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High-throughput detection of RNA processing in bacteria

Overview of attention for article published in BMC Genomics, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

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1 news outlet
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19 X users

Citations

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32 Dimensions

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82 Mendeley
Title
High-throughput detection of RNA processing in bacteria
Published in
BMC Genomics, March 2018
DOI 10.1186/s12864-018-4538-8
Pubmed ID
Authors

Erin E. Gill, Luisa S. Chan, Geoffrey L. Winsor, Neil Dobson, Raymond Lo, Shannan J. Ho Sui, Bhavjinder K. Dhillon, Patrick K. Taylor, Raunak Shrestha, Cory Spencer, Robert E. W. Hancock, Peter J. Unrau, Fiona S. L. Brinkman

Abstract

Understanding the RNA processing of an organism's transcriptome is an essential but challenging step in understanding its biology. Here we investigate with unprecedented detail the transcriptome of Pseudomonas aeruginosa PAO1, a medically important and innately multi-drug resistant bacterium. We systematically mapped RNA cleavage and dephosphorylation sites that result in 5'-monophosphate terminated RNA (pRNA) using monophosphate RNA-Seq (pRNA-Seq). Transcriptional start sites (TSS) were also mapped using differential RNA-Seq (dRNA-Seq) and both datasets were compared to conventional RNA-Seq performed in a variety of growth conditions. The pRNA-Seq library revealed known tRNA, rRNA and transfer-messenger RNA (tmRNA) processing sites, together with previously uncharacterized RNA cleavage events that were found disproportionately near the 5' ends of transcripts associated with basic bacterial functions such as oxidative phosphorylation and purine metabolism. The majority (97%) of the processed mRNAs were cleaved at precise codon positions within defined sequence motifs indicative of distinct endonucleolytic activities. The most abundant of these motifs corresponded closely to an E. coli RNase E site previously established in vitro. Using the dRNA-Seq library, we performed an operon analysis and predicted 3159 potential TSS. A correlation analysis uncovered 105 antiparallel pairs of TSS that were separated by 18 bp from each other and were centered on single palindromic TAT(A/T)ATA motifs (likely - 10 promoter elements), suggesting that, consistent with previous in vitro experimentation, these sites can initiate transcription bi-directionally and may thus provide a novel form of transcriptional regulation. TSS and RNA-Seq analysis allowed us to confirm expression of small non-coding RNAs (ncRNAs), many of which are differentially expressed in swarming and biofilm formation conditions. This study uses pRNA-Seq, a method that provides a genome-wide survey of RNA processing, to study the bacterium Pseudomonas aeruginosa and discover extensive transcript processing not previously appreciated. We have also gained novel insight into RNA maturation and turnover as well as a potential novel form of transcription regulation. NOTE: All sequence data has been submitted to the NCBI sequence read archive. Accession numbers are as follows: [NCBI sequence read archive: SRX156386, SRX157659, SRX157660, SRX157661, SRX157683 and SRX158075]. The sequence data is viewable using Jbrowse on www.pseudomonas.com .

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 81 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 32%
Researcher 10 12%
Student > Bachelor 7 9%
Student > Master 7 9%
Other 6 7%
Other 11 13%
Unknown 15 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 29%
Agricultural and Biological Sciences 20 24%
Immunology and Microbiology 11 13%
Chemistry 2 2%
Medicine and Dentistry 2 2%
Other 2 2%
Unknown 21 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 May 2021.
All research outputs
#1,821,230
of 23,749,054 outputs
Outputs from BMC Genomics
#435
of 10,805 outputs
Outputs of similar age
#40,932
of 331,445 outputs
Outputs of similar age from BMC Genomics
#11
of 216 outputs
Altmetric has tracked 23,749,054 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,805 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,445 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.