Identification and prediction of biological outcomes of single nucleotide polymorphisms in non-coding RNA sequences and their targets in Canis lupus familiaris

• Grant number: 24/10086-4
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: May 01, 2025
• End date: March 31, 2027
• Field of knowledge: Biological Sciences - Genetics - Animal Genetics
• Principal Investigator: Flavia Lombardi Lopes
• Grantee: Matheus Fujimura Soares
• Host Institution: Faculdade de Medicina Veterinária (FMVA). Universidade Estadual Paulista (UNESP). Campus de Araçatuba. Araçatuba , SP, Brazil

Abstract

The next-generation sequencing popularization has significantly increased the amount of data produced for analysis in genetic and functional studies. The most common genetic mutation is the single nucleotide polymorphism (SNP). Studies mainly focus on the association of SNPs in protein-coding regions, but the majority of SNPs are in non-coding regions. Among the non-coding regions are those that give rise to non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). miRNAs play a role in the post-transcriptional regulation of mRNAs by binding their seed region to the 3' UTR region of target mRNAs. On the other hand, lncRNAs perform various biological functions, such as chromatin regulation, transcriptional regulation, nuclear organization and post-transcriptional regulation. SNPs located in regions of miRNAs and lncRNAs in humans and livestock animals have already been associated with altered phenotypes and diseases. However, studies are poorly developed in the specie that has the largest number of mapped SNPs among animals, the domestic dog (Canis lupus familiaris). Therefore, our goal is to identify SNPs in non-coding regions of the dog genome, especially miRNAs, 3' UTR regions of mRNA-targets of miRNAs, and lncRNAs and infer biological significance, since this specie is an excellent model for comparative biology studies with humans. To do this, we will use the largest current database of SNPs in domestic dogs, together with reliable and constantly updated databases of miRNAs, 3' UTR positions and lncRNAs in the specie. We will also use computational tools to verify the presence of SNPs in these regions and provide biological inferences.