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Sequence, Secondary Structure, and Phylogenetic Conservation of MicroRNAs in Arabidopsis thaliana.

Authors :
Mazhar, Muhammad Waqar
Yusof, Nik Yusnoraini
Shaheen, Tayyaba
Saif, Saira
Raza, Ahmad
Mazhar, Fatima
Source :
Bioinformatics & Biology Insights. 12/19/2022, p1-15. 15p.
Publication Year :
2022

Abstract

MicroRNAs are small non-coding RNA molecules that are produced in a cell endogenously. They are made up of 18 to 26 nucleotides in strength. Due to their evolutionary conserved nature, most of the miRNAs provide a logical basis for the prediction of novel miRNAs and their clusters in plants such as sunflowers related to the Asteraceae family. In addition, they participate in different biological processes of plants, including cell signaling and metabolism, development, growth, and tolerance to (biotic and abiotic) stresses. In this study profiling, conservation and characterization of novel miRNA possessing conserved nature in various plants and their targets annotation in sunflower (Asteraceae) were obtained by using various computational tools and software. As a result, we looked at 152 microRNAs in Arabidopsis thaliana that had already been predicted. Drought tolerance stress is mediated by these 152 non-coding RNAs. Following that, we used local alignment to predict novel microRNAs that were specific to Helianthus annuus. We used BLAST to do a local alignment, and we chose sequences with an identity of 80% to 100%. MIR156a, MIR164a, MIR165a, MIR170, MIR172a, MIR172b, MIR319a, MIR393a, MIR394a, MIR399a, MIR156h, and MIR414 are the new anticipated miRNAs. We used MFold to predict the secondary structure of new microRNAs. We used conservation analysis and phylogenetic analysis against a variety of organisms, including Gossypium hirsutum, H. annuus, A. thaliana, Triticum aestivum, Saccharum officinarum, Zea mays, Brassica napus, Solanum tuberosum, Solanum lycopersicum, and Oryza sativa, to determine the evolutionary history of these novel non-coding RNAs. Clustal W was used to analyze the evolutionary history of discovered miRNAs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11779322
Database :
Academic Search Index
Journal :
Bioinformatics & Biology Insights
Publication Type :
Academic Journal
Accession number :
160886895
Full Text :
https://doi.org/10.1177/11779322221142116