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. tructuredonoding (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.

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.

Small nucleolar RNAs (snoRNAs) are among the first discovered and most extensively studied group of small non-coding RNA. However, most studies focused on a small subset of snoRNAs that guide the modification of ribosomal RNA. In this study, we annotated the expression pattern of all box C/D snoRNAs in normal and cancer cell lines independent of their functions. The results indicate that C/D snoRNAs are expressed as two distinct forms differing in their ends with respect to boxes C and D and in their terminal stem length. Both forms are overexpressed in cancer cell lines but display a conserved end distribution. Surprisingly, the long forms are more dependent than the short forms on the expression of the core snoRNP protein NOP58, thought to be essential for C/D snoRNA production. In contrast, a subset of short forms are dependent on the splicing factor RBFOX2. Analysis of the potential secondary structure of both forms indicates that the k-turn motif required for binding of NOP58 is less stable in short forms which are thus less likely to mature into a canonical snoRNP. Taken together the data suggest that C/D snoRNAs are divided into at least two groups with distinct maturation and functional preferences.

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With the emergence of high-throughput sequence characterization methods and the subsequent improvements in gene annotations, it is becoming increasingly clear that a large proportion of eukaryotic protein-coding genes (as many as 50% in human) serve as host genes for non-coding RNA genes. Amongst the most extensively characterized embedded non-coding RNA genes, small nucleolar RNAs and microRNAs represent abundant families. Encoded individually or clustered, in sense or antisense orientation with respect to their host and independently expressed or dependent on host expression, the genomic characteristics of embedded genes determine their biogenesis and the extent of their relationship with their host gene. Not only can host genes and the embedded genes they harbour be co-regulated and mutually modulate each other, many are functionally coupled playing a role in the same cellular pathways. And while host-non-coding RNA relationships can be highly conserved, mechanisms have been identified, and in particular an association with transposable elements, allowing the appearance of copies of non-coding genes nested in host genes, or the migration of embedded genes from one host gene to another. The study of embedded non-coding genes and their relationship with their host genes increases the complexity of cellular networks and provides important new regulatory links that are essential to properly understand cell function.