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Bioinformatic discovery of novel exons expressed in human brain and their association with neurodevelopmental disorders

par Reggiani, Claudio
Président du jury Jansen, Maarten
Promoteur Smits, Guillaume
Co-Promoteur Bontempi, Gianluca
Publication Non publié, 2018-03-16

Thèse de doctorat

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Résumé :

An important quest in genomics since the publication of the first complete human genome in 2003 has been its functional annotation. DNA holds the instructions to the production of the components necessary for the life of cells and organisms. A complete functional catalog of genomic regions will help the understanding of the cell body and its dynamics, thus creating links between genotype and phenotypic traits. The need for annotations prompted the development of several bioinformatic methods. In the context of promoter and first exon predictors, the majority of models relies principally on structural and chemical properties of the DNA sequence. Some of them integrate information from epigenomic and transcriptomic data as secondary features. Current genomic research asserts that reference genome annotations are far from being fully annotated (human organism included).Physicians rely on reference genome annotations and functional databases to understand disorders with genetic basis, and missing annotations may lead to unresolved cases. Because of their complexity, neurodevelopmental disorders are under study to figure out all genetic regions that are involved. Besides functional validation on model organisms, the search for genotype-phenotype association is supported by statistical analysis, which is typically biased towards known functional regions.This thesis addresses the use of an in-silico integrative analysis to improve reference genome annotations and discover novel functional regions associated with neurodevelopemental disorders. The contributions outlined in this document have practical applications in clinical settings. The presented bioinformatic method is based on epigenomic and transcriptomic data, thus excluding features from DNA sequence. Such integrative approach applied on brain data allowed the discovery of two novel promoters and coding first exons in the human DLG2 gene, which were also found to be statistically associated with neurodevelopmental disorders and intellectual disability in particular. The application of the same methodology to the whole genome resulted in the discovery of other novel exons expressed in brain. Concerning the in-silico method itself, the research demanded a high number of functional and clinical datasets to properly support and validate our discoveries.This work describes a bioinformatic method for genome annotation, in the specific area of promoter and first exons. So far the method has been applied on brain data, and the extension to the whole body data would be a logical by-product. We will leverage distributed frameworks to tackle the even higher amount of data to analyse, a task that has already begun. Another interesting research direction that came up from this work is the temporal enrichment analysis of epigenomics data across different developmental stages, in which changes of epigenomic enrichment suggest time-specific and tissue-specific functional gene and gene isoforms regulation.