Genomics of clinal local adaptation in Pinus sylvestris under continuous environmental and spatial genetic setting

• Published in: bioRxiv
• Main Authors: Tyrmi, Jaakko S, Vuosku, Jaana, Acosta, Juan J, Li, Zhen, Sterck, Lieven, Savolainen, Outi, Pyhajarvi, Tanja
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 27.05.2019; Cold Spring Harbor Laboratory
• Edition: 1.3
• Subjects: Adaptation; Breeding; Decay; Environmental conditions; Genetic diversity; Genomes; Genomics; Keystone species; Linkage disequilibrium; Pinus sylvestris; Population structure; Recombination; Resource management; population genetics – empirical; adaptation; landscape genetics; gymnosperms
• DOI: 10.1101/647412
• ISSN: 2692-8205

In species with large continuous distributions the phenotypic signal of local adaptation is frequently clear, but the genetic background often remains elusive. Here, we examine the patterns of genetic diversity in Pinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range, spanning from mountains of southern Spain to taigas of eastern Siberia. Decades of forestry research indicate it is locally adapted to the various environmental conditions found within its range. Yet, little is known about the molecular basis of this adaptation and details of the species population structure remains poorly characterized at the genome-wide level, as the massive size and repetitive nature of conifer genomes has prevented large scale genomic surveys. We have now generated a genome-wide dataset using a targeted sequencing approach and uncovered a very limited pattern of population structure within the species main range, along with rapid decay of linkage disequilibrium within the genome. Using divergence-based and landscape genomics methods we found several loci putatively underlying local adaptation. With divergence-based methods we discovered a very large putative inversion, spanning over 300 Mbp, present in the eastern part of the species distribution and possibly contributing to local adaptation. Better characterization of the genomic variation will contribute to breeding and genetic resource management and the detection of the large inversion may also have consequences for tree breeding as it has potential to limit recombination in the region. Footnotes * Figure 4 revised.