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Tytuł:
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MicroRNA annotation in plants: current status and challenges.
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Autorzy:
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Zhao Y; Beijing Academy of Agriculture and Forestry Sciences, China.
Kuang Z; Peking University and Beijing Academy of Agriculture and Forestry Sciences, China.
Wang Y; Peking University, China.
Li L; School of Advanced Agricultural Sciences and School of Life Sciences at the Peking University, China.
Yang X; Beijing Academy of Agriculture and Forestry Sciences, China.
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Źródło:
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Briefings in bioinformatics [Brief Bioinform] 2021 Sep 02; Vol. 22 (5).
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Typ publikacji:
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Journal Article; Research Support, Non-U.S. Gov't; Review
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Język:
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English
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Imprint Name(s):
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Publication: Oxford : Oxford University Press
Original Publication: London ; Birmingham, AL : H. Stewart Publications, [2000-
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MeSH Terms:
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Databases, Genetic*
Computational Biology/*methods
MicroRNAs/*genetics
Plants/*genetics
RNA, Plant/*genetics
Artificial Intelligence ; Computational Biology/statistics & numerical data ; Gene Expression Profiling/methods ; Gene Expression Regulation, Plant ; Gene Regulatory Networks/genetics ; Molecular Sequence Annotation/methods ; Plants/classification
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Contributed Indexing:
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Keywords: artificial intelligence; bioinformatics tools; miRNA annotation; miRNA database; microRNA (miRNA); plant
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Substance Nomenclature:
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0 (MicroRNAs)
0 (RNA, Plant)
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Entry Date(s):
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Date Created: 20210323 Date Completed: 20211122 Latest Revision: 20211122
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Update Code:
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20240105
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DOI:
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10.1093/bib/bbab075
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PMID:
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33754625
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Last two decades, the studies on microRNAs (miRNAs) and the numbers of annotated miRNAs in plants and animals have surged. Herein, we reviewed the current progress and challenges of miRNA annotation in plants. Via the comparison of plant and animal miRNAs, we pinpointed out the difficulties on plant miRNA annotation and proposed potential solutions. In terms of recalling the history of methods and criteria in plant miRNA annotation, we detailed how the major progresses made and evolved. By collecting and categorizing bioinformatics tools for plant miRNA annotation, we surveyed their advantages and disadvantages, especially for ones with the principle of mimicking the miRNA biogenesis pathway by parsing deeply sequenced small RNA (sRNA) libraries. In addition, we summarized all available databases hosting plant miRNAs, and posted the potential optimization solutions such as how to increase the signal-to-noise ratio (SNR) in these databases. Finally, we discussed the challenges and perspectives of plant miRNA annotations, and indicated the possibilities offered by an all-in-one tool and platform according to the integration of artificial intelligence.
(© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
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