Evidence map›Paper›PMID 32660958›Full record

ArticleGenome research2020

Simple and efficient profiling of transcription initiation and transcript levels with STRIPE-seq.

Robert A Policastro, R Taylor Raborn, Volker P Brendel, Gabriel E Zentner

Abstract read
In one paragraph

Article in Genome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  12. A data-driven genome annotation approach for cassava.The Plant journal : for cell and molecular biology · 2024
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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

4 authors.

Robert A PolicastroDepartment of Biology.ORCID 0000-0002-5562-9901
R Taylor RabornDepartment of Biology.ORCID 0000-0001-6249-8033
Volker P BrendelDepartment of Biology.
Gabriel E ZentnerDepartment of Biology.ORCID 0000-0002-0801-7646

Funding

Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Causes and Population-genetic Consequences of Molecular VariationR35GM122566 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI Michael R LYNCH · 2017 to 2026
$7.7M
Regulation of transcription by the Mediator complexR35GM128631 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI ZENTNER, GABRIEL · 2018 to 2020
$1.2M
NCATS NIH HHS UL1 TR001108NIGMS NIH HHS R35 GM122566NIGMS NIH HHS R35 GM128631
6 · The paper itself

Abstract

Accurate mapping of transcription start sites (TSSs) is key for understanding transcriptional regulation. However, current protocols for genome-wide TSS profiling are laborious and/or expensive. We present Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing (STRIPE-seq), a simple, rapid, and cost-effective protocol for sequencing capped RNA 5' ends from as little as 50 ng total RNA. Including depletion of uncapped RNA and reaction cleanups, a STRIPE-seq library can be constructed in about 5 h. We show application of STRIPE-seq to TSS profiling in yeast and human cells and show that it can also be effectively used for quantification of transcript levels and analysis of differential gene expression. In conjunction with our ready-to-use computational workflows, STRIPE-seq is a straightforward, efficient means by which to probe the landscape of transcriptional initiation.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingSequence Analysis, RNATranscription Initiation, GeneticTranscriptomeCluster AnalysisComputational BiologyGene OntologyHumansPromoter Regions, GeneticTranscription Initiation SiteYeasts

Identifiers

PMID32660958
PMCPMC7370879

What OpenQuestion holds

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LicenceCC BY-NC
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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.