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A Systematic Analysis of miRNA Transcriptome in Marek’s Disease Virus-Induced Lymphoma Reveals Novel and Differentially Expressed miRNAs

Overview of attention for article published in PLOS ONE, November 2012
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Title
A Systematic Analysis of miRNA Transcriptome in Marek’s Disease Virus-Induced Lymphoma Reveals Novel and Differentially Expressed miRNAs
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0051003
Pubmed ID
Authors

Ling Lian, Lujiang Qu, Yanmei Chen, Susan J. Lamont, Ning Yang

Abstract

Marek's disease is a lymphoproliferative neoplastic disease of the chicken, which poses a serious threat to poultry health. Marek's disease virus (MDV)-induced T-cell lymphoma is also an excellent biomedical model for neoplasia research. Recently, miRNAs have been demonstrated to play crucial roles in mediating neoplastic transformation. To investigate host miRNA expression profiles in the tumor transformation phase of MDV infection, we performed deep sequencing in two MDV-infected samples (tumorous spleen and MD lymphoma from liver), and two non-infected controls (non-infected spleen and lymphocytes). In total, 187 and 16 known miRNAs were identified in chicken and MDV, respectively, and 17 novel chicken miRNAs were further confirmed by qPCR. We identified 28 down-regulated miRNAs and 11 up-regulated miRNAs in MDV-infected samples by bioinformatic analysis. Of nine further tested by qPCR, seven were verified. The gga-miR-181a, gga-miR-26a, gga-miR-221, gga-miR-222, gga-miR-199*, and gga-miR-140* were down-regulated, and gga-miR-146c was up-regulated in MDV-infected tumorous spleens and MD lymphomas. In addition, 189 putative target genes for seven differentially expressed miRNAs were predicted. The luciferase reporter gene assay showed interactions of gga-miR-181a with MYBL1, gga-miR-181a with IGF2BP3, and gga-miR-26a with EIF3A. Differential expression of miRNAs and the predicted targets strongly suggest that they contribute to MDV-induced lymphomagenesis.

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Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 43 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 25%
Researcher 10 23%
Student > Master 6 14%
Student > Postgraduate 4 9%
Professor > Associate Professor 4 9%
Other 5 11%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 41%
Biochemistry, Genetics and Molecular Biology 4 9%
Medicine and Dentistry 4 9%
Veterinary Science and Veterinary Medicine 3 7%
Immunology and Microbiology 3 7%
Other 4 9%
Unknown 8 18%