MochiView: versatile software for genome browsing and DNA motif analysis

Background  

As high-throughput technologies rapidly generate genome-scale data, it becomes increasingly important to visually integrate these data so that specific hypotheses can be formulated and tested.     

Evolution of genome space occupation in ferns: linking genome diversity and species richness

Background and AimsThe dynamics of genome evolution caused by whole genome duplications and other processes are hypothesized to shape the diversification of plants and thus contribute to the astonishing variation in species richness among the main lineages of land plants. Ferns, the second most species-rich lineage of land plants, are highly suitable to test this hypothesis because of several unique features that distinguish fern genomes from those of seed plants. In this study, we tested the hypothesis that genome diversity and disparity shape fern species diversity by recording several parameters related to genome size and chromosome number.MethodsWe conducted de novo measurement of DNA C-values across the fern phylogeny to reconstruct the phylogenetic history of the genome space occupation in ferns by integrating genomic parameters such as genome size, chromosome number and average DNA amount per chromosome into a time-scaled phylogenetic framework. Using phylogenetic generalized least square methods, we determined correlations between chromosome number and genome size, species diversity and evolutionary rates of their transformation.Key ResultsThe measurements of DNA C-values for 233 species more than doubled the taxon coverage from ~2.2 % in previous studies to 5.3 % of extant diversity. The dataset not only documented substantial differences in the accumulation of genomic diversity and disparity among the major lineages of ferns but also supported the predicted correlation between species diversity and the dynamics of genome evolution.ConclusionsOur results demonstrated substantial genome disparity among different groups of ferns and supported the prediction that alterations of reproductive modes alter trends of genome evolution. Finally, we recovered evidence for a close link between the dynamics of genome evolution and species diversity in ferns for the first time.     

Bioinformatics visualization and integration with open standards: the Bluejay genomic browser

We have created a new Java-based integrated computational environment for the exploration of genomic data, called Bluejay. The system is capable of using almost any XML file related to genomic data. Non-XML data sources can be accessed via a proxy server. Bluejay has several features, which are new to Bioinformatics, including an unlimited semantic zoom capability, coupled with Scalable Vector Graphics (SVG) outputs; an implementation of the XLink standard, which features access to MAGPIE Genecards as well as any BioMOBY service accessible over the Internet; and the integration of gene chip analysis tools with the functional assignments. The system can be used as a signed web applet, Web Start, and a local stand-alone application, with or without connection to the Internet. It is available free of charge and as open source via http://bluejay.ucalgary.ca.     

CAGO: a software tool for dynamic visual comparison and correlation measurement of genome organization

CAGO (Comparative Analysis of Genome Organization) is developed to address two critical shortcomings of conventional genome atlas plotters: lack of dynamic exploratory functions and absence of signal analysis for genomic properties. With dynamic exploratory functions, users can directly manipulate chromosome tracks of a genome atlas and intuitively identify distinct genomic signals by visual comparison. Signal analysis of genomic properties can further detect inconspicuous patterns from noisy genomic properties and calculate correlations between genomic properties across various genomes. To implement dynamic exploratory functions, CAGO presents each genome atlas in Scalable Vector Graphics (SVG) format and allows users to interact with it using a SVG viewer through JavaScript. Signal analysis functions are implemented using R statistical software and a discrete wavelet transformation package waveslim. CAGO is not only a plotter for generating complex genome atlases, but also a platform for exploring genome atlases with dynamic exploratory functions for visual comparison and with signal analysis for comparing genomic properties across multiple organisms. The web-based application of CAGO, its source code, user guides, video demos, and live examples are publicly available and can be accessed at http://cbs.ym.edu.tw/cago.     

Distribution of hospital provision: policy themes and resource variations.

There has been much discussion in the past about the inequitable distribution of N.H.S. resources between different regions. This paper examines the distribution of hospital resources in terms of current revenue and beds in different specialties in eight regions (49 area health authorities). Variations between A.H.A.s are far more important than those between regions, and indeed they are so large (even in the acute specialties) that it is doubtful whether some A.H.A.s can be considered to be offering a comprehensive service. In the light of these findings the paper explores policy problems involved in trying to secure a more equitable distribution of N.H.S. resources at a time of financial stringency.     

Easyfig: a genome comparison visualizer

Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface. BLAST comparisons between multiple genomic regions, ranging from single genes to whole prokaryote chromosomes, can be generated, visualized and interactively coloured, enabling a rapid transition between analysis and the preparation of publication quality figures. AVAILABILITY: Easyfig is freely available (under a GPL license) for download (for Mac OS X, Unix and Microsoft Windows) from the SourceForge web site: http://easyfig.sourceforge.net/.     

Mass spectrometry of RNA: linking the genome to the proteome.

Ribonucleic acids (RNAs) are continuing to attract increased attention as they are found to play pivotal roles in biological systems. Just as genomics and proteomics have been enabled by the development of effective analytical techniques and instrumentation, the large-scale analysis of non-protein coding (nc)RNAs will benefit as new analytical methodologies, such as mass spectrometry (MS), are developed for their analysis. Mass spectrometry offers a number of advantages for RNA analysis arising from its ability to provide mass and sequence information starting with limited amounts of sample. This review will highlight recent developments in the field of MS that enable the characterization of RNA modification status, RNA tertiary structures, and ncRNA expression levels. These developments will also be placed in perspective of how MS of RNAs can help elucidate the link between the genome and proteome.     

Association of reovirus mRNA with viral proteins: A possible mechanism for linking the genome segments

Reovirus mRNA molecules released from polysomes of infected cells by EDTA are noncovalently linked. This association which is stable in 1 m NaCl but disrupted by protease treatment, is mediated by viral proteins. The ribonucleoprotein complexes may be precursors of virions and involved in the regulation of viral protein synthesis.     

