RT Journal Article
SR Electronic
T1 SPORTS1.0: a tool for annotating and profiling non-coding RNAs optimized for rRNA- and tRNA-derived small RNAs
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 296970
DO 10.1101/296970
A1 Junchao Shi
A1 Eun-A Ko
A1 Kenton M. Sanders
A1 Qi Chen
A1 Tong Zhou
YR 2018
UL http://biorxiv.org/content/early/2018/04/07/296970.abstract
AB High-throughput RNA-seq has revolutionized the process of small RNA (sRNA) discovery, leading to a rapid expansion of sRNA categories. In addition to previously well-characterized sRNAs such as miRNAs, piRNAs and snoRNAs, recent emerging studies have spotlighted on tsRNAs (tRNA-derived small RNAs) and rsRNAs (rRNA-derived small RNAs) as new categories of sRNAs that bear versatile functions. Since existing software and pipelines for sRNA annotation are mostly focusing on analyzing miRNAs or piRNAs, here we developed SPORTS1.0 (small RNA annotation pipeline optimized for rRNA- and tRNA-derived small RNAs), which is optimized for analyzing tsRNAs and rsRNAs from sRNA-seq data, also with the capacity to annotate canonical sRNAs such as miRNAs and piRNAs. In addition, SPORTS1.0 can predict potential RNA modification sites basing 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 additional species for analyses could be readily expanded upon end users’ input. As an example, SPORTS1.0 revealed distinct tsRNA and rsRNA signatures from different mice tissues/cells; and discovered that tsRNAs bear the highest mismatch rate compared with other sRNA species, which is consistent with their highly modified nature. SPORTS1.0 is an open-source software deposited at https://github.com/junchaoshi/sports1.0.