Unraveling the post-transcriptional regulatory chain in Leishmania by multi'omic integration.

Trypanosomatids are protozoan parasites which have evolved a gene expression system that is remarkably different from other Eukaryotes. Instead of being individually controlled by transcription factors, Trypanosomatid genes are transcribed constitutively in long arrays of tens to hundreds of functionally unrelated genes. In this study, we aim to understand how Trypanosomatids, despite this constitutive transcription system, can generate and regulate the major diversity in transcript and protein levels that is typically observed during their life cycle. Using Leishmania donovani as a model system, we will carry out the first deep characterization of transcript isoforms (using long-read PacBio sequencing) and their degree of translation ('translatome'), during the parasite's life cycle. Using state-of-the art pattern mining and machine learning approaches we will then identify mRNA sequence and structural patterns that play a role in modulating transcript stability and/or their translation efficiency. Finally, we will generate an integrated, systems biology model of protein production and its post-transcriptional regulation in Leishmania, validated by previously collected multi-?omic data. The study will lead to novel insights in the post-transcriptional regulatory chain of Trypansomatids, which remains poorly understood to this date.

Keywords:TRANSCRIPTION, TRANSCRIPTOMICS, BIOINFORMATICS, LEISHMANIA

Disciplines:Analysis of next-generation sequence data, Bioinformatics data integration and network biology, Computational biomodelling and machine learning, Development of bioinformatics software, tools and databases, Transcription and translation, Genomics, Proteomics, Transcriptomics