519 research outputs found

    Genome sequence of an Australian kangaroo, Macropus eugenii, provides insight into the evolution of mammalian reproduction and development.

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    BACKGROUND: We present the genome sequence of the tammar wallaby, Macropus eugenii, which is a member of the kangaroo family and the first representative of the iconic hopping mammals that symbolize Australia to be sequenced. The tammar has many unusual biological characteristics, including the longest period of embryonic diapause of any mammal, extremely synchronized seasonal breeding and prolonged and sophisticated lactation within a well-defined pouch. Like other marsupials, it gives birth to highly altricial young, and has a small number of very large chromosomes, making it a valuable model for genomics, reproduction and development. RESULTS: The genome has been sequenced to 2 × coverage using Sanger sequencing, enhanced with additional next generation sequencing and the integration of extensive physical and linkage maps to build the genome assembly. We also sequenced the tammar transcriptome across many tissues and developmental time points. Our analyses of these data shed light on mammalian reproduction, development and genome evolution: there is innovation in reproductive and lactational genes, rapid evolution of germ cell genes, and incomplete, locus-specific X inactivation. We also observe novel retrotransposons and a highly rearranged major histocompatibility complex, with many class I genes located outside the complex. Novel microRNAs in the tammar HOX clusters uncover new potential mammalian HOX regulatory elements. CONCLUSIONS: Analyses of these resources enhance our understanding of marsupial gene evolution, identify marsupial-specific conserved non-coding elements and critical genes across a range of biological systems, including reproduction, development and immunity, and provide new insight into marsupial and mammalian biology and genome evolution

    Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

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    Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation

    Application of a Naïve Bayes Classifier to Assign Polyadenylation Sites from 3\u27 End Deep Sequencing Data: A Dissertation

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    Cleavage and polyadenylation of a precursor mRNA is important for transcription termination, mRNA stability, and regulation of gene expression. This process is directed by a multitude of protein factors and cis elements in the pre-mRNA sequence surrounding the cleavage and polyadenylation site. Importantly, the location of the cleavage and polyadenylation site helps define the 3’ untranslated region of a transcript, which is important for regulation by microRNAs and RNA binding proteins. Additionally, these sites have generally been poorly annotated. To identify 3’ ends, many techniques utilize an oligo-dT primer to construct deep sequencing libraries. However, this approach can lead to identification of artifactual polyadenylation sites due to internal priming in homopolymeric stretches of adenines. Previously, simple heuristic filters relying on the number of adenines in the genomic sequence downstream of a putative polyadenylation site have been used to remove these sites of internal priming. However, these simple filters may not remove all sites of internal priming and may also exclude true polyadenylation sites. Therefore, I developed a naïve Bayes classifier to identify putative sites from oligo-dT primed 3’ end deep sequencing as true or false/internally primed. Notably, this algorithm uses a combination of sequence elements to distinguish between true and false sites. Finally, the resulting algorithm is highly accurate in multiple model systems and facilitates identification of novel polyadenylation sites

    Detecting and comparing non-coding RNAs in the high-throughput era.

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    In recent years there has been a growing interest in the field of non-coding RNA. This surge is a direct consequence of the discovery of a huge number of new non-coding genes and of the finding that many of these transcripts are involved in key cellular functions. In this context, accurately detecting and comparing RNA sequences has become important. Aligning nucleotide sequences is a key requisite when searching for homologous genes. Accurate alignments reveal evolutionary relationships, conserved regions and more generally any biologically relevant pattern. Comparing RNA molecules is, however, a challenging task. The nucleotide alphabet is simpler and therefore less informative than that of amino-acids. Moreover for many non-coding RNAs, evolution is likely to be mostly constrained at the structural level and not at the sequence level. This results in very poor sequence conservation impeding comparison of these molecules. These difficulties define a context where new methods are urgently needed in order to exploit experimental results to their full potential. This review focuses on the comparative genomics of non-coding RNAs in the context of new sequencing technologies and especially dealing with two extremely important and timely research aspects: the development of new methods to align RNAs and the analysis of high-throughput data

    A systems-based approach for detecting molecular interactions across tissues.

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    Current high-throughput gene expression experiments have a straightforward design of examining the gene expression of one group or condition relative to that of another. The data is typically analyzed as if they represent strictly intracellular events, and often treats genes as coming from a homogeneous population. Although intracellular events are crucial to nearly all biological processes, cell-cell interactions are often just as important, especially when gene expression data is generated from heterogeneous cell populations, such as from whole tissues. Cell-cell molecular interactions are generally lost in the available analytical procedures and as a result, are not examined experimentally, at least not accurately or with efficiency. Most importantly, this imposes major limitations when studying gene expression changes in multiple samples that interact with one another. In order to addresses the limitations of current techniques, we have developed a novel systems-based approach that expands the traditional analysis of gene expression in two stages. This includes a novel sequence-based meta-analytic tool, AbsIDconvert, that allows for conversion of annotated features using an interval tree for storing and querying absolute genomic coordinates for comparison of multi-scale macro-molecule identifiers across platforms and/or organisms. In addition, a systems-based heuristic algorithm is developed to find intercellular interactions between two sets of genes, potentially from different tissues by utilizing location information of each gene along with the information available in the secondary databases in the form of interactions, pathways and signaling. AbsIDconvert is shown to provide a high accuracy in identifier conversion as compared to other available methodologies (typically at an average rate of 84%) while maintaining a higher efficiency (O(n*log(n)). Our intercellular interaction approach and underlying visualization shows promise in allowing researchers to uncover novel signaling pathways in an intercellular fashion that to this point has not been possible

