Over the last decades, the formerly irrevocable believe that proteins are the only key-factors in the complex regulatory machinery of a cell was crushed by a plethora of findings in all major eukaryotic lineages. These suggested a rugged landscape in the eukaryotic genome consist- ing of sequential, overlapping, or even bi-directional transcripts and myriads of regulatory elements. The vast part of the genome is indeed transcribed into an RNA intermediate, but solely a small fraction is finally translated into functional proteins. The sweeping majority, however, is either degraded or functions as a non-protein coding RNA (ncRNA). Due to continuous developments in experimental and computational research, the variety of ncRNA classes grew larger and larger, ranging from key-processes in the cellular lifespan to regulatory processes that are driven and guided by ncRNAs. The bioinformatical part pri- marily concentrates on the prediction, annotation, and extraction of characteristic properties of novel ncRNAs. Due to conservation of sequence and/or structure, this task is often deter- mined by an homology-search that utilizes information about functional, and hence conserved regions, as an indicator. This thesis focuses mainly on a special class of ncRNAs, small nucleolar RNAs (snoRNAs). These abundant molecules are mainly responsible for the guidance of 2’-O-ribose-methylations and pseudouridylations in different types of RNAs, such as ribosomal and spliceosomal RNAs. Although the relevance of single modifications is still rather unclear, the elimination of a bunch of modifications is shown to cause severe effects, including lethality. Several de novo prediction programs have been published over the last years and a substantial amount of publicly available snoRNA databases has originated. Normally, these are restricted to a small amount of species and a collection of experimentally extracted snoRNA. The detection of snoRNAs by means of wet lab experiments and/or de novo prediction tools is generally time consuming (wet lab) and a quite tedious task (identification of snoRNA-specific characteristics). The snoRNA annotation pipeline snoStrip was developed with the intention to circumvent these obstacles. It therefore utilizes a homology-based search procedure to reliably predict snoRNA genes in genomic sequences. In a subsequent step, all candidates are filtered with respect to specific sequence motifs and secondary structures. In a functional analysis, poten- tial target sites are predicted in ribosomal and spliceosomal RNA sequences. In contrast to de novo prediction tools, snoStrip focuses on the extension of the known snoRNA world to uncharted organisms and the mapping and unification of the existing diversity of snoRNAs into functional, homologous families. The pipeline is properly suited to analyze a manifold set of organisms in search for their snoRNAome in short timescales. This offers the opportunity to generate large scale analyses over whole eukaryotic kingdoms to gain insights into the evolutionary history of these spe- cial ncRNA molecules. A set of experimentally validated snoRNA genes in Deuterostomia and Fungi were starting points for highly comprehensive surveys searching and analyzing the snoRNA repertoire in these two major eukaryotic clades. In both cases, the snoStrip pipeline proved itself as a fast and reliable tool and collected thousands of snoRNA genes in nearly 200 organisms. Additionally, the Interaction Conservation Index (ICI), which is am- plified to additionally work on single lineages, provides a convenient measure to analyze and evaluate the conservation of snoRNA-targetRNA interactions across different species. The massive amount of data and the possibility to score the conservation of predicted interactions constitute the main pillars to gain an extraordinary insight into the evolutionary history of snoRNAs on both the sequence and the functional level. A substantial part of the snoR- NAome is traceable down to the root of both eukaryotic lineages and might indicate an even more ancient origin of these snoRNAs. However, a plenitude of lineage specific innovation and deletion events are also discernible. Due to its automated detection of homologous and functionally related snoRNA sequences, snoStrip identified extraordinary target switches in fungi. These unveiled a coupled evolutionary history of several snoRNA families that were previously thought to be independent. Although these findings are exceedingly interesting, the