Computer identification of snoRNA genes using a Mammalian Orthologous Intron Database

Small nucleolar RNAs: continuing identification of novel members and increasing diversity of their molecular mechanisms of action

Identified five decades ago amongst the most abundant cellular RNAs, small nucleolar RNAs (snoRNAs) were initially described as serving as guides for the methylation and pseudouridylation of ribosomal RNA through direct base pairing. In recent years, however, increasingly powerful high-throughput genomic approaches and strategies have led to the discovery of many new members of the family and surprising diversity in snoRNA functionality and mechanisms of action. SnoRNAs are now known to target RNAs of many biotypes for a wider range of modifications, interact with diverse binding partners, compete with other binders for functional interactions, recruit diverse players to targets and affect protein function and accessibility through direct interaction. This mini-review presents the continuing characterization of the snoRNome through the identification of new snoRNA members and the discovery of their mechanisms of action, revealing a highly versatile noncoding family playing central regulatory roles and connecting the main cellular processes.

Comprehensive database and evolutionary dynamics of U12-type introns

During nuclear maturation of most eukaryotic pre-messenger RNAs and long non-coding RNAs, introns are removed through the process of RNA splicing. Different classes of introns are excised by the U2-type or the U12-type spliceosomes, large complexes of small nuclear ribonucleoprotein particles and associated proteins. We created intronIC, a program for assigning intron class to all introns in a given genome, and used it on 24 eukaryotic genomes to create the Intron Annotation and Orthology Database (IAOD). We then used the data in the IAOD to revisit several hypotheses concerning the evolution of the two classes of spliceosomal introns, finding support for the class conversion model explaining the low abundance of U12-type introns in modern genomes.

Regulatory role of small nucleolar RNAs in human diseases

Small nucleolar RNAs (snoRNAs) are appreciable players in gene expression regulation in human cells. The canonical function of box C/D and box H/ACA snoRNAs is posttranscriptional modification of ribosomal RNAs (rRNAs), namely, 2'-O-methylation and pseudouridylation, respectively. A series of independent studies demonstrated that snoRNAs, as well as other noncoding RNAs, serve as the source of various short regulatory RNAs. Some snoRNAs and their fragments can also participate in the regulation of alternative splicing and posttranscriptional modification of mRNA. Alterations in snoRNA expression in human cells can affect numerous vital cellular processes. SnoRNA level in human cells, blood serum, and plasma presents a promising target for diagnostics and treatment of human pathologies. Here we discuss the relation between snoRNAs and oncological, neurodegenerative, and viral diseases and also describe changes in snoRNA level in response to artificial stress and some drugs.

Class-specific prediction of ncRNAs

Many RNA families, i.e., groups of homologous RNA genes, belong to RNA classes, such as tRNAs, snoRNAs, or microRNAs, that are characterized by common sequence motifs and/or common secondary structure features. The detection of new members of RNA classes, as well as the comprehensive annotation of genomes with members of RNA classes is a challenging task that goes beyond simple homology search. Computational methods addressing this problem typically use a three-tiered approach: In the first step an efficient and sensitive filter is employed. In the second step the candidate set is narrowed down using computationally expensive methods geared towards specificity. In the final step the hits are annotated with class-specific features and scored. Here we review the tools that are currently available for a diverse set of RNA classes.

Biology and applications of small nucleolar RNAs

Small nucleolar RNAs (snoRNAs) constitute a group of non-coding RNAs principally involved in posttranscriptional modification of ubiquitously expressed ribosomal and small nuclear RNAs. However, a number of tissue-specific snoRNAs have recently been identified that apparently do not target conventional substrates and are presumed to guide processing of primary transcripts of protein-coding genes, potentially expanding the diapason of regulatory RNAs that control translation of mRNA to proteins. Here, we review biogenesis of snoRNAs and redefine their function in light of recent exciting discoveries. We also discuss the potential of recombinant snoRNAs to be used in modulation of gene expression.

SNOntology: Myriads of novel snoRNAs or just a mirage?

Background

Small nucleolar RNAs (snoRNAs) are a large group of non-coding RNAs (ncRNAs) that mainly guide 2'-O-methylation (C/D RNAs) and pseudouridylation (H/ACA RNAs) of ribosomal RNAs. The pattern of rRNA modifications and the set of snoRNAs that guide these modifications are conserved in vertebrates. Nearly all snoRNA genes in vertebrates are localized in introns of other genes and are processed from pre-mRNAs. Thus, the same promoter is used for the transcription of snoRNAs and host genes.

Results

The series of studies by Dahai Zhu and coworkers on snoRNAs and their genes were critically considered. We present evidence that dozens of species-specific snoRNAs that they described in vertebrates are experimental artifacts resulting from the improper use of Northern hybridization. The snoRNA genes with putative intrinsic promoters that were supposed to be transcribed independently proved to contain numerous substitutions and are, most likely, pseudogenes. In some cases, they are localized within introns of overlooked host genes. Finally, an increased number of snoRNA genes in mammalian genomes described by Zhu and coworkers is also an artifact resulting from two mistakes. First, numerous mammalian snoRNA pseudogenes were considered as genes, whereas most of them are localized outside of host genes and contain substitutions that question their functionality. Second, Zhu and coworkers failed to identify many snoRNA genes in non-mammalian species. As an illustration, we present 1352 C/D snoRNA genes that we have identified and annotated in vertebrates.

