Landscape genomics training (AUS) ‒ LASIG ‐ EPFL

Pop. and Landscape genomics workshop, Canberra 2014

Contact:

Session notes and slides :

Course (.pdf document)

The practical work on landscape genomics uses data on Loblolly pine (Pinus taeda) sampled in the US by the Eckert lab http://eckertdata.blogspot.ch/, (Eckert et al., 2010; Eckert et al., 2010). The purpose is to compute association models between SNPs data and environmental variables that will be downloaded or computed in a GIS.

We will use a GIS software mostly to visualize data (Quantum GIS), another one to produce environmental variables from Digital Elevation Models (DEMs) (SAGA GIS), and a third one to compute spatial statistics (OpenGeoda).

Quantum GIS can be found here:

For windows: http://www.qgis.org/en/site/forusers/download.html
For Mac OS: http://www.kyngchaos.com/software/qgis

SAGA GIS can be found here:

For Windows (recommended) : http://sourceforge.net/projects/saga-gis/files/
For Mac OS : http://sourceforge.net/apps/trac/saga-gis/wiki/Compiling SAGA on MacOSX
Compilation of SAGA GIS for Mac OS is quite complicated. I would recommend to borrow a computer running Windows for this part.

OpenGeoda can be found here:

For Windows
For MacOS

Landscape Genomics software

We will use are SamBada – based on multivariate logistic regressions -, LFMM, which considers population structure, and Admixture which computes membership coefficients to populations for each individual.

SamBada can be found here for Linux, Windows and Mac OS:
http://www.epfl.ch/labs/lasig/sambada
LFMM can be found here for Mac OS, Linux and Windows 64 bits (GUI version will be easier but slower): http://membres-timc.imag.fr/Eric.Frichot/lfmm/software.htm
Admixture can be found here for Linux and Mac OS: http://www.genetics.ucla.edu/software/admixture/download.html
For Windows users we recommend to install a virtual box using Ubuntu or to borrow a computer running Mac OS or Linux. You could also use STRUCTURE to obtain similar coefficients
Virtual box: https://www.virtualbox.org/wiki/Downloads
Ubuntu: http://www.ubuntu.com/download/desktop
STRUCTURE: http://pritchardlab.stanford.edu/structure_software/release_versions/v2.3.4/html/structure.html

We will also use R for statistical analyses. You can install a modified GUI for R such as R studio

R (Linux, Mac OS, Windows): http://www.r-project.org/
R Studio (Linux, Mac OS, Windows): https://www.rstudio.com/ide/download/desktop

Following packages should be installed as well:

RSAGA

Genetic Data

We transformed genetic data to PLINK format in both binary (BED) and ordinary (PED) format.

Data can be found here:

Environmental Data

Sampling locations with aridity variables can be found here:

Loblolly Pine coordinates

Several individuals have identical coordinates. In the purpose of visualizing them all in a GIS, we suggest modified coordinates.

Loblolly Pine Visualization Coordinates
Shapefile – Loblolly Pine Visualization Coordinates with admixture coefficients

Examples for Spatial Autocorrelation

We will use climatic variables from Worldclim datasets.

In the interest of time, we have created a subset for our study zone that you can download from our server : WorldClim_Subset.zip

Original datasets can be downloaded either by thiles or for the entire world:

Entire world: http://www.worldclim.org/current
By tiles: http://www.worldclim.org/tiles.php

DEMs can be found on Earth Explorer (subscription is mandatory before download):

http://earthexplorer.usgs.gov/ We will use GTOPO30 only.

If you dont want to sign up on EarthExplorer, you can download the DEM here

Recommended readings

Papers regarding practical work datasets can be found on Eckert’s blog:

http://eckertdata.blogspot.ch/ at the date of 27 January 2012

We also recommend reading papers and documentation related to the software we will use

SamBada

Joost S., Bonin A., Bruford M.W., Despres L., Conord C., Erhardt G. & Taberlet P. (2007) A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation. Molecular Ecology 16, 3955-69.

LFMM

Admixture