Evidence map›Paper›PMID 34791188›Full record

ArticleG3 (Bethesda, Md.)2022

Application of RNA subcellular fraction estimation method to explore RNA localization regulation.

Xiaomin Dai, Yangmengjie Li, Weizhen Liu, Xiuqi Pan, Chenyue Guo, Xiaojing Zhao, Jingwen Lv, Haixin Lei, Liye Zhang

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 45% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Xiaomin DaiSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Yangmengjie LiInstitute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian 116044, China.
Weizhen LiuSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Xiuqi PanSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Chenyue GuoSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Xiaojing ZhaoSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Jingwen LvSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Haixin LeiInstitute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian 116044, China.
Liye ZhangSchool of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.ORCID 0000-0003-2104-6828
ShanghaiTech University · CNChinese Academy of Sciences · CNDalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Biological PhenomenaRNAProtein IsoformsSubcellular FractionsProtein IsoformsRNAcis-elementsisoformnuclear retentionRBPRNA localizationsubcellular RNA abundance

Identifiers

PMID34791188
PMCPMC8727992
OpenAlexW3213225851

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.