PubMed Health⌕ Search

Biomedical subjects

Laura Clarke

Publications and source records attributed to Laura Clarke.

6 recordsLinked to original sources

High-grade glioma formation results from postnatal pten loss or mutant epidermal growth factor receptor expression in a transgenic mouse glioma model.

High-grade gliomas are devastating brain tumors associated with a mean survival of <50 weeks. Two of the most common genetic changes observed in these tumors are overexpression/mutation of the epidermal growth factor receptor (EGFR) vIII and loss of PTEN/MMAC1 expression. To determine whether somatically acquired EGFRvIII expression or Pten loss accelerates high-grade glioma development, we used a previously characterized RasB8 glioma-prone mouse strain, in which these specific genetic changes were focally introduced at 4 weeks of age. We show that both postnatal EGFRvIII expression and Pten inactivation in RasB8 mice potentiate high-grade glioma development. Moreover, we observe a concordant loss of Pten and EGFR overexpression in nearly all high-grade gliomas induced by either EGFRvIII introduction or Pten inactivation. This novel preclinical model of high-grade glioma will be useful in evaluating brain tumor therapies targeted to the pathways specifically dysregulated by EGFR expression or Pten loss.

Animals↗

An overview of Ensembl.

Ensembl (http://www.ensembl.org/) is a bioinformatics project to organize biological information around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of individual genomes, and of the synteny and orthology relationships between them. It is also a framework for integration of any biological data that can be mapped onto features derived from the genomic sequence. Ensembl is available as an interactive Web site, a set of flat files, and as a complete, portable open source software system for handling genomes. All data are provided without restriction, and code is freely available. Ensembl's aims are to continue to "widen" this biological integration to include other model organisms relevant to understanding human biology as they become available; to "deepen" this integration to provide an ever more seamless linkage between equivalent components in different species; and to provide further classification of functional elements in the genome that have been previously elusive.

Computational Biology↗

The Ensembl automatic gene annotation system.

As more genomes are sequenced, there is an increasing need for automated first-pass annotation which allows timely access to important genomic information. The Ensembl gene-building system enables fast automated annotation of eukaryotic genomes. It annotates genes based on evidence derived from known protein, cDNA, and EST sequences. The gene-building system rests on top of the core Ensembl (MySQL) database schema and Perl Application Programming Interface (API), and the data generated are accessible through the Ensembl genome browser (http://www.ensembl.org). To date, the Ensembl predicted gene sets are available for the A. gambiae, C. briggsae, zebrafish, mouse, rat, and human genomes and have been heavily relied upon in the publication of the human, mouse, rat, and A. gambiae genome sequence analysis. Here we describe in detail the gene-building system and the algorithms involved. All code and data are freely available from http://www.ensembl.org.

Animals↗

The Ensembl analysis pipeline.

The Ensembl pipeline is an extension to the Ensembl system which allows automated annotation of genomic sequence. The software comprises two parts. First, there is a set of Perl modules ("Runnables" and "RunnableDBs") which are 'wrappers' for a variety of commonly used analysis tools. These retrieve sequence data from a relational database, run the analysis, and write the results back to the database. They inherit from a common interface, which simplifies the writing of new wrapper modules. On top of this sits a job submission system (the "RuleManager") which allows efficient and reliable submission of large numbers of jobs to a compute farm. Here we describe the fundamental software components of the pipeline, and we also highlight some features of the Sanger installation which were necessary to enable the pipeline to scale to whole-genome analysis.

Base Sequence↗

The genome sequence of Caenorhabditis briggsae: a platform for comparative genomics.

The soil nematodes Caenorhabditis briggsae and Caenorhabditis elegans diverged from a common ancestor roughly 100 million years ago and yet are almost indistinguishable by eye. They have the same chromosome number and genome sizes, and they occupy the same ecological niche. To explore the basis for this striking conservation of structure and function, we have sequenced the C. briggsae genome to a high-quality draft stage and compared it to the finished C. elegans sequence. We predict approximately 19,500 protein-coding genes in the C. briggsae genome, roughly the same as in C. elegans. Of these, 12,200 have clear C. elegans orthologs, a further 6,500 have one or more clearly detectable C. elegans homologs, and approximately 800 C. briggsae genes have no detectable matches in C. elegans. Almost all of the noncoding RNAs (ncRNAs) known are shared between the two species. The two genomes exhibit extensive colinearity, and the rate of divergence appears to be higher in the chromosomal arms than in the centers. Operons, a distinctive feature of C. elegans, are highly conserved in C. briggsae, with the arrangement of genes being preserved in 96% of cases. The difference in size between the C. briggsae (estimated at approximately 104 Mbp) and C. elegans (100.3 Mbp) genomes is almost entirely due to repetitive sequence, which accounts for 22.4% of the C. briggsae genome in contrast to 16.5% of the C. elegans genome. Few, if any, repeat families are shared, suggesting that most were acquired after the two species diverged or are undergoing rapid evolution. Coclustering the C. elegans and C. briggsae proteins reveals 2,169 protein families of two or more members. Most of these are shared between the two species, but some appear to be expanding or contracting, and there seem to be as many as several hundred novel C. briggsae gene families. The C. briggsae draft sequence will greatly improve the annotation of the C. elegans genome. Based on similarity to C. briggsae, we found strong evidence for 1,300 new C. elegans genes. In addition, comparisons of the two genomes will help to understand the evolutionary forces that mold nematode genomes.

Animals↗

Biopipe: a flexible framework for protocol-based bioinformatics analysis.

We identify several challenges facing bioinformatics analysis today. Firstly, to fulfill the promise of comparative studies, bioinformatics analysis will need to accommodate different sources of data residing in a federation of databases that, in turn, come in different formats and modes of accessibility. Secondly, the tsunami of data to be handled will require robust systems that enable bioinformatics analysis to be carried out in a parallel fashion. Thirdly, the ever-evolving state of bioinformatics presents new algorithms and paradigms in conducting analysis. This means that any bioinformatics framework must be flexible and generic enough to accommodate such changes. In addition, we identify the need for introducing an explicit protocol-based approach to bioinformatics analysis that will lend rigorousness to the analysis. This makes it easier for experimentation and replication of results by external parties. Biopipe is designed in an effort to meet these goals. It aims to allow researchers to focus on protocol design. At the same time, it is designed to work over a compute farm and thus provides high-throughput performance. A common exchange format that encapsulates the entire protocol in terms of the analysis modules, parameters, and data versions has been developed to provide a powerful way in which to distribute and reproduce results. This will enable researchers to discuss and interpret the data better as the once implicit assumptions are now explicitly defined within the Biopipe framework.

Amino Acid Sequence↗