Revealing stable processing products from ribosome-associated small RNAs by deep-sequencing data analysis

Abstract

The exploration of the non-protein-coding RNA (ncRNA) transcriptome is currently focused on profiling of microRNA expression and detection of novel ncRNA transcription units. However, recent studies suggest that RNA processing can be a multi-layer process leading to the generation of ncRNAs of diverse functions from a single primary transcript. Up to date no methodology has been presented to distinguish stable functional RNA species from rapidly degraded side products of nucleases. Thus the correct assessment of widespread RNA processing events is one of the major obstacles in transcriptome research. Here, we present a novel automated computational pipeline, named APART, providing a complete workflow for the reliable detection of RNA processing products from next-generation-sequencing data. The major features include efficient handling of non-unique reads, detection of novel stable ncRNA transcripts and processing products and annotation of known transcripts based on multiple sources of information. To disclose the potential of APART, we have analyzed a cDNA library derived from small ribosome-associated RNAs in Saccharomyces cerevisiae. By employing the APART pipeline, we were able to detect and confirm by independent experimental methods multiple novel stable RNA molecules differentially processed from well known ncRNAs, like rRNAs, tRNAs or snoRNAs, in a stress-dependent manner.

Slicing tRNAs to boost functional ncRNA diversity

“…However, in both cleavage scenarios, the stability of the two generated tRNA halves can be asymmetric and change within the same organism, depending on the encountered stress condition and life stage. 42,46 This is well exemplified in two independent transcriptome studies in the unicellular eukaryote Trypanosoma cruzi. Franzen et al detected 88.9% of the tRNA halves deriving from the 3′ part of the genuine tRNA of epimastigotic organisms, with a preference for tRNA His .…”

Identification of urinary exosomal noncoding RNAs as novel biomarkers in chronic kidney disease

“…In addition to known computational pipelines, a novel algorithm has previously been developed by our group, which also predicts novel ncRNA species, i.e., the automated pipeline for analysis of RNA transcripts (APART) (Zywicki et al 2012), based on prediction of stable transcripts from RNA-seq data. In order to identify novel, as well as known differentially expressed exRNAs, we thus have combined several of these specialized tools and adapted the APART algorithm to generate a simple customizable pipeline, designated as ncRNASeqScan, which is mainly written in the R programming language.…”

“…The clustering procedure is based on the clustering algorithm of APART (Zywicki et al 2012) and divided into two major steps, i.e., within conditions (within healthy controls and within CKD) and between conditions (between healthy controls and CKD). Initially, contiguous sequencing stretches (contigs) are generated from sequencing reads.…”

mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing

“…17 and MIReNA. 18 In addition, several integrated ncRNA analysis tools have been released, such as SeqCluster, 19 DARIO,20 ncPRO-seq, 21 CPSS, 22 Shortran, 23 NORAHDESK, 24 APART, 25 and smyRNA. 26 We previously developed a web service, mirTools 1.0, which provides annotation of miRNAs based on NGS and has been widely used.…”