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Peter J Tonellato

Publications and source records attributed to Peter J Tonellato.

15 recordsLinked to original sources
PubMed2006

BN phenome: detailed characterization of the cardiovascular, renal, and pulmonary systems of the sequenced rat.

The postgenome era has provided resources to link disease phenotypes to the genomic sequence, i.e., creating a disease "phenome." Our detailed characterization of the sequenced BN rat strain (BN/NHsdMcwi) provides the first concerted effort in creating a direct link between a sequenced genome and its resulting biology. For the BN sequence to be of broad value to investigators, these measures need to be put into the context of the spectrum of the laboratory rats, so that their physiology can be benchmarked against the sequenced BN. As a major step in generating a comprehensive cardiovascular and pulmonary disease phenome, we measured 281 traits related to diseases of the heart, lung, and blood (http://pga.mcw.edu) in the sequenced BN. We compared these data with those of the same traits measured across multiple genetic backgrounds, both genders, and differing environments. We show that no single strain, inbred or outbred, can be considered a physiological control strain; what is normal depends on what trait is being measured and the strains' genome backgrounds. We find vast differences between the genders, also dependent on genome background. By combining the values across all strains studied, we generated a "population" mean and normal range of values for each of these traits, which are more genetically representative than the measured values in any single inbred or outbred strain. These data provide a baseline for physiological comparison of traits related to cardiovascular, lung, blood, and renal function in the sequenced BN rats relative to the major strains of rats studied in biomedical research.

Animals↗
PubMed2005

Tools and strategies for physiological genomics: the Rat Genome Database.

The broad goal of physiological genomics research is to link genes to their functions using appropriate experimental and computational techniques. Modern genomics experiments enable the generation of vast quantities of data, and interpretation of this data requires the integration of information derived from many diverse sources. Computational biology and bioinformatics offer the ability to manage and channel this information torrent. The Rat Genome Database (RGD; http://rgd.mcw.edu) has developed computational tools and strategies specifically supporting the goal of linking genes to their functional roles in rat and, using comparative genomics, to human and mouse. We present an overview of the database with a focus on these unique computational tools and describe strategies for the use of these resources in the area of physiological genomics.

Animals↗
PubMed2004

B.E.A.R. GeneInfo: a tool for identifying gene-related biomedical publications through user modifiable queries.

BACKGROUND: Once specific genes are identified through high throughput genomics technologies there is a need to sort the final gene list to a manageable size for validation studies. The triaging and sorting of genes often relies on the use of supplemental information related to gene structure, metabolic pathways, and chromosomal location. Yet in disease states where the genes may not have identifiable structural elements, poorly defined metabolic pathways, or limited chromosomal data, flexible systems for obtaining additional data are necessary. In these situations having a tool for searching the biomedical literature using the list of identified genes while simultaneously defining additional search terms would be useful. RESULTS: We have built a tool, BEAR GeneInfo, that allows flexible searches based on the investigators knowledge of the biological process, thus allowing for data mining that is specific to the scientist's strengths and interests. This tool allows a user to upload a series of GenBank accession numbers, Unigene Ids, Locuslink Ids, or gene names. BEAR GeneInfo takes these IDs and identifies the associated gene names, and uses the lists of gene names to query PubMed. The investigator can add additional modifying search terms to the query. The subsequent output provides a list of publications, along with the associated reference hyperlinks, for reviewing the identified articles for relevance and interest. An example of the use of this tool in the study of human prostate cancer cells treated with Selenium is presented. CONCLUSIONS: This tool can be used to further define a list of genes that have been identified through genomic or genetic studies. Through the use of targeted searches with additional search terms the investigator can limit the list to genes that match their specific research interests or needs. The tool is freely available on the web at http://prostategenomics.org1, and the authors will provide scripts and database components if requested mdatta@mcw.edu

Databases, Genetic↗
PubMed2004

ChromSorter PC: a database of chromosomal regions associated with human prostate cancer.

BACKGROUND: Our increasing use of genetic and genomic strategies to understand human prostate cancer means that we need access to simplified and integrated information present in the associated biomedical literature. In particular, microarray gene expression studies and associated genetic mapping studies in prostate cancer would benefit from a generalized understanding of the prior work associated with this disease. This would allow us to focus subsequent laboratory studies to genomic regions already related to prostate cancer by other scientific methods. We have developed a database of prostate cancer related chromosomal information from the existing biomedical literature. The input material was based on a broad literature search with subsequent hand annotation of information relevant to prostate cancer. DESCRIPTION: The database was then analyzed for identifiable trends in the whole scale literature. We have used this database, named ChromSorter PC, to present graphical summaries of chromosomal regions associated with prostate cancer broken down by age, ethnicity and experimental method. In addition we have placed the database information on the human genome using the Generic Genome Browser tool that allows the visualization of the data with respect to user generated datasets. CONCLUSIONS: We have used this database as an additional dataset for the filtering of genes identified through genetics and genomics studies as warranting follow-up validation studies. We would like to make this dataset publicly available for use by other groups. Using the Genome Browser allows for the graphical analysis of the associated data http://www.prostategenomics.org/datamining/chrom-sorter_pc.html. Additional material from the database can be obtained by contacting the authors (mdatta@mcw.edu).