broad majority of snoRNA families is found to show remarkable conservation of the se- quence and the predicted target interactions. On two occasions, this thesis will shift its focus from a genuine snoRNA inspection to an analysis of introns. Both investigations, however, are still conducted under an evolutionary viewpoint. In case of the ubiquitously present U3 snoRNA, functional genes in a notable amount of fungi are found to be disrupted by U2-dependent introns. The set of previously known U3 genes is considerably enlarged by an adapted snoStrip-search procedure. Intron- disrupted genes are found in several fungal lineages, while their precise insertion points within the snoRNA-precursor are located in a small and homologous region. A potential targetRNA of snoRNA genes, U6 snRNA, is also found to contain intronic sequences. Within this work, U6 genes are detected and annotated in nearly all fungal organisms. Although a few U6 intron- carrying genes have been known before, the widespread of these findings and the diversity regarding the particular insertion points are surprising. Those U6 genes are commonly found to contain more than just one intron. In both cases of intron-disrupted non-coding RNA genes, the detected RNA molecules seem to be functional and the intronic sequences show remarkable sequence conservation for both their splice sites and the branch site. In summary, the snoStrip pipeline is shown to be a reliable and fast prediction tool that works on homology-based search principles. Large scale analyses on whole eukaryotic lineages become feasible on short notice. Furthermore, the automated detection of functionally related but not yet mapped snoRNA families adds a new layer of information. Based on surveys covering the evolutionary history of Fungi and Deuterostomia, profound insights into the evolutionary history of this ncRNA class are revealed suggesting ancient origin for a main part of the snoRNAome. Lineage specific innovation and deletion events are also found to occur at a large number of distinct timepoints.

DGCR8 (DiGeorge critical region 8) protein constitutes part of the Microprocessor complex together with Drosha, and is involved in the nuclear phase of microRNA (miRNA) biogenesis. DGCR8 recognises the hairpin RNA substrates of precursor miRNAs through two double-stranded RNA (dsRNA) binding motifs and acts as a molecular anchor to direct Drosha cleavage at the base of the pri-miRNA hairpin. Recent characterisation of the RNA targets of the Microprocessor by HITSCLIP of DGCR8 protein revealed that this complex also binds and regulates the stability of several types of transcripts, including mRNAs, lncRNAs and retrotransposons. Of particular interest is the binding of DGCR8 to mature small nucleolar RNA (snoRNA) transcripts, since the stability of these transcripts is dependent on DGCR8, but independent of Drosha. This raises the interesting possibility that there could be alternative DGCR8 complex/es using different nucleases to process a variety of cellular RNAs. We performed mass spectrometry experiments and revealed that DGCR8 copurifies with subunits of the nucleolar exosome, which contains the exonuclease RRP6. We demonstrated DGCR8 and the exosome form a nucleolar complex, which degrade the mature snoRNAs tested within this study. Interestingly, we also show that DGCR8/exosome complex controls the stability of the human telomerase RNA component (hTR/TERC), and absence of DGCR8 creates a concomitant telomere phenotype. In order to identify the RNA targets of the DGCR8/Exosome complex on a global scale we performed iCLIP of endogenous and overexpressed RRP6 (wild-type and a catalytically inactive form). Thus, intersection of CLIP datasets from DGCR8 and RRP6 identified common substrates; accordingly snoRNAs were the most represented. In addition, we identified the cellular RNA targets of the RRP6 associated human exosome. The use of a catalytically inactive form of RRP6 stabilised important in vivo interactions that are highly dynamic and transient and also highlighted the role of RRP6-mediated trimming of 3’flanks of immature non-coding RNAs. We will present a global view of the RNA-binding capacity of the RRP6-associated exosome. In sum, we identified a novel function for DGCR8, acting as an adaptor to recruit the exosome to structured RNAs and induce their degradation. Moreover, we have identified DGCR8-depenedent substrates of the exosome and have demonstrated the requirement of RRP6 for 3’ processing of ncRNAs.

