 2010) and family trees (Velemínský & Dobisíkov a, 2005). Therefore, those populations that share specific patterns of morphological variation are considered more closely related genetically than those that do not share them.…”

Inferring human neutral genetic variation from craniodental phenotypes

“…A standard approach for quantifying the utility of a given craniodental data type in capturing a neutral genomic signature is to estimate phenotypic distances among worldwide modern human populations, on the one hand, and to compare them to neutral genomic distances estimated among the same or closely matched set of populations on the other ( 1 , 2 , 52 ). These analyses, hereafter termed D P – D G comparisons, have been extensively performed for cranial metric data ( 14 , 16 , 17 , 19 , 20 , 51 , 53 , 54 ), dental metric data ( 18 , 55 ), cranial nonmetric trait data ( 51 , 56 , 57 ), and dental nonmetric trait data ( 10 , 15 , 18 , 58 ). However, the estimated levels of neutrality of the different craniodental data types reported in previous D P – D G studies are not directly comparable, since different populations have been sampled and diverse methodological approaches for calculating between-population distances have been employed at different geospatial scales ( 54 ).…”