The current genetic makeup of Latin America has been shaped by a history of extensive admixture between Africans, Europeans and Native Americans, a process taking place within the context of extensive geographic and social stratification. We estimated individual ancestry proportions in a sample of 7,342 subjects ascertained in five countries (Brazil, Chile, Colombia, México and Perú). These individuals were also characterized for a range of physical appearance traits and for self-perception of ancestry. The geographic distribution of admixture proportions in this sample reveals extensive population structure, illustrating the continuing impact of demographic history on the genetic diversity of Latin America. Significant ancestry effects were detected for most phenotypes studied. However, ancestry generally explains only a modest proportion of total phenotypic variation. Genetically estimated and self-perceived ancestry correlate significantly, but certain physical attributes have a strong impact on self-perception and bias self-perception of ancestry relative to genetically estimated ancestry.

Here we report a genome-wide association study for non-pathological pinna morphology in over 5,000 Latin Americans. We find genome-wide significant association at seven genomic regions affecting: lobe size and attachment, folding of antihelix, helix rolling, ear protrusion and antitragus size (linear regression P values 2 × 10−8 to 3 × 10−14). Four traits are associated with a functional variant in the Ectodysplasin A receptor (EDAR) gene, a key regulator of embryonic skin appendage development. We confirm expression of Edar in the developing mouse ear and that Edar-deficient mice have an abnormally shaped pinna. Two traits are associated with SNPs in a region overlapping the T-Box Protein 15 (TBX15) gene, a major determinant of mouse skeletal development. Strongest association in this region is observed for SNP rs17023457 located in an evolutionarily conserved binding site for the transcription factor Cartilage paired-class homeoprotein 1 (CART1), and we confirm that rs17023457 alters in vitro binding of CART1.

Limited sample sizes imply parametric assumptions could be violated, even if traits have been reported to fulfil parametric assumptions. Parametric studies have addressed a non-significant influence of CSN1S1 genes on Murciano-Granadina milk yield, fat, protein and dry extract. We used non-parametric categorical tests to find alternative statistical methods to analyse the power to explain the variability found in the population regarding milk yield and its components. We analysed 2090 records for milk yield, and its components from 710 Murciano-Granadina CSN1S1-genotyped goats. Categorical regression equations were issued to predict which and at what level these factors may determine milk yield (kg), fat (kg), protein (kg) and dry extract (kg). All environmental (farm and parturition year) and animal-inherent factors (genotype, birth type and age) resulted statistically significant (p < .05) except for birth season and month. CSN1S1 genotype was highly statistically significant and explained from 8.3% to 9.2% of protein and fat content variability, resembling the values for highly selected French breeds. Seasonal peaks and lows resembled other breeds'. Heterozygote advantage of certain combinations of E allele with those alleles strongly or weakly influencing milk components and yield such as A, B, B2, F and homozygote BB genotype reported the highest statistically significant effects on milk components and yield. Our results suggest that non-parametric tests may report contextually valid results when having a large sample size is not possible. Selecting for certain CSN1S1 genotypes may promote the efficient production of better-quality milk in greater amounts, improving the international competitiveness and profitability of local breeds. HIGHLIGHTS Non-parametric tests are crucial if normality and heteroskedasticity analyses fail. Murciano-Granadina milk traits compared with highly selected international breeds'. E allele combinations and BB reported highest effects on milk components and yield.