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The research project is related to evolutionary biology and aims to investigate the variation in evolutionary patterns of polymorphism induced by domestication, at the genome scale, using high throughput sequencing technologies (HTS), in 3 related horticultural crop species, belonging to the Solanaceae family: tomato, pepper and eggplant both at (1) the intra specific level and (2) the interspecific level. Surprisingly, only few studies have investigated such patterns in nuclear genes in plants. Within Solanaceae these species are of both economical and scientific interest and have undergone different domestication history. We are specifically targeting the transcriptome of both domestic and wild accessions in each species while using (1) methodological approaches in evolutionary biology to reveal genes under positive or stabilizing selection, (2) use statistical developments to investigate domestication scenarios and (3) conduct a comparative genomic study to decipher the similarity and differences in nucleotide patterns and expression modifications induced by the domestication across the 3 species.
During the report period (2012-2016), for each of the three species, we collected the sequencing data, adapted and tuned an existing analytical pipeline to detect sequence variants. From the mapped data, we achieved population genomics analyses to decipher and compare the genome-wide patterns of nucleotide diversity between crop and wild groups for each species. In tomato, we inferred the demographic history of the species using a two-dimensions site frequency spectrum approach, as implemented in the software dadi, to the variation of parameters such as population migration or population size during the domestication process. From the gene expression level we conducted the detection of differentially expressed genes (DEG) between the crop and the wild group in tomato. From these DEG, we tested whether the co-expression patterns of these DEG was also affected by the domestication process. Finally, gene ontologies were associated to the DEG.
Following my hiring as a research associate, I developed my own independent thinking and leadership qualities through the supervising of technicians and Msc. and PhD students. I gained knowledge in bioinformatic by learning a scripting language (python). In 2015, I succeeded in getting a PhD grant and I had the opportunity to hire a PhD student to work on the present project, for a 3 years period.
The methods developed and the results obtained were disseminated to my host institution through bioinformatic working sessions but also towards the scientific community (at the European level) and private breeding companies through oral communications mainly. A webpage dedicated to the researched project was developed to ensure the dissemination of the obtained results.

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