Ancestry-specific recent effective population size in the Americas

<div><p>Populations change in size over time due to factors such as population growth, migration, bottleneck events, natural disasters, and disease. The historical effective size of a population affects the power and resolution of genetic association studies. For admixed populations, it is not only the overall effective population size that is of interest, but also the effective sizes of the component ancestral populations. We use identity by descent and local ancestry inferred from genome-wide genetic data to estimate overall and ancestry-specific effective population size during the past hundred generations for nine admixed American populations from the Hispanic Community Health Study/Study of Latinos, and for African-American and European-American populations from two US cities. In these populations, the estimated pre-admixture effective sizes of the ancestral populations vary by sampled population, suggesting that the ancestors of different sampled populations were drawn from different sub-populations. In addition, we estimate that overall effective population sizes dropped substantially in the generations immediately after the commencement of European and African immigration, reaching a minimum around 12 generations ago, but rebounded within a small number of generations afterwards. Of the populations that we considered, the population of individuals originating from Puerto Rico has the smallest bottleneck size of one thousand, while the Pittsburgh African-American population has the largest bottleneck size of two hundred thousand.</p></div

Estimated ancestry-specific effective population size in HCHS/SOL data.

<p>The y-axes show ancestry-specific effective population size (<i>N</i>_<i>e</i>), plotted on a log scale. The x-axes show generations before the present. The lines show estimated ancestry-specific effective population sizes, and the colored regions show 95% bootstrap confidence intervals.</p

Ancestry-specific effective population size for selected populations.

<p>The y-axes show ancestry-specific effective population size (<i>N</i>_<i>e</i>), plotted on a log scale. The x-axes show generations before present. The lines show estimated ancestry-specific effective population sizes, and the colored regions show 95% bootstrap confidence intervals. Each plot shows a different ancestral component. HCHS/SOL populations are included if the sample size multiplied by the average genome-wide ancestry proportion for the given ancestry in that population is at least 100. African ancestry for African American (AA) in Memphis, and European ancestry for European American (EA) in Memphis are included for comparison.</p

HCHS/SOL populations.

<p>HCHS/SOL populations.</p

Health ABC populations.

<p>Health ABC populations.</p

Estimated effective population size in two US cities.

<p>The y-axes show ancestry-specific effective population size (<i>N</i>_<i>e</i>), plotted on a log scale. The x-axes show generations before present. The solid lines show estimated effective population sizes, and the colored regions show 95% bootstrap confidence intervals. Overall effective sizes are shown for the African American (AA) and European American (EA) populations, as well as ancestry-specific effective sizes for African and European ancestry in the African-American populations.</p

Maximum and minimum estimated effective population sizes (95% confidence intervals, in thousands).

<p>Maximum and minimum estimated effective population sizes (95% confidence intervals, in thousands).</p

Estimated ancestry-specific effective population size in simulated data.

<p>Analysis of 500 simulated individuals from a three-way admixed population. Each column is one of the three simulated ancestries. The y-axes show ancestry-specific effective population size (<i>N</i>_<i>e</i>), plotted on a log scale. The x-axes show generations before present. The dashed lines show simulated effective population sizes. The solid black lines show estimated ancestry-specific effective population sizes, and the gray regions show 95% bootstrap confidence intervals.</p

Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology

<div><p>Numerous lines of evidence point to a genetic basis for facial morphology in humans, yet little is known about how specific genetic variants relate to the phenotypic expression of many common facial features. We conducted genome-wide association meta-analyses of 20 quantitative facial measurements derived from the 3D surface images of 3118 healthy individuals of European ancestry belonging to two US cohorts. Analyses were performed on just under one million genotyped SNPs (Illumina OmniExpress+Exome v1.2 array) imputed to the 1000 Genomes reference panel (Phase 3). We observed genome-wide significant associations (p < 5 x 10⁻⁸) for cranial base width at 14q21.1 and 20q12, intercanthal width at 1p13.3 and Xq13.2, nasal width at 20p11.22, nasal ala length at 14q11.2, and upper facial depth at 11q22.1. Several genes in the associated regions are known to play roles in craniofacial development or in syndromes affecting the face: <i>MAFB</i>, <i>PAX9</i>, <i>MIPOL1</i>, <i>ALX3</i>, <i>HDAC8</i>, and <i>PAX1</i>. We also tested genotype-phenotype associations reported in two previous genome-wide studies and found evidence of replication for nasal ala length and SNPs in <i>CACNA2D3</i> and <i>PRDM16</i>. These results provide further evidence that common variants in regions harboring genes of known craniofacial function contribute to normal variation in human facial features. Improved understanding of the genes associated with facial morphology in healthy individuals can provide insights into the pathways and mechanisms controlling normal and abnormal facial morphogenesis.</p></div

LocusZoom plots showing genome-wide significant associations observed in the meta-analysis for intercanthal width (Fig 1H).

<p>(A) chromosome 1 and (B) chromosome X. LocusZoom plots show the association (left y-axis; log10-transformed p-values) with facial traits. Genotyped SNPs are depicted by stars and imputed SNPs are depicted by circles. Shading of the points represent the linkage disequilibrium (r², based on the 1000 Genomes Project Europeans) between each SNP and the top SNP, indicated by purple shading. The blue overlay shows the recombination rate (right y-axis). Positions of genes are shown below the plot.</p