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At least 487 records · Page 27Linked to original sources
PubMed2003

Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes.

Full genome sequencing, high-density genotyping, expanding sets of microarray assays, and systematic phenotyping of neuroanatomical and behavioral traits are producing a wealth of data on the mouse central nervous system (CNS). These disparate resources are still poorly integrated. One solution is to acquire these data using a common reference population of isogenic lines of mice, providing a point of integration between the data types. Recombinant inbred (RI) mice, derived through inbreeding of progeny from an inbred cross, are a powerful tool for complex trait mapping and analysis of the challenging phenotypes of neuroscientific interest. These isogenic RI lines are a retrievable genetic resource that can be repeatedly studied using a wide variety of assays. Diverse data sets can be related through fixed and known genomes, using tools such as the interactive web-based system for complex trait analysis, www.WebQTL.org. In this report, we demonstrate the use of WebQTL to explore complex interactions among a wide variety of traits--from mRNA transcripts to the impressive behavioral and pharmacological variation among RI strains. The relational approach exploiting a common set of strains facilitates study of multiple effects of single genes (pleiotropy) without a priori hypotheses required. Here we demonstrate the power of this technique through genetic correlation of gene expression with a database of neurobehavioral phenotypes collected in these strains of mice through more than 20 years of experimentation. By repeatedly studying the same panel of mice, early data can be re-examined in light of technological advances unforeseen at the time of their initial collection.

Animals↗
PubMed1998

Comorbid migraine with aura, anxiety, and depression is associated with dopamine D2 receptor (DRD2) NcoI alleles.

BACKGROUND: Unrelated individuals (n = 242) were interviewed directly for the presence of migraine, anxiety disorders, and major depression. MATERIALS AND METHODS: The data described in this study are derived from a clinical genetic relational database that was developed initially for the genetic analysis of migraine. Genotyping of the DRD2 NcoI C to T polymorphism located in exon 6 (His313His) was performed using previously described primers. RESULTS: A significantly increased incidence of migraine with aura (MWA), major depression, generalized anxiety disorder (GAD), panic attacks, and phobia was observed in individuals with the DRD2 NcoI C/C genotype compared with individuals with an DRD2 NcoI T allele. Specifically, 69% (91/131) of DRD2 NcoI C/C individuals in the present study met criteria for at least one of these neuropsychiatric disorders versus only 22% (4/18) of the DRD2 NcoI T/T individuals (Chi-square = 15.29; p < 0.00005). The DRD2 NcoI C allele frequency is significantly higher (Chi-square = 17.13; p < 0.00002) in individuals with MWA, anxiety disorders, and/or major depression (C allele frequency = 0.80) than in individuals who have none of these disorders (C allele frequency = 0.67). CONCLUSIONS: These data indicate that MWA, anxiety disorders, and major depression can be components of a distinct clinical syndrome associated with allelic variations within the DRD2 gene. Clinical recognition of this genetically based syndrome has significant diagnostic and therapeutic implications.

Alleles↗
PubMed2006

Increase in linkage information by stratification of pedigree data into gold-standard and standard diagnoses: application to the NIMH Alzheimer Disease Genetics Initiative Dataset.

Patients diagnosed with a standard clinical method (subject to misclassification error) are often combined with patients diagnosed with a gold-standard method (with zero or very small misclassification error) in family-based studies of complex disease. For example, non-autopsied patients (NAP) are often included along with autopsy-proven (AP) patients in family-based studies of complex diseases, such as Alzheimer's disease (AD). Theoretical and simulation studies suggest that certain misclassification errors can result in severe reduction of power in genetic linkage and association analyses and that phenotype (or diagnostic) error can produce misleading results. Morton's test for heterogeneity can identify genomic regions where error may have led to loss in power. We applied this test to pedigree data from the NIMH Alzheimer's Disease Genetics Initiative Database separated into AP and NAP pedigrees. Morton's test identified one highly significant region of heterogeneity on chromosome 2. The source of the heterogeneity was due to significant indication of linkage in the AP pedigrees at position 109 cM (p value = 6.68 x 10(-5)) with no indication in the NAP pedigrees. Furthermore, Morton's test showed no evidence for heterogeneity on chromosome 19 in early-onset pedigrees that showed highly significant evidence for linkage in other published reports. These results suggest that supplementing linkage analysis with Morton's test can be usefully applied to genetic data sets that have AP and NAP samples, or other sample mixtures that include a 'gold standard' subgroup with reduced error rate, to increase power to detect linkage in the presence of diagnostic misclassification.

Alzheimer Disease↗
PubMed2005

Bioinformatics toolbox for narrowing rodent quantitative trait loci.

