Small RNA Targets: Advances in Prediction Tools and High-Throughput Profiling

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F22%3A00128671" target="_blank" >RIV/00216224:14740/22:00128671 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2079-7737/11/12/1798" target="_blank" >https://www.mdpi.com/2079-7737/11/12/1798</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/biology11121798" target="_blank" >10.3390/biology11121798</a>

Result language

angličtina

Original language name

Small RNA Targets: Advances in Prediction Tools and High-Throughput Profiling

Original language description

Simple Summary MicroRNAs (miRNAs) are a category of small RNAs (sRNAs) that have been found to regulate gene expression. Through the mediation of proteins from the Argonaute family, miRNAs target messenger RNAs (mRNAs) for destruction (cleavage or repression). Other types of sRNAs, including transfer-RNA-derived fragments (tRFs) and small interfering RNAs (siRNAs), have been indicated as potential regulators of gene expression. The complex network of RNA-RNA interactions is still under exploration, which can be assisted by the development of computational techniques. Here, we report the recent advancements in the field of bioinformatical and Machine Learning tools for the prediction of sRNA targets, and a brief overview of the development of high-throughput sequencing technologies. MicroRNAs (miRNAs) are an abundant class of small non-coding RNAs that regulate gene expression at the post-transcriptional level. They are suggested to be involved in most biological processes of the cell primarily by targeting messenger RNAs (mRNAs) for cleavage or translational repression. Their binding to their target sites is mediated by the Argonaute (AGO) family of proteins. Thus, miRNA target prediction is pivotal for research and clinical applications. Moreover, transfer-RNA-derived fragments (tRFs) and other types of small RNAs have been found to be potent regulators of Ago-mediated gene expression. Their role in mRNA regulation is still to be fully elucidated, and advancements in the computational prediction of their targets are in their infancy. To shed light on these complex RNA-RNA interactions, the availability of good quality high-throughput data and reliable computational methods is of utmost importance. Even though the arsenal of computational approaches in the field has been enriched in the last decade, there is still a degree of discrepancy between the results they yield. This review offers an overview of the relevant advancements in the field of bioinformatics and machine learning and summarizes the key strategies utilized for small RNA target prediction. Furthermore, we report the recent development of high-throughput sequencing technologies, and explore the role of non-miRNA AGO driver sequences.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10600 - Biological sciences

Project

<a href="/en/project/GJ19-10976Y" target="_blank" >GJ19-10976Y: Seed-agnostic miRNA binding site classification</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

BIOLOGY-BASEL

ISSN

2079-7737

e-ISSN

—

Volume of the periodical

11

Issue of the periodical within the volume

12

Country of publishing house

CH - SWITZERLAND

Number of pages

24

Pages from-to

1798

UT code for WoS article

000902293400001

EID of the result in the Scopus database

2-s2.0-85144969710