The transcriptionally active regions in the genome of Bacillus subtilis

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Abstract

The majority of all genes have so far been identified and annotated systematically through in silico gene finding. Here we report the finding of 3662 strand-specific transcriptionally active regions (TARs) in the genome of Bacillus subtilis by the use of tiling arrays. We have measured the genome-wide expression during mid-exponential growth on rich (LB) and minimal (M9) medium. The identified TARs account for 77.3% of the genes as they are currently annotated and additionally we find 84 putative non-coding RNAs (ncRNAs) and 127 antisense transcripts. One ncRNA, ncr22, is predicted to act as a translational control on cstA and an antisense transcript was observed opposite the housekeeping sigma factor sigA. Through this work we have discovered a long conserved 3′ untranslated region (UTR) in a group of membrane-associated genes that is predicted to fold into a large and highly stable secondary structure. One of the genes having this tail is efeN, which encodes a target of the twin-arginine translocase (Tat) protein translocation system.

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The transcriptional landscape of the yeast genome defined by RNA sequencing.

U Nagalakshmi, Z. Wang, K. Waern … (2008)

The identification of untranslated regions, introns, and coding regions within an organism remains challenging. We developed a quantitative sequencing-based method called RNA-Seq for mapping transcribed regions, in which complementary DNA fragments are subjected to high-throughput sequencing and mapped to the genome. We applied RNA-Seq to generate a high-resolution transcriptome map of the yeast genome and demonstrated that most (74.5%) of the nonrepetitive sequence of the yeast genome is transcribed. We confirmed many known and predicted introns and demonstrated that others are not actively used. Alternative initiation codons and upstream open reading frames also were identified for many yeast genes. We also found unexpected 3'-end heterogeneity and the presence of many overlapping genes. These results indicate that the yeast transcriptome is more complex than previously appreciated.

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Measuring the accuracy of diagnostic systems.

J Swets (1988)

Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.

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Bidirectional promoters generate pervasive transcription in yeast.

Zhenyu Xu, Wu Wei, Julien Gagneur … (2009)

Genome-wide pervasive transcription has been reported in many eukaryotic organisms, revealing a highly interleaved transcriptome organization that involves hundreds of previously unknown non-coding RNAs. These recently identified transcripts either exist stably in cells (stable unannotated transcripts, SUTs) or are rapidly degraded by the RNA surveillance pathway (cryptic unstable transcripts, CUTs). One characteristic of pervasive transcription is the extensive overlap of SUTs and CUTs with previously annotated features, which prompts questions regarding how these transcripts are generated, and whether they exert function. Single-gene studies have shown that transcription of SUTs and CUTs can be functional, through mechanisms involving the generated RNAs or their generation itself. So far, a complete transcriptome architecture including SUTs and CUTs has not been described in any organism. Knowledge about the position and genome-wide arrangement of these transcripts will be instrumental in understanding their function. Here we provide a comprehensive analysis of these transcripts in the context of multiple conditions, a mutant of the exosome machinery and different strain backgrounds of Saccharomyces cerevisiae. We show that both SUTs and CUTs display distinct patterns of distribution at specific locations. Most of the newly identified transcripts initiate from nucleosome-free regions (NFRs) associated with the promoters of other transcripts (mostly protein-coding genes), or from NFRs at the 3' ends of protein-coding genes. Likewise, about half of all coding transcripts initiate from NFRs associated with promoters of other transcripts. These data change our view of how a genome is transcribed, indicating that bidirectionality is an inherent feature of promoters. Such an arrangement of divergent and overlapping transcripts may provide a mechanism for local spreading of regulatory signals-that is, coupling the transcriptional regulation of neighbouring genes by means of transcriptional interference or histone modification.

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Author and article information

Journal

Journal ID (nlm-ta): Mol Microbiol

Journal ID (publisher-id): mmi

Title: Molecular Microbiology

Publisher: Blackwell Publishing Ltd

ISSN (Print): 0950-382X

ISSN (Electronic): 1365-2958

Publication date (Print): September 2009

Publication date (Electronic): 26 August 2009

Volume: 73

Issue: 6

Pages: 1043-1057

Affiliations

simpleCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark 2800 Lyngby, Denmark

Author notes

*For correspondence. E-mail hanne@ 123456cbs.dtu.dk ; Tel. (+45) 45 25 61 48; Fax (+45) 45 93 15 85.

Article

DOI: 10.1111/j.1365-2958.2009.06830.x

PMC ID: 2784878

PubMed ID: 19682248

SO-VID: f86001cf-2308-4f41-b478-2ac3621a17a8

License:

Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

History

Date accepted : 23 July 2009

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