Pt(II) chemotherapies, including cisplatin and oxaliplatin, have been used in cancer treatment since the 1970s, however, a full understanding of the mechanism by which these drugs function is still lacking. While the interaction between Pt(II) drugs and DNA has been extensively studied and subsequently indicted in the cellular response to Pt(II) drugs, recent data indicates non-DNA targets play important roles as well. To gain insight into the non-DNA damage-based effects induced by these drugs, MDA-MB-468 cells were treated at therapeutic concentrations of cisplatin between 30 minutes and 24 hours. Not only does this data provide insight into the complex time-dependent nature of the cellular response to cisplatin, but novel responses were also observed. First, I describe how the expression of numerous snoRNAs decreases as early as 30 minutes post-treatment with either cisplatin or oxaliplatin, and differential expression analysis indicates this occurs before activation of the DNA damage response. Since snoRNAs are necessary components in ribosome processing, we sought to determine the role snoRNAs play in the cellular response to Pt(II) drugs. A subgroup of our identified snoRNAs direct modification of helix 69 on the 28S ribosome. Quantification of methylation of helix 69 and other locations suggests cisplatin induced changes in snoRNA expression leads to dysregulation of rRNA modification, likely altering ribosome activity. I also observe varied activation of different types of DNA damage and cell cycle arrest between 3 and 12 hours of cisplatin treatment while early expression changes show downregulation of mitochondrial genes. We also identify a number of lncRNAs previously associated with TNBC that are downregulated after cisplatin treatment. This study establishes a gene expression profile induced by cisplatin treatment of triple-negative breast cancer that demonstrates the complex interplay of multiple means of stress induction. Lastly, we establish a method for analyzing direct DNA binding targets of platinum(II) chemotherapeutics. This pilot study confirms high accumulation of platinum(II) compounds on guanine-rich DNA and suggests DNA binding of significant genes leads to changes in their RNA expression. / 10000-01-01

Background: Small nucleolar RNAs (snoRNAs) are one of the most ancient families amongst non-protein-coding RNAs. They are ubiquitous in Archaea and Eukarya but absent in bacteria. Their main function is to target chemical modifications of ribosomal RNAs. They fall into two classes, box C/D snoRNAs and box H/ACA snoRNAs, which are clearly distinguished by conserved sequence motifs and the type of chemical modification that they govern. Similarly to microRNAs, snoRNAs appear in distinct families of homologs that affect homologous targets. In animals, snoRNAs and their evolution have been studied in much detail. In plants, however, their evolution has attracted comparably little attention. Results: In order to chart the phylogenetic distribution of individual snoRNA families in plants, we applied a sophisticated approach for identifying homologs of known plant snoRNAs across the plant kingdom. In response to the relatively fast evolution of snoRNAs, information on conserved sequence boxes, target sequences, and secondary structure is combined to identify additional snoRNAs. We identified 296 families of snoRNAs in 24 species and traced their evolution throughout the plant kingdom. Many of the plant snoRNA families comprise paralogs. We also found that targets are well-conserved for most snoRNA families. Conclusions: The sequence conservation of snoRNAs is sufficient to establish homologies between phyla. The degree of this conservation tapers off, however, between land plants and algae. Plant snoRNAs are frequently organized in highly conserved spatial clusters. As a resource for further investigations we provide carefully curated and annotated alignments for each snoRNA family under investigation.

