The Wilms’ tumour suppressor gene WT1, encodes a structurally diverse and multifunctional protein with tightly controlled expression throughout the development of several organ systems. Although initially defined as a tumor suppressor, WT1 has been found to be overexpressed in some cancers. How WT1 contributes to the shift from normal to aberrant development, or from normal function to oncogenic function, is poorly understood. Recent studies have shown an abundance of bidirectional transcription across metazoan genomes suggesting that non-coding antisense transcripts may have important roles in cell function. WT1-AS transcripts are capable of positively modulating WT1 protein levels in vitro, but relatively little is known about the functions of these antisense transcripts in vivo. The aim of this thesis was to characterize the role of a highly conserved region, Mcr2, located upstream of human and mouse WT1. Our data suggests that Mcr2 is not translated into protein and is transcribed in an antisense orientation. Mcr2 was found partially conserved in fish and well conserved in terrestrial vertebrates. By analysing novel mouse strains with genetically modified Mcr2 we have identified that Mcr2 may have a role in both fertility and embryonic survival, as well as regulating liquid homeostasis in the adult mouse.

Saccharomyces cerevisiae, the best-known representative of the Saccharomycotina subphylum, is an intron-poor organism with introns in only 5 % of its protein-coding genes. The most popular model of intron evolution suggests that intron-poor eukaryotes, such as S. cerevisiae, have undergone extensive intron loss throughout their evolutionary history. Against this background of intron loss, the retention of specific introns in the S. cerevisiae genome might be attributable to an evolutionary advantage that they provide. Introns have been shown to exhibit ‘function’ in various ways: through recognition of their sequence by RNA binding proteins, the adoption of secondary structures after transcription, the mechanism of splicing itself, and noncoding RNA genes embedded within them. In order to understand how RNA structures contribute to intron function, we first performed a computational screen using 306 alignments of S. cerevisiae intron orthologs. We identified conserved RNA structures in 19 introns that act either in trans as independent intron-encoded ncRNA genes or in cis within the pre-mRNA. Our results showed that introns with conserved secondary structures are conserved in yeast and experimental validation revealed they are frequently maintained in the cells after splicing. Our results suggest that the intron in GLC7 contains a novel ncRNA that regulates expression of its host transcript under stress conditions. Secondly, we focused on the HAC1 intron, which is known to be spliced upon the unfolded protein response by an endoribonuclease IRE1. We showed that the conservation of known intron-defining RNA hairpins in HAC1 extends to Fungi and Metazoa. Concurrently, we identified with high confidence those species that have lost the mechanism of this unconventional splicing. Thirdly, we investigated rates and mechanisms of intron loss within the whole Saccharomycetaceae family in order to develop our findings on the conservation of introns with RNA structures within the context of yeast evolution on both the species and clade level. Computational intron prediction supplemented by RNAseq data from four yeast species demonstrated that both intron loss and conservation of intronic ncRNAs were prevalent in yeast species, and that these patterns have been shaped by whole genome duplication. Lastly, we hypothesise that intron loss in recent yeast evolutionary history has been promoted by double strand break repair machinery.

The diversity and range of the biological functions of non-coding RNA molecules (ncRNA) have only recently been realised, and phylogenetic analysis of the RNA genes that define these molecules can provide important insights into the evolutionary pressures acting on RNA genes, and can lead to a better understanding of the structure and function of ncRNA. An appropriate dataset is fundamental to any evolutionary analysis, and because existing RNA alignments are unsuitable, I describe a software pipeline to derive RNA gene datasets from genomic alignments. RNA gene prediction software has not previously been evaluated on such sets of known RNA genes, and I find that two popular methods fail to predict the genes in approximately half of the alignments. In addition, high numbers of predictions are made in flanking regions that lack RNA genes, and these results provide motivation for subsequent phylogenetic analyses, because a better understanding of RNA gene evolution should lead to improved methods of prediction. I analyse the RNA gene alignments with a range of evolutionary models of substitution and examine which models best describe the changes evident in the alignment. The best models are expected to provide more accurate trees, and their properties can also shed light on the evolutionary processes that occur in RNA genes. Comparing DNA and RNA substitution models is non-trivial however, because they describe changes between two different types of state, so I present a proof that allows models with different state spaces to be compared in a statistically valid manner. I find that a large proportion of RNA genes are well described by a single RNA model that includes parameters describing both nucleotides and RNA structure, highlighting the multiple levels of constraint that act on the genes. The choice of model affects the inference of a phylogenetic tree, suggesting that model selection, with RNA models, should be standard practice for analysis of RNA genes.

