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Master thesis

Prédiction de transcriptome : analyse comparative multi-gènes, orthologues

Nicolas Guillaudeux 1
1 Dyliss - Dynamics, Logics and Inference for biological Systems and Sequences
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : The formation of eukaryotic gene transcripts is due to an alternative splicing process that selects some regions, called exons, in which some will be translated into proteins. Partners of this study have developed a method for predicting transcripts called CG-Alcode, taking advantage of the conservation principle of sequences of the same gene between two species (called orthologous genes). This work aims to extend the method in order to deal with multi-species comparison, first based on three study species (human, mouse and dog). The study involves a cohort of 2,167 triplets of orthologous genes and is illustrated on one gene in particular : the CREM gene. The protocol used reinjects transcript predictions of an expressible source gene into the target species’ repertory. This aims to complete current knowledge and to annotate the transcriptome of the species, especially the dog transcriptome, which is still poorly documented. 7,201 transcripts are predicted that way. From there, the construction of orthology relationship graphs was implemented to provide an overview on the evolution of genes and their expressed transcripts. 83 orthologous gene triplets were found as having an identical fine gene structure between the three species, these gene triplets have been shared since the ancestor Eutheria. These results thus show a first track of understanding evolution, in terms of information gain and loss, in gene structures.
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Master thesis
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https://hal.inria.fr/hal-01948461
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  • HAL Id : hal-01948461, version 1

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Nicolas Guillaudeux. Prédiction de transcriptome : analyse comparative multi-gènes, orthologues. Bio-informatique [q-bio.QM]. 2018. ⟨hal-01948461⟩

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