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Research within Synbreed: project S3

Our research was funded by the Synbreed program, which aimed to develop knowledge and advanced technologies to promote a sustainable agricultural production. Synbreed was funded by the German Federal Ministry of Education and Research (BMBF) within the scope of the competitive grants program “Networks of excellence in agricultural and nutrition research”.

Background:

Population genetics theory generates two key predictions. First, the expected
patterns of nucleotide diversity (SNPs frequencies) are known for various types of selection, e.g. for positive selection it is known as a selective sweep (Maynard Smith and Haig, Genet Res Camb, 1974). Second, such patterns of selection should be distinguished from the signatures resulting from the action of other forces such as structure of populations, pedigree, population size changes,... It is thus crucial when searching for footprints of selection (natural or breeding process) to analyse in extenso the structure of populations and past population size changes. The coalescent theory is a tool which can be used to do so in coordination with statistical methods of inference such as the Approximate Bayesian Computation (ABC). The key objective of the proposed project S3 is to develop such methods of inference to analyse genome wide polymorphism data in domesticated species in order to pinpoint genes under selection.

Our projects:

We worked on understanding selective and neutral processess in maize after teh whole genome duplication (work by Saurabh Pophaly) and to derive new inference methods for domesticated species with pedigree information (work by Florence Parat) or for crop species with complex demographic history (work by Florence Parat, Jean-Tristan Brandenburg and Amaryllis Vidali).