Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data.

Thibaut Paul Patrick Sellinger,Markus Moest,Aurélien Tellier,Diala Abu Awad,Rodney Mauricio

doi:10.1371/journal.pgen.1008698

Thibaut Paul Patrick Sellinger, Markus Moest + Show 3 more

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https://doi.org/10.1371/journal.pgen.1008698

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Abstract

Several methods based on the Sequential Markovian coalescence (SMC) have been developed that make use of genome sequence data to uncover population demographic history, which is of interest in its own right and is a key requirement to generate a null model for selection tests. While these methods can be applied to all possible kind of species, the underlying assumptions are sexual reproduction in each generation and non-overlapping generations. However, in many plants, invertebrates, fungi and other taxa, those assumptions are often violated due to different ecological and life history traits, such as self-fertilization or long term dormant structures (seed or egg-banking). We develop a novel SMC-based method to infer 1) the rates/parameters of dormancy and of self-fertilization, and 2) the populations' past demographic history. Using simulated data sets, we demonstrate the accuracy of our method for a wide range of demographic scenarios and for sequence lengths from one to 30 Mb using four sampled genomes. Finally, we apply our method to a Swedish and a German population of Arabidopsis thaliana demonstrating a selfing rate of ca. 0.87 and the absence of any detectable seed-bank. In contrast, we show that the water flea Daphnia pulex exhibits a long lived egg-bank of three to 18 generations. In conclusion, we here present a novel method to infer accurate demographies and life-history traits for species with selfing and/or seed/egg-banks. Finally, we provide recommendations for the use of SMC-based methods for non-model organisms, highlighting the importance of the per site and the effective ratios of recombination over mutation.

Highlights

Genomes, and especially genetic polymorphisms, are shaped by molecular forces, such as mutation and recombination, and ecological forces intrinsic to, or independent of, the biology of the species [1]
Inference is based on modeling single nucleotide polymorphism (SNPs) along the genome across individuals, the density of which results from the interplay between mutation, time to common ancestors and recombination
We find a strong signature of self-fertilization in Arabidopsis thaliana and a strong signature of eggbanks in Daphnia pulex

Summary

Introduction

Especially genetic polymorphisms, are shaped by molecular forces, such as mutation and recombination, and ecological forces intrinsic to, or independent of, the biology of the species [1]. It is common practice to simulate the past demography of a population as a null model in order to define thresholds for selection scan methods. An accurate demographic inference should yield more reliable selection results [8, 9]. To this aim, new models and methods have been developed to extract previously unavailable information from whole genome sequence data [10,11,12,13,14]. Inference is based on modeling single nucleotide polymorphism (SNPs) along the genome across individuals, the density of which results from the interplay between mutation, time to common ancestors and recombination. The common denominator in all these methods is their reliance on the per site ratio recombination (r) and the mutation (μ) rate of the species (r), m or, more precisely, on its effective value r

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