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Small RNA fragments derived from multiple RNA classes – the missing element of multi-omics characteristics of the hepatitis C virus cell culture model

Overview of attention for article published in BMC Genomics, June 2017
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Title
Small RNA fragments derived from multiple RNA classes – the missing element of multi-omics characteristics of the hepatitis C virus cell culture model
Published in
BMC Genomics, June 2017
DOI 10.1186/s12864-017-3891-3
Pubmed ID
Authors

Paulina Jackowiak, Anna Hojka-Osinska, Anna Philips, Agnieszka Zmienko, Lucyna Budzko, Patrick Maillard, Agata Budkowska, Marek Figlerowicz

Abstract

A pool of small RNA fragments (RFs) derived from diverse cellular RNAs has recently emerged as a rich source of functionally relevant molecules. Although their formation and accumulation has been connected to various stress conditions, the knowledge on RFs produced upon viral infections is very limited. Here, we applied the next generation sequencing (NGS) to characterize RFs generated in the hepatitis C virus (HCV) cell culture model (HCV-permissive Huh-7.5 cell line). We found that both infected and non-infected cells contained a wide spectrum of RFs derived from virtually all RNA classes. A significant fraction of identified RFs accumulated to similar levels as miRNAs. Our analysis, focused on RFs originating from constitutively expressed non-coding RNAs, revealed three major patterns of parental RNA cleavage. We found that HCV infection induced significant changes in the accumulation of low copy number RFs, while subtly altered the levels of high copy number ones. Finally, the candidate RFs potentially relevant for host-virus interactions were identified. Our results indicate that RFs should be considered an important component of the Huh-7.5 transcriptome and suggest that the main factors influencing the RF biogenesis are the RNA structure and RNA protection by interacting proteins. The data presented here significantly complement the existing transcriptomic, miRnomic, proteomic and metabolomic characteristics of the HCV cell culture model.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 21%
Researcher 6 21%
Student > Doctoral Student 3 11%
Student > Master 3 11%
Student > Bachelor 2 7%
Other 4 14%
Unknown 4 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 36%
Agricultural and Biological Sciences 8 29%
Medicine and Dentistry 2 7%
Immunology and Microbiology 2 7%
Veterinary Science and Veterinary Medicine 1 4%
Other 0 0%
Unknown 5 18%
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 02 July 2017.
All research outputs
#18,558,284
of 22,985,065 outputs
Outputs from BMC Genomics
#8,221
of 10,689 outputs
Outputs of similar age
#240,664
of 314,551 outputs
Outputs of similar age from BMC Genomics
#172
of 221 outputs
Altmetric has tracked 22,985,065 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,689 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 221 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.