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Methods Mol Biol. 2016;1361:345-60. doi: 10.1007/978-1-4939-3079-1_19.

On the Mapping of Epistatic Genetic Interactions in Natural Isolates: Combining Classical Genetics and Genomics.

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Department of Genetics, Genomics and Microbiology, CNRS, UMR7156, Université de Strasbourg, Strasbourg, France.
Department of Genetics, Genomics and Microbiology, CNRS, UMR7156, Université de Strasbourg, Strasbourg, France.


Genetic variation within species is the substrate of evolution. Epistasis, which designates the non-additive interaction between loci affecting a specific phenotype, could be one of the possible outcomes of genetic diversity. Dissecting the basis of such interactions is of current interest in different fields of biology, from exploring the gene regulatory network, to complex disease genetics, to the onset of reproductive isolation and speciation. We present here a general workflow to identify epistatic interactions between independently evolving loci in natural populations of the yeast Saccharomyces cerevisiae. The idea is to exploit the genetic diversity present in the species by evaluating a large number of crosses and analyzing the phenotypic distribution in the offspring. For a cross of interest, both parental strains would have a similar phenotypic value, whereas the resulting offspring would have a bimodal distribution of the phenotype, possibly indicating the presence of epistasis. Classical segregation analysis of the tetrads uncovers the penetrance and complexity of the interaction. In addition, this segregation could serve as the guidelines for choosing appropriate mapping strategies to narrow down the genomic regions involved. Depending on the segregation patterns observed, we propose different mapping strategies based on bulk segregant analysis or consecutive backcrosses followed by high-throughput genome sequencing. Our method is generally applicable to all systems with a haplodiplobiontic life cycle and allows high resolution mapping of interacting loci that govern various DNA polymorphisms from single nucleotide mutations to large-scale structural variations.


Bimodal trait; Bulk segregant analysis; Genetic interaction; Introgression; Next-generation sequencing; Segregation

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