The mouse genome database: a resource for today and tomorrow

The Mouse Genome Database supports the use of mice in genome research, offering researchers information on gene characterization, genetic maps, comparative genomic data, and phenotypes.     

Identification of polymorphic tandem repeats by direct comparison of genome sequence from different bacterial strains : a web-based resource

Background

Polymorphic tandem repeat typing is a new generic technology which has been proved to be very efficient for bacterial pathogens such as B. anthracis, M. tuberculosis, P. aeruginosa, L. pneumophila, Y. pestis. The previously developed tandem repeats database takes advantage of the release of genome sequence data for a growing number of bacteria to facilitate the identification of tandem repeats. The development of an assay then requires the evaluation of tandem repeat polymorphism on well-selected sets of isolates. In the case of major human pathogens, such as S. aureus, more than one strain is being sequenced, so that tandem repeats most likely to be polymorphic can now be selected in silico based on genome sequence comparison.

Results

In addition to the previously described general Tandem Repeats Database, we have developed a tool to automatically identify tandem repeats of a different length in the genome sequence of two (or more) closely related bacterial strains. Genome comparisons are pre-computed. The results of the comparisons are parsed in a database, which can be conveniently queried over the internet according to criteria of practical value, including repeat unit length, predicted size difference, etc. Comparisons are available for 16 bacterial species, and the orthopox viruses, including the variola virus and three of its close neighbors.

Conclusions

We are presenting an internet-based resource to help develop and perform tandem repeats based bacterial strain typing. The tools accessible at http://minisatellites.u-psud.fr now comprise four parts. The Tandem Repeats Database enables the identification of tandem repeats across entire genomes. The Strain Comparison Page identifies tandem repeats differing between different genome sequences from the same species. The "Blast in the Tandem Repeats Database" facilitates the search for a known tandem repeat and the prediction of amplification product sizes. The "Bacterial Genotyping Page" is a service for strain identification at the subspecies level.

     

Longevity regulation in Saccharomyces cerevisiae: linking metabolism, genome stability, and heterochromatin.

When it was first proposed that the budding yeast Saccharomyces cerevisiae might serve as a model for human aging in 1959, the suggestion was met with considerable skepticism. Although yeast had proved a valuable model for understanding basic cellular processes in humans, it was difficult to accept that such a simple unicellular organism could provide information about human aging, one of the most complex of biological phenomena. While it is true that causes of aging are likely to be multifarious, there is a growing realization that all eukaryotes possess surprisingly conserved longevity pathways that govern the pace of aging. This realization has come, in part, from studies of S. cerevisiae, which has emerged as a highly informative and respected model for the study of life span regulation. Genomic instability has been identified as a major cause of aging, and over a dozen longevity genes have now been identified that suppress it. Here we present the key discoveries in the yeast-aging field, regarding both the replicative and chronological measures of life span in this organism. We discuss the implications of these findings not only for mammalian longevity but also for other key aspects of cell biology, including cell survival, the relationship between chromatin structure and genome stability, and the effect of internal and external environments on cellular defense pathways. We focus on the regulation of replicative life span, since recent findings have shed considerable light on the mechanisms controlling this process. We also present the specific methods used to study aging and longevity regulation in S. cerevisiae.     

The minimal genome: a metabolic and environmental comparison

The field of Synthetic Biology seeks to apply engineering principles to biology in order to produce novel biological systems. One approach to accomplish this goal is the genome-driven cell engineering approach, which searches for functioning minimal genomes in naturally occurring microorganisms, which can then be used as a template for future systems. Currently a prototypical minimal genome has not been discovered. This review analyzes the organisms Mycoplasma pneumoniae, Pelagibacter ubique, Vesicomyosocius okutanii and Prochlorococcus marinus as models of heterotrophic symbiont, heterotrophic free-living, autotrophic symbiont and autotrophic free-living organisms respectively and compares them to the current minimal cell model in order to determine which most closely resembles a true minimal genome. M. pneumoniae possesses a genome of 816 394 base pairs (bp) with 688 open reading frames (ORF) and a severely limited metabolism. Pelagibacter ubique possesses a 1 308 000 bp genome with 1354 ORF and has a fully functional metabolism but requires a reduced form of sulphur. Vesicomyosocius okutanii possesses a 1 020 000 bp genome with 975 ORF and is deficient in the production of threonine, isoleucine and ubiquinone. Prochlorococcus marinus possesses a 1 751 080 bp genome with 1884 ORF and has a complete metabolism with no deficiencies. The current minimal cell model requires a genome to be of limited size, culturalble and having minimal media requirements as such it is the conclusion of this review that P. marinus best fits this model. Further, future research should concentrate on genome reduction experiments using P. marinus and the search for additional minimal genomes should concentrate on autotrophic free-living organisms.     

The TIGR rice genome annotation resource: annotating the rice genome and creating resources for plant biologists

Rice is not only a major food staple for the world's population but it also is a model species for a major group of flowering plants, the monocotyledonous plants. Draft genomic sequence of two subspecies of rice, Oryza sativa spp. japonica and indica ssp. are publicly available. To provide the community with a resource to data-mine the rice genome, we have constructed an annotation resource for rice (http://www.tigr.org/tdb/e2k1/osa1/). In this resource, we have annotated the rice genome for gene content, identified motifs/domains within the predicted genes, constructed a rice repeat database, identified related sequences in other plant species, and identified syntenic sequences between rice and maize. All of the data is available through web-based interfaces, FTP downloads, and a Distributed Annotation System.