272 research outputs found

    Conserved intron positions in ancient protein modules

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    BACKGROUND: The timing of the origin of introns is of crucial importance for an understanding of early genome architecture. The Exon theory of genes proposed a role for introns in the formation of multi-exon proteins by exon shuffling and predicts the presence of conserved splice sites in ancient genes. In this study, large-scale analysis of potential conserved splice sites was performed using an intron-exon database (ExInt) derived from GenBank. RESULTS: A set of conserved intron positions was found by matching identical splice sites sequences from distantly-related eukaryotic kingdoms. Most amino acid sequences with conserved introns were homologous to consensus sequences of functional domains from conserved proteins including kinases, phosphatases, small GTPases, transporters and matrix proteins. These included ancient proteins that originated before the eukaryote-prokaryote split, for instance the catalytic domain of protein phosphatase 2A where a total of eleven conserved introns were found. Using an experimental setup in which the relation between a splice site and the ancientness of its surrounding sequence could be studied, it was found that the presence of an intron was positively correlated to the ancientness of its surrounding sequence. Intron phase conservation was linked to the conservation of the gene sequence and not to the splice site sequence itself. However, no apparent differences in phase distribution were found between introns in conserved versus non-conserved sequences. CONCLUSION: The data confirm an origin of introns deep in the eukaryotic branch and is in concordance with the presence of introns in the first functional protein modules in an 'Exon theory of genes' scenario. A model is proposed in which shuffling of primordial short exonic sequences led to the formation of the first functional protein modules, in line with hypotheses that see the formation of introns integral to the origins of genome evolution. REVIEWERS: This article was reviewed by Scott Roy (nominated by Anthony Poole), Sandro de Souza (nominated by Manyuan Long), and Gáspár Jékely

    Modelling evolution on design-by-contract predicts an origin of Life through an abiotic double-stranded RNA world

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    BACKGROUND: It is generally believed that life first evolved from single-stranded RNA (ssRNA) that both stored genetic information and catalyzed the reactions required for self-replication. PRESENTATION OF THE HYPOTHESIS: By modeling early genome evolution on the engineering paradigm design-by-contract, an alternative scenario is presented in which life started with the appearance of double-stranded RNA (dsRNA) as an informational storage molecule while catalytic single-stranded RNA was derived from this dsRNA template later in evolution. TESTING THE HYPOTHESIS: It was investigated whether this scenario could be implemented mechanistically by starting with abiotic processes. Double-stranded RNA could be formed abiotically by hybridization of oligoribonucleotides that are subsequently non-enzymatically ligated into a double-stranded chain. Thermal cycling driven by the diurnal temperature cycles could then replicate this dsRNA when strands of dsRNA separate and later rehybridize and ligate to reform dsRNA. A temperature-dependent partial replication of specific regions of dsRNA could produce the first template-based generation of catalytic ssRNA, similar to the developmental gene transcription process. Replacement of these abiotic processes by enzymatic processes would guarantee functional continuity. Further transition from a dsRNA to a dsDNA world could be based on minor mutations in template and substrate recognition sites of an RNA polymerase and would leave all existing processes intact. IMPLICATIONS OF THE HYPOTHESIS: Modeling evolution on a design pattern, the 'dsRNA first' hypothesis can provide an alternative mechanistic evolutionary scenario for the origin of our genome that preserves functional continuity. REVIEWERS: This article was reviewed by Anthony Poole, Eugene Koonin and Eugene Shakhnovic

    Characterization of the ubiquitin-like protein Hub1 and its role in pre-mRNA splicing in human cells

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    Oogenesis: Single cell development and differentiation

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    AbstractOocytes express a unique set of genes that are essential for their growth, for meiotic recombination and division, for storage of nutrients, and for fertilization. We have utilized the newly sequenced genome of Strongylocentrotus purpuratus to identify genes that help the oocyte accomplish each of these tasks. This study emphasizes four classes of genes that are specialized for oocyte function: (1) Transcription factors: many of these factors are not significantly expressed in embryos, but are shared by other adult tissues, namely the ovary, testis, and gut. (2) Meiosis: A full set of meiotic genes is present in the sea urchin, including those involved in cohesion, in synaptonemal complex formation, and in meiotic recombination. (3) Yolk uptake and storage: Nutrient storage for use during early embryogenesis is essential to oocyte function in most animals; the sea urchin accomplishes this task by using the major yolk protein and a family of accessory proteins called YP30. Comparison of the YP30 family members across their conserved, tandem fasciclin domains with their intervening introns reveals an incongruence in the evolution of its major clades. (4) Fertilization: This set of genes includes many of the cell surface proteins involved in sperm interaction and in the physical block to polyspermy. The majority of these genes are active only in oocytes, and in many cases, their anatomy reflects the tandem repeating interaction domains essential for the function of these proteins. Together, the expression profile of these four gene classes highlights the transitions of the oocyte from a stem cell precursor, through stages of development, to the clearing and re-programming of gene expression necessary to transition from oocyte, to egg, to embryo

    Genomics and phylogeny of cytoskeletal proteins: Tools and analyses.

