Implementation of computational approaches for identification of long noncoding RNAs involved in neural differentiation

Author(s)

Gabriel Francisco Zaniboni

• Document type: Master's Dissertation
• Press: São Paulo.
• Institution: Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI)
• Defense date: 2015-12-03

Examining board members

Eduardo Moraes Rego Reis; Helder Takashi Imoto Nakaya; Marcelo da Silva Reis

• Advisor: Eduardo Moraes Rego Reis; Alan Mitchell Durham

Abstract

Increasingly, long noncoding RNAs (lncRNAs) emerge as important regulators of cell biology, especially in differentiation processes during development. The interest in the study of functions and mechanisms of action of this class of transcripts during these processes is growing, and shows quite relevant in the neural differentiation process by which neurons and glia are generated. The P19 cell line, pluripotent cells arising from a type of murine embryonal carcinoma, is well established as an in vitro model of neural differentiation. After treatment with retinoic acid, it is capable of differentiating into neurons and glial cells (astrocytes and oligodendrocytes). In search of evidence that indicate the action of lncRNAs during the neural differentiation process, our group conducted experiments using microarrays to assess gene expression levels of lncRNAs and protein coding genes (mRNAs) during differentiation of P19 cells into neurons (mainly after 10 days of differentiation) and glial cells (mainly after 14 days of differentiation). At first was performed the reannotation of the probes relating to these microarrays lncRNAs, as the information provided in the annotation files were very scarce or outdated. LncRNAs and mRNAs records were obtained from public databases for this purpose, and at the end of this stage approximately 25.0% of the probes without annotation were reannotated with identifiers arising from these databases. From the expression data, we identified all lncRNAs and mRNAs that showed differential expression between the different studied conditions. The information of differentially expressed mRNAs were then used to perform Gene Ontology enrichment, in the ontologies biological process and molecular function. From the reannotated probes, coexpression analyses were performed for lncRNAs and mRNAs. From the crosscheck of information obtained, we selected those lncRNAs that by the principles of guilt by association proved likely to play a regulatory role in neural differentiation. Thus, the information generated in this study will serve as a basis for future studies of functional validation of these lncRNAs. (AU)

• FAPESP's process: 12/12045-6 - Implementation of computational approaches to identify long noncoding RNAs involved in neuronal differentiation
• Grantee: Gabriel Francisco Zaniboni
• Support Opportunities: Scholarships in Brazil - Master