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In-depth characterization of the microRNA transcriptome in a leukemia progression model

Overview of attention for article published in Genome Research, November 2008
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)

Mentioned by

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1 patent

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148 Mendeley
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8 CiteULike
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Title
In-depth characterization of the microRNA transcriptome in a leukemia progression model
Published in
Genome Research, November 2008
DOI 10.1101/gr.077578.108
Pubmed ID
Authors

Florian Kuchenbauer, Ryan D. Morin, Bob Argiropoulos, Oleh I. Petriv, Malachi Griffith, Michael Heuser, Eric Yung, Jessica Piper, Allen Delaney, Anna-Liisa Prabhu, Yongjun Zhao, Helen McDonald, Thomas Zeng, Martin Hirst, Carl L. Hansen, Marco A. Marra, R. Keith Humphries

Abstract

MicroRNAs (miRNAs) have been shown to play important roles in physiological as well as multiple malignant processes, including acute myeloid leukemia (AML). In an effort to gain further insight into the role of miRNAs in AML, we have applied the Illumina massively parallel sequencing platform to carry out an in-depth analysis of the miRNA transcriptome in a murine leukemia progression model. This model simulates the stepwise conversion of a myeloid progenitor cell by an engineered overexpression of the nucleoporin 98 (NUP98)-homeobox HOXD13 fusion gene (ND13), to aggressive AML inducing cells upon transduction with the oncogenic collaborator Meis1. From this data set, we identified 307 miRNA/miRNA species in the ND13 cells and 306 miRNA/miRNA species in ND13+Meis1 cells, corresponding to 223 and 219 miRNA genes. Sequence counts varied between two and 136,558, indicating a remarkable expression range between the detected miRNA species. The large number of miRNAs expressed and the nature of differential expression suggest that leukemic progression as modeled here is dictated by the repertoire of shared, but differentially expressed miRNAs. Our finding of extensive sequence variations (isomiRs) for almost all miRNA and miRNA species adds additional complexity to the miRNA transcriptome. A stringent target prediction analysis coupled with in vitro target validation revealed the potential for miRNA-mediated release of oncogenes that facilitates leukemic progression from the preleukemic to leukemia inducing state. Finally, 55 novel miRNAs species were identified in our data set, adding further complexity to the emerging world of small RNAs.

Mendeley readers

The data shown below were compiled from readership statistics for 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 6%
United Kingdom 4 3%
Canada 2 1%
Russian Federation 1 <1%
Spain 1 <1%
Japan 1 <1%
Czech Republic 1 <1%
Unknown 129 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 50 34%
Student > Ph. D. Student 47 32%
Student > Master 12 8%
Professor > Associate Professor 11 7%
Student > Bachelor 7 5%
Other 21 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 102 69%
Biochemistry, Genetics and Molecular Biology 22 15%
Medicine and Dentistry 10 7%
Unspecified 3 2%
Computer Science 3 2%
Other 8 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 October 2014.
All research outputs
#2,509,038
of 9,400,242 outputs
Outputs from Genome Research
#1,520
of 2,545 outputs
Outputs of similar age
#90,270
of 262,262 outputs
Outputs of similar age from Genome Research
#38
of 43 outputs
Altmetric has tracked 9,400,242 research outputs across all sources so far. This one has received more attention than most of these and is in the 58th percentile.
So far Altmetric has tracked 2,545 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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 262,262 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.