Literature DB >> 27450008

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

Shaaretha Pelly1, Kathryn Winglee1, Fang Fang Xia2, Rick L Stevens2, William R Bishai1,3, Gyanu Lamichhane1.   

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.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Mycobacterium tuberculosis; Operon; RNAseq

Mesh:

Substances:

Year:  2016        PMID: 27450008      PMCID: PMC4967370          DOI: 10.1016/j.tube.2016.04.010

Source DB:  PubMed          Journal:  Tuberculosis (Edinb)        ISSN: 1472-9792            Impact factor:   3.131


  47 in total

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9.  Mycobacterium tuberculosis gene expression during adaptation to stationary phase and low-oxygen dormancy.

Authors:  M I Voskuil; K C Visconti; G K Schoolnik
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Review 2.  A computational system for identifying operons based on RNA-seq data.

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Journal:  Methods       Date:  2019-04-04       Impact factor: 3.608

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Authors:  Michael J Pepi; Shibin Chacko; Gary M Marqus; Vinayak Singh; Zhe Wang; Kyle Planck; Ryan T Cullinane; Penchala N Meka; Deviprasad R Gollapalli; Thomas R Ioerger; Kyu Y Rhee; Gregory D Cuny; Helena I M Boshoff; Lizbeth Hedstrom
Journal:  ACS Infect Dis       Date:  2022-01-11       Impact factor: 5.578

4.  Multiple transcription factors co-regulate the Mycobacterium tuberculosis adaptation response to vitamin C.

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  4 in total

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