0% Complete
Home
/
15th International Conference on Computer and Knowledge Engineering
Characterizing Microsatellite Distribution Patterns Across Distinct Gene Categories in Human
Authors :
Elahe Mehrazin
1
Mahmoud Naghibzadeh
2
Sara Jamali
3
1- Dept. of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
2- Dept. of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
3- Dept. of Medical Genetics, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
Keywords :
Genome،Gene،Microsatellite،Coding Sequence،Protein-Coding genes،Simple Sequence Repeat (SSR)،Distribution pattern،Long non-coding RNAs،protein
Abstract :
Microsatellites are genomic regions composed of short repeat units (typically 1–6 base pairs) that are tandemly repeated multiple times and are distributed throughout the genome of various organisms, including humans. With the growing understanding of their roles in the human genome, such as involvement in the development of diseases like hereditary neurological disorders and certain colorectal tumors, as well as their use as genetic markers in population studies and forensic science, numerous algorithms have been developed to identify these sequences across the genome. To date, many studies using such algorithms have statistically analyzed the distribution patterns of microsatellites across different genomic regions, though most of them have focused on exonic, intronic, intergenic, and coding regions. In this study, we used SQL and the powerful Power BI tool to investigate the distribution patterns of microsatellite sequences in the human genome, with a specific emphasis on different types of genes and coding regions. The results revealed that the distribution pattern of microsatellites varies among different gene types. Protein-coding genes contained the highest number of microsatellites, whereas small nucleolar RNA (snoRNA) and microRNA (miRNA) genes included very few, and some gene types, such as small nuclear RNA (snRNA) and transfer RNA (tRNA), were completely devoid of them. Interestingly, protein-coding genes had the highest frequency of microsatellite occurrences, including long repeats over 100 nucleotides. Distribution analysis in coding regions showed that among all repeats, trinucleotide sequences such as ACG, CAG, and GAG were the most frequently found in Known messenger RNA (mRNA), contributing to the formation of repeat-rich polypeptides composed of threonine, glutamine, and glutamic acid. We also provided a list of protein-coding genes with the highest number of protein products encoded from microsatellite-containing regions.
Papers List
List of archived papers
Maximum diffusion of news in social media with the approach of reducing the search space
Masoud Karian
Leveraging the Power of Object Detection Models in Identifying Litter for a Significant Reduction in Environmental Pollution
Lim Zhen Xian - Ervin Gubin Moung - Jason Teo Tze Wi - Nordin Saad - Farashazillah Yahya - Tiong Lin Rui - Ali Farzamnia
XAI for Transparent Autonomous Vehicles: A New Approach to Understanding Decision-Making in Self-driving Cars
Maryam Sadat Hosseini Azad - Amir Abbas Hamidi Imani - Shahriar Baradaran Shokouhi
Hate Sentiment Recognition System For Persian Language
Pegah Shams jey - Arash Hemmati - Ramin Toosi - Mohammad ali Akhaee
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm
Zaniar Sharifi - Khabat Soltanian - Ali Amiri
Soccer Video Event Detection Using Metric Learning
Ali Karimi - Ramin Toosi - Mohammad Ali Akhaee
Enhanced Duplicate Bug Report Detection in Anonymized Environments: A Parallelized Multi-Task Learning Framework
Alireza Shorafa - Abolfazl Zarghani
Security Analysis of MiniApps: Vulnerabilities, Exploits, and a Tailored Mitigation Framework
Keyhan Mohammadi - Arman Moradi - Reza Ebrahimi Atani
A Systematic Embedded Software Design Flow for Robotic Applications
Navid Mahdian - Seyed-Hosein Attarzadeh-Niaki - Armin Salimi-Badr
ROCT-Net: A new ensemble deep convolutional model with improved spatial resolution learning for detecting common diseases from retinal OCT images
Mohammad Rahimzadeh - Mahmoud Reza Mohammadi
more
Samin Hamayesh - Version 43.7.0