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Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

Overview of attention for article published in Microbiome, May 2016
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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 (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

blogs
1 blog
twitter
24 X users
patent
1 patent
video
1 YouTube creator

Citations

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63 Dimensions

Readers on

mendeley
140 Mendeley
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1 CiteULike
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Title
Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains
Published in
Microbiome, May 2016
DOI 10.1186/s40168-016-0162-5
Pubmed ID
Authors

Yemin Lan, Gail Rosen, Ruth Hershberg

Abstract

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that the percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. Our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 <1%
United States 1 <1%
Unknown 138 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 20%
Researcher 22 16%
Student > Bachelor 18 13%
Student > Master 16 11%
Student > Doctoral Student 7 5%
Other 15 11%
Unknown 34 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 34%
Biochemistry, Genetics and Molecular Biology 28 20%
Immunology and Microbiology 7 5%
Environmental Science 5 4%
Computer Science 4 3%
Other 8 6%
Unknown 41 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 01 June 2023.
All research outputs
#1,571,027
of 25,712,965 outputs
Outputs from Microbiome
#550
of 1,790 outputs
Outputs of similar age
#25,468
of 313,225 outputs
Outputs of similar age from Microbiome
#6
of 14 outputs
Altmetric has tracked 25,712,965 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,790 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.4. This one has gotten more attention than average, scoring higher than 69% 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 313,225 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.