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    Leveraging EST Evidence to Automatically Predict Alternatively Spliced Genes, Master\u27s Thesis, December 2006

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    Current methods for high-throughput automatic annotation of newly sequenced genomes are largely limited to tools which predict only one transcript per gene locus. Evidence suggests that 20-50% of genes in higher eukariotic organisms are alternatively spliced. This leaves the remainder of the transcripts to be annotated by hand, an expensive time-consuming process. Genomes are being sequenced at a much higher rate than they can be annotated. We present three methods for using the alignments of inexpensive Expressed Sequence Tags in combination with HMM-based gene prediction with N-SCAN EST to recreate the vast majority of hand annotations in the D.melanogaster genome. In our first method, we “piece together” N-SCAN EST predictions with clustered EST alignments to increase the number of transcripts per locus predicted. This is shown to be a sensitve and accurate method, predicting the vast majority of known transcripts in the D.melanogaster genome. We present an approach of using these clusters of EST alignments to construct a Multi-Pass gene prediction phase, again, piecing it together with clusters of EST alignments. While time consuming, Multi-Pass gene prediction is very accurate and more sensitive than single-pass. Finally, we present a new Hidden Markov Model instance, which augments the current N-SCAN EST HMM, that predicts multiple splice forms in a single pass of prediction. This method is less time consuming, and performs nearly as well as the multi-pass approach

    The development of computational methods for large-scale comparisons and analyses of genome evolution

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    The last four decades have seen the development of a number of experimental methods for the deduction of the whole genome sequences of an ever-increasing number of organisms. These sequences have in the first instance, allowed their investigators the opportunity to examine the molecular primary structure of areas of scientific interest, but with the increased sampling of organisms across the phylogenetic tree and the improved quality and coverage of genome sequences and their associated annotations, the opportunity to undertake detailed comparisons both within and between taxonomic groups has presented itself. The work described in this thesis details the application of comparative bioinformatics analyses on inter- and intra-genomic datasets, to elucidate those genomic changes, which may underlie organismal adaptations and contribute to changes in the complexity of genome content and structure over time. The results contained herein demonstrate the power and flexibility of the comparative approach, utilising whole genome data, to elucidate the answers to some of the most pressing questions in the biological sciences today.As the volume of genomic data increases, both as a result of increased sampling of the tree of life and due to an increase in the quality and throughput of the sequencing methods, it has become clear that there is a necessity for computational analyses of these data. Manual analysis of this volume of data, which can extend beyond petabytes of storage space, is now impossible. Automated computational pipelines are therefore required to retrieve, categorise and analyse these data. Chapter two discusses the development of a computational pipeline named the Genome Comparison and Analysis Toolkit (GCAT). The pipeline was developed using the Perl programming language and is tightly integrated with the Ensembl Perl API allowing for the retrieval and analyses of their rich genomic resources. In the first instance the pipeline was tested for its robustness by retrieving and describing various components of genomic architecture across a number of taxonomic groups. Additionally, the need for programmatically independent means of accessing data and in particular the need for Semantic Web based protocols and tools for the sharing of genomics resources is highlighted. This is not just for the requirements of researchers, but for improved communication and sharing between computational infrastructure. A prototype Ensembl REST web service was developed in collaboration with the European Bioinformatics Institute (EBI) to provide a means of accessing Ensembl’s genomic data without having to rely on their Perl API. A comparison of the runtime and memory usage of the Ensembl Perl API and prototype REST API were made relative to baseline raw SQL queries, which highlights the overheads inherent in building wrappers around the SQL queries. Differences in the efficiency of the approaches were highlighted, and the importance of investing in the development of Semantic Web technologies as a tool to improve access to data for the wider scientific community are discussed.Data highlighted in chapter two led to the identification of relative differences in the intron structure of a number of organisms including teleost fish. Chapter three encompasses a published, peer-reviewed study. Inter-genomic comparisons were undertaken utilising the 5 available teleost genome sequences in order to examine and describe their intron content. The number and sizes of introns were compared across these fish and a frequency distribution of intron size was produced that identified a novel expansion in the Zebrafish lineage of introns in the size range of approximately 500-2,000 bp. Further hypothesis driven analyses of the introns across the whole distribution of intron sizes identified that the majority, but not all of the introns were largely comprised of repetitive elements. It was concluded that the introns in the Zebrafish peak were likely the result of an ancient expansion of repetitive elements that had since degraded beyond the ability of computational algorithms to identify them. Additional sampling throughout the teleost fish lineage will allow for more focused phylogenetically driven analyses to be undertaken in the future.In chapter four phylogenetic comparative analyses of gene duplications were undertaken across primate and rodent taxonomic groups with the intention of identifying significantly expanded or contracted gene families. Changes in the size of gene families may indicate adaptive evolution. A larger number of expansions, relative to time since common ancestor, were identified in the branch leading to modern humans than in any other primate species. Due to the unique nature of the human data in terms of quantity and quality of annotation, additional analyses were undertaken to determine whether the expansions were methodological artefacts or real biological changes. Novel approaches were developed to test the validity of the data including comparisons to other highly annotated genomes. No similar expansion was seen in mouse when comparing with rodent data, though, as assemblies and annotations were updated, there were differences in the number of significant changes, which brings into question the reliability of the underlying assembly and annotation data. This emphasises the importance of an understanding that computational predictions, in the absence of supporting evidence, may be unlikely to represent the actual genomic structure, and instead be more an artefact of the software parameter space. In particular, significant shortcomings are highlighted due to the assumptions and parameters of the models used by the CAFE gene family analysis software. We must bear in mind that genome assemblies and annotations are hypotheses that themselves need to be questioned and subjected to robust controls to increase the confidence in any conclusions that can be drawn from them.In addition functional genomics analyses were undertaken to identify the role of significantly changed genes and gene families in primates, testing against a hypothesis that would see the majority of changes involving immune, sensory or reproductive genes. Gene Ontology (GO) annotations were retrieved for these data, which enabled highlighting the broad GO groupings and more specific functional classifications of these data. The results showed that the majority of gene expansions were in families that may have arisen due to adaptation, or were maintained due to their necessary involvement in developmental and metabolic processes. Comparisons were made to previously published studies to determine whether the Ensembl functional annotations were supported by the de-novo analyses undertaken in those studies. The majority were not, with only a small number of previously identified functional annotations being present in the most recent Ensembl releases.The impact of gene family evolution on intron evolution was explored in chapter five, by analysing gene family data and intron characteristics across the genomes of 61 vertebrate species. General descriptive statistics and visualisations were produced, along with tests for correlation between change in gene family size and the number, size and density of their associated introns. There was shown to be very little impact of change in gene family size on the underlying intron evolution. Other, non-family effects were therefore considered. These analyses showed that introns were restricted to euchromatic regions, with heterochromatic regions such as the centromeres and telomeres being largely devoid of any such features. A greater involvement of spatial mechanisms such as recombination, GC-bias across GC-rich isochores and biased gene conversion was thus proposed to play more of a role, though depending largely on population genetic and life history traits of the organisms involved. Additional population level sequencing and comparative analyses across a divergent group of species with available recombination maps and life history data would be a useful future direction in understanding the processes involved

