Inference of seed bank parameters in two wild tomato species using ecological and genetic data

Abstract

Seed and egg dormancy is a prevalent life-history trait in plants and invertebrates whose storage effect buffers against environmental variability, modulates species extinction in fragmented habitats, and increases genetic variation. Experimental evidence for reliable differences in dormancy over evolutionary scales (e.g., differences in seed banks between sister species) is scarce because complex ecological experiments in the field are needed to measure them. To cope with these difficulties, we developed an approximate Bayesian computation (ABC) framework that integrates ecological information on population census sizes in the priors of the parameters, along with a coalescent model accounting simultaneously for seed banks and spatial genetic structuring of populations. We collected SNP data at seven nuclear loci (over 300 SNPs) using a combination of three spatial sampling schemes: population, pooled, and species-wide samples. We provide evidence for the existence of a seed bank in two wild tomato species (Solanum chilense and Solanum peruvianum) found in western South America. Although accounting for uncertainties in ecological data, we infer for each species (i) the past demography and (ii) ecological parameters, such as the germination rate, migration rates, and minimum number of demes in the metapopulation. The inferred difference in germination rate between the two species may reflect divergent seed dormancy adaptations, in agreement with previous population genetic analyses and the ecology of these two sister species: Seeds spend, on average, a shorter time in the soil in the specialist species (S. chilense) than in the generalist species (S. peruvianum).Bayesian analysis | bet-hedging | coalescent theory T he effective size of a population or species (N e ) defines its evolutionary potential because it determines the rate at which adaptive substitutions appear and get fixed (1), as well as the vulnerability to loss of genetic diversity by genetic drift. A fundamental question in plant evolutionary biology, and of practical relevance for conservation biology, is to understand how the census size of a population above ground (N cs ) is affected by ecological disturbances and how this process, in turn, affects the N e (2). Habitat loss and fragmentation attributable to human activities are indeed acute problems for conservation of spatially structured populations because they reduce deme sizes (N e and N cs ) and gene flow among demes. The genetic diversity, reflected by the N e , of many plant (and invertebrate) species, can be seen as an iceberg. The tip of the iceberg is composed of individuals observable above ground (N cs ), whereas the major part of the diversity is accounted for by among-population differences (3, 4) and seed banks (5-8).Most, if not all, plant and animal species exist as spatially structured populations (metapopulations) with many demes linked by migration, which may be subjected to extinction/ recolonization (9). Depending on extinction/recolonization rates and the type of group fo...

Genetic Diversity in Tomato (Solanum lycopersicum) and Its Wild Relatives

“…This would allow investigating demographic scenarios and estimating the parameters of these scenarios (bottleneck intensity, ancestral population size, migration rates) using Markovian model implemented in tools such as IM * program (Hey and Nielsen 2004) or ABC 1 methodology (Beaumont, Zhang et al 2002;Lopes and Beaumont 2010). Very recently, this approach has been implemented to infer past demography and ecological parameters of two tomato wild relatives, S. chilense and S. peruvianum (Tellier, Laurent et al 2011). …”

Fisher–Wright model with deterministic seed bank and selection

“…In practice this means that the spatial structure of populations and seed bank effects on demography and selection are difficult to disentangle [6]. Nevertheless, Tellier et al [37] could use this rescaled seed bank coalescent model [26] and Approximate Bayesian Computation to infer the germination rate in two wild tomato species Solanum chilense and S. peruvianum from polymorphism data [38]. A second class of models assumes a strong seed bank effect, whereby the time seeds can spend in the bank is very long, that is longer than the population coalescent time [18], or the time for two lineages to coalesce can be unbounded.…”

“…In effect, the model of [26] represents a special case, also called a weak seed bank, where the time for lineages to coalesce is finite because the maximum time that seeds can spend in the bank is bounded. In the following we mainly have the weak seed bank model in mind where the time in the seed bank is bounded to a small finite number assumed to be realistic for most plant species [13,24,38,39]. Even if we allow for unbounded times a seed may be stored within the soil, we assume that the germination probability decreases rapidly with age such that e.g.…”

Coalescence 2.0: a multiple branching of recent theoretical developments and their applications

“…The Kingman coalescent applied to a metapopulation suggests that the genealogy is divided into a short scattering phase and a long collecting phase (Wakeley & Aliacar 2001), while the rates of coalescence in these phases depend on the deme size and level of gene flow between demes. Using different sampling strategies, it is possible to take into account the genealogies of these phases and to study neutral and selective processes acting at the local (scattering phase) and the whole species (collecting phase) level (Städler et al 2009;Tellier et al 2011).…”

“…(Watterson 1984;Kaj & Krone 2003), single panmictic population (e.g. Wakeley & Aliacar 2001;Charlesworth et al 2003), and non-overlapping generations (Tellier et al 2011). Modifications of the Kingman coalescent are obtained by using time-rescaling argument to accommodate variable rates of coalescence in time (Kaj & Krone 2003).…”