Common microgeographical selection patterns revealed in four European conifers. Issue 2 (14th November 2022) - Scotti, Ivan; Lalagüe, Hadrien; Oddou‐Muratorio, Sylvie; Scotti‐Saintagne, Caroline; Ruiz Daniels, Rose; Grivet, Delphine; Lefevre, François; Cubry, Philippe; Fady, Bruno; González‐Martínez, Santiago C.; Roig, Anne; Lesur‐Kupin, Isabelle; et al.
Abstract: 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.