Looking for local adaptation: Convergent microevolution in aleppo pine (pinus halepensis)

Rose Ruiz Daniels, Richard S. Taylor, Santiago C.González Martínez, Giovanni G. Vendramin, Bruno Fady, Sylvie Oddou Muratorio, Andrea Piotti, Guillaume Simioni, Delphine Grivet*, Mark A. Beaumont

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

8 Citations (Scopus)
163 Downloads (Pure)


Finding outlier loci underlying local adaptation is challenging and is best approached by suitable sampling design and rigorous method selection. In this study, we aimed to detect outlier loci (single nucleotide polymorphisms, SNPs) at the local scale by using Aleppo pine (Pinus halepensis), a drought resistant conifer that has colonized many habitats in the Mediterranean Basin, as the model species. We used a nested sampling approach that considered replicated altitudinal gradients for three contrasting sites. We genotyped samples at 294 SNPs located in genomic regions selected to maximize outlier detection. We then applied three di_erent statistical methodologies—Two Bayesian outlier methods and one latent factor principal component method—To identify outlier loci. No SNP was an outlier for all three methods, while eight SNPs were detected by at least two methods and 17 were detected only by one method. From the intersection of outlier SNPs, only one presented an allelic frequency pattern associated with the elevational gradient across the three sites. In a context of multiple populations under similar selective pressures, our results underline the need for careful examination of outliers detected in genomic scans before considering them as candidates for convergent adaptation.

Original languageEnglish
Article number673
Number of pages16
Issue number9
Publication statusPublished - 4 Sept 2019


  • Altitudinal gradients
  • Natural selection
  • Outliers
  • Pinus halepensis
  • SNP


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