↓ Skip to main content

Diversity and signature of small RNA in different bodily fluids using next generation sequencing

Overview of attention for article published in BMC Genomics, May 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
5 X users
patent
1 patent

Citations

dimensions_citation
67 Dimensions

Readers on

mendeley
84 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Diversity and signature of small RNA in different bodily fluids using next generation sequencing
Published in
BMC Genomics, May 2018
DOI 10.1186/s12864-018-4785-8
Pubmed ID
Authors

Mohamed El-Mogy, Bernard Lam, Taha A. Haj-Ahmad, Shannon McGowan, Darrick Yu, Lucas Nosal, Nezar Rghei, Pam Roberts, Yousef Haj-Ahmad

Abstract

Small RNAs are critical components in regulating various cellular pathways. These molecules may be tissue-associated or circulating in bodily fluids and have been shown to associate with different tumors. Next generation sequencing (NGS) on small RNAs is a powerful tool for profiling and discovery of microRNAs (miRNAs). In this study, we isolated total RNA from various bodily fluids: blood, leukocytes, serum, plasma, saliva, cell-free saliva, urine and cell-free urine. Next, we used Illumina's NGS platform and intensive bioinformatics analysis to investigate the distribution and signature of small RNAs in the various fluids. Successful NGS was accomplished despite the variations in RNA concentrations among the different fluids. Among the fluids studied, blood and plasma were found to be the most promising fluids for small RNA profiling as well as novel miRNA prediction. Saliva and urine yielded lower numbers of identifiable molecules and therefore were less reliable in small RNA profiling and less useful in predicting novel molecules. In addition, all fluids shared many molecules, including 139 miRNAs, the most abundant tRNAs, and the most abundant piwi-interacting RNAs (piRNAs). Fluids of similar origin (blood, urine or saliva) displayed closer clustering, while each fluid still retains its own characteristic signature based on its unique molecules and its levels of the common molecules. Donor urine samples showed sex-dependent differential clustering, which may prove useful for future studies. This study shows the successful clustering and unique signatures of bodily fluids based on their miRNA, tRNA and piRNA content. With this information, cohorts may be differentiated based on multiple molecules from each small RNA class by a multidimensional assessment of the overall molecular signature.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 84 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 21%
Student > Ph. D. Student 10 12%
Student > Bachelor 8 10%
Student > Master 8 10%
Student > Postgraduate 5 6%
Other 9 11%
Unknown 26 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 29%
Agricultural and Biological Sciences 10 12%
Medicine and Dentistry 6 7%
Neuroscience 5 6%
Unspecified 1 1%
Other 6 7%
Unknown 32 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 28 December 2021.
All research outputs
#4,509,012
of 22,769,322 outputs
Outputs from BMC Genomics
#1,875
of 10,639 outputs
Outputs of similar age
#89,017
of 330,316 outputs
Outputs of similar age from BMC Genomics
#57
of 262 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,639 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 82% 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 330,316 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 72% of its contemporaries.
We're also able to compare this research output to 262 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.