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Transcription start site profiling uncovers divergent transcription and enhancer-associated RNAs in Drosophila melanogaster

Overview of attention for article published in BMC Genomics, February 2018
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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 (71st percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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12 tweeters
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1 Facebook page

Citations

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15 Dimensions

Readers on

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57 Mendeley
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Title
Transcription start site profiling uncovers divergent transcription and enhancer-associated RNAs in Drosophila melanogaster
Published in
BMC Genomics, February 2018
DOI 10.1186/s12864-018-4510-7
Pubmed ID
Authors

Michael P. Meers, Karen Adelman, Robert J. Duronio, Brian D. Strahl, Daniel J. McKay, A. Gregory Matera

Abstract

High-resolution transcription start site (TSS) mapping in D. melanogaster embryos and cell lines has revealed a rich and detailed landscape of both cis- and trans-regulatory elements and factors. However, TSS profiling has not been investigated in an orthogonal in vivo setting. Here, we present a comprehensive dataset that links TSS dynamics with nucleosome occupancy and gene expression in the wandering third instar larva, a developmental stage characterized by large-scale shifts in transcriptional programs in preparation for metamorphosis. The data recapitulate major regulatory classes of TSSs, based on peak width, promoter-proximal polymerase pausing, and cis-regulatory element density. We confirm the paucity of divergent transcription units in D. melanogaster, but also identify notable exceptions. Furthermore, we identify thousands of novel initiation events occurring at unannotated TSSs that can be classified into functional categories by their local density of histone modifications. Interestingly, a sub-class of these unannotated TSSs overlaps with functionally validated enhancer elements, consistent with a regulatory role for "enhancer RNAs" (eRNAs) in defining developmental transcription programs. High-depth TSS mapping is a powerful strategy for identifying and characterizing low-abundance and/or low-stability RNAs. Global analysis of transcription initiation patterns in a developing organism reveals a vast number of novel initiation events that identify potential eRNAs as well as other non-coding transcripts critical for animal development.

Twitter Demographics

The data shown below were collected from the profiles of 12 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 33%
Student > Bachelor 9 16%
Researcher 8 14%
Student > Master 5 9%
Professor 3 5%
Other 7 12%
Unknown 6 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 53%
Agricultural and Biological Sciences 16 28%
Environmental Science 1 2%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Computer Science 1 2%
Other 2 4%
Unknown 6 11%

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 23 June 2019.
All research outputs
#4,248,078
of 17,538,071 outputs
Outputs from BMC Genomics
#1,871
of 9,332 outputs
Outputs of similar age
#81,740
of 283,247 outputs
Outputs of similar age from BMC Genomics
#2
of 12 outputs
Altmetric has tracked 17,538,071 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,332 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 79% 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 283,247 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 12 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.