Evidence map›Paper›PMID 19015660›Full record

ReviewNature reviews. Genetics2009

RNA-Seq: a revolutionary tool for transcriptomics.

Zhong Wang, Mark Gerstein, Michael Snyder

2 registry-linked trialsAbstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 6,123 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6,123citing papers in PubMed, 1 pooled it
–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.

NCT01889992 phase1terminatednot on this mapstarted 2013, after this paper: background citation

Cardiac Allograft Remodeling and Effects of Sirolimus on Its Progression

TypeinterventionalSponsorUniversity of NebraskaRan2013 to 2018Enrolled42ConditionsCardiac Hypertrophy, ImmunosuppressionArmsCardiac MRI, Coronary angiography with IVUS, Cardiac Allograft Remodeling, M-TOR Immunosuppression, Cardiac Biopsy C4D stain
NCT05378282 completednot on this mapstarted 2021, after this paper: background citation

Identification of Diabetic Nephropathy Biomarkers Through Transcriptomics

TypeobservationalSponsorHospital Juarez de MexicoRan2021 to 2023Enrolled40ConditionsType 2 Diabetes, Type 2 Diabetes With Renal Manifestations
3 · Its place in the literature

Who cites it

6,123 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Profiling Nascent RNA Transcription with TT-Seq.Methods in molecular biology (Clifton, N.J.) · 2027
    Article
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  13. Identification of Changes in Gene Expression.Biometrical journal. Biometrische Zeitschrift · 2026
    Article
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  17. Review
  18. Article
  19. Integrated Transcriptomic Analysis of Skin Pigmentation Development inInternational journal of molecular sciences · 2026
    Article
  20. Article

6,063 more citing papers are in PubMed but not listed here.

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.

Zhong WangDepartment of Molecular, Cellular and Developmental Biology, Yale University, 219 Prospect Street, New Haven, Connecticut 06520, USA.
Mark Gerstein
Michael Snyder

Funding

Human Genome Array: Technology for Functional AnalysisP50HG002357 · NHGRI · YALE UNIVERSITY · PI SNYDER, MICHAEL P. · 2001 to 2010
$31.9M
Global Analysis of Transcription Regulatory NetworksR01CA077808 · NCI · YALE UNIVERSITY · PI SNYDER, MICHAEL P. · 1997 to 2009
$6.8M
NCI NIH HHS R01 CA077808NHGRI NIH HHS P50 HG002357
6 · The paper itself

Abstract

RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.

Indexed as

Transcription, GeneticAnimalsBase SequenceChromosome MappingExonsGene Expression ProfilingHumansModels, GeneticMolecular Sequence DataRNASequence Analysis, RNARNA

Identifiers

PMID19015660
PMCPMC2949280

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

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.