Age Factors↗
PubMed2004

High-density rat radiation hybrid maps containing over 24,000 SSLPs, genes, and ESTs provide a direct link to the rat genome sequence.

The laboratory rat is a major model organism for systems biology. To complement the cornucopia of physiological and pharmacological data generated in the rat, a large genomic toolset has been developed, culminating in the release of the rat draft genome sequence. The rat draft sequence used a variety of assembly packages, as well as data from the Radiation Hybrid (RH) map of the rat as part of their validation. As part of the Rat Genome Project, we have been building a high-density RH map to facilitate data integration from multiple maps and now to help validate the genome assembly. By incorporating vectors from our lab and several other labs, we have doubled the number of simple sequence length polymorphisms (SSLPs), genes, expressed sequence tags (ESTs), and sequence-tagged sites (STSs) compared to any other genome-wide rat map, a total of 24,437 elements. During the process, we also identified a novel approach for integrating the RH placement results from multiple maps. This new integrated RH map contains approximately 10 RH-mapped elements per Mb on the genome assembly, enabling the RH maps to serve as a scaffold for a variety of data visualization tools.

Animals↗
PubMed2004

Integrative genomics: in silico coupling of rat physiology and complex traits with mouse and human data.

Integration of the large variety of genome maps from several organisms provides the mechanism by which physiological knowledge obtained in model systems such as the rat can be projected onto the human genome to further the research on human disease. The release of the rat genome sequence provides new information for studies using the rat model and is a key reference against which existing and new rat physiological results can be aligned. Previously, we described comparative maps of the rat, mouse, and human based on EST sequence comparisons combined with radiation hybrid maps. Here, we use new data and introduce the Integrated Genomics Environment, an extensive database of curated and integrated maps, markers, and physiological results. These results are integrated by using VCMapview, a java-based map integration and visualization tool. This unique environment allows researchers to relate results from cytogenetic, genetic, and radiation hybrid studies to the genome sequence and compare regions of interest between human, mouse, and rat. Integrating rat physiology with mouse genetics and clinical results from human by using the respective genomes provides a novel route to capitalize on comparative genomics and the strengths of model organism biology.

Animals↗
PubMed2003

Genomic map of cardiovascular phenotypes of hypertension in female Dahl S rats.

Genetic linkage analyses in human populations have traditionally combined male and female progeny for determination of quantitative trait loci (QTL). In contrast, most rodent studies have focused primarily on males. This study represents an extensive female-specific linkage analysis in which 236 neuroendocrine, renal, and cardiovascular traits related to arterial pressure (BP) were determined in 99 female F2 rats derived from a cross of Dahl salt-sensitive SS/JrHsdMcwi (SS) and Brown Norway normotensive BN/SsNHsdMcwi (BN) rats. We identified 126 QTL for 96 traits on 19 of the 20 autosomal chromosomes of the female progeny. Four chromosomes (3, 6, 7, and 11) were identified as especially important in regulation of arterial pressure and renal function, since aggregates of 8-11 QTL mapped together on these chromosomes. BP QTL in this female population differed considerably from those previously found in male, other female, or mixed sex population linkage analysis studies using SS rats. Kidney weight divided by body weight was identified as an intermediate phenotype that mapped to the same region of the genome as resting diastolic blood pressure and was correlated with that same BP phenotype. Seven other phenotypes were considered as "potential intermediate phenotypes, " which mapped to the same region of the genome as a BP QTL but were not correlated with BP. These included renal vascular responses to ANG II and ACh and indices of baroreceptor responsiveness. Secondary traits were also identified that were likely to be consequences of hypertension (correlated with BP but not mapped to a BP QTL). Seven such traits were found, notably heart rate, plasma cholesterol, and renal glomerular injury. The development of a female rat systems biology map of cardiovascular function represents the first attempt to prioritize those regions of the genome important for development of hypertension and end organ damage in female rats.

Animals↗
PubMed2003

Evolutionary dynamics of oncogenes and tumor suppressor genes: higher intensities of purifying selection than other genes.