Thesis advisor: Michelle M. Meyer / Non-coding RNA (ncRNA) perform vital functions in cells, but the impact of diversity across structure and function of homologous motifs has yet to be fully investigated. One reason for this is that the standard phylogenetic analysis used to address these questions in proteins cannot easily be applied to ncRNA due to their inherent characteristics. Compared to proteins, ncRNA have shorter sequence lengths, lower sequence conservation, and secondary structures that need to be incorporated into the analysis. This has necessitated an effort to develop methodology for investigating the evolutionary and functional relationship between sets of ncRNA. In this pursuit, I studied closely related riboswitches. Riboswitches are structured ncRNA found in bacterial mRNA that regulate gene expressions using their two major components: the aptamer and the expression platform. The aptamer of a riboswitch is able to bind a specific small molecule (ligand), and the bound/unbound state of the aptamer influences conformational changes in the expressions platform that can lead to increased or decreased downstream gene expression. Utilizing sequence and structural similarity metrics combined with graph clustering and de novo community detection algorithms I have determined a methodology for investigating the functional and evolutionary relationship between closely related riboswitches, and other ncRNA by extension, that are found across a range of diverse phyla. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Drought (soil water deficit) as a major adverse environmental condition can result in serious reduction in plant growth and crop production. Plants respond and adapt to drought stresses by triggering various signalling pathways leading to physiological, metabolic and developmental changes that may ultimately contribute to enhanced tolerance to the stress. Here, a novel non-coding RNA (ncRNA) involved in plant drought stress tolerance was identified. We showed that increasing the expression of this ncRNA led to enhanced sensitivity during seed germination and seedling growth to the phytohormone abscisic acid. The mutant seedlings are also more sensitive to osmotic stress inhibition of lateral root growth. Consistently, seedlings with enhanced expression of this ncRNA exhibited reduced transiprational water loss and were more drought-tolerant than the wild type. Future analyses of the mechanism for its role in drought tolerance may help us to understand how plant drought tolerance could be further regulated by this novel ncRNA.

No description available.

No description available.

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.

In this thesis the processing mechanisms of short non-coding RNAs (ncRNAs) is investigated by using data generated by the current method of high-throughput sequencing (HTS). The recently adapted short RNA-seq protocol allows the sequencing of RNA fragments of microRNA-like length (∼18-28nt). Thus, after mapping the data back to a reference genome, it is possible to not only measure, but also visualize the expression of all ncRNAs that are processed to fragments of this specific length. Short RNA-seq data was used to show that a highly abundant class of small RNAs, called microRNA-offset-RNAs (moRNAs), which was formerly detected in a basal chordate, is also produced from human microRNA precursors. To simplify the search, the blockbuster tool that automatically recognizes blocks of reads to detect specific expression patterns was developed. By using blockbuster, blocks from moRNAs were detected directly next to the miR or miR* blocks and could thus easily be registered in an automated way. When further investigating the short RNA-seq data it was realized that not only microRNAs give rise to short ∼22nt long RNA pieces, but also almost all other classes of ncRNAs, like tRNAs, snoRNAs, snRNAs, rRNAs, Y-RNAs, or vault RNAs. The formed read patterns that arise after mapping these RNAs back to a reference genome seem to reflect the processing of each class and are thus specific for the RNA transcripts of which they are derived from. The potential of this patterns in classification and identification of non-coding RNAs was explored. Using a random forest classifier which was trained on a set of characteristic features of the individual ncRNA classes, it was possible to distinguish three types of ncRNAs, namely microRNAs, tRNAs, and snoRNAs. To make the classification available to the research community, the free web service ‘DARIO’ that allows to study short read data from small RNA-seq experiments was developed. The classification has shown that read patterns are specific for different classes of ncRNAs. To make use of this feature, the tool deepBlockAlign was developed. deepBlockAlign introduces a two-step approach to align read patterns with the aim of quickly identifying RNAs that share similar processing footprints. In order to find possible exceptions to the well-known microRNA maturation by Dicer and to identify additional substrates for Dicer processing the small RNA sequencing data of a Dicer knockdown experiment in MCF-7 cells was re-evaluated. There were several Dicer-independent microRNAs, among them the important tumor supressor mir-663a. It is known that many aspects of the RNA maturation leave traces in RNA sequencing data in the form of mismatches from the reference genome. It is possible to recover many well- known modified sites in tRNAs, providing evidence that modified nucleotides are a pervasive phenomenon in these data sets.

The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes in extant taxa. Indeed, in all eukaryotic genomes, genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this, I consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. I find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, chromatin level mechanisms are likely regulators of this phenomenon. Firstly established in Primates and then expanded to compacted genome of yeasts, the phenomenon of correlation in change in gene expression of the neighbouring genes I describe as “expression piggy-backing”, an analog of hitchhiking. Extending the same principle to non-coding genes I find a possible role of lincRNAs in regulating expression of their neighbours, mediated by a coupling between splicing and chromatin modification. Finally I employ insertions of human endogenous retroviruses (HERVs), as a naturally occurring transgene experiment, to find out how randomly scattered sequences would affect the expression profile of their neighboring genes. I show these retroviruses to be the focus of transcription in human ES cells and define a transcription factor, LBP9, as a novel pluripotency-associated agent. Transcription results in neighbourhood modification including the generation of chimaeric transcripts. Predictions were confirmed experimentally by collaborators.