snoDB 2.0: an enhanced interactive database, specializing in human snoRNAs.

snoDB is an interactive database of human small nucleolar RNAs (snoRNAs) that includes up-to-date information on snoRNA features, genomic location, conservation, host gene, snoRNA-RNA targets and snoRNA abundance and provides links to other resources. In the second edition of this database (snoDB 2.0), we added an entirely new section on ribosomal RNA (rRNA) chemical modifications guided by snoRNAs with easy navigation between the different rRNA versions used in the literature and experimentally measured levels of modification. We also included new layers of information, including snoRNA motifs, secondary structure prediction, snoRNA-protein interactions, copy annotations and low structure bias expression data in a wide panel of tissues and cell lines to bolster functional probing of snoRNA biology. Version 2.0 features updated identifiers, more links to external resources and duplicate entry resolution. As a result, snoDB 2.0, which is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/snoDB/, represents a one-stop shop for snoRNA features, rRNA modification targets, functional impact and potential regulators.

snoDB: an interactive database of human snoRNA sequences, abundance and interactions.

Small nucleolar RNAs (snoRNAs) are an abundant type of non-coding RNA with conserved functions in all known eukaryotes. Classified into two main families, the box C/D and H/ACA snoRNAs, they enact their most well characterized role of guiding site specific modifications in ribosomal RNA, through the formation of specific ribonucleoprotein complexes, with fundamental implications in ribosome biogenesis. However, it is becoming increasingly clear that the landscape of snoRNA cellular functionality is much broader than it once seemed with novel members, non-uniform expression patterns, new and diverse targets as well as several emerging non-canonical functions ranging from the modulation of alternative splicing to the regulation of chromatin architecture. In order to facilitate the further characterization of human snoRNAs in a holistic manner, we introduce an online interactive database tool: snoDB. Its purpose is to consolidate information on human snoRNAs from different sources such as sequence databases, target information, both canonical and non-canonical from the literature and from high-throughput RNA-RNA interaction datasets, as well as high-throughput sequencing data that can be visualized interactively.

Simultaneous sequencing of coding and noncoding RNA reveals a human transcriptome dominated by a small number of highly expressed noncoding genes.

Comparing the abundance of one RNA molecule to another is crucial for understanding cellular functions but most sequencing techniques can target only specific subsets of RNA. In this study, we used a new fragmented ribodepleted TGIRT sequencing method that uses a thermostable group II intron reverse transcriptase (TGIRT) to generate a portrait of the human transcriptome depicting the quantitative relationship of all classes of nonribosomal RNA longer than 60 nt. Comparison between different sequencing methods indicated that FRT is more accurate in ranking both mRNA and noncoding RNA than viral reverse transcriptase-based sequencing methods, even those that specifically target these species. Measurements of RNA abundance in different cell lines using this method correlate with biochemical estimates, confirming tRNA as the most abundant nonribosomal RNA biotype. However, the single most abundant transcript is 7SL RNA, a component of the signal recognition particle. Structured noncoding RNAs (sncRNAs) associated with the same biological process are expressed at similar levels, with the exception of RNAs with multiple functions like U1 snRNA. In general, sncRNAs forming RNPs are hundreds to thousands of times more abundant than their mRNA counterparts. Surprisingly, only 50 sncRNA genes produce half of the non-rRNA transcripts detected in two different cell lines. Together the results indicate that the human transcriptome is dominated by a small number of highly expressed sncRNAs specializing in functions related to translation and splicing.