Oncogenes and tumor suppressor genes (hereafter referred to as "cancer genes") result in cancer when they experience substitutions that prevent or distort their normal function. We examined evolutionary pressures acting on cancer genes and other classes of disease-related genes and compared our results to analyses of genes without known association to disease. We compared synonymous and nonsynonymous substitution rates in 3,035 human genes-approximately 10% of the genome-measuring the intensity of purifying selection on 311 human disease genes, including 122 cancer-related genes. Although the genes examined are similar to nondisease genes in product, expression, function, and pathway affiliation, we found intriguing differences in the selective pressures experienced by cancer genes relative to other (noncancer) disease-related and non-disease-related genes. We found a statistically significant increase in the intensity of purifying selection exerted on cancer genes (the average ratio of nonsynonymous to synonymous substitutions, omega, was 0.079) relative to all other disease-related genes groups (omega = 0.101) and non-disease-related genes (omega = 0.100). This difference indicates a striking increase in selection against nonsynonymous substitutions in oncogenes and tumor suppressor genes. This finding provides insight into the etiology of cancer and the differences between genes involved in cancer and those implicated in other human diseases. Specifically, we found a significant overlap between human oncogenes and tumor suppressor genes and "essential genes," human homologs of mouse lethal genes identified by knockout experiments. This insight may improve our ability to identify cancer-related genes and enhances our understanding of the nature of these genes.

Evolution, Molecular↗
PubMed2003

Multiple approaches to data-mining of proteomic data based on statistical and pattern classification methods.

The data-mining challenge presented is composed of two fundamental problems. Problem one is the separation of forty-one subjects into two classifications based on the data produced by the mass spectrometry of protein samples from each subject. Problem two is to find the specific differences between protein expression data of two sets of subjects. In each problem, one group of subjects has a disease, while the other group is nondiseased. Each problem was approached with the intent to introduce a new and potentially useful tool to analyze protein expression from mass spectrometry data. A variety of methodologies, both conventional and nonconventional were used in the analysis of these problems. The results presented show both overlap and discrepancies. What is important is the breadth of the techniques and the future direction this analysis will create.

Artificial Intelligence↗
PubMed2003

A novel approach for high-quality microarray processing using third-dye array visualization technology.

Historically, microarray image processing has been technically challenging in obtaining quality gene expression data. After hybridization of Cy3- and Cy5-labeled samples, images are collected and processed to obtain gene expression ratio measurements for each of the elements on the array. The hybridization process often brings in contaminating noise, which can make correct identification of the signal difficult. In addition, spot intensity levels are highly variable due to the expression differences of different genes, and weak spots are often difficult to detect. These conditions are further complicated by inherent irregularities in spot position, shape, and size commonly found on high-density microarrays, making image processing an often labor-intensive task that is difficult to reliably automate. We previously reported a novel third-dye array visualization (TDAV) technology that allows prehybridization visualization and quality control of printed arrays. Here, we present a new microarray image processing approach utilizing TDAV. By incorporating the third-dye image, we show that overall quality of the microarray data is significantly improved, and automation of processing is feasible and reliable. Furthermore, we demonstrate use of the third-dye image to better quality control microarray image analysis. Both the principle and implementation of the approach are presented in detail, with experimental results.

Algorithms↗
PubMed2002

Rat Genome Database (RGD): mapping disease onto the genome.

The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is 'to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community'. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.

Animals↗
PubMed2002

Identification of hypertension-related QTLs in African American sib pairs.

To link hypertension-related phenotypes with chromosomal loci, genome scans were performed in 150 African American sib pairs concordant for essential hypertension. Phenotypes included blood pressure, anthropomorphic measurements, and estimates of body fluid compartments as determined by impedance plethysmography. These phenotypes were also measured in 335 normotensive African Americans. Phenotypes with LOD scores >3.3 were further evaluated for significance by use of permutation procedures. Significant linkage was detected for body mass index (BMI) on chromosomes 1 and 8 and for the ratio of extracellular water to total body water (ECF/TBW) on chromosomes 3, 5, 6, and 7. Both BMI and ECF/TBW were greater in hypertensive sibs than in normotensive subjects (P<0.001). In a subset of hypertensive sibs and normotensive subjects, average 24-hour blood pressures were correlated with ECF/TBW (P<0.01). A region linked to BMI in the hypertensive sibs corresponds to a region of conserved synteny containing blood pressure-related QTLs in an F2 cross of Brown NorwayxDahl salt-sensitive rats. Focusing on hypertension-related phenotypes is a promising approach for identifying the genetic determinants of hypertension.

Adolescent↗
PubMedDate not supplied

Peptide identification using peptide amino acid attribute vectors.

We describe the theoretical basis for a peptide identification method wherein peptides are represented as vectors based on their amino acid composition and grouped into clusters. Unknown peptides are identified by finding the database cluster and peptide entries with the shortest Euclidian distance. We demonstrate that the amino acid composition of peptides is virtually as informative as the sequence and allows rapid peptide identification more accurately than peptide mass alone.

Algorithms↗