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Co-sequencing and novel delayed anti-correlation identify function for pancreatic enriched microRNA biomarkers in a rat model of acute pancreatic injury

Overview of attention for article published in BMC Genomics, April 2018
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Title
Co-sequencing and novel delayed anti-correlation identify function for pancreatic enriched microRNA biomarkers in a rat model of acute pancreatic injury
Published in
BMC Genomics, April 2018
DOI 10.1186/s12864-018-4657-2
Pubmed ID
Authors

Zhihua Li, Rodney Rouse

Abstract

Co-sequencing of messenger ribonucleic acid (mRNA) and micro ribonucleic acid (miRNA) across a time series (1, 3, 6, 24, and 48 h post injury) was used to identify potential miRNA-gene interactions during pancreatic injury, associate serum and tissue levels of candidate miRNA biomarkers of pancreatic injury, and functionally link these candidate miRNA biomarkers to observed histopathology. RNAs were derived from pancreatic tissues obtained in experiments characterizing the serum levels of candidate miRNA biomarkers in response to acute pancreatic injury in rats. No correlation was discovered between tissue and serum levels of the miRNAs. A combination of differential gene expression, novel delayed anti-correlation analysis and experimental database interrogation was used to identify messenger RNAs and miRNAs that experienced significant expression change across the time series, that were negatively correlated, that were complementary in sequence, and that had experimentally supported relationships. This approach yielded a complex signaling network for future investigation and a link for the specific candidate miRNA biomarkers, miR-216a-5p and miR-217-5p, to cellular processes that were in fact the prominent histopathology observations in the same experimental samples. RNA quality bias by treatment was observed in the study samples and a statistical correction was applied. The relevance and impact of that correction on significant results is discussed. The described approach allowed extraction of miRNA function from genomic data and defined a mechanistic anchor for these miRNAs as biomarkers. Functional and mechanistic conclusions are supported by histopathology findings.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Lecturer 1 11%
Professor 1 11%
Student > Master 1 11%
Researcher 1 11%
Other 1 11%
Unknown 2 22%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 1 11%
Biochemistry, Genetics and Molecular Biology 1 11%
Agricultural and Biological Sciences 1 11%
Physics and Astronomy 1 11%
Medicine and Dentistry 1 11%
Other 1 11%
Unknown 3 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 2019.
All research outputs
#17,947,156
of 23,045,021 outputs
Outputs from BMC Genomics
#7,612
of 10,697 outputs
Outputs of similar age
#236,901
of 326,468 outputs
Outputs of similar age from BMC Genomics
#164
of 238 outputs
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