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Application of RNA subcellular fraction estimation method to explore RNA localization regulation
RNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation-based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized transcripts p...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8727992/ https://www.ncbi.nlm.nih.gov/pubmed/34791188 http://dx.doi.org/10.1093/g3journal/jkab371 |
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author | Dai, Xiaomin Li, Yangmengjie Liu, Weizhen Pan, Xiuqi Guo, Chenyue Zhao, Xiaojing Lv, Jingwen Lei, Haixin Zhang, Liye |
author_facet | Dai, Xiaomin Li, Yangmengjie Liu, Weizhen Pan, Xiuqi Guo, Chenyue Zhao, Xiaojing Lv, Jingwen Lei, Haixin Zhang, Liye |
author_sort | Dai, Xiaomin |
collection | PubMed |
description | RNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation-based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized transcripts per millions of different subcellular fractions without considering the difference in total RNA abundances in different fractions), however, absolute ratios may yield different results on the preference to different cellular compartment. Experimentally, adding external Spike-in RNAs to different fractionation can be used to obtain absolute ratios. In addition, a spike-in independent computational approach based on multiple linear regression model can also be used. However, currently, no custom tool is available. To solve this problem, we developed a method called subcellular fraction abundance estimator to correctly estimate relative RNA abundances of different subcellular fractionations. The ratios estimated by our method were consistent with existing reports. By applying the estimated ratios for different fractions, we explored the RNA localization pattern in cell lines and also predicted RBP motifs that were associated with different localization patterns. In addition, we showed that different isoforms of same genes could exhibit distinct localization patterns. To conclude, we believed our tool will facilitate future subcellular fractionation-related sequencing study to explore the function of RNA localization in various biological problems. |
format | Online Article Text |
id | pubmed-8727992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-87279922022-01-05 Application of RNA subcellular fraction estimation method to explore RNA localization regulation Dai, Xiaomin Li, Yangmengjie Liu, Weizhen Pan, Xiuqi Guo, Chenyue Zhao, Xiaojing Lv, Jingwen Lei, Haixin Zhang, Liye G3 (Bethesda) Investigation RNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation-based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized transcripts per millions of different subcellular fractions without considering the difference in total RNA abundances in different fractions), however, absolute ratios may yield different results on the preference to different cellular compartment. Experimentally, adding external Spike-in RNAs to different fractionation can be used to obtain absolute ratios. In addition, a spike-in independent computational approach based on multiple linear regression model can also be used. However, currently, no custom tool is available. To solve this problem, we developed a method called subcellular fraction abundance estimator to correctly estimate relative RNA abundances of different subcellular fractionations. The ratios estimated by our method were consistent with existing reports. By applying the estimated ratios for different fractions, we explored the RNA localization pattern in cell lines and also predicted RBP motifs that were associated with different localization patterns. In addition, we showed that different isoforms of same genes could exhibit distinct localization patterns. To conclude, we believed our tool will facilitate future subcellular fractionation-related sequencing study to explore the function of RNA localization in various biological problems. Oxford University Press 2021-11-13 /pmc/articles/PMC8727992/ /pubmed/34791188 http://dx.doi.org/10.1093/g3journal/jkab371 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigation Dai, Xiaomin Li, Yangmengjie Liu, Weizhen Pan, Xiuqi Guo, Chenyue Zhao, Xiaojing Lv, Jingwen Lei, Haixin Zhang, Liye Application of RNA subcellular fraction estimation method to explore RNA localization regulation |
title | Application of RNA subcellular fraction estimation method to explore RNA localization regulation |
title_full | Application of RNA subcellular fraction estimation method to explore RNA localization regulation |
title_fullStr | Application of RNA subcellular fraction estimation method to explore RNA localization regulation |
title_full_unstemmed | Application of RNA subcellular fraction estimation method to explore RNA localization regulation |
title_short | Application of RNA subcellular fraction estimation method to explore RNA localization regulation |
title_sort | application of rna subcellular fraction estimation method to explore rna localization regulation |
topic | Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8727992/ https://www.ncbi.nlm.nih.gov/pubmed/34791188 http://dx.doi.org/10.1093/g3journal/jkab371 |
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