Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Sexual dimorphism in resource acquisition and deployment: both size and timing matter.

Background and Aims The males and females of many dioecious plant species differ from one another in important life-history traits, such as their size. If male and female reproductive functions draw on different resources, for example, one should expect males and females to display different allocation strategies as they grow. Importantly, these strategies may differ not only between the two sexes, but also between plants of different age and therefore size. Results are presented from an experiment that asks whether males and females of Mercurialis annua, an annual plant with indeterminate growth, differ over time in their allocation of two potentially limiting resources (carbon and nitrogen) to vegetative (below-and above-ground) and reproductive tissues.Methods Comparisons were made of the temporal patterns of biomass allocation to shoots, roots and reproduction and the nitrogen content in the leaves between the sexes of M. annua by harvesting plants of each sex after growth over different periods of time.Key Results and Conclusions Males and females differed in their temporal patterns of allocation. Males allocated more to reproduction than females at early stages, but this trend was reversed at later stages. Importantly, males allocated proportionally more of their biomass towards roots at later stages, but the roots of females were larger in absolute terms. The study points to the important role played by both the timing of resource deployment and the relative versus absolute sizes of the sinks and sources in sexual dimorphism of an annual plant.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.