The Empirical Distribution of Singletons for Geographic Samples of DNA Sequences.

Philippe Cubry,Olivier François,Yves Vigouroux

doi:10.3389/fgene.2017.00139

Philippe Cubry, Olivier François + Show 1 more

Open Access

https://doi.org/10.3389/fgene.2017.00139

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Abstract

Rare variants are important for drawing inference about past demographic events in a species history. A singleton is a rare variant for which genetic variation is carried by a unique chromosome in a sample. How singletons are distributed across geographic space provides a local measure of genetic diversity that can be measured at the individual level. Here, we define the empirical distribution of singletons in a sample of chromosomes as the proportion of the total number of singletons that each chromosome carries, and we present a theoretical background for studying this distribution. Next, we use computer simulations to evaluate the potential for the empirical distribution of singletons to provide a description of genetic diversity across geographic space. In a Bayesian framework, we show that the empirical distribution of singletons leads to accurate estimates of the geographic origin of range expansions. We apply the Bayesian approach to estimating the origin of the cultivated plant species Pennisetum glaucum [L.] R. Br. (pearl millet) in Africa, and find support for range expansion having started from Northern Mali. Overall, we report that the empirical distribution of singletons is a useful measure to analyze results of sequencing projects based on large scale sampling of individuals across geographic space.

Highlights

High-throughput sequencing technologies have enabled studies of genomic diversity in model and non-model species at a dramatically increasing rate
How singletons are distributed across geographic space provides a local measure of genetic diversity that can be measured at the individual level
We developed a theoretical background for the empirical distribution of singletons in a sample of chromosomes

Summary

Introduction

High-throughput sequencing technologies have enabled studies of genomic diversity in model and non-model species at a dramatically increasing rate. Rare variation has attracted considerable interest from genome sequencing projects for model organisms, including plants (Zhu et al, 2011; Weigel, 2012; Memon et al, 2016). Rare variants are important for drawing inference about past demographic events in a species history (Schraiber and Akey, 2015). Studies of human populations have shown that our Distribution of Singletons for Geographic Samples species has experienced a complex demographic history, and that a recent period of explosive growth has resulted in an excess of those variants (Coventry et al, 2010; Keinan and Clark, 2012). The analysis of private and rare variation has been used to reveal signals of differential demographic history among populations, and to refine models of human evolution (Marth et al, 2004; Gravel et al, 2011; Mathieson and McVean, 2014). Estimating rare allele frequencies has enabled estimates of gene flow between populations, and has facilitated inference of finescale population structure (Slatkin, 1985; Novembre and Slatkin, 2009; O’Connor et al, 2015)

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