Joel Nunes Leite Junior
@usp.br
Universidade de São Paulo
Genome and Transposable Elements
PhD student in the Interunit Postgraduate Program in Bioinformatics at the University of São Paulo (USP) under the supervision of Professor Dr. Marie-Anne Van Sluys, investigating the role of long non-coding RNAs in an experiment on the interaction of sugarcane with pathogenic and beneficial microorganisms, with a current FAPESP scholarship. He holds a bachelor's degree in Biological Sciences - Genetics Modality from the Federal University of Rio de Janeiro. He was a volunteer monitor for the General Biology discipline for the 1st period of his undergraduate degree in biology, having done his scientific initiation internship at the Laboratory of Plant Molecular Biology, at UFRJ, under the supervision of Professor Dr. Paulo Cavalcanti Gomes Ferreira, whose project consisted of using plants with altered cell cycle during the association with beneficial and pathogenic bacteria, analyzing the expression profile of microRNAs, where he was a PIBIC / CNPq scholarship holder from July 2018 to
EDUCATION
PhD student in the Interunit Postgraduate Program in Bioinformatics at the University of São Paulo (USP)
Bachelor's degree in Biological Sciences - Genetics Modality from the Federal University of Rio de Janeiro (UFRJ)
RESEARCH, TEACHING, or OTHER INTERESTS
Genetics, Plant Science, Agronomy and Crop Science, Biotechnology
FUTURE PROJECTS
DECODING THE STRUCTURAL LANDSCAPE OF TRANSPOSABLE ELEMENTS DERIVED LONG NON-CODING RNAS USING ARTIFICAL INTELLIGENCE
Long non-coding RNAs (lncRNAs) are gaining increasing recognition due to their association with what was once considered "junk DNA" often dismissed in earlier studies. However, it is now known that these sequences play a pivotal role in gene regulation and contribute significantly to organismal complexity. This class of molecules may also be derived from transposable elements (TEs) and participate in regulating these repetitive sequences, influencing development and responses to disease or stress to which the organism is exposed. Little is known about the impact of lncRNAs in polyploid genomes, such as that of sugarcane (Saccharum sp.). In addition to technical challenges related to mapping and predicting lncRNAs in a genome with millions of transcripts and over 60% TE content, there is a need for strategies to predict their function based on their structure, utilizing RNA folding models and artificial intelligence (AI).
Applications Invited
Collaborators