Conclusions

Our results demonstrate that conclusions based only on databases with automatically annotated ncRNAs can be erroneous. Special investigations aimed to distinguish true RNA genes from their pseudogenes should be done. Zhu and coworkers, as well as most other groups studying vertebrate snoRNAs, give new names to newly described homologs of human snoRNAs, which significantly complicates comparison between different species. It seems necessary to develop a uniform nomenclature for homologs of human snoRNAs in other vertebrates, e.g., human gene names prefixed with several-letter code denoting the vertebrate species.

Animal snoRNAs and scaRNAs with exceptional structures

The overwhelming majority of small nucleolar RNAs (snoRNAs) fall into two clearly defined classes characterized by distinctive secondary structures and sequence motifs. A small group of diverse ncRNAs, however, shares the hallmarks of one or both classes of snoRNAs but differs substantially from the norm in some respects. Here, we compile the available information on these exceptional cases, conduct a thorough homology search throughout the available metazoan genomes, provide improved and expanded alignments, and investigate the evolutionary histories of these ncRNA families as well as their mutual relationships.

Critical association of ncRNA with introns

It has been widely acknowledged that non-coding RNAs are master-regulators of genomic functions. However, the significance of the presence of ncRNA within introns has not received proper attention. ncRNA within introns are commonly produced through the post-splicing process and are specific signals of gene transcription events, impacting many other genes and modulating their expression. This study, along with the following discussion, details the association of thousands of ncRNAs—snoRNA, miRNA, siRNA, piRNA and long ncRNA—within human introns. We propose that such an association between human introns and ncRNAs has a pronounced synergistic effect with important implications for fine-tuning gene expression patterns across the entire genome.

Computational prediction of Caenorhabditis box H/ACA snoRNAs using genomic properties of their host genes

Identification of small nucleolar RNAs (snoRNAs) in genomic sequences has been challenging due to the relative paucity of sequence features. Many current prediction algorithms rely on detection of snoRNA motifs complementary to target sites in snRNAs and rRNAs. However, recent discovery of snoRNAs without apparent targets requires development of alternative prediction methods. We present an approach that combines rule-based filters and a Bayesian Classifier to identify a class of snoRNAs (H/ACA) without requiring target sequence information. It takes advantage of unique attributes of their genomic organization and improved species-specific motif characterization to predict snoRNAs that may otherwise be difficult to discover. Searches in the genomes of Caenorhabditis elegans and the closely related Caenorhabditis briggsae suggest that our method performs well compared to recent benchmark algorithms. Our results illustrate the benefits of training gene discovery engines on features restricted to particular phylogenetic groups and the utility of incorporating diverse data types in gene prediction.

Psiscan: a computational approach to identify H/ACA-like and AGA-like non-coding RNA in trypanosomatid genomes

Background

Detection of non coding RNA (ncRNA) molecules is a major bioinformatics challenge. This challenge is particularly difficult when attempting to detect H/ACA molecules which are involved in converting uridine to pseudouridine on rRNA in trypanosomes, because these organisms have unique H/ACA molecules (termed H/ACA-like) that lack several of the features that characterize H/ACA molecules in most other organisms.

Results

We present here a computational tool called Psiscan, which was designed to detect H/ACA-like molecules in trypanosomes. We started by analyzing known H/ACA-like molecules and characterized their crucial elements both computationally and experimentally.

Next, we set up constraints based on this analysis and additional phylogenic and functional data to rapidly scan three trypanosome genomes (T. brucei, T. cruzi and L. major) for sequences that observe these constraints and are conserved among the species. In the next step, we used minimal energy calculation to select the molecules that are predicted to fold into a lowest energy structure that is consistent with the constraints. In the final computational step, we used a Support Vector Machine that was trained on known H/ACA-like molecules as positive examples and on negative examples of molecules that were identified by the computational analyses but were shown experimentally not to be H/ACA-like molecules. The leading candidate molecules predicted by the SVM model were then subjected to experimental validation.

Conclusion

The experimental validation showed 11 molecules to be expressed (4 out of 25 in the intermediate stage and 7 out of 19 in the final validation after the machine learning stage). Five of these 11 molecules were further shown to be bona fide H/ACA-like molecules. As snoRNA in trypanosomes are organized in clusters, the new H/ACA-like molecules could be used as starting points to manually search for additional molecules in their neighbourhood. All together this study increased our repertoire by fourteen H/ACA-like and six C/D snoRNAs molecules from T. brucei and L. Major. In addition the experimental analysis revealed that six ncRNA molecules that are expressed are not downregulated in CBF5 silenced cells, suggesting that they have structural features of H/ACA-like molecules but do not have their standard function. We termed this novel class of molecules AGA-like, and we are exploring their function.

