Title |
A next generation sequencing based approach to identify extracellular vesicle mediated mRNA transfers between cells
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Published in |
BMC Genomics, December 2017
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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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 3 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 67% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 62 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 19 | 31% |
Student > Bachelor | 8 | 13% |
Student > Master | 7 | 11% |
Student > Doctoral Student | 4 | 6% |
Researcher | 4 | 6% |
Other | 8 | 13% |
Unknown | 12 | 19% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 17 | 27% |
Medicine and Dentistry | 8 | 13% |
Agricultural and Biological Sciences | 7 | 11% |
Engineering | 5 | 8% |
Immunology and Microbiology | 3 | 5% |
Other | 7 | 11% |
Unknown | 15 | 24% |