Global Transcriptional Start Site Mapping Using Differential RNA Sequencing Reveals Novel Antisense RNAs in Escherichia coli
While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the E. coli transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish b...
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Published in | Journal of bacteriology Vol. 197; no. 1; pp. 18 - 28 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Society for Microbiology
01.01.2015
|
Subjects | |
Online Access | Get full text |
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Abstract | While the model organism
Escherichia coli
has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the
E. coli
transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type
E. coli
and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the
rnc
and
rne
mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in
E. coli
and is easily accessible, together with the cDNA coverage plots, in an online genome browser. |
---|---|
AbstractList | While the model organism
Escherichia coli
has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the
E. coli
transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type
E. coli
and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the
rnc
and
rne
mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in
E. coli
and is easily accessible, together with the cDNA coverage plots, in an online genome browser. While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the E. coli transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type E. coli and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the rnc and rne mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in E. coli and is easily accessible, together with the cDNA coverage plots, in an online genome browser. While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the E. coli transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type E. coli and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the rnc and rne mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in E. coli and is easily accessible, together with the cDNA coverage plots, in an online genome browser.While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the E. coli transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type E. coli and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the rnc and rne mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in E. coli and is easily accessible, together with the cDNA coverage plots, in an online genome browser. |
Author | Herbig, Alexander Nieselt, Kay Sharma, Cynthia M. Storz, Gisela Eisenbart, Sara K. Bischler, Thorsten Förstner, Konrad U. Zhang, Aixia Thomason, Maureen K. |
Author_xml | – sequence: 1 givenname: Maureen K. surname: Thomason fullname: Thomason, Maureen K. organization: Cell Biology and Metabolism Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA – sequence: 2 givenname: Thorsten surname: Bischler fullname: Bischler, Thorsten organization: Research Center for Infectious Diseases (ZINF), University of Würzburg, Würzburg, Germany – sequence: 3 givenname: Sara K. surname: Eisenbart fullname: Eisenbart, Sara K. organization: Cell Biology and Metabolism Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA, Research Center for Infectious Diseases (ZINF), University of Würzburg, Würzburg, Germany – sequence: 4 givenname: Konrad U. surname: Förstner fullname: Förstner, Konrad U. organization: Research Center for Infectious Diseases (ZINF), University of Würzburg, Würzburg, Germany – sequence: 5 givenname: Aixia surname: Zhang fullname: Zhang, Aixia organization: Cell Biology and Metabolism Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA – sequence: 6 givenname: Alexander surname: Herbig fullname: Herbig, Alexander organization: Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany – sequence: 7 givenname: Kay surname: Nieselt fullname: Nieselt, Kay organization: Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Tübingen, Germany – sequence: 8 givenname: Cynthia M. surname: Sharma fullname: Sharma, Cynthia M. organization: Cell Biology and Metabolism Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA, Research Center for Infectious Diseases (ZINF), University of Würzburg, Würzburg, Germany – sequence: 9 givenname: Gisela surname: Storz fullname: Storz, Gisela organization: Cell Biology and Metabolism Program, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25266388$$D View this record in MEDLINE/PubMed |
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Notes | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 M.K.T. and T.B. are joint first authors. Citation Thomason MK, Bischler T, Eisenbart SK, Förstner KU, Zhang A, Herbig A, Nieselt K, Sharma CM, Storz G. 2015. Global transcriptional start site mapping using differential RNA sequencing reveals novel antisense RNAs in Escherichia coli. J Bacteriol 197:18–28. doi:10.1128/JB.02096-14. Present address: Maureen K. Thomason, Department of Microbiology, University of Washington, Seattle, Washington, USA. |
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Snippet | While the model organism
Escherichia coli
has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here... While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here... |
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SubjectTerms | Algorithms Bacteriology Chromosome Mapping complementary DNA Deoxyribonucleic acid DNA E coli Escherichia coli Escherichia coli - genetics Escherichia coli - metabolism Gene expression Gene Expression Regulation, Bacterial - physiology genes Genetics Genome, Bacterial Genomics Growth conditions mutation prediction ribonucleases Ribonucleic acid RNA RNA, Antisense - genetics RNA, Antisense - metabolism RNA, Bacterial - genetics RNA, Bacterial - metabolism Sequence Analysis, RNA - methods surveys transcription (genetics) Transcription Initiation Site - physiology Transcriptome |
Title | Global Transcriptional Start Site Mapping Using Differential RNA Sequencing Reveals Novel Antisense RNAs in Escherichia coli |
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