Small nucleolar RNAs (snoRNAs) are one of the most abundant and evolutionary ancient group of small non-coding RNAs. Their main function is to target chemical modifications of ribosomal RNAs (rRNAs) and small nuclear (snRNAs). They fall into two classes, box C/D snoRNAs and box H/ACA snoRNAs, which are clearly distinguished by conserved sequence motifs and the type of modification that they govern. The box H/ACA snoRNAs are responsible for targeting pseudouridylation sites and the box C/D snoRNAs for directing 2’-O-methylation of ribonucleotides. A subclass that localize to the Cajal bodies, termed scaRNAs, are responsible for methylation and pseudouridylation of snRNAs. In addition an amazing diversity of non-canonical functions of individual snoRNAs arose. The modification patterns in rRNAs and snRNAs are retained during evolution making it even possible to project them from yeast onto human. The stringent conservation of modification sites and the slow evolution of rRNAs and snRNAs contradicts the rapid evolution of snoRNA sequences. Recent studies that incorporate high-throughput sequencing experiments still identify undetected snoRNAs even in well studied organisms as human. The snoRNAbase, which has been the standard database for human snoRNAs has not been updated ince 2006 and misses these new data. Along with the lack of a centralized data collection across species, which incorporates also snoRNA class specific characteristics the need to integrate distributed data from literature and databases into a comprehensive snoRNA set arose. Although several snoRNA studies included pro forma target predictions in individual species and more and more studies focus on non-canonical functions of subclasses a systematic survey on the guiding function and especially functional homologies of snoRNAs was not available. To establish a sound set of snoRNAs a computational snoRNA annotation pipeline, named snoStrip that identifies homologous snoRNAs in related species was employed. For large scale investigation of the snoRNA function, state-of-the-art target pedictions were performed with our software RNAsnoop and PLEXY. Further, a new measure the Interaction Conservation Index (ICI) was developed to evaluate the conservation of snoRNA function. The snoStrip pipeline was applied to vertebrate species, where the genome sequence has been available. In addition, it was used in several ncRNA annotation studies (48 avian, spotted gar) of newly assembled genomes to contribute the snoRNA genes. Detailed target analysis of the new vertebrate snoRNA set revealed that in general functions of homologous snoRNAs are evolutionarily stable, thus, members of the same snoRNA family guide equivalent modifications. The conservation of snoRNA sequences is high at target binding regions while the remaining sequence varies significantly. In addition to elucidating principles of correlated evolution it was possible, with the help of the ICI measure, to assign functions to previously orphan snoRNAs and to associate snoRNAs as partners to known but so far unexplained chemical modifications. As further pattern redundant guiding became apparent. For many modification sites more than one snoRNA encodes the appropriate antisense element (ASE), which could ensure constant modification through snoRNAs that have different expression patterns. Furthermore, predictions of snoRNA functions in conjunction with sequence conservation could identify distant homologies. Due to the high overall entropy of snoRNA sequences, such relationships are hard to detect by means of sequence homology search methods alone. The snoRNA interaction network was further expanded through novel snoRNAs that were detected in data from high-throughput experiments in human and mouse. Through subsequent target analysis the new snoRNAs could immediately explain known modifications that had no appropriate snoRNA guide assigned before. In a further study a full catalog of expressed snoRNAs in human was provided. Beside canonical snoRNAs also recent findings like AluACAs, sno-lncRNAs and extraordinary short SNORD-like transcripts were taken into account. Again the target analysis workflow identified undetected connections between snoRNA guides and modifications. Especially some species/clade specific interactions of SNORD-like genes emerged that seem to act as bona fide snoRNA guides for rRNA and snRNA modifications. For all high confident new snoRNA genes identified during this work official gene names were requested from the HUGO Gene Nomenclature Committee (HGNC) avoiding further naming confusion.

Over the last decades, the formerly irrevocable believe that proteins are the only key-factors in the complex regulatory machinery of a cell was crushed by a plethora of findings in all major eukaryotic lineages. These suggested a rugged landscape in the eukaryotic genome consist- ing of sequential, overlapping, or even bi-directional transcripts and myriads of regulatory elements. The vast part of the genome is indeed transcribed into an RNA intermediate, but solely a small fraction is finally translated into functional proteins. The sweeping majority, however, is either degraded or functions as a non-protein coding RNA (ncRNA). Due to continuous developments in experimental and computational research, the variety of ncRNA classes grew larger and larger, ranging from key-processes in the cellular lifespan to regulatory processes that are driven and guided by ncRNAs. The bioinformatical part pri- marily concentrates on the prediction, annotation, and extraction of characteristic