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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.
Affiliation
  • Dai X; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
  • Li Y; CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai 200031, China.
  • Liu W; University of Chinese Academy of Sciences, Beijing 100049, China.
  • Pan X; Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian 116044, China.
  • Guo C; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
  • Zhao X; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
  • Lv J; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
  • Lei H; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
  • Zhang L; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
G3 (Bethesda) ; 12(1)2022 01 04.
Article in En | MEDLINE | ID: mdl-34791188
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biological Phenomena / RNA Type of study: Prognostic_studies Language: En Journal: G3 (Bethesda) Year: 2022 Document type: Article Affiliation country: China Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biological Phenomena / RNA Type of study: Prognostic_studies Language: En Journal: G3 (Bethesda) Year: 2022 Document type: Article Affiliation country: China Country of publication: Reino Unido