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miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades
microRNAs (miRNAs) are a large class of small non-coding RNAs which post-transcriptionally regulate the expression of a large fraction of all animal genes and are important in a wide range of biological processes. Recent advances in high-throughput sequencing allow miRNA detection at unprecedented s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245920/ https://www.ncbi.nlm.nih.gov/pubmed/21911355 http://dx.doi.org/10.1093/nar/gkr688 |
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author | Friedländer, Marc R. Mackowiak, Sebastian D. Li, Na Chen, Wei Rajewsky, Nikolaus |
author_facet | Friedländer, Marc R. Mackowiak, Sebastian D. Li, Na Chen, Wei Rajewsky, Nikolaus |
author_sort | Friedländer, Marc R. |
collection | PubMed |
description | microRNAs (miRNAs) are a large class of small non-coding RNAs which post-transcriptionally regulate the expression of a large fraction of all animal genes and are important in a wide range of biological processes. Recent advances in high-throughput sequencing allow miRNA detection at unprecedented sensitivity, but the computational task of accurately identifying the miRNAs in the background of sequenced RNAs remains challenging. For this purpose, we have designed miRDeep2, a substantially improved algorithm which identifies canonical and non-canonical miRNAs such as those derived from transposable elements and informs on high-confidence candidates that are detected in multiple independent samples. Analyzing data from seven animal species representing the major animal clades, miRDeep2 identified miRNAs with an accuracy of 98.6–99.9% and reported hundreds of novel miRNAs. To test the accuracy of miRDeep2, we knocked down the miRNA biogenesis pathway in a human cell line and sequenced small RNAs before and after. The vast majority of the >100 novel miRNAs expressed in this cell line were indeed specifically downregulated, validating most miRDeep2 predictions. Last, a new miRNA expression profiling routine, low time and memory usage and user-friendly interactive graphic output can make miRDeep2 useful to a wide range of researchers. |
format | Online Article Text |
id | pubmed-3245920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-32459202012-01-03 miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades Friedländer, Marc R. Mackowiak, Sebastian D. Li, Na Chen, Wei Rajewsky, Nikolaus Nucleic Acids Res Computational Biology microRNAs (miRNAs) are a large class of small non-coding RNAs which post-transcriptionally regulate the expression of a large fraction of all animal genes and are important in a wide range of biological processes. Recent advances in high-throughput sequencing allow miRNA detection at unprecedented sensitivity, but the computational task of accurately identifying the miRNAs in the background of sequenced RNAs remains challenging. For this purpose, we have designed miRDeep2, a substantially improved algorithm which identifies canonical and non-canonical miRNAs such as those derived from transposable elements and informs on high-confidence candidates that are detected in multiple independent samples. Analyzing data from seven animal species representing the major animal clades, miRDeep2 identified miRNAs with an accuracy of 98.6–99.9% and reported hundreds of novel miRNAs. To test the accuracy of miRDeep2, we knocked down the miRNA biogenesis pathway in a human cell line and sequenced small RNAs before and after. The vast majority of the >100 novel miRNAs expressed in this cell line were indeed specifically downregulated, validating most miRDeep2 predictions. Last, a new miRNA expression profiling routine, low time and memory usage and user-friendly interactive graphic output can make miRDeep2 useful to a wide range of researchers. Oxford University Press 2012-01 2011-09-10 /pmc/articles/PMC3245920/ /pubmed/21911355 http://dx.doi.org/10.1093/nar/gkr688 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Friedländer, Marc R. Mackowiak, Sebastian D. Li, Na Chen, Wei Rajewsky, Nikolaus miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades |
title | miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades |
title_full | miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades |
title_fullStr | miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades |
title_full_unstemmed | miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades |
title_short | miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades |
title_sort | mirdeep2 accurately identifies known and hundreds of novel microrna genes in seven animal clades |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245920/ https://www.ncbi.nlm.nih.gov/pubmed/21911355 http://dx.doi.org/10.1093/nar/gkr688 |
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