Non-coding DNA: A Methodology for Detection and Analysis of Pseudogenes

Gabriella Trucco, Vittorio Cerioli

2021

Abstract

It is well known that elements lying outside the coding regions of the human genome are involved in many human diseases. Therefore, the efforts to detect and characterize functional elements in the non-coding regions are rapidly increasing. Among many types of non-coding DNA, pseudogenes are sequences that share some similarities with their parental genes but have lost their ability to code for proteins. In this paper, we propose a methodology for detection and analysis of pseudogenes, based on transition probabilities of the nucleotides and their occurrences. The 1000 base pairs length downstream region of each detected pseudogene is analyzed in order to find a polyA tail and a polyadenylation signal. We implemented a Hidden Markov Model with the Viterbi algorithm to decode the upstream regions of the previously detected pseudogenes in order to search for CpG islands. In order to identify motif signals in the selected pseudogenes, we implemented the Gibbs sampling algorithm and we executed it on the flanking regions of some pseudogenes. Results demonstrate that the proposed methodology is an efficacious solution to detect new potential loci, especially when the query coverage of the alignment is shorter than the coding strand. These loci can be classed as pseudogene fragments.

Paper Citation

in Harvard Style

Trucco G. and Cerioli V. (2021). Non-coding DNA: A Methodology for Detection and Analysis of Pseudogenes. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 3: BIOINFORMATICS; ISBN 978-989-758-490-9, SciTePress, pages 93-100. DOI: 10.5220/0010190400002865

in Bibtex Style

@conference{bioinformatics21,
author={Gabriella Trucco and Vittorio Cerioli},
title={Non-coding DNA: A Methodology for Detection and Analysis of Pseudogenes},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 3: BIOINFORMATICS},
year={2021},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010190400002865},
isbn={978-989-758-490-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 3: BIOINFORMATICS
TI - Non-coding DNA: A Methodology for Detection and Analysis of Pseudogenes
SN - 978-989-758-490-9
AU - Trucco G.
AU - Cerioli V.
PY - 2021
SP - 93
EP - 100
DO - 10.5220/0010190400002865
PB - SciTePress