Evidence map›Paper›PMID 25118256›Full record

ArticlePlant physiology2014

Digital inventory of Arabidopsis transcripts revealed by 61 RNA sequencing samples.

Xiaoyong Sun, Qiuying Yang, Zhiping Deng, Xinfu Ye

Abstract read
In one paragraph

Article in Plant physiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Modern Approaches for Transcriptome Analyses in Plants.Advances in experimental medicine and biology · 2021
    Article
  2. Article
  3. Article
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

4 authors.

Xiaoyong SunAgricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, Shandong 271018, China (X.S.);Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas 75235 (Q.Y.);State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control, Institute of Virology and Biotechnology, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China (Z.D.); andFruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350013, China (X.Y.) johnsunx1@gmail.com.ORCID http://orcid.org/0000-0002-2425-3526
Qiuying YangAgricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, Shandong 271018, China (X.S.);Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas 75235 (Q.Y.);State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control, Institute of Virology and Biotechnology, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China (Z.D.); andFruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350013, China (X.Y.).
Zhiping DengAgricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, Shandong 271018, China (X.S.);Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas 75235 (Q.Y.);State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control, Institute of Virology and Biotechnology, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China (Z.D.); andFruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350013, China (X.Y.).
Xinfu YeAgricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, Shandong 271018, China (X.S.);Department of Physiology, University of Texas Southwestern Medical Center, Dallas, Texas 75235 (Q.Y.);State Key Laboratory Breeding Base for Zhejiang Sustainable Pest and Disease Control, Institute of Virology and Biotechnology, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China (Z.D.); andFruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350013, China (X.Y.).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternative splicing is an essential biological process to generate proteome diversity and phenotypic complexity. Recent improvements in RNA sequencing accuracy and computational algorithms have provided unprecedented opportunities to examine the expression levels of Arabidopsis (Arabidopsis thaliana) transcripts. In this article, we analyzed 61 RNA sequencing samples from 10 totally independent studies of Arabidopsis and calculated the transcript expression levels in different tissues, treatments, developmental stages, and varieties. These data provide a comprehensive profile of Arabidopsis transcripts with single-base resolution. We quantified the expression levels of 40,745 transcripts annotated in The Arabidopsis Information Resource 10, comprising 73% common transcripts, 15% rare transcripts, and 12% nondetectable transcripts. In addition, we investigated diverse common transcripts in detail, including ubiquitous transcripts, dominant/subordinate transcripts, and switch transcripts, in terms of their expression and transcript ratio. Interestingly, alternative splicing was the highly enriched function for the genes related to dominant/subordinate transcripts and switch transcripts. In addition, motif analysis revealed that TC motifs were enriched in dominant transcripts but not in subordinate transcripts. These motifs were found to have a strong relationship with transcription factor activity. Our results shed light on the complexity of alternative splicing and the diversity of the contributing factors.

Indexed as

Alternative SplicingArabidopsisGenes, PlantRNA, MessengerRNA, PlantRNA, MessengerRNA, Plant

Identifiers

PMID25118256
PMCPMC4213114

What OpenQuestion holds

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Registered trials

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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.