A variant-centric perspective on geographic patterns of human allele frequency variation.

Arjun Biddanda,Daniel P Rice,John Novembre

doi:10.7554/elife.60107

Abstract

A key challenge in human genetics is to understand the geographic distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, drawing inferences over many variants. Here, we introduce an alternative representation of genetic variation that reveals the relative abundance of different allele frequency patterns. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are found globally, regardless of whether the individuals are from the same region or different regions. Our variant-centric visualization clarifies the geographic patterns of human variation and can help address misconceptions about genetic differentiation among populations.

Highlights

Understanding human genetic variation, including its origins and its consequences, is one of the long-standing challenges of human biology
The distribution of codes is heavily concentrated, with 85% of variants falling into just eight codes out of the 242 that are possible (35–1: three frequency categories in each of five regional groupings, subtracting the code ‘UUUUU’ as each variant has been observed by definition)
Instead, when a variant is found to be common (>5% allele frequency) in one population, the modal pattern (37.3%) is that it is common across the five regions (‘CCCCC’)

Summary

Introduction

Understanding human genetic variation, including its origins and its consequences, is one of the long-standing challenges of human biology. How often do variants have an allele at high frequency in one narrow region of the world that is absent everywhere else? For answering many applied questions, we need to know how many variants show any particular geographic pattern in their allele frequencies. In order to answer such questions, one needs to measure the frequencies of many alleles around the world without the ascertainment biases that affect genotyping arrays and other probe-based technologies (International HapMap Consortium, 2005; Li et al, 2008). Large genetic data sets present a visualization challenge: how does one show the allele frequency patterns of millions of variants? We need visualizations that intuitively summarize allele frequency variation across several populations

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Conclusion