Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs

View ORCID ProfileJunchao Shi, View ORCID ProfileEun-A Ko, View ORCID ProfileKenton M. Sanders, View ORCID ProfileQi Chen, View ORCID ProfileTong Zhou
doi: https://doi.org/10.1101/296970
Junchao Shi
Department of Physiology and Cell Biology, Reno School of Medicine, University of Nevada, Reno, NV 89512, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Junchao Shi
Eun-A Ko
Department of Physiology and Cell Biology, Reno School of Medicine, University of Nevada, Reno, NV 89512, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Eun-A Ko
Kenton M. Sanders
Department of Physiology and Cell Biology, Reno School of Medicine, University of Nevada, Reno, NV 89512, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Kenton M. Sanders
Qi Chen
Department of Physiology and Cell Biology, Reno School of Medicine, University of Nevada, Reno, NV 89512, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Qi Chen
Tong Zhou
Department of Physiology and Cell Biology, Reno School of Medicine, University of Nevada, Reno, NV 89512, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Tong Zhou
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

High-throughput RNA-seq has revolutionized the process of small RNA (sRNA) discovery, leading to a rapid expansion of sRNA categories. In addition to the previously well-characterized sRNAs such as microRNAs (miRNAs), Piwi-interacting RNA (piRNAs), and small nucleolar RNA (snoRNAs), recent emerging studies have spotlighted on tRNA-derived sRNAs (tsRNAs) and rRNA-derived sRNAs (rsRNAs) as new categories of sRNAs that bear versatile functions. Since existing software and pipelines for sRNA annotation are mostly focused on analyzing miRNAs or piRNAs, here we developed the sRNA annotation pipeline optimized for rRNA- and tRNA- derived sRNAs (SPORTS1.0). SPORTS1.0 is optimized for analyzing tsRNAs and rsRNAs from sRNA-seq data, in addition to its capacity to annotate canonical sRNAs such as miRNAs and piRNAs. Moreover, SPORTS1.0 can predict potential RNA modification sites based on nucleotide mismatches within sRNAs. SPORTS1.0 is precompiled to annotate sRNAs for a wide range of 68 species across bacteria, yeast, plant, and animal kingdoms, while additional species for analyses could be readily expanded upon end users’ input. For demonstration, by analyzing sRNA datasets using SPORTS1.0, we reveal that distinct signatures are present in tsRNAs and rsRNAs from different mouse cell types. We also find that compared to other sRNA species, tsRNAs bear the highest mismatch rate which is consistent with their highly modified nature. SPORTS1.0 is an open-source software and can be publically accessed at https://github.com/junchaoshi/sports1.0.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted April 26, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs
Junchao Shi, Eun-A Ko, Kenton M. Sanders, Qi Chen, Tong Zhou
bioRxiv 296970; doi: https://doi.org/10.1101/296970
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs
Junchao Shi, Eun-A Ko, Kenton M. Sanders, Qi Chen, Tong Zhou
bioRxiv 296970; doi: https://doi.org/10.1101/296970

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4246)
  • Biochemistry (9175)
  • Bioengineering (6807)
  • Bioinformatics (24066)
  • Biophysics (12160)
  • Cancer Biology (9567)
  • Cell Biology (13847)
  • Clinical Trials (138)
  • Developmental Biology (7661)
  • Ecology (11739)
  • Epidemiology (2066)
  • Evolutionary Biology (15547)
  • Genetics (10673)
  • Genomics (14365)
  • Immunology (9515)
  • Microbiology (22916)
  • Molecular Biology (9135)
  • Neuroscience (49170)
  • Paleontology (358)
  • Pathology (1487)
  • Pharmacology and Toxicology (2584)
  • Physiology (3851)
  • Plant Biology (8351)
  • Scientific Communication and Education (1473)
  • Synthetic Biology (2301)
  • Systems Biology (6207)
  • Zoology (1304)