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Differentiation of ncRNAs from small mRNAs in Escherichia coli O157:H7 EDL933 (EHEC) by combined RNAseq and RIBOseq – ryhB encodes the regulatory RNA RyhB and a peptide, RyhP

Overview of attention for article published in BMC Genomics, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
10 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
20 Mendeley
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2 CiteULike
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Title
Differentiation of ncRNAs from small mRNAs in Escherichia coli O157:H7 EDL933 (EHEC) by combined RNAseq and RIBOseq – ryhB encodes the regulatory RNA RyhB and a peptide, RyhP
Published in
BMC Genomics, February 2017
DOI 10.1186/s12864-017-3586-9
Pubmed ID
Authors

Klaus Neuhaus, Richard Landstorfer, Svenja Simon, Steffen Schober, Patrick R. Wright, Cameron Smith, Rolf Backofen, Romy Wecko, Daniel A. Keim, Siegfried Scherer

Abstract

While NGS allows rapid global detection of transcripts, it remains difficult to distinguish ncRNAs from short mRNAs. To detect potentially translated RNAs, we developed an improved protocol for bacterial ribosomal footprinting (RIBOseq). This allowed distinguishing ncRNA from mRNA in EHEC. A high ratio of ribosomal footprints per transcript (ribosomal coverage value, RCV) is expected to indicate a translated RNA, while a low RCV should point to a non-translated RNA. Based on their low RCV, 150 novel non-translated EHEC transcripts were identified as putative ncRNAs, representing both antisense and intergenic transcripts, 74 of which had expressed homologs in E. coli MG1655. Bioinformatics analysis predicted statistically significant target regulons for 15 of the intergenic transcripts; experimental analysis revealed 4-fold or higher differential expression of 46 novel ncRNA in different growth media. Out of 329 annotated EHEC ncRNAs, 52 showed an RCV similar to protein-coding genes, of those, 16 had RIBOseq patterns matching annotated genes in other enterobacteriaceae, and 11 seem to possess a Shine-Dalgarno sequence, suggesting that such ncRNAs may encode small proteins instead of being solely non-coding. To support that the RIBOseq signals are reflecting translation, we tested the ribosomal-footprint covered ORF of ryhB and found a phenotype for the encoded peptide in iron-limiting condition. Determination of the RCV is a useful approach for a rapid first-step differentiation between bacterial ncRNAs and small mRNAs. Further, many known ncRNAs may encode proteins as well.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 30%
Student > Ph. D. Student 6 30%
Student > Doctoral Student 2 10%
Student > Postgraduate 1 5%
Other 1 5%
Other 4 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 45%
Agricultural and Biological Sciences 7 35%
Veterinary Science and Veterinary Medicine 1 5%
Unspecified 1 5%
Immunology and Microbiology 1 5%
Other 1 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 13 March 2018.
All research outputs
#1,864,059
of 12,639,455 outputs
Outputs from BMC Genomics
#1,021
of 7,445 outputs
Outputs of similar age
#55,311
of 252,228 outputs
Outputs of similar age from BMC Genomics
#3
of 16 outputs
Altmetric has tracked 12,639,455 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,445 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 86% 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 252,228 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 77% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.