Banca de DEFESA: PITÁGORAS DE AZEVEDO ALVES SOBRINHO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : PITÁGORAS DE AZEVEDO ALVES SOBRINHO
DATE: 29/01/2021
TIME: 13:00
LOCAL: Google Meet meet.google.com/ubw-bfhq-xqq
TITLE:

RNA-Gatherer: a computational tool for annotation of non-coding RNAs in understudied organisms

KEY WORDS:

ncRNA. Arapaima Gigas. Gene Annotation. Function Prediction

PAGES: 76
BIG AREA: Ciências Biológicas
AREA: Biologia Geral
SUMMARY:

Non-coding RNAs are molecules that play decisive roles in several types of gene regulation. Identifying them is necessary for understanding the genetics of a species. Several factors, such as: low level of expression, the broad spectrum of subtypes, diverse attributes, heterogeneous functions and absence of homology between species; make the detection of ncRNAs genes a challenge. The latest bioinformatics strategies for detecting ncRNA genes have tried to identify their locations in the genomes and their secondary structures, using covariance models and artificial intelligence. The co-expression of these genes has been computationally analyzed in order to reveal their functional annotations. However, there is no consensus on which metrics and parameters to use in the process of predicting the functions of these molecules. In organisms little known, such as Arapaima gigas, the lack of reference information increases the difficulty. Additionally, even for known long non-coding RNAs, there is little functional information, which makes it difficult to explain the roles of these genes. In this work, we describe a software for discovering the non-coding genes, including their diverse types, and their functions in eukaryotic genomes. It was validated by annotating a model species (Mus musculus) and then used to explore the landscape of ncRNA in Arapaima gigas. Comparing the similarity between the functions of co- expressed genes allowed us to define confidence levels for the metrics that measure co-expression, and thus, develop a pipeline for predicting lncRNA functions, which includes metrics for non-linear correlations. The described software suite made 63307 non-coding annotations in A. gigas, including 11 types of ncRNA and 4 types of cis-regulatory regions. Of these annotations, only 706 are similar to ncRNAs already known in other species and the remaining were never described before. The exploratory analysis of lncRNA also revealed 19854 tissue specific lncRNAs and 256 lncRNAs ubiquitously expressed. Predicting the functions of these molecules revealed RNAs involved in skin pigmentation, sex differentiation, growth and defense against tumors.

BANKING MEMBERS:
Presidente - 055.795.577-79 - WILFREDO BLANCO FIGUEROLA - UFRN
Interno - 2170415 - JORGE ESTEFANO SANTANA DE SOUZA
Externo à Instituição - ÂNDREA KELY CAMPOS RIBEIRO DOS SANTOS - UFPA