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Úvodní stránka Aktuality Volná místa Montpellier, France: PhD to identify genomic signatures of selection
Montpellier, France: PhD to identify genomic signatures of selection PDF Tisk Email
A PhD position is available at the Centre of Biology for the Management 
of Populations (CBGP) in Montpellier (France), co-funded by the French 
National Institute for Agricultural Research (INRA) and the European 
network BiodivERsA
Analysing genetic differentiation to identify genomic signatures of 
The rapid development of high throughput sequencing and genotyping 
technologies (Next Generation Sequencing, NGS) permits the comparison of 
patterns of polymorphisms at a very large number of molecular markers, 
which allows a detailed characterization of the genomic regions involved 
in the adaptation of organisms to their environment. However, most of 
the statistical methods developed so far to identify signatures of 
selection in the genomes rely on over-simplified demo-genetic models, 
and generally ignore the information brought by linkage disequilibrium 
(LD) between genetic markers.
The aim of this PhD project is to propose and evaluate new model-based 
methods to identify signatures of selection using allele frequency data 
in a Bayesian framework, along two main axes:
(i) improving the underlying demo-genetic models, by extending existing 
approaches based on a migration-drift equilibrium model (Vitalis et al. 
2014), or the explicit modelling of the divergence history of 
populations (Gautier et Vitalis, 2013). An alternative approach will 
consist in estimating the correlation structure of allele frequencies 
between populations (Guillot et al., 2014).
(ii) using the information brought by the spatial organization of 
markers (LD). This might be achieved, e.g., by integrating the 
correlation of gene frequencies at neighbouring SNPs in the models, 
using hidden Markov models or autoregressive models; or by analysing 
phased data (obtained by haplotype reconstruction using unsupervised 
classification techniques) and considering haplotype blocks as 
multi-allelic loci.
These new methods will be directly applied on NGS (pool-seq) data 
obtained within the European (BiodivERsA) programme EXOTIC, which aims 
at characterizing the genetic bases of adaptation during the invasion of 
an iconic species: the Harlequin ladybird Harmonia axyridis (Lombaert et 
al. 2014). These data, which are already available, will be used to 
contrast the genomic characteristics of native and invasive populations, 
at a worldwide scale.
We seek a highly motivated candidate with a Master degree, trained in 
mathematical modelling and/or biostatistics, with a strong interest for 
evolutionary biology and the analysis of data (NGS in particular). A 
good knowledge of population genetics principles and likelihood-based 
inference techniques will be appreciated. Advanced programming skills in 
one programming language (e.g., C, C++, Fortran), and the statistical 
software R, are required.
This PhD will be co-supervised by Renaud Vitalis and Mathieu Gautier, at 
the Centre of Biology for the Management of Populations (CBGP), in 
Montpellier, France. The application of the new methods developed on the 
Harlequin ladybird will benefit from a close collaboration with Arnaud 
Estoup and Benoit Facon.
We invite the interested candidates to send us a detailed CV, a 
motivation letter and the e-mail address of one referee, at: 

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before July 1st 2015. A first selection round will be done based on this 
information, and the successful candidates will be interviewed through 
Skype before July 10th 2015.
Funding: ca. 1 757 euros (gross) per month (for 3 years), starting 
October 1st 2015.
Montpellier is located in Southern France, and benefits  from a vibrant 
scientific community, in particular in the fields of Ecology and Evolution.
Selected publications in relation to the subject:
Gautier M and Vitalis R (2012) rehh : An R package to detect footprints 
of selection in genome-wide SNP data from haplotype structure. 
Bioinformatics, 28: 1176-1177
Gautier M and Vitalis R (2013) Inferring population histories using 
genome-wide allele frequency data. Molecular Biology and Evolution, 30: 
Guillot G, Vitalis R, le Rouzic A and Gautier M (2014) Detecting 
correlation between allele frequencies and environmental variables as a 
signature of selection. A fast computational approach for genome-wide 
studies. Spatial Statistics, 8: 145-155
Lombaert E, Guillemaud T, Lundgren J, Koch R, Facon B, Grez A, Loomans 
A, Malausa T, Nedved O, Rhule E, Staverlokk A, Steenberg T and Estoup A 
(2014) Complementarity of statistical treatments to reconstruct 
worldwide routes of invasion: the case of the Asian ladybird Harmonia 
axyridis. Molecular Ecology, 23: 5931ÂĄV6205.
Vitalis R, Gautier M, Dawson KJ, and Beaumont MA (2014) Detecting and 
measuring selection from gene frequency data. Genetics, 196: 799-817
Renaud Vitalis
Centre de Biologie pour la Gestion des Populations
755 avenue du campus Agropolis
CS 30016
34988 Montferrier-sur-Lez cedex
Tel : +33 (0)4 99 62 33 42
Fax : +33 (0)4 99 62 33 45
E-mail : 
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Web    : http://www1.montpellier.inra.fr/CBGP/?q=fr/users/vitalis-renaud
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