PREDICTION OF SMALL PROTEIN-CODING REGIONS IN THE 5’ UTR REGION OF TRANSCRIPTS.

Jéssica  De Paula Silva; Denilson Fagundes Barbosa; ALEXANDRE ROSSI PASCHOAL; ANDRE YOSHIAKI KASHIWABARA

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Submission

Paper Title

PREDICTION OF SMALL PROTEIN-CODING REGIONS IN THE 5’ UTR REGION OF TRANSCRIPTS.

Authors

Jéssica De Paula Silva
Denilson Fagundes Barbosa
ALEXANDRE ROSSI PASCHOAL
ANDRE YOSHIAKI KASHIWABARA

Modality

Xpress presentation

Subject area

Database and Software Development

Publishing Date

26/04/2022

Country of Publishing

Brasil

Language of Publishing

Inglês

Paper Page

https://www.even3.com.br/anais/xmeetingxp2021/420191-prediction-of-small-protein-coding-regions-in-the-5-utr-region-of-transcripts

ISBN

978-65-5941-645-5

Keywords

uORFs, Prediction, Computational methods, GHMM.

Summary

Upstream Open Reading Frames (uORF) are located in the 5'UTR region and present in about 50% of the human transcriptome, with evidence for conservation across species. In the mRNA, the uORF may present in (i) a different reading frame from the main ORF, (ii) sharing the same reading frame, and (iii) overlapping the main ORF. Relative to the main ORF, the ribosomal complex can either translate uORF and dissociate or translate uORF and remain associated with the mRNA to restart translation of the main ORF. Thus, uORF plays a regulatory role in translation and may negatively impact protein expression and contribute to the emergence of human diseases. This fact highlights the need for computational methods to advance studies involving uORF prediction to aid in the characterization of small peptides encoded by uORFs. Concerning the facts presented, we propose to adapt the models from CodAn (Coding sequence Annotator) to find the uORFs, which encode proteins, in the 5'UTR regions of the transcripts of eukaryotic organisms. This work presents a probabilistic model based on the Generalized Hidden Markov Model (GHMM) for identifying these uORFs, presenting three states to describe the transcripts based on the distributions generated. We performed a preliminary analysis for modeling purposes using public data from the species Caenorhabditis elegans and Drosophila melanogaster. Our initial studies show that uORFs have non-canonical start codons and an estimated length of 33 codons and show overlap concerning the main ORF in these organisms. In conclusion, to properly model the uORF, we need to train novel probabilistic models representing the start codon and the duration distribution of each GHMM state.

Title of the Event: X-Meeting XPerience 2021
Title of the Proceedings of the event: X-Meeting presentations
Name of the Publisher: Even3
Means of Dissemination: Meio Digital

How to cite

SILVA, Jéssica De Paula et al.. PREDICTION OF SMALL PROTEIN-CODING REGIONS IN THE 5’ UTR REGION OF TRANSCRIPTS... In: X-Meeting presentations. Anais...São Paulo(SP) AB3C, 2021. Available in: https//www.even3.com.br/anais/xmeetingxp2021/420191-PREDICTION-OF-SMALL-PROTEIN-CODING-REGIONS-IN-THE-5-UTR-REGION-OF-TRANSCRIPTS. Access in: 06/06/2025