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A next generation sequencing based approach to identify extracellular vesicle mediated mRNA transfers between cells

Overview of attention for article published in BMC Genomics, December 2017
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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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

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14 Dimensions

Readers on

mendeley
62 Mendeley
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Title
A next generation sequencing based approach to identify extracellular vesicle mediated mRNA transfers between cells
Published in
BMC Genomics, December 2017
DOI 10.1186/s12864-017-4359-1
Pubmed ID
Authors

Jialiang Yang, Jacob Hagen, Kalyani V. Guntur, Kimaada Allette, Sarah Schuyler, Jyoti Ranjan, Francesca Petralia, Stephane Gesta, Robert Sebra, Milind Mahajan, Bin Zhang, Jun Zhu, Sander Houten, Andrew Kasarskis, Vivek K. Vishnudas, Viatcheslav R. Akmaev, Rangaprasad Sarangarajan, Niven R. Narain, Eric E. Schadt, Carmen A. Argmann, Zhidong Tu

Abstract

Exosomes and other extracellular vesicles (EVs) have emerged as an important mechanism of cell-to-cell communication. However, previous studies either did not fully resolve what genetic materials were shuttled by exosomes or only focused on a specific set of miRNAs and mRNAs. A more systematic method is required to identify the genetic materials that are potentially transferred during cell-to-cell communication through EVs in an unbiased manner. In this work, we present a novel next generation of sequencing (NGS) based approach to identify EV mediated mRNA exchanges between co-cultured adipocyte and macrophage cells. We performed molecular and genomic profiling and jointly considered data from RNA sequencing (RNA-seq) and genotyping to track the "sequence varying mRNAs" transferred between cells. We identified 8 mRNAs being transferred from macrophages to adipocytes and 21 mRNAs being transferred in the opposite direction. These mRNAs represented biological functions including extracellular matrix, cell adhesion, glycoprotein, and signal peptides. Our study sheds new light on EV mediated RNA communications between adipocyte and macrophage cells, which may play a significant role in developing insulin resistance in diabetic patients. This work establishes a new method that is applicable to examining genetic material exchanges in many cellular systems and has the potential to be extended to in vivo studies as well.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 31%
Student > Bachelor 8 13%
Student > Master 7 11%
Researcher 5 8%
Student > Doctoral Student 4 6%
Other 7 11%
Unknown 12 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 27%
Medicine and Dentistry 9 15%
Agricultural and Biological Sciences 7 11%
Engineering 5 8%
Immunology and Microbiology 3 5%
Other 6 10%
Unknown 15 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 03 January 2018.
All research outputs
#1,669,538
of 12,376,381 outputs
Outputs from BMC Genomics
#903
of 7,251 outputs
Outputs of similar age
#66,042
of 351,681 outputs
Outputs of similar age from BMC Genomics
#74
of 550 outputs
Altmetric has tracked 12,376,381 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,251 research outputs from this source. They receive a mean Attention Score of 4.3. 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 351,681 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 550 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.