↓ Skip to main content

Promoter-based identification of novel non-coding RNAs reveals the presence of dicistronic snoRNA-miRNA genes in Arabidopsis thaliana

Overview of attention for article published in BMC Genomics, November 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

twitter
5 X users
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
38 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
Promoter-based identification of novel non-coding RNAs reveals the presence of dicistronic snoRNA-miRNA genes in Arabidopsis thaliana
Published in
BMC Genomics, November 2015
DOI 10.1186/s12864-015-2221-x
Pubmed ID
Authors

Ge Qu, Katarzyna Kruszka, Patrycja Plewka, Shu-Yi Yang, Tzyy-Jen Chiou, Artur Jarmolowski, Zofia Szweykowska-Kulinska, Manuel Echeverria, Wojciech M. Karlowski

Abstract

In the past few decades, non-coding RNAs (ncRNAs) have emerged as important regulators of gene expression in eukaryotes. Most studies of ncRNAs in plants have focused on the identification of silencing microRNAs (miRNAs) and small interfering RNAs (siRNAs). Another important family of ncRNAs that has been well characterized in plants is the small nucleolar RNAs (snoRNAs) and the related small Cajal body-specific RNAs (scaRNAs). Both target chemical modifications of ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs). In plants, the snoRNA genes are organized in clusters, transcribed by RNA Pol II from a common promoter and subsequently processed into mature molecules. The promoter regions of snoRNA polycistronic genes in plants are highly enriched in two conserved cis-regulatory elements (CREs), Telo-box and Site II, which coordinate the expression of snoRNAs and ribosomal protein coding genes throughout the cell cycle. In order to identify novel ncRNA genes, we have used the snoRNA Telo-box/Site II motifs combination as a functional promoter indicator to screen the Arabidopsis genome. The predictions generated by this process were tested by detailed exploration of available RNA-Seq and expression data sets and experimental validation. As a result, we have identified several snoRNAs, scaRNAs and 'orphan' snoRNAs. We also show evidence for 16 novel ncRNAs that lack similarity to any reported RNA family. Finally, we have identified two dicistronic genes encoding precursors that are processed to mature snoRNA and miRNA molecules. We discuss the evolutionary consequences of this result in the context of a tight link between snoRNAs and miRNAs in eukaryotes. We present an alternative computational approach for non-coding RNA detection. Instead of depending on sequence or structure similarity in the whole genome screenings, we have explored the properties of promoter regions of well-characterized ncRNAs. Interestingly, besides expected ncRNAs predictions we were also able to recover single precursor arrangement for snoRNA-miRNA. Accompanied by analyses performed on rice sequences, we conclude that such arrangement might have interesting functional and evolutionary consequences and discuss this result in the context of a tight link between snoRNAs and miRNAs in eukaryotes.

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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 3%
Mexico 1 3%
Denmark 1 3%
Unknown 35 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 9 24%
Professor 6 16%
Student > Doctoral Student 2 5%
Student > Postgraduate 2 5%
Other 5 13%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 45%
Biochemistry, Genetics and Molecular Biology 14 37%
Computer Science 1 3%
Medicine and Dentistry 1 3%
Chemistry 1 3%
Other 0 0%
Unknown 4 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 February 2017.
All research outputs
#6,292,734
of 22,834,308 outputs
Outputs from BMC Genomics
#2,736
of 10,655 outputs
Outputs of similar age
#98,050
of 386,751 outputs
Outputs of similar age from BMC Genomics
#81
of 388 outputs
Altmetric has tracked 22,834,308 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 73% 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 386,751 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 74% of its contemporaries.
We're also able to compare this research output to 388 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.