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Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis
Degradome sequencing (degradome-seq) was widely used for cleavage site mapping on the microRNA (miRNA) targets. Here, the application value of degradome-seq data in tracking the miRNA processing intermediates was reported. By adopting the parameter “signal/noise” ratio, prominent degradome signals o...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6246748/ https://www.ncbi.nlm.nih.gov/pubmed/30487815 http://dx.doi.org/10.3389/fgene.2018.00546 |
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author | Yu, Dongliang Xu, Min Ito, Hidetaka Shao, Weishan Ma, Xiaoxia Wang, Huizhong Meng, Yijun |
author_facet | Yu, Dongliang Xu, Min Ito, Hidetaka Shao, Weishan Ma, Xiaoxia Wang, Huizhong Meng, Yijun |
author_sort | Yu, Dongliang |
collection | PubMed |
description | Degradome sequencing (degradome-seq) was widely used for cleavage site mapping on the microRNA (miRNA) targets. Here, the application value of degradome-seq data in tracking the miRNA processing intermediates was reported. By adopting the parameter “signal/noise” ratio, prominent degradome signals on the miRNA precursors were extracted. For the 15 species analyzed, the processing of many miRNA precursors were supported by the degradome-seq data. We found that the supporting ratio of the “high-confidence” miRNAs annotated in miRBase was much higher than that of the “low-confidence.” For a specific species, the percentage of the miRNAs with degradome-supported processing signals was elevated by the increment of degradome sampling diversity. More interestingly, the tissue- or cell line-specific processing patterns of the miRNA precursors partially contributed to the accumulation patterns of the mature miRNAs. In this study, we also provided examples to show the value of the degradome-seq data in miRNA annotation. Based on the distribution of the processing signals, a renewed model was proposed that the stems of the miRNA precursors were diced through a “single-stranded cropping” mode, and “loop-to-base” processing was much more prevalent than previously thought. Together, our results revealed the remarkable capacity of degradome-seq in tracking miRNA processing signals. |
format | Online Article Text |
id | pubmed-6246748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62467482018-11-28 Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis Yu, Dongliang Xu, Min Ito, Hidetaka Shao, Weishan Ma, Xiaoxia Wang, Huizhong Meng, Yijun Front Genet Genetics Degradome sequencing (degradome-seq) was widely used for cleavage site mapping on the microRNA (miRNA) targets. Here, the application value of degradome-seq data in tracking the miRNA processing intermediates was reported. By adopting the parameter “signal/noise” ratio, prominent degradome signals on the miRNA precursors were extracted. For the 15 species analyzed, the processing of many miRNA precursors were supported by the degradome-seq data. We found that the supporting ratio of the “high-confidence” miRNAs annotated in miRBase was much higher than that of the “low-confidence.” For a specific species, the percentage of the miRNAs with degradome-supported processing signals was elevated by the increment of degradome sampling diversity. More interestingly, the tissue- or cell line-specific processing patterns of the miRNA precursors partially contributed to the accumulation patterns of the mature miRNAs. In this study, we also provided examples to show the value of the degradome-seq data in miRNA annotation. Based on the distribution of the processing signals, a renewed model was proposed that the stems of the miRNA precursors were diced through a “single-stranded cropping” mode, and “loop-to-base” processing was much more prevalent than previously thought. Together, our results revealed the remarkable capacity of degradome-seq in tracking miRNA processing signals. Frontiers Media S.A. 2018-11-14 /pmc/articles/PMC6246748/ /pubmed/30487815 http://dx.doi.org/10.3389/fgene.2018.00546 Text en Copyright © 2018 Yu, Xu, Ito, Shao, Ma, Wang and Meng. 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) and the copyright owner(s) 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 | Genetics Yu, Dongliang Xu, Min Ito, Hidetaka Shao, Weishan Ma, Xiaoxia Wang, Huizhong Meng, Yijun Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis |
title | Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis |
title_full | Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis |
title_fullStr | Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis |
title_full_unstemmed | Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis |
title_short | Tracking microRNA Processing Signals by Degradome Sequencing Data Analysis |
title_sort | tracking microrna processing signals by degradome sequencing data analysis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6246748/ https://www.ncbi.nlm.nih.gov/pubmed/30487815 http://dx.doi.org/10.3389/fgene.2018.00546 |
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