↓ Skip to main content

Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize

Overview of attention for article published in Genome Biology, July 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
5 news outlets
twitter
32 X users
facebook
1 Facebook page

Readers on

mendeley
171 Mendeley
citeulike
2 CiteULike
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
Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize
Published in
Genome Biology, July 2017
DOI 10.1186/s13059-017-1273-4
Pubmed ID
Authors

Rurika Oka, Johan Zicola, Blaise Weber, Sarah N. Anderson, Charlie Hodgman, Jonathan I. Gent, Jan-Jaap Wesselink, Nathan M. Springer, Huub C. J. Hoefsloot, Franziska Turck, Maike Stam

Abstract

While most cells in multicellular organisms carry the same genetic information, in each cell type only a subset of genes is being transcribed. Such differentiation in gene expression depends, for a large part, on the activation and repression of regulatory sequences, including transcriptional enhancers. Transcriptional enhancers can be located tens of kilobases from their target genes, but display characteristic chromatin and DNA features, allowing their identification by genome-wide profiling. Here we show that integration of chromatin characteristics can be applied to predict distal enhancer candidates in Zea mays, thereby providing a basis for a better understanding of gene regulation in this important crop plant. To predict transcriptional enhancers in the crop plant maize (Zea mays L. ssp. mays), we integrated available genome-wide DNA methylation data with newly generated maps for chromatin accessibility and histone 3 lysine 9 acetylation (H3K9ac) enrichment in young seedling and husk tissue. Approximately 1500 intergenic regions, displaying low DNA methylation, high chromatin accessibility and H3K9ac enrichment, were classified as enhancer candidates. Based on their chromatin profiles, candidate sequences can be classified into four subcategories. Tissue-specificity of enhancer candidates is defined based on the tissues in which they are identified and putative target genes are assigned based on tissue-specific expression patterns of flanking genes. Our method identifies three previously identified distal enhancers in maize, validating the new set of enhancer candidates and enlarging the toolbox for the functional characterization of gene regulation in the highly repetitive maize genome.

X Demographics

X Demographics

The data shown below were collected from the profiles of 32 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 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 171 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 26%
Researcher 32 19%
Student > Master 22 13%
Student > Doctoral Student 14 8%
Student > Bachelor 13 8%
Other 18 11%
Unknown 28 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 86 50%
Biochemistry, Genetics and Molecular Biology 42 25%
Computer Science 6 4%
Nursing and Health Professions 2 1%
Engineering 2 1%
Other 2 1%
Unknown 31 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 56. 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 14 May 2018.
All research outputs
#750,338
of 25,382,440 outputs
Outputs from Genome Biology
#493
of 4,468 outputs
Outputs of similar age
#15,501
of 324,641 outputs
Outputs of similar age from Genome Biology
#8
of 60 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 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 done well, scoring higher than 88% 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 324,641 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 95% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.