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  • 1
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 01 February 2011, Vol.108(5), pp.2124-9
    Description: There has been an increasing interest in cyanobacteria because these photosynthetic organisms convert solar energy into biomass and because of their potential for the production of biofuels. However, the exploitation of cyanobacteria for bioengineering requires knowledge of their transcriptional organization. Using differential RNA sequencing, we have established a genome-wide map of 3,527 transcriptional start sites (TSS) of the model organism Synechocystis sp. PCC6803. One-third of all TSS were located upstream of an annotated gene; another third were on the reverse complementary strand of 866 genes, suggesting massive antisense transcription. Orphan TSS located in intergenic regions led us to predict 314 noncoding RNAs (ncRNAs). Complementary microarray-based RNA profiling verified a high number of noncoding transcripts and identified strong ncRNA regulations. Thus, ∼64% of all TSS give rise to antisense or ncRNAs in a genome that is to 87% protein coding. Our data enhance the information on promoters by a factor of 40, suggest the existence of additional small peptide-encoding mRNAs, and provide corrected 5' annotations for many genes of this cyanobacterium. The global TSS map will facilitate the use of Synechocystis sp. PCC6803 as a model organism for further research on photosynthesis and energy research.
    Keywords: Transcription, Genetic ; Synechocystis -- Genetics
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 2
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 10 September 2013, Vol.110(37), pp.E3487-96
    Description: Small RNAs (sRNAs) constitute a large and heterogeneous class of bacterial gene expression regulators. Much like eukaryotic microRNAs, these sRNAs typically target multiple mRNAs through short seed pairing, thereby acting as global posttranscriptional regulators. In some bacteria, evidence for hundreds to possibly more than 1,000 different sRNAs has been obtained by transcriptome sequencing. However, the experimental identification of possible targets and, therefore, their confirmation as functional regulators of gene expression has remained laborious. Here, we present a strategy that integrates phylogenetic information to predict sRNA targets at the genomic scale and reconstructs regulatory networks upon functional enrichment and network analysis (CopraRNA, for Comparative Prediction Algorithm for sRNA Targets). Furthermore, CopraRNA precisely predicts the sRNA domains for target recognition and interaction. When applied to several model sRNAs, CopraRNA revealed additional targets and functions for the sRNAs CyaR, FnrS, RybB, RyhB, SgrS, and Spot42. Moreover, the mRNAs gdhA, lrp, marA, nagZ, ptsI, sdhA, and yobF-cspC were suggested as regulatory hubs targeted by up to seven different sRNAs. The verification of many previously undetected targets by CopraRNA, even for extensively investigated sRNAs, demonstrates its advantages and shows that CopraRNA-based analyses can compete with experimental target prediction approaches. A Web interface allows high-confidence target prediction and efficient classification of bacterial sRNAs.
    Keywords: E. Coli ; RNA–RNA Interaction ; Regulatory RNA ; RNA, Bacterial -- Genetics
    ISSN: 00278424
    E-ISSN: 1091-6490
    Library Location Call Number Volume/Issue/Year Availability
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