Common microgeographical selection patterns revealed in four European conifers.

Microgeographical adaptation occurs when the effects of directional selection persist despite gene flow. Traits and genetic loci under selection can then show adaptive divergence, against the backdrop of little differentiation at other traits or loci. How common such events are and how strong the selection is that underlies them remain open questions. Here, we discovered and analysed microgeographical patterns of genomic divergence in four European and Mediterranean conifers with widely differing life-history traits and ecological requirements (Abies alba MIll., Cedrus atlantica [Endl.] Manetti, Pinus halepensis Mill. and Pinus pinaster Aiton) by screening pairs from geographically close forest stands sampled along steep ecological gradients. We inferred patterns of genomic divergence by applying a combination of divergence outlier detection methods, demographic modelling, Approximate Bayesian Computation inferences and genomic annotation to genomic data. Surprisingly for such small geographical scales, we showed that selection is strong in all species but generally affects different loci in each. A clear signature of selection was systematically detected on a fraction of the genome, of the order of 0.1%-1% of the loci depending on the species. The novel modelling method we designed for estimating selection coefficients showed that the microgeographical selection coefficient scaled by population size (Ns) was 2-30. Our results convincingly suggest that selection maintains within-population diversity at microgeographical scales in spatially heterogeneous environments. Such genetic diversity is likely to be a major reservoir of adaptive potential, helping populations to adapt under fluctuating environmental conditions.

Venomics survey of six myrmicine ants provides insights into the molecular and structural diversity of their peptide toxins.

Among ants, Myrmicinae represents the most speciose subfamily. The venom composition previously described for these social insects is extremely variable, with alkaloids predominant in some genera while, conversely, proteomics studies have revealed that some myrmicine ant venoms are peptide-rich. Using integrated transcriptomic and proteomic approaches, we characterized the venom peptidomes of six ants belonging to the different tribes of Myrmicinae. We identified a total of 79 myrmicitoxins precursors which can be classified into 38 peptide families according to their mature sequences. Myrmicine ant venom peptidomes showed heterogeneous compositions, with linear and disulfide-bonded monomers as well as dimeric toxins. Several peptide families were exclusive to a single venom whereas some were retrieved in multiple species. A hierarchical clustering analysis of precursor signal sequences led us to divide the myrmicitoxins precursors into eight families, including some that have already been described in other aculeate hymenoptera such as secapin-like peptides and voltage-gated sodium channel (NaV) toxins. Evolutionary and structural analyses of two representatives of these families highlighted variation and conserved patterns that might be crucial to explain myrmicine venom peptide functional adaptations to biological targets.

An Integrated Proteomic and Transcriptomic Analysis Reveals the Venom Complexity of the Bullet Ant Paraponera clavata.

A critical hurdle in ant venom proteomic investigations is the lack of databases to comprehensively and specifically identify the sequence and function of venom proteins and peptides. To resolve this, we used venom gland transcriptomics to generate a sequence database that was used to assign the tandem mass spectrometry (MS) fragmentation spectra of venom peptides and proteins to specific transcripts. This was performed alongside a shotgun liquid chromatography-mass spectrometry (LC-MS/MS) analysis of the venom to confirm that these assigned transcripts were expressed as proteins. Through the combined transcriptomic and proteomic investigation of Paraponera clavata venom, we identified four times the number of proteins previously identified using 2D-PAGE alone. In addition to this, by mining the transcriptomic data, we identified several novel peptide sequences for future pharmacological investigations, some of which conform with inhibitor cysteine knot motifs. These types of peptides have the potential to be developed into pharmaceutical or bioinsecticide peptides.

Genome-environment association study suggests local adaptation to climate at the regional scale in Fagus sylvatica.

The evolutionary potential of long-lived species, such as forest trees, is fundamental for their local persistence under climate change (CC). Genome-environment association (GEA) analyses reveal if species in heterogeneous environments at the regional scale are under differential selection resulting in populations with potential preadaptation to CC within this area. In 79 natural Fagus sylvatica populations, neutral genetic patterns were characterized using 12 simple sequence repeat (SSR) markers, and genomic variation (144 single nucleotide polymorphisms (SNPs) out of 52 candidate genes) was related to 87 environmental predictors in the latent factor mixed model, logistic regressions and isolation by distance/environmental (IBD/IBE) tests. SSR diversity revealed relatedness at up to 150 m intertree distance but an absence of large-scale spatial genetic structure and IBE. In the GEA analyses, 16 SNPs in 10 genes responded to one or several environmental predictors and IBE, corrected for IBD, was confirmed. The GEA often reflected the proposed gene functions, including indications for adaptation to water availability and temperature. Genomic divergence and the lack of large-scale neutral genetic patterns suggest that gene flow allows the spread of advantageous alleles in adaptive genes. Thereby, adaptation processes are likely to take place in species occurring in heterogeneous environments, which might reduce their regional extinction risk under CC.

Detecting short spatial scale local adaptation and epistatic selection in climate-related candidate genes in European beech (Fagus sylvatica) populations.

Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech (Fagus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south-eastern France). We performed both single and multilocus analysis of selection based on 53 climate-related candidate genes containing 546 SNPs. FST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by Ohta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an FST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.