↓ Skip to main content

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
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
43 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Student > Master 6 14%
Student > Bachelor 6 14%
Student > Doctoral Student 5 12%
Student > Postgraduate 4 9%
Other 7 16%
Unknown 5 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 30%
Agricultural and Biological Sciences 13 30%
Immunology and Microbiology 5 12%
Computer Science 3 7%
Engineering 2 5%
Other 2 5%
Unknown 5 12%
Attention Score in Context

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
#6,416,008
of 25,067,172 outputs
Outputs from BMC Genomics
#2,520
of 11,154 outputs
Outputs of similar age
#86,461
of 300,738 outputs
Outputs of similar age from BMC Genomics
#47
of 208 outputs
Altmetric has tracked 25,067,172 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 11,154 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 77% 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 300,738 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 208 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.