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Simultaneous profiling of transcriptome and DNA methylome from a single cell

Overview of attention for article published in Genome Biology, May 2016
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  • 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 (84th percentile)

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2 news outlets
blogs
3 blogs
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19 X users
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2 patents

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355 Mendeley
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3 CiteULike
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Title
Simultaneous profiling of transcriptome and DNA methylome from a single cell
Published in
Genome Biology, May 2016
DOI 10.1186/s13059-016-0950-z
Pubmed ID
Authors

Youjin Hu, Kevin Huang, Qin An, Guizhen Du, Ganlu Hu, Jinfeng Xue, Xianmin Zhu, Cun-Yu Wang, Zhigang Xue, Guoping Fan

Abstract

Single-cell transcriptome and single-cell methylome technologies have become powerful tools to study RNA and DNA methylation profiles of single cells at a genome-wide scale. A major challenge has been to understand the direct correlation of DNA methylation and gene expression within single-cells. Due to large cell-to-cell variability and the lack of direct measurements of transcriptome and methylome of the same cell, the association is still unclear. Here, we describe a novel method (scMT-seq) that simultaneously profiles both DNA methylome and transcriptome from the same cell. In sensory neurons, we consistently identify transcriptome and methylome heterogeneity among single cells but the majority of the expression variance is not explained by proximal promoter methylation, with the exception of genes that do not contain CpG islands. By contrast, gene body methylation is positively associated with gene expression for only those genes that contain a CpG island promoter. Furthermore, using single nucleotide polymorphism patterns from our hybrid mouse model, we also find positive correlation of allelic gene body methylation with allelic expression. Our method can be used to detect transcriptome, methylome, and single nucleotide polymorphism information within single cells to dissect the mechanisms of epigenetic gene regulation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 355 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 <1%
Germany 1 <1%
Norway 1 <1%
Unknown 350 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 93 26%
Researcher 66 19%
Student > Bachelor 30 8%
Student > Master 25 7%
Student > Doctoral Student 18 5%
Other 45 13%
Unknown 78 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 114 32%
Agricultural and Biological Sciences 71 20%
Computer Science 20 6%
Medicine and Dentistry 15 4%
Engineering 10 3%
Other 34 10%
Unknown 91 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 49. 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 17 January 2024.
All research outputs
#854,684
of 25,373,627 outputs
Outputs from Genome Biology
#568
of 4,467 outputs
Outputs of similar age
#15,024
of 312,436 outputs
Outputs of similar age from Genome Biology
#12
of 76 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 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 87% 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 312,436 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 76 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.