Evidence map›Paper›PMID 21295131›Full record

ArticleGenomics2011

Computational dissection of Arabidopsis smRNAome leads to discovery of novel microRNAs and short interfering RNAs associated with transcription start sites.

Xiangfeng Wang, John D Laurie, Tao Liu, Jacqueline Wentz, X Shirley Liu

Open access · greenAbstract read
In one paragraph

Article in Genomics, 2011. 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
0.8field-weighted citation impact, top 21% 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, 9 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

5 authors at 3 institutions in 1 country.

Xiangfeng WangSchool of Plant Sciences, University of Arizona, 1140 E. South Campus Drive, Tucson, AZ 85721, USA. xwang1@cals.arizona.edu
John D Laurie
Tao Liu
Jacqueline Wentz
X Shirley Liu
Dana-Farber Cancer Institute · USUniversity of Arizona · USMassachusetts Institute of Technology · US

Funding

Computational Models for Mechanisms of Global Transcription RegulationR01HG004069 · NHGRI · DANA-FARBER CANCER INST · PI LIU, XIAOLE SHIRLEY · 2006 to 2013
$3.6M
NHGRI NIH HHS HG004069NHGRI NIH HHS R01 HG004069
6 · The paper itself

Abstract

The profiling of small RNAs by high-throughput sequencing (smRNA-Seq) has revealed the complexity of the RNA world. Here, we describe a computational scheme for dissecting the plant smRNAome by integrating smRNA-Seq datasets in Arabidopsis thaliana. Our analytical approach first defines ab initio the genomic loci that produce smRNAs as basic units, then utilizes principal component analysis (PCA) to predict novel miRNAs. Secondary structure prediction of candidates' putative precursors discovered a group of long hairpin double-stranded RNAs (lh-dsRNAs) formed by inverted duplications of decayed coding genes. These gene remnants produce miRNA-like small RNAs which are predominantly 21- and 22-nt long, dependent of DCL1 but independent of RDR2 and DCL2/3/4, and associated with AGO1. Additionally, we found two classes of transcription start site associated (TSSa) RNAs located at sense (+) and antisense (-) approximately 100-200 bp downstream of TSSs, but are differentially incorporated into AGO1 and AGO4, respectively.

Indexed as

Transcription Initiation SiteArabidopsisArabidopsis ProteinsArgonaute ProteinsComputational BiologyMicroRNAsPrincipal Component AnalysisRNA-Dependent RNA PolymeraseRNA, Double-StrandedRNA, Small InterferingSequence Analysis, DNAAGO1 protein, ArabidopsisAGO4 protein, ArabidopsisArabidopsis ProteinsArgonaute ProteinsMicroRNAsRDR2 protein, ArabidopsisRNA-Dependent RNA PolymeraseRNA, Double-StrandedRNA, Small Interfering

Identifiers

PMID21295131
PMCPMC3707929
OpenAlexW2045556775

What OpenQuestion holds

Textmetadata
LicenceTDM
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.