Development of a pipeline for analyzing the gene expression profile of transcripts

• Grant number: 22/07085-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2022
• End date: July 31, 2023
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Mariana Camargo Maschietto
• Grantee: Julia de Pietro Bigi
• Host Institution: Centro Infantil de Investigações Hematológicas Dr Domingos A Boldrini (CIB). Campinas , SP, Brazil

Abstract

DNA molecules contain genetic information about organisms in their composition. Gene expression is the process by which stretches of DNA are transcribed into different types of RNA, coding or non-coding, with the coding being translated into proteins, impacting the phenotype and function of cells. The observation of this process under different conditions is relevant, for example, to identify mechanisms associated with diseases such as cell signaling pathways, possible biomarkers that can be used for diagnosis or therapeutic targets. Advances in sequencing and bioinformatics techniques have made it possible to analyze a large number of transcripts simultaneously. Thus, the main objective of this project is to develop a reproducible pipeline for analyzing the gene expression profile of transcripts. This pipeline includes counting the expression levels in each sample, annotating the transcripts, their cellular and metabolic pathways, gene co-expression networks and principal component analysis. Each stage of this methodology will be carried out by software or bioinformatics packages. For annotation of transcripts, DAVID and Annocript were chosen for comparison. In the case of differential expression analysis, DESeq2 and edgeR softwares were selected. In turn, in the construction of networks, the GWENA and WGCNA packages will be used. Finally, in the analysis of principal components, GEPHI and plotPCA softwares were chosen. The different programs will be validated using data obtained from public repositories and/or internal data from the Boldrini Children's Center already analyzed in the literature, including 35 osteosarcoma samples. Those tools that obtain the best results, when compared to the existing literature, will be incorporated in the definitive pipeline. (AU)