Article

Looking for Local Adaptation: Convergent Microevolution in Aleppo Pine (Pinus halepensis)

Details

Citation

Ruiz Daniels R, Taylor RS, González-Martínez SC, Vendramin GG, Fady B, Oddou-Muratorio S, Piotti A, Simioni G, Grivet D & Beaumont MA (2019) Looking for Local Adaptation: Convergent Microevolution in Aleppo Pine (Pinus halepensis). Genes, 10 (9), Art. No.: 673. https://doi.org/10.3390/genes10090673

Abstract
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 different 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.

Keywords
Pinus halepensis; natural selection; outliers; SNP; altitudinal gradients

Journal
Genes: Volume 10, Issue 9

StatusPublished
FundersMinistry of Economy and Competitiveness (Spain), Ministry of Economy and Competitiveness (Spain) and Ministry of Economy and Competitiveness (Spain)
Publication date31/12/2019
Publication date online04/09/2019
Date accepted by journal03/09/2019
URLhttp://hdl.handle.net/1893/35889
PublisherMDPI AG
eISSN2073-4425

People (1)

Dr Rose Ruiz Daniels

Dr Rose Ruiz Daniels

Lecturer in Aquaculture Genomics, Institute of Aquaculture

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