    Characterization of the ubiquitin-like protein Hub1 and its role in pre-mRNA splicing in human cells

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    Combining automated processing and customized analysis for large-scale sequencing data

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    Extensive application of high-throughput methods in life sciences has brought substantial new challenges for data analysis. Often many different steps have to be applied to a large number of samples. Here, workflow management systems support scientists through the automated execution of corresponding large analysis workflows. The first part of this cumulative dissertation concentrates on the development of Watchdog, a novel workflow management system for the automated analysis of large-scale experimental data. Watchdog`s main features include straightforward processing of replicate data, support for distributed computer systems, customizable error detection and manual intervention into workflow execution. A graphical user interface enables workflow construction using a pre-defined toolset without programming experience and a community sharing platform allows scientists to share toolsets and workflows efficiently. Furthermore, we implemented methods for resuming execution of interrupted or partially modified workflows and for automated deployment of software using package managers and container virtualization. Using Watchdog, we implemented default analysis workflows for typical types of large-scale biological experiments, such as RNA-seq and ChIP-seq. Although they can be easily applied to new datasets of the same type, at some point such standard workflows reach their limit and customized methods are required to resolve specific questions. Hence, the second part of this dissertation focuses on combining standard analysis workflows with the development of application-specific novel bioinformatics approaches to address questions of interest to our biological collaboration partners. The first study concentrates on identifying the binding motif of the ZNF768 transcription factor, which consists of two anchor regions connected by a variable linker region. As standard motif finding methods detected only the anchors of the motifs separately, a custom method was developed for determining the spaced motif with the linker region. The second study focused on the effect of CDK12 inhibition on transcription. Results obtained from standard RNA-seq analysis indicated substantial transcript shortening upon CDK12 inhibition. We thus developed a new measure to quantify the degree of transcript shortening. In addition, a customized meta-gene analysis framework was developed to model RNA polymerase II progression using ChIP-seq data. This revealed that CDK12 inhibition causes an RNA polymerase II processivity defect resulting in the detected transcript shortening. In summary, the methods developed in this thesis represent both general contributions to large-scale sequencing data analysis and served to resolve specific questions regarding transcription factor binding and regulation of elongating RNA Polymerase II
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