    Work ow-based systematic design of high throughput genome annotation

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    The genus Eimeria belongs to the phylum Apicomplexa, which includes many obligate intra-cellular protozoan parasites of man and livestock. E. tenella is one of seven species that infect the domestic chicken and cause the intestinal disease coccidiosis which is economy important for poultry industry. E. tenella is highly pathogenic and is often used as a model species for the Eimeria biology studies. In this PhD thesis, a comprehensive annotation system named as \WAGA" (Workflow-based Automatically Genome Annotation) was built and applied to the E. tenella genome. InforSense KDE, and its BioSense plug-in (products of the InforSense Company), were the core softwares used to build the workflows. Workflows were made by integrating individual bioinformatics tools into a single platform. Each workflow was designed to provide a standalone service for a particular task. Three major workflows were developed based on the genomic resources currently available for E. tenella. These were of ESTs-based gene construction, HMM-based gene prediction and protein-based annotation. Finally, a combining workflow was built to sit above the individual ones to generate a set of automatic annotations using all of the available information. The overall system and its three major components were deployed as web servers that are fully tuneable and reusable for end users. WAGA does not require users to have programming skills or knowledge of the underlying algorithms or mechanisms of its low level components. E. tenella was the target genome here and all the results obtained were displayed by GBrowse. A sample of the results is selected for experimental validation. For evaluation purpose, WAGA was also applied to another Apicomplexa parasite, Plasmodium falciparum, the causative agent of human malaria, which has been extensively annotated. The results obtained were compared with gene predictions of PHAT, a gene finder designed for and used in the P. falciparum genome project

    Development of computational tools and resources for systems biology of bacterial pathogens

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    Bacterial pathogens are a major cause of diseases in human, agricultural plants and farm animals. Even after decades of research they remain a challenge to health care as they are known to rapidly evolve and develop resistance to the existing drugs. Systems biology is an emerging area of research where all of the components of the system, their interactions, and the dynamics can be studied in a comprehensive, quantitative, and integrative fashion to generate predictive models. When applied to bacterial pathogenesis, systems biology approaches will help identify potential novel molecular targets for drug discovery. A pre-requisite for conducting systems analysis is the identification of the building blocks of the system i.e. individual components of the system (structural annotation), identification of their functions (functional annotation) and identification of the interactions among the individual components (interaction prediction). In the context of bacterial pathogenesis, it is necessary to identify the host-pathogen interactions. This dissertation work describes computational resources that enable comprehensive systems level study of host pathogen system to enhance our understanding of bacterial pathogenesis. It specifically focuses on improving the structural and functional annotation of pathogen genomes as well as identifying host-pathogen interactions at a genome scale. The novel contributions of this dissertation towards systems biology of bacterial pathogens include three computational tools/resources. “TAAPP” (Tiling array analysis pipeline for prokaryotes) is a web based tool for the analysis of whole genome tiling array data for bacterial pathogens. TAAPP helps improve the structural annotation of bacterial genomes. “ISO-IEA” (Inferred from sequence orthology - Inferred from electronic annotation) is a tool that can be used for the functional annotation of any sequenced genome. “HPIDB” (Host pathogen interaction database) is developed with data a mining capability that includes host-pathogen interaction prediction. The new knowledge gained due to the implementation of these tools is the description of the non coding RNA as well as a computationally predicted host-pathogen interaction network for the human respiratory pathogen Streptococcus pneumoniae. In summary, the computation tools and resources developed in this dissertation study will enable building systems biology models of bacterial pathogens

    Complex architecture and regulated expression of the Sox2ot locus during vertebrate development

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    The Sox2 gene is a key regulator of pluripotency embedded within an intron of a long noncoding RNA (ncRNA), termed Sox2 overlapping transcript (Sox2ot), which is transcribed in the same orientation. However, this ncRNA remains uncharacterized. Here we show that Sox2ot has multiple transcription start sites associated with genomic features that indicate regulated expression, including highly conserved elements (HCEs) and chromatin marks characteristic of gene promoters. To identify biological processes in which Sox2ot may be involved, we analyzed its expression in several developmental systems, compared to expression of Sox2. We show that Sox2ot is a stable transcript expressed in mouse embryonic stem cells, which, like Sox2, is down-regulated upon induction of embryoid body (EB) differentiation. However, in contrast to Sox2, Sox2ot is up-regulated during EB mesoderm-lineage differentiation. In adult mouse, Sox2ot isoforms were detected in tissues where Sox2 is expressed, as well as in different tissues, supporting independent regulation of expression of the ncRNA. Sox2dot, an isoform of Sox2ot transcribed from a distal HCE located >500 kb upstream of Sox2, was detected exclusively in the mouse brain, with enrichment in regions of adult neurogenesis. In addition, Sox2ot isoforms are transcribed from HCEs upstream of Sox2 in other vertebrates, including in several regions of the human brain. We also show that Sox2ot is dynamically regulated during chicken and zebrafish embryogenesis, consistently associated with central nervous system structures. These observations provide insight into the structure and regulation of the Sox2ot gene, and suggest conserved roles for Sox2ot orthologs during vertebrate development
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