Evidence map›Paper›PMID 34195958›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Identification of Intronic Lariat-Derived Circular RNAs in Arabidopsis by RNA Deep Sequencing.

Taiyun Wang, Xiaotuo Zhang, Binglian Zheng

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
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

3 authors at 2 institutions in 1 country.

Taiyun WangState Key Laboratory of Genetic Engineering, Ministry of Education Key Laboratory of Biodiversity Sciences and Ecological Engineering, Collaborative Innovation Center of Genetics and Development, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai, China.
Xiaotuo ZhangState Key Laboratory of Genetic Engineering, Ministry of Education Key Laboratory of Biodiversity Sciences and Ecological Engineering, Collaborative Innovation Center of Genetics and Development, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai, China.
Binglian ZhengState Key Laboratory of Genetic Engineering, Ministry of Education Key Laboratory of Biodiversity Sciences and Ecological Engineering, Collaborative Innovation Center of Genetics and Development, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai, China. zhengbl@fudan.edu.cn.
Fudan University · CNState Key Laboratory of Genetic Engineering

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lariat RNAs are well-known by-products of pre-mRNA splicing in eukaryotes, which are produced by the excised introns when the 5' splice site (5' ss) joins with the branchpoint (BP) during splicing. In general, most of lariat RNAs are usually linearized by RNA debranching enzyme 1 (DBR1), followed by degradation for intron turnover. However, with the high-throughput RNA sequencing technology and bioinformatics methods, increasing evidences have shown that many lariat RNAs can stably accumulate under physiological conditions in both animals and plants. Here, we describe a large-scale analysis to systematically identify the lariat RNAs (i.e., intronic circular RNAs) in Arabidopsis by utilizing the RNA-sequencing data.

Indexed as

ArabidopsisHigh-Throughput Nucleotide SequencingAnimalsIntronsRNARNA, CircularRNA PrecursorsRNA SplicingRNARNA, CircularRNA PrecursorsBioinformaticsCircular RNAIntronLariat RNARNA-seqRNA splicing

Identifiers

PMID34195958
OpenAlexW3174225928

What OpenQuestion holds

Textmetadata
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.