Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata

Leempoel, Kevin; Parisod, Christian Gérard; Geiser, Céline; Joost, Stéphane (2018). Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata. Ecology and evolution, 8(3), pp. 1794-1806. John Wiley & Sons, Inc. 10.1002/ece3.3778

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Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS) > Ecological Genomics
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS)

UniBE Contributor:

Parisod, Christian Gérard

Subjects:

500 Science > 580 Plants (Botany)

ISSN:

2045-7758

Publisher:

John Wiley & Sons, Inc.

Language:

English

Submitter:

Peter Alfred von Ballmoos-Haas

Date Deposited:

01 May 2018 16:47

Last Modified:

01 May 2018 16:47

Publisher DOI:

10.1002/ece3.3778

Uncontrolled Keywords:

amplified fragment length polymorphism, digital elevation model, landscape genomics, local adaptation, multiscale analysis

BORIS DOI:

10.7892/boris.111732

URI:

https://boris.unibe.ch/id/eprint/111732

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