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Unraveling the evolution and coevolution of small regulatory RNAs and coding genes in Listeria

Overview of attention for article published in BMC Genomics, November 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 (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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8 tweeters

Citations

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8 Dimensions

Readers on

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35 Mendeley
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Title
Unraveling the evolution and coevolution of small regulatory RNAs and coding genes in Listeria
Published in
BMC Genomics, November 2017
DOI 10.1186/s12864-017-4242-0
Pubmed ID
Authors

Franck Cerutti, Ludovic Mallet, Anaïs Painset, Claire Hoede, Annick Moisan, Christophe Bécavin, Mélodie Duval, Olivier Dussurget, Pascale Cossart, Christine Gaspin, Hélène Chiapello

Abstract

Small regulatory RNAs (sRNAs) are widely found in bacteria and play key roles in many important physiological and adaptation processes. Studying their evolution and screening for events of coevolution with other genomic features is a powerful way to better understand their origin and assess a common functional or adaptive relationship between them. However, evolution and coevolution of sRNAs with coding genes have been sparsely investigated in bacterial pathogens. We designed a robust and generic phylogenomics approach that detects correlated evolution between sRNAs and protein-coding genes using their observed and inferred patterns of presence-absence in a set of annotated genomes. We applied this approach on 79 complete genomes of the Listeria genus and identified fifty-two accessory sRNAs, of which most were present in the Listeria common ancestor and lost during Listeria evolution. We detected significant coevolution between 23 sRNA and 52 coding genes and inferred the Listeria sRNA-coding genes coevolution network. We characterized a main hub of 12 sRNAs that coevolved with genes encoding cell wall proteins and virulence factors. Among them, an sRNA specific to L. monocytogenes species, rli133, coevolved with genes involved either in pathogenicity or in interaction with host cells, possibly acting as a direct negative post-transcriptional regulation. Our approach allowed the identification of candidate sRNAs potentially involved in pathogenicity and host interaction, consistent with recent findings on known pathogenicity actors. We highlight four sRNAs coevolving with seven internalin genes, some of which being important virulence factors in Listeria.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Student > Doctoral Student 6 17%
Student > Bachelor 6 17%
Student > Master 5 14%
Student > Postgraduate 3 9%
Other 4 11%
Unknown 3 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 34%
Agricultural and Biological Sciences 9 26%
Immunology and Microbiology 5 14%
Computer Science 3 9%
Engineering 2 6%
Other 1 3%
Unknown 3 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 04 December 2017.
All research outputs
#3,706,915
of 15,922,434 outputs
Outputs from BMC Genomics
#1,685
of 8,860 outputs
Outputs of similar age
#101,058
of 405,544 outputs
Outputs of similar age from BMC Genomics
#173
of 828 outputs
Altmetric has tracked 15,922,434 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,860 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 80% 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 405,544 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 75% of its contemporaries.
We're also able to compare this research output to 828 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.