This study demonstrates the power of tight collaboration between computational and experimental approaches in a combined effort to reveal the repertoire of ncRNA molecles.

A computational screen for C/D box snoRNAs in the human genomic region associated with Prader-Willi and Angelman syndromes

Small nucleolar RNAs (snoRNAs) play a significant role in Prader-Willi Syndrome (PWS) and Angelman Syndrome (AS), which are genomic disorders resulting from deletions in the human chromosomal region 15q11-q13. To identify snoRNAs in the region, our computational study employs key motif features of C/D box snoRNAs and introduces a complementary RNA-RNA hybridization test. We identify three previously unknown methylation guide snoRNAs targeting ribosomal 18S and 28S RNAs, and two snoRNAs targeting serotonin receptor 2C mRNA. We show that the three snoRNA candidates likely possess methylation strands complementary to, and form stable complexes with, human ribosomal RNAs. Our screen also identifies 8 other snoRNA candidates that do not pass the rRNA-complementarity and/or hybridization tests. Two of these candidates have extensive sequence similarity to HBII-52, a snoRNA that regulates the alternative splicing of serotonin receptor 2C mRNA. Six out of our eleven candidate snoRNAs are also predicted by other existing methods.

Exploration of small RNAs

For several decades, only a limited number of noncoding RNAs, such as ribosomal and transfer RNA, have been studied in any depth. In recent years, additional species of noncoding RNAs have increasingly been discovered. Of these, small RNA species attract particular interest because of their essential roles in processes such as RNA silencing and modifications. Detailed analyses revealed several pathways associated with the function of small RNAs. Although these pathways show evolutional conservation, there are substantial differences. Advanced technologies to profile RNAs have accelerated the field further resulting in the discovery of an increasing number of novel species, suggesting that we are only just beginning to appreciate the complexity of small RNAs and their functions. Here, we review recent progress in novel small RNA exploration, including discovered small RNA species, their pathways, and devised technologies.

snoTARGET shows that human orphan snoRNA targets locate close to alternative splice junctions

Among thousands of non-protein-coding RNAs which have been found in humans, a significant group represents snoRNA molecules that guide other types of RNAs to specific chemical modifications, cleavages, or proper folding. Yet, hundreds of mammalian snoRNAs have unknown function and are referred to as "orphan" molecules. In 2006, for the first time, it was shown that a particular orphan snoRNA (HBII-52) plays an important role in the regulation of alternative splicing of the serotonin receptor gene in humans and other mammals. In order to facilitate the investigation of possible involvement of snoRNAs in the regulation of pre-mRNA processing, we developed a new computational web resource, snoTARGET, which searches for possible guiding sites for snoRNAs among the entire set of human and rodent exonic and intronic sequences. Application of snoTARGET for finding possible guiding sites for a number of human and rodent orphan C/D-box snoRNAs showed that another subgroup of these molecules (HBII-85) have statistically elevated guiding preferences toward exons compared to introns. Moreover, these energetically favorable putative targets of HBII-85 snoRNAs are non-randomly associated with genes producing alternatively spliced mRNA isoforms. The snoTARGET resource is freely available at: (http://hsc.utoledo.edu/depts/bioinfo/snotarget.html).

RNAs everywhere: genome-wide annotation of structured RNAs

Starting with the discovery of microRNAs and the advent of genome-wide transcriptomics, non-protein-coding transcripts have moved from a fringe topic to a central field research in molecular biology. In this contribution we review the state of the art of "computational RNomics", i.e., the bioinformatics approaches to genome-wide RNA annotation. Instead of rehashing results from recently published surveys in detail, we focus here on the open problem in the field, namely (functional) annotation of the plethora of putative RNAs. A series of exploratory studies are used to provide non-trivial examples for the discussion of some of the difficulties.

snoSeeker: an advanced computational package for screening of guide and orphan snoRNA genes in the human genome

Small nucleolar RNAs (snoRNAs) represent an abundant group of non-coding RNAs in eukaryotes. They can be divided into guide and orphan snoRNAs according to the presence or absence of antisense sequence to rRNAs or snRNAs. Current snoRNA-searching programs, which are essentially based on sequence complementarity to rRNAs or snRNAs, exist only for the screening of guide snoRNAs. In this study, we have developed an advanced computational package, snoSeeker, which includes CDseeker and ACAseeker programs, for the highly efficient and specific screening of both guide and orphan snoRNA genes in mammalian genomes. By using these programs, we have systematically scanned four human-mammal whole-genome alignment (WGA) sequences and identified 54 novel candidates including 26 orphan candidates as well as 266 known snoRNA genes. Eighteen novel snoRNAs were further experimentally confirmed with four snoRNAs exhibiting a tissue-specific or restricted expression pattern. The results of this study provide the most comprehensive listing of two families of snoRNA genes in the human genome till date.