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A Comprehensive Prescription for Plant miRNA Identification
microRNAs (miRNAs) are tiny ribo-regulatory molecules involved in various essential pathways for persistence of cellular life, such as development, environmental adaptation, and stress response. In recent years, miRNAs have become a major focus in molecular biology because of their functional and di...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5258749/ https://www.ncbi.nlm.nih.gov/pubmed/28174574 http://dx.doi.org/10.3389/fpls.2016.02058 |
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author | Alptekin, Burcu Akpinar, Bala A. Budak, Hikmet |
author_facet | Alptekin, Burcu Akpinar, Bala A. Budak, Hikmet |
author_sort | Alptekin, Burcu |
collection | PubMed |
description | microRNAs (miRNAs) are tiny ribo-regulatory molecules involved in various essential pathways for persistence of cellular life, such as development, environmental adaptation, and stress response. In recent years, miRNAs have become a major focus in molecular biology because of their functional and diagnostic importance. This interest in miRNA research has resulted in the development of many specific software and pipelines for the identification of miRNAs and their specific targets, which is the key for the elucidation of miRNA-modulated gene expression. While the well-recognized importance of miRNAs in clinical research pushed the emergence of many useful computational identification approaches in animals, available software and pipelines are fewer for plants. Additionally, existing approaches suffers from mis-identification and annotation of plant miRNAs since the miRNA mining process for plants is highly prone to false-positives, particularly in cereals which have a highly repetitive genome. Our group developed a homology-based in silico miRNA identification approach for plants, which utilizes two Perl scripts “SUmirFind” and “SUmirFold” and since then, this method helped identify many miRNAs particularly from crop species such as Triticum or Aegliops. Herein, we describe a comprehensive updated guideline by the implementation of two new scripts, “SUmirPredictor” and “SUmirLocator,” and refinements to our previous method in order to identify genuine miRNAs with increased sensitivity in consideration of miRNA identification problems in plants. Recent updates enable our method to provide more reliable and precise results in an automated fashion in addition to solutions for elimination of most false-positive predictions, miRNA naming and miRNA mis-annotation. It also provides a comprehensive view to genome/transcriptome-wide location of miRNA precursors as well as their association with transposable elements. The “SUmirPredictor” and “SUmirLocator” scripts are freely available together with a reference high-confidence plant miRNA list. |
format | Online Article Text |
id | pubmed-5258749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52587492017-02-07 A Comprehensive Prescription for Plant miRNA Identification Alptekin, Burcu Akpinar, Bala A. Budak, Hikmet Front Plant Sci Plant Science microRNAs (miRNAs) are tiny ribo-regulatory molecules involved in various essential pathways for persistence of cellular life, such as development, environmental adaptation, and stress response. In recent years, miRNAs have become a major focus in molecular biology because of their functional and diagnostic importance. This interest in miRNA research has resulted in the development of many specific software and pipelines for the identification of miRNAs and their specific targets, which is the key for the elucidation of miRNA-modulated gene expression. While the well-recognized importance of miRNAs in clinical research pushed the emergence of many useful computational identification approaches in animals, available software and pipelines are fewer for plants. Additionally, existing approaches suffers from mis-identification and annotation of plant miRNAs since the miRNA mining process for plants is highly prone to false-positives, particularly in cereals which have a highly repetitive genome. Our group developed a homology-based in silico miRNA identification approach for plants, which utilizes two Perl scripts “SUmirFind” and “SUmirFold” and since then, this method helped identify many miRNAs particularly from crop species such as Triticum or Aegliops. Herein, we describe a comprehensive updated guideline by the implementation of two new scripts, “SUmirPredictor” and “SUmirLocator,” and refinements to our previous method in order to identify genuine miRNAs with increased sensitivity in consideration of miRNA identification problems in plants. Recent updates enable our method to provide more reliable and precise results in an automated fashion in addition to solutions for elimination of most false-positive predictions, miRNA naming and miRNA mis-annotation. It also provides a comprehensive view to genome/transcriptome-wide location of miRNA precursors as well as their association with transposable elements. The “SUmirPredictor” and “SUmirLocator” scripts are freely available together with a reference high-confidence plant miRNA list. Frontiers Media S.A. 2017-01-24 /pmc/articles/PMC5258749/ /pubmed/28174574 http://dx.doi.org/10.3389/fpls.2016.02058 Text en Copyright © 2017 Alptekin, Akpinar and Budak. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Alptekin, Burcu Akpinar, Bala A. Budak, Hikmet A Comprehensive Prescription for Plant miRNA Identification |
title | A Comprehensive Prescription for Plant miRNA Identification |
title_full | A Comprehensive Prescription for Plant miRNA Identification |
title_fullStr | A Comprehensive Prescription for Plant miRNA Identification |
title_full_unstemmed | A Comprehensive Prescription for Plant miRNA Identification |
title_short | A Comprehensive Prescription for Plant miRNA Identification |
title_sort | comprehensive prescription for plant mirna identification |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5258749/ https://www.ncbi.nlm.nih.gov/pubmed/28174574 http://dx.doi.org/10.3389/fpls.2016.02058 |
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