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

Abstract

<jats:title>Abstract</jats:title><jats:p>Several methods based on the Sequential Markovian Coalescent (SMC) have been developed to use full genome sequence data to uncover population demographic history, which is of interest in its own right and a key requirement to generate a null model for selection tests. While these methods can be applied to all possible species, the underlying assumptions are sexual reproduction at each generation and no overlap of generations. However, in many plant, invertebrate, fungi and other species, 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 of seed/egg-bank 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 <jats:italic>Arabidopsis thaliana</jats:italic> demonstrating a selfing rate of <jats:italic>ca.</jats:italic> 0.8 and the absence of any detectable seed-bank. In contrast, we show that the water flea <jats:italic>Daphnia pulex</jats:italic> 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 on 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.</jats:p>

Weak seed banks influence the signature and detectability of selective sweeps

“…In other words, even if the recombination rate is slowed down by a factor b because only above-ground plants may recombine, as the coalescent tree is lengthened by a factor there are on average recombination events per coalescent tree. This property of the ARG was used in T. Sellinger et al .…”

“…Unless stated otherwise, mutations are neutral and the number of new mutations is sampled analogously from a Poisson distribution with rate parameter µ . We assume here that mutations are also introduced at every generation in dormant individuals at the same rate (see justification in T. Sellinger et al .…”

“…The germination function was previously simplified by assuming that the distribution of germination rate follows a geometric function with rate b , so that b = β when m is large enough (Tellier, Laurent, et al . 2011; Živković and Tellier 2012; T. Sellinger et al .…”

“…Only one lineage is, however, affected by recombination in the backward-in-time model so that the population recombination rate is . Indeed, the recombination rate r needs to be multiplied by the probability of germination b as only active individuals can recombine (Živković and Tellier 2018; T. Sellinger et al .…”

“…2019). Importantly, the balance of population mutation rate and recombination rate defines the amount of nucleotide diversity in the genome as well as the amount of linkage disequilibrium, a property which we used to develop an Sequential Markovian Coalescent (SMC) approach to jointly estimate past demographic history and the germination rate (T. Sellinger et al .…”