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Quantitative MNase-seq accurately maps nucleosome occupancy levels

Overview of attention for article published in Genome Biology (Online Edition), September 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

news
1 news outlet
twitter
24 tweeters
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
42 Dimensions

Readers on

mendeley
142 Mendeley
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Title
Quantitative MNase-seq accurately maps nucleosome occupancy levels
Published in
Genome Biology (Online Edition), September 2019
DOI 10.1186/s13059-019-1815-z
Pubmed ID
Authors

Răzvan V. Chereji, Terri D. Bryson, Steven Henikoff

Abstract

Micrococcal nuclease (MNase) is widely used to map nucleosomes. However, its aggressive endo-/exo-nuclease activities make MNase-seq unreliable for determining nucleosome occupancies, because cleavages within linker regions produce oligo- and mono-nucleosomes, whereas cleavages within nucleosomes destroy them. Here, we introduce a theoretical framework for predicting nucleosome occupancies and an experimental protocol with appropriate spike-in normalization that confirms our theory and provides accurate occupancy levels over an MNase digestion time course. As with human cells, we observe no overall differences in nucleosome occupancies between Drosophila euchromatin and heterochromatin, which implies that heterochromatic compaction does not reduce MNase accessibility of linker DNA.

Twitter Demographics

The data shown below were collected from the profiles of 24 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 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 142 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 20%
Researcher 28 20%
Student > Bachelor 17 12%
Student > Master 16 11%
Student > Doctoral Student 11 8%
Other 16 11%
Unknown 26 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 69 49%
Agricultural and Biological Sciences 28 20%
Medicine and Dentistry 4 3%
Computer Science 3 2%
Physics and Astronomy 3 2%
Other 7 5%
Unknown 28 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 25 May 2022.
All research outputs
#1,164,732
of 21,407,661 outputs
Outputs from Genome Biology (Online Edition)
#1,036
of 3,966 outputs
Outputs of similar age
#25,428
of 285,824 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 21,407,661 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,966 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 73% 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 285,824 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them