SALTS – SURFR (sncRNA) And LAGOOn (lncRNA) Transcriptomics Suite

Abstract

The widespread utilization of high-throughput sequencing technologies has unequivocally demonstrated that eukaryotic transcriptomes consist primarily (>98%) of non-coding RNA (ncRNA) transcripts significantly more diverse than their protein-coding counterparts. ncRNAs are typically divided into two categories based on their length. (1) ncRNAs less than 200 nucleotides (nt) long are referred as small non-coding RNAs (sncRNAs) and include microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), transfer ribonucleic RNAs (tRNAs), etc., and the majority of these are thought to function primarily in controlling gene expression. That said, the full repertoire of sncRNAs remains fairly poorly defined as evidenced by two entirely new classes of sncRNAs only recently being reported, i.e., snoRNA-derived RNAs (sdRNAs) and tRNA-derived fragments (tRFs). (2) ncRNAs longer than 200 nt long are known as long ncRNAs (lncRNAs). lncRNAs represent the 2nd largest transcriptional output of the cell (behind only ribosomal RNAs), and although functional roles for several lncRNAs have been reported, most lncRNAs remain largely uncharacterized due to a lack of predictive tools aimed at guiding functional characterizations. Importantly, whereas the cost of high-throughput transcriptome sequencing is now feasible for most active research programs, tools necessary for the interpretation of these sequencings typically require significant computational expertise and resources markedly hindering widespread utilization of these datasets. In light of this, we have developed a powerful new ncRNA transcriptomics suite, SALTS, which is highly accurate, markedly efficient, and extremely user-friendly. SALTS stands for SURFR (sncRNA) And LAGOOn (lncRNA) Transcriptomics Suite and offers platforms for comprehensive sncRNA and lncRNA profiling and discovery, ncRNA functional prediction, and the identification of significant differential expressions among datasets. Notably, SALTS is accessed through an intuitive Web-based interface, can be used to analyze either user-generated, standard next-generation sequencing (NGS) output file uploads (e.g., FASTQ) or existing NCBI Sequence Read Archive (SRA) data, and requires absolutely no dataset pre-processing or knowledge of library adapters/oligonucleotides. SALTS constitutes the first publically available, Web-based, comprehensive ncRNA transcriptomic NGS analysis platform designed specifically for users with no computational background, providing a much needed, powerful new resource capable of enabling more widespread ncRNA transcriptomic analyses. The SALTS WebServer is freely available online at http://salts.soc.southalabama.edu.

Salmonella Outer Membrane Vesicles contain tRNA Fragments (tRFs) that Inhibit Bacteriophage P22 infection

“…Therefore, in light of having found that tRNA-Thr-CGT-1-1, 44-73 tRF intracellular sequestration improves P22 infectivity, we next explored the potential role of tRNA-Thr-CGT-1-1, 44-73 tRF in OMV-mediated P22 restriction. SURFr 30,31 analysis of available S. Typhimurium OMV RNA-sequencing data (SRR6843039) 35 and qRT-PCR of our own OMV RNA isolates both confirm the presence of tRNA-Thr-CGT-1-1, 44-73 tRF within S. Typhimurium OMVs. What's more, we find tRNA-Thr-CGT-1-1, 44-73 tRF levels are ~3.5x higher in OMV RNA isolates than in total cellular RNA (Figure 3A).…”

“…SRA IDs corresponding to bacterial small RNA-seq datasets were obtained from the NCBI SRA database 45 and entered directly into SURFr, a real-time NGS data analytic tool to identify and analyze ncRNA-derived RNAs, for analysis after selecting the desired bacterial species 30,31 . Filter was set to "tRNA" only, and all tables, reports, and images downloaded.…”

“…tRNA-Thr-CGT-1-1, 44-73. (A) SURFr 30,31 "Differential Expression Vector" window depicting each nucleotide within tRNA-Thr-CGT-1-1 and indicating the fragment recurrently identified with a blue rectangle. The x-axis represents the position in the ncRNA selected (tRNA-Thr-CGT-1-1), and the y-axis depicts the expression level of the ncRNA at each position.…”

“…As such, we recently screened 12 preexisting small RNA seq datasets: six generated by our group 27 and six by others 28,29 for the presence of recurrent, specifically excised tRFs. Through employing a novel RNA-seq analysis platform designed to annotate fragments excised from longer noncoding RNAs, (SURFr) 30,31 , we have successfully identified 31 recurrent, relatively abundant tRFs expressed by S. Typhimurium. These tRFs average 26.7 nt in length ranging between 19 nt for the shortest (tRNA-Pro-TGG-1-1, 49-75) and 38 nt for the longest (tRNA-fMet-CAT-2-1, 33-70).…”

Salmonella Outer Membrane Vesicles contain tRNA Fragments (tRFs) that Inhibit Bacteriophage P22 infection

“…As such, we recently screened 12 preexisting small RNA seq datasets: six generated by our group 27 and six by others 28,29 for the presence of recurrent, speci cally excised tRFs. Through employing a novel RNA-seq analysis platform designed to annotate fragments excised from longer noncoding RNAs, (SURFr) 30,31 , we have successfully identi ed 31 recurrent, relatively abundant tRFs expressed by S. Typhimurium. These tRFs average 26.7 nt in length ranging between 19 nt for the shortest (tRNA-Pro-TGG-1-1, 49-75) and 38 nt for the longest (tRNA-fMet-CAT-2-1, 33-70).…”