In silico study to identify association between miRNAs and differentially expressed genes in Down Syndrome

• Grant number: 19/21548-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: November 01, 2019
• End date: October 31, 2020
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Erika Cristina Pavarino
• Grantee: Isabela Possari
• Host Institution: Faculdade de Medicina de São José do Rio Preto (FAMERP). Secretaria de Desenvolvimento Econômico (São Paulo - Estado). São José do Rio Preto , SP, Brazil

Abstract

The latest catalog of gene annotation and microRNAs (miRNAs), non-coding RNAs molecules involved in post-transcriptional gene regulation of chromosome 21, includes more than 223 coding genes and 30 miRNAs (HGNC, 2019). The contribution of these miRNAs to the Down syndrome (DS) phenotype is poorly investigated, but there is evidence some change in their expression could be related to manifestations of the syndrome. The phenotype of DS is complex and variable among individuals; it includes immunological changes that result in increased frequency of infections and autoimmune diseases. Studies have showed that some genes involved in the immune system have altered expression in individuals with DS; however, little is known about the interactions between inflammation, immune response and miRNAs expression. Taking into account the metabolic scenario of DS; differential expression of microRNAs, located on other chromosomes rather than on chromosome 21, could also result in altered expression of numerous genes, including those involved in the immune response. Thus, the present proposal aims: to perform a bioinformatics analysis (in silico) to identify an association between miRNAs and genes, related to the immune system, differentially expressed in our previous studies in children with DS, using the online software MicroT -CDS; to identify the most represented biological processes between the differentially expressed genes and the microRNAs that regulate these genes using Database for Annotation, Visualization and Integrated Discovery (DAVID) v 6.7 program and to analyze the interaction between proteins by means of the STRING t - v 11.0 tool.