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Monday the 14th of December 2020, at 2:00 PM, Jérôme BOURRET will defend his PhD thesis entitled

Measuring and understand codon usage bias:
collection of applications and evolution of paralogs and polyomaviruses


This PhD defence will be done by videoconference through StarLeaf. You can access it with the following link :

> https://meet.starleaf.com/4317852139/app

Apparently, the best solution is to download the StarLeaf app proposed by this like. This app won’t exactly install itself on your computer, but rather allow you to follow the defense.


Jérôme will defend this PhD thesis in front of a jury comprised of :

·      Céline Scornavacca (president)
·      Laurent Duret (referee)
·      Gwenael Piganeau (referee)
·      Anna-Sophie Fiston-Lavier (examiner)
·      Céline Bressollette (examiner)
·      Lucie Etienne (examiner)
·      Ignacio Gonzalez Bravo (PhD supervisor)
·      Samuel Alizon (PhD supervisor)


Abstract :

During the cellular translation process, the ribosomal machinery synthesizes a protein through the successive reading of codons along the messenger RNA. With each codon read, the ribosomes call upon the transfer RNAs, which are loaded with an amino acid (the basic unit of proteins). The complementarity between the codon on the mRNA and the anticodon on the tRNA is evaluated, eventually leading to the polymerization of the amino acid onto the nascent protein. There are 64 codons classically associated with 20 amino acids. Several codons, qualified as synonyms, can thus be associated with the same amino acid. Codon use bias (CUB) refers to the differential use of synonymous codons at the gene, genomic region or genome scale. CUB can be associated with mutational processes, at the origin of local peculiarities of nucleotide composition, but also with selection processes improving the protein synthesis dynamics. The influence of these two processes on CUB has been demonstrated in prokaryotes and in some eukaryotes. However, there is no strong evidence of selection acting at the Vertebrate gene level, and more specifically in mammals. Do we consider the CUB in these species from a correct angle? Do we have the necessary tools to draw such conclusions? To answer these questions, we propose a mathematical, computational and analytical approach to CUB through the analysis of vertebrate paralogs and human viruses.

We have designed a new CUB index called COUSIN (COdon Usage Similarity INdex), which quantifies the distance between the CUB of a sequence and that of a reference, and which stands out from other existing indices by its clarity in the interpretation of results. This index is implemented within an eponymous tool (http://cousin.ird.fr). In a second step, we performed a study of the evolutionary history and CUB of the Vertebrates paralogous genes Polypyrimidine Tract-Binding Protein (PTBP) whose tissue-specific expression could be associated with differences in their CUB. We show that PTBP1 paralogs appear to be mutagenically biased towards GC enrichment, while the CUB of PTBP2 paralogs may reflect a translational selection towards the use of rare codons in the genome. We interpret that the evolution of the CUB of PTBPs is compatible with a scenario of paralog sub-functionalization by differential expression during vertebrate development. Finally, we studied CUB in human viruses through human polyomaviruses (PyVs). Due to their obligate parasitism on the cellular protein synthesis machinery, the CUB of viruses could impact the clinical presentation of the infection. Our choice of human PyVs comes precisely from their genotypic diversity as well as their multiplicity of clinical manifestations. Infections with human PyVs are highly prevalent and asymptomatic but, in a context of immunosuppression, they can cause heavy and sometimes fatal tissue symptoms. Polyomavirus BK (BKPyV) is known to cause nephropathy in kidney transplant recipients. To prepare the analysis of longitudinal viremia, viruria and genetic data on kidney transplant patients, we have built two pipelines performing an analysis of the PyV genomes, and in particular of their genotype. In order to better understand the evolutionary dynamics of BKPyV in kidney disease, we have analyzed the evolution and CUB of PyVs in the context of the host-parasite relationship.