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Interview with Dr Nicolas Gilleman

Posted Mon, Sep, 28,2015

This author interview is by Dr Nicolas Guillemin, of Université Laval. Dr Guillemin's full paper, A Genetical Genomics Methodology to Identify Genetic Markers of a Bovine Fertility Phenotype Based on CYP19A1 Gene Expression, is available for download in Gene Expression to Genetical Genomics.

Please summarize for readers the content of your article.
This article describes my postdoctoral work to set a new methodology to identify single-nucleotide polymorphisms (SNPs) in dairy cattle, based on the genetical genomics principle. Genetical genomics conjugates both genetics and genomics within the same samples; genomics to generate a gene list to study with genetics. That way, it decreases the part of genomic DNA to genotype. This technique is also accurate and allows us to zoom inside QTL (quantitative trait loci.) For example, I identified some SNPs which are in known QTL. Previous studies demonstrated that such regions are related with the trait of interest, but have only indirect genetic markers. My study identified direct SNP markers, meaning the industry can make genetic tests directly with those SNPs.

How did you come to be involved in your area of study?
After my PhD in meat tenderness and proteomics, I had the opportunity to do a postdoc to set prediction models - from SNPs markers - and set up a new methodology. I was interested by the challenge. Moreover, I worked on a complex phenotype during my PhD and my postdoc also focused on a complex phenotype (fertility). I like to study such phenotypes and decode DNA to identify lever for phenotypes.

What was previously known about the topic of your article?
From a biology point a view, some QTL regions, genes, and SNPs were already known for fertility. With the aromatase gene expression, I needed to start from 0 as previous information was generated in a different context (and not accurate to take directly) or just hidden by other labs who are already working on it (information is rarely shared in the domain.)
From a methodological point of view, this technique has never been used on bovine. I also adapted the genetical genomics to the laboratory and university's capabilities and materials. Some interesting papers demonstrated that genetical genomics successfully identified genetic markers of various phenotypes and models, so it should work on bovine too. I was also inspired by an article of Fan Liu (2009) for the statistical methodology. He kindly recommended I do my analysis with R and dedicated modules. And of course, I was inspired by Ritsert Jansen for the genetical genomics principle.

How has your work in this area advanced understanding of the topic?
Thanks to this work, new SNPs have been identified, and some previously known QTL were explained. For industry, it means they can do accurate genetic tests, based on SNPs which directly influence the complex phenotype.

What do you regard as being the most important aspect of the results reported in the article?
It could be strange, but for me the most important part is not the SNPs identification. To me, it is the methodology itself which is the main result. Thanks to the genetical genomics principle, I was able to identify SNPs markers of complex phenotypes. My work adapted this principle and demonstrated that this method is able to identify significant SNP markers of complex phenotypes.
Since my postdoc work in Canada, I moved to Zagreb, on a 4 year mission to set up a new laboratory at the Faculty of Veterinary Medicine. I will be in charge of the genetics/genomics department inside an ERA chair project (http://www.vetmedzg.eu/en/)

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