Evidence map›Paper›PMID 27450008›Full record

ArticleTuberculosis (Edinburgh, Scotland)2016

REMap: Operon map of M. tuberculosis based on RNA sequence data.

Shaaretha Pelly, Kathryn Winglee, Fang Fang Xia, Rick L Stevens, William R Bishai, Gyanu Lamichhane

Open access · greenAbstract read
In one paragraph

Article in Tuberculosis (Edinburgh, Scotland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Exopolysaccharide Biosynthesis inInternational journal of molecular sciences · 2023
    Article
  3. Article
  4. Review
  5. Article
  6. 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

6 authors at 3 institutions in 1 country.

Shaaretha Pelly *Center for Tuberculosis Research, School of Medicine, Johns Hopkins University, 1550 Orleans St, Baltimore, MD 21287, USA.
Kathryn Winglee *Center for Tuberculosis Research, School of Medicine, Johns Hopkins University, 1550 Orleans St, Baltimore, MD 21287, USA.
Fang Fang XiaArgonne National Laboratory, Argonne, IL 60439, USA.
Rick L StevensArgonne National Laboratory, Argonne, IL 60439, USA.
William R BishaiCenter for Tuberculosis Research, School of Medicine, Johns Hopkins University, 1550 Orleans St, Baltimore, MD 21287, USA.
Gyanu LamichhaneCenter for Tuberculosis Research, School of Medicine, Johns Hopkins University, 1550 Orleans St, Baltimore, MD 21287, USA.
Johns Hopkins University · USArgonne National Laboratory · USHoward Hughes Medical Institute · US

Funding

Training Program in Cellular and Molecular MedicineT32GM008752 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI RAO, RAJINI · 2000 to 2019
$11.7M
New Drug for Treatment of Chronic Bacterial InfectionDP2OD008459 · OD · JOHNS HOPKINS UNIVERSITY · PI LAMICHHANE, GYANU · 2011 to 2013
$2.6M
NIGMS NIH HHS T32 GM008752NIH HHS DP2 OD008459
6 · The paper itself

Abstract

A map of the transcriptional organization of genes of an organism is a basic tool that is necessary to understand and facilitate a more accurate genetic manipulation of the organism. Operon maps are largely generated by computational prediction programs that rely on gene conservation and genome architecture and may not be physiologically relevant. With the widespread use of RNA sequencing (RNAseq), the prediction of operons based on actual transcriptome sequencing rather than computational genomics alone is much needed. Here, we report a validated operon map of Mycobacterium tuberculosis, developed using RNAseq data from both the exponential and stationary phases of growth. At least 58.4% of M. tuberculosis genes are organized into 749 operons. Our prediction algorithm, REMap (RNA Expression Mapping of operons), considers the many cases of transcription coverage of intergenic regions, and avoids dependencies on functional annotation and arbitrary assumptions about gene structure. As a result, we demonstrate that REMap is able to more accurately predict operons, especially those that contain long intergenic regions or functionally unrelated genes, than previous operon prediction programs. The REMap algorithm is publicly available as a user-friendly tool that can be readily modified to predict operons in other bacteria.

Indexed as

Computational BiologyOperonSequence Analysis, RNAAlgorithmsDatabases, GeneticDecision TreesGene Expression Regulation, BacterialMycobacterium tuberculosisRNA, BacterialTranscription, GeneticRNA, BacterialMycobacterium tuberculosisOperonRNAseq

Identifiers

PMID27450008
PMCPMC4967370
OpenAlexW2342513075

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.