properties of novel ncRNAs. Due to conservation of sequence and/or structure, this task is often deter- mined by an homology-search that utilizes information about functional, and hence conserved regions, as an indicator. This thesis focuses mainly on a special class of ncRNAs, small nucleolar RNAs (snoRNAs). These abundant molecules are mainly responsible for the guidance of 2’-O-ribose-methylations and pseudouridylations in different types of RNAs, such as ribosomal and spliceosomal RNAs. Although the relevance of single modifications is still rather unclear, the elimination of a bunch of modifications is shown to cause severe effects, including lethality. Several de novo prediction programs have been published over the last years and a substantial amount of publicly available snoRNA databases has originated. Normally, these are restricted to a small amount of species and a collection of experimentally extracted snoRNA. The detection of snoRNAs by means of wet lab experiments and/or de novo prediction tools is generally time consuming (wet lab) and a quite tedious task (identification of snoRNA-specific characteristics). The snoRNA annotation pipeline snoStrip was developed with the intention to circumvent these obstacles. It therefore utilizes a homology-based search procedure to reliably predict snoRNA genes in genomic sequences. In a subsequent step, all candidates are filtered with respect to specific sequence motifs and secondary structures. In a functional analysis, poten- tial target sites are predicted in ribosomal and spliceosomal RNA sequences. In contrast to de novo prediction tools, snoStrip focuses on the extension of the known snoRNA world to uncharted organisms and the mapping and unification of the existing diversity of snoRNAs into functional, homologous families. The pipeline is properly suited to analyze a manifold set of organisms in search for their snoRNAome in short timescales. This offers the opportunity to generate large scale analyses over whole eukaryotic kingdoms to gain insights into the evolutionary history of these spe- cial ncRNA molecules. A set of experimentally validated snoRNA genes in Deuterostomia and Fungi were starting points for highly comprehensive surveys searching and analyzing the snoRNA repertoire in these two major eukaryotic clades. In both cases, the snoStrip pipeline proved itself as a fast and reliable tool and collected thousands of snoRNA genes in nearly 200 organisms. Additionally, the Interaction Conservation Index (ICI), which is am- plified to additionally work on single lineages, provides a convenient measure to analyze and evaluate the conservation of snoRNA-targetRNA interactions across different species. The massive amount of data and the possibility to score the conservation of predicted interactions constitute the main pillars to gain an extraordinary insight into the evolutionary history of snoRNAs on both the sequence and the functional level. A substantial part of the snoR- NAome is traceable down to the root of both eukaryotic lineages and might indicate an even more ancient origin of these snoRNAs. However, a plenitude of lineage specific innovation and deletion events are also discernible. Due to its automated detection of homologous and functionally related snoRNA sequences, snoStrip identified extraordinary target switches in fungi. These unveiled a coupled evolutionary history of several snoRNA families that were previously thought to be independent. Although these findings are exceedingly interesting, the broad majority of snoRNA families is found to show remarkable conservation of the se- quence and the predicted target interactions. On two occasions, this thesis will shift its focus from a genuine snoRNA inspection to an analysis of introns. Both investigations, however, are still conducted under an evolutionary viewpoint. In case of the ubiquitously present U3 snoRNA, functional genes in a notable amount of fungi are found to be disrupted by U2-dependent introns. The set of previously known U3 genes is considerably enlarged by an adapted snoStrip-search procedure. Intron- disrupted genes are found in several fungal lineages, while their precise insertion points within the snoRNA-precursor are located in a small and homologous region. A potential targetRNA of snoRNA genes, U6 snRNA, is also found to contain intronic sequences. Within this work, U6 genes are detected and annotated in nearly all fungal organisms. Although a few U6 intron- carrying genes have been known before, the widespread of these findings and the diversity regarding the particular insertion points are surprising. Those U6 genes are commonly found to contain more than just one intron. In both cases of intron-disrupted non-coding RNA genes, the detected RNA molecules seem to be functional and the intronic sequences show remarkable sequence conservation for both their splice sites and the branch site. In summary, the snoStrip pipeline is shown to be a reliable and fast prediction tool that works on homology-based search principles. Large scale analyses on whole eukaryotic lineages become feasible on short notice. Furthermore, the automated detection of functionally related but not yet mapped snoRNA families adds a new layer of information. Based on surveys covering the evolutionary history of Fungi and Deuterostomia, profound insights into the evolutionary history of this ncRNA class are revealed suggesting ancient origin for a main part of the snoRNAome. Lineage specific innovation and deletion events are also found to occur at a large number of distinct timepoints.

