Optimizing the management and sustainable
use of forest genetic resources in Europe

Summer school on ‘Integrated methods to detect polygenic adaptation from genomic data’

28 Aug – 30 Aug 2017, Zurich, Switzerland
Bird view of the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) in Birmensdorf (close to Zürich, Switzerland). Credit: WSL

Together with the Graduate Campus of University of Zürich, the EVOLTREE network and WSL, GenTree is co-sponsoring a three-day summer school at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), in Birmensdorf (close to Zürich, Switzerland) to learn about methodologies to detect polygenic adaptation from genomic data. These approaches can be applied to tree species investigated in GenTree and offer new tools to decipher the role of genetic diversity and environmental variability in shaping adaptive traits in trees.

Why this event?

Over the last decade, the genomic revolution has offered the possibility to generate tremendous amounts of data that contain valuable information on the genetic basis of phenotypic traits, such as those linked to human diseases or those involved in species' adaptation to changing environments.

Most ecologically and economically relevant traits are controlled by a large number of genes with small individual effects on trait variation, but that are connected with one another through complex developmental, metabolic, and biochemical networks. As a result, it has recently been suggested that most adaptation events in natural populations are reached via correlated changes at multiple genes at a time, for which the name polygenic adaptation has been coined.

Detecting polygenic signals of adaptation in genomes is challenging and current genomic approaches often reveal only a small proportion of the genetic determinants of trait variation. We will explore what relevant information needs to be extracted from genomic data to detect signals of polygenic selection and eventually predict phenotypic evolution.

Course objectives

This Summer School will offer the opportunity to learn new approaches to analyze genomic data to detect the signature of selection on polygenic traits, such as integrating functional data from gene interaction networks, or use information about genetic co-variation among genomic polymorphisms. Training in computational modeling will also be offered to learn how to generate genetic data and test the accuracy of proposed methods to detect signals of selection.

Who is it for?

The course is aiming at PhD students, post-docs, and researchers that are using genomic data to study local adaptation, the genetic basis of phenotypic traits, and epistasis. Hands-on exercises will be mainly in R, but there will no introductory lesson to R. Therefore, basic knowledge of R is highly recommended.


Registrations are now closed. Please visit the project website for more information.

The summer school will be followed by a symposium on the same topic (31 Aug - 1 Sept, ETH Zürich, Switzerland).

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