18 research outputs found

    Rat Strain Ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD

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    BACKGROUND: The Rat Genome Database (RGD) ( http://rgd.mcw.edu/) is the premier site for comprehensive data on the different strains of the laboratory rat (Rattus norvegicus). The strain data are collected from various publications, direct submissions from individual researchers, and rat providers worldwide. Rat strain, substrain designation and nomenclature follow the Guidelines for Nomenclature of Mouse and Rat Strains, instituted by the International Committee on Standardized Genetic Nomenclature for Mice. While symbols and names aid in identifying strains correctly, the flat nature of this information prohibits easy search and retrieval, as well as other data mining functions. In order to improve these functionalities, particularly in ontology-based tools, the Rat Strain Ontology (RS) was developed. RESULTS: The Rat Strain Ontology (RS) reflects the breeding history, parental background, and genetic manipulation of rat strains. This controlled vocabulary organizes strains by type: inbred, outbred, chromosome altered, congenic, mutant and so on. In addition, under the chromosome altered category, strains are organized by chromosome, and further by type of manipulations, such as mutant or congenic. This allows users to easily retrieve strains of interest with modifications in specific genomic regions. The ontology was developed using the Open Biological and Biomedical Ontology (OBO) file format, and is organized on the Directed Acyclic Graph (DAG) structure. Rat Strain Ontology IDs are included as part of the strain report (RS: ######). CONCLUSIONS: As rat researchers are often unaware of the number of substrains or altered strains within a breeding line, this vocabulary now provides an easy way to retrieve all substrains and accompanying information. Its usefulness is particularly evident in tools such as the PhenoMiner at RGD, where users can now easily retrieve phenotype measurement data for related strains, strains with similar backgrounds or those with similar introgressed regions. This controlled vocabulary also allows better retrieval and filtering for QTLs and in genomic tools such as the GViewer. The Rat Strain Ontology has been incorporated into the RGD Ontology Browser ( http://rgd.mcw.edu/rgdweb/ontology/view.html?acc_id=RS:0000457#s) and is available through the National Center for Biomedical Ontology ( http://bioportal.bioontology.org/ontologies/1150) or the RGD ftp site ( ftp://rgd.mcw.edu/pub/ontology/rat_strain/)

    The MmeI family: type II restriction–modification enzymes that employ single-strand modification for host protection

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    The type II restriction endonucleases form one of the largest families of biochemically-characterized proteins. These endonucleases typically share little sequence similarity, except among isoschizomers that recognize the same sequence. MmeI is an unusual type II restriction endonuclease that combines endonuclease and methyltransferase activities in a single polypeptide. MmeI cuts DNA 20 bases from its recognition sequence and modifies just one DNA strand for host protection. Using MmeI as query we have identified numerous putative genes highly similar to MmeI in database sequences. We have cloned and characterized 20 of these MmeI homologs. Each cuts DNA at the same distance as MmeI and each modifies a conserved adenine on only one DNA strand for host protection. However each enzyme recognizes a unique DNA sequence, suggesting these enzymes are undergoing rapid evolution of DNA specificity. The MmeI family thus provides a rich source of novel endonucleases while affording an opportunity to observe the evolution of DNA specificity. Because the MmeI family enzymes employ modification of only one DNA strand for host protection, unlike previously described type II systems, we propose that such single-strand modification systems be classified as a new subgroup, the type IIL enzymes, for Lone strand DNA modification

    Lysozyme transgenic goats’ milk positively impacts intestinal cytokine expression and morphology

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    In addition to its well-recognized antimicrobial properties, lysozyme can also modulate the inflammatory response. This ability may be particularly important in the gastrointestinal tract where inappropriate inflammatory reactions can damage the intestinal epithelium, leading to significant health problems. The consumption of milk from transgenic goats producing human lysozyme (hLZ) in their milk therefore has the potential to positively impact intestinal health. In order to investigate the effect of hLZ-containing milk on the inflammatory response, young pigs were fed pasteurized milk from hLZ or non-transgenic control goats and quantitative real-time PCR was performed to assess local expression of TNF-α, IL-8, and TGF-β1 in the small intestine. Histological changes were also investigated, specifically looking at villi width, length, crypt depth, and lamina propria thickness along with cell counts for intraepithelial lymphocytes and goblet cells. Significantly higher expression of anti-inflammatory cytokine TGF-β1 was seen in the ileum of pigs fed pasteurized milk containing hLZ (P = 0.0478), along with an increase in intraepithelial lymphocytes (P = 0.0255), and decrease in lamina propria thickness in the duodenum (P = 0.0001). Based on these results we conclude that consuming pasteurized milk containing hLZ does not induce an inflammatory response and improves the health of the small intestine in pigs

    Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies

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    Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features
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