Gene expression is the conduit by which genetic information is connected into cellular phenotypes. Recently, it was shown that gene expression in mammalian cells is governed, at least in part, by the expression of short double stranded RNA (dsRNA). This mode of gene regulation is influenced by a large group of dsRNA binding proteins that could either stabilize or trigger the degradation of dsRNA. Indeed, double stranded RNA (dsRNA) specific ribonucleases (RNases) play an important role in regulating gene expression. In most eukaryotes, members of the dsRNA specific RNase III family trigger RNA degradation and initiate cellular immune response. Disruption of human . RNase III (Dicer) deregulates fetal gene expression and promotes the development of cancer. However, very little is known about the housekeeping function of eukaryotic RNase III and the mechanism by which they distinguish between exogenous and endogenous cellular RNA species. This thesis elucidates how dsRNAs are selected for cleavage and demonstrates their contribution to RNA metabolism in yeast as model eukaryote. Initially, the reactivity determinants of yeast RNase III (Rnt1p) were identified in vitro and used to study the global impact of Rnt1p on the processing of non-coding RNA. The results indicate that Rnt1p is required for the processing of all small nucleolar RNAs (snoRNAs) involved in rRNA methylation and identify a new role of Rnt1p in the processing of intronic snoRNAs. It was shown that Rnt1p cleavage helps to coordinate the expression of some ribosomal protein genes hosting intronic snoRNAs. Direct snoRNA processing from the pre-mRNA blocks the expression of the host gene, while delayed snoRNA processing from the excised intron allows the expression of both genes. In this way, the cell can carefully calibrate the amount of snoRNA and ribosomal proteins required for ribosome biogenesis. In addition, a global analysis of snoRNA processing identified new forms of Rnt1p cleavage signals that do not exhibit a conserved sequence motif but instead use a new RNA fold to recruit the enzyme to the cleavage site. This finding led to the conclusion that Rnt1p may use a wide combination of structural motifs to identify its substrates and thus increases the theoretical number of potential degradation targets in vivo . To evaluate this possibility, a new search for snoRNA independent Rnt1p cleavage targets was performed. Interestingly, many Rnt1p cleavage signals were identified in intergenic regions devoid of known RNA transcripts. In vivo , it was shown that Rnt1p induce the termination of non-polyadenylated transcripts and functions as a surveillance mechanism for transcription read-through. This finding directly links Rnt1p to the transcription machinery and provides a new mechanism for polyadenylation independent transcription termination. Together the work described in this thesis presents an example of how eukaryotic RNase III may identify its substrates and present a case study where transcription, RNA processing and stability are linked.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

The nucleolus of eukaryotic cells contain a number of the intron-coding small nucleolar RNAs (snoRNAs), which functions are related to covalent modification of pre-rRNAs. The snoRNA that from long, phylogenetically conserved sequence complementarity to 28S, 18S, 5.8S and 5S rRNAs are designated as 28S, 18S, 5.8S and 5S snoRNAs, respectively. In the present study, studying on human 5S snoRNAs had been carried out. The human genome encoding candidate 5S snoRNAs were searched using database mining. The transcripts of 5S snoRNA genes were identified by RT-PCR analyses and DNA sequencing. No appreciable diversities of 5S snoRNA genes were observed as evidenced by single strand conformation polymorphism (SSCP) and high resolution agarose gel. Moreover, sequence conservation of 5S snoRNAs reflects a requirement for maintaining their secondary structure on exerting their function. The results of RT-PCR analyses revealed a tissue-specific transcription of 5S snoRNAs. A 5S snoRNA designated as N117 was identified to be highly expressed in normal brain. On the contrary, its expression markly decreased in brain tumor (meningioma). This seems to be associated with the expression of host gene, which encodes a protein similar to synapsin III protein. Consequently, this may implicate that the use of snoRNA as a potential index for the transcription of its host gene.

No description available.