Quantitative trait locus (QTL) analysis is a powerful method for localizing disease genes, but identifying the causal gene remains difficult. Rodent models of disease facilitate QTL gene identification, and causal genes underlying rodent QTL are often associated with the corresponding human diseases. Recently developed bioinformatics methods, including comparative genomics, combined cross analysis, interval-specific and genome-wide haplotype analysis, followed by sequence and expression analysis, each facilitated by public databases, provide new tools for narrowing rodent QTLs. Here we discuss each tool, illustrate its application and generate a bioinformatics strategy for narrowing QTLs. Combining these bioinformatics tools with classical experimental methods should accelerate QTL gene identification.

Animals↗
PubMed2002

FunSpec: a web-based cluster interpreter for yeast.

BACKGROUND: For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time. RESULTS: We present here a web-based tool (FunSpec) for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations (e.g. functional roles, biochemical properties, localization). FunSpec is available online at http://funspec.med.utoronto.ca CONCLUSION: FunSpec is helpful for interpretation of any data type that generates groups of related genes and proteins, such as gene expression clustering and protein complexes, and is useful for predictive methods employing "guilt-by-association."

Cluster Analysis↗
PubMed2004

Privacy and policy for genetic research.

I begin with a discussion of the value of privacy and what we lose without it. I then turn to the difficulties of preserving privacy for genetic information and other medical records in the face of advanced information technology. I suggest three alternative public policy approaches to the problem of protecting individual privacy and also preserving databases for genetic research: (1) governmental guidelines and centralized databases, (2) corporate self-regulation, and (3) my hybrid approach. None of these are unproblematic; I discuss strengths and drawbacks of each, emphasizing the importance of protecting the privacy of sensitive medical and genetic information as well as letting information technology flourish to aid patient care, public health and scientific research.

Access to Information↗
PubMed2006

Djinn Lite: a tool for customised gene transcript modelling, annotation-data enrichment and exploration.

BACKGROUND: There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences. RESULTS: Djinn Lite is designed to be an intuitive program for storing and visually exploring of custom annotations relating to a eukaryotic gene sequence and its modelled gene products. In particular, it is helpful in developing hypothesis regarding alternate splicing of transcripts by allowing the construction of model transcripts and inspection of their resulting translations. It facilitates the ability to view a gene and its gene products in one synchronised graphical view, allowing one to drill down into sequence related data. Colour highlighting of selected sequences and added annotations further supports exploration, visualisation of sequence regions and motifs known or predicted to be biologically significant. CONCLUSION: Gene annotating remains an ongoing and challenging task that will continue as gene structures, gene transcription repertoires, disease loci, protein products and their interactions become more precisely defined. Djinn Lite offers an accessible interface to help accumulate, enrich, and individualize sequence annotations relating to a gene, its transcripts and translations. The mechanism of transcript definition and creation, and subsequent navigation and exploration of features, are very intuitive and demand only a short learning curve. Ultimately, Djinn Lite can form the basis for providing valuable clues to plan new experiments, providing storage of sequences and annotations for dedication to customised projects. The application is appropriate for Windows 98-ME-2000-XP-2003 operating systems.

Alternative Splicing↗
PubMed2006

Unraveling male and female histories from human genetic data.

The increasing availability of large-scale genetic datasets has made it possible to ask detailed questions about the structure of human genetic diversity, and what that structure can teach us about human demographic history. Global, multi-locus analyses have suggested that human genetic diversity may fall into clusters that correspond approximately to continental origin. Detailed comparisons of mitochondrial DNA and the Y chromosome have revealed a history of sex-biased migration patterns that can vary widely across human populations. These patterns can be understood, however, when we incorporate our knowledge of local histories and cultural practices into our genetic analyses.

Databases, Genetic↗
PubMedDate not supplied

Recent trends in population genetics: more data! More math! Simple models?

Recent developments in population genetics are reviewed and placed in a historical context. Current and future challenges, both in computational methodology and in analytical theory, are to develop models and techniques to extract the most information possible from multilocus DNA datasets. As an example of the theoretical issues, five limiting forms of the island model of population subdivision with migration are presented in a unified framework. These approximations illustrate the interplay between migration and drift in structuring gene genealogies, and some of them make connections between the fairly complicated island-model genealogical process and the much simpler, unstructured neutral coalescent process which underlies most inferential techniques in population genetics.

Computational Biology↗
PubMed2005

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST).

BACKGROUND: BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. RESULTS: W.ND-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN). W.ND-BLAST provides intuitive Graphic User Interfaces (GUI) for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of W.ND-BLAST. W.ND-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes (11 hours) on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV) and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. CONCLUSION: W.ND-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for W.ND-BLAST is freely downloadable from http://liru.ars.usda.gov/mainbioinformatics.html. With registration the software is free, installation, networking, and usage instructions are provided as well as a support forum.

Algorithms↗
PubMed2001

A web-based tool to retrieve human genome polymorphisms from public databases.

Single Nucleotide Polymorphisms (SNPs) are the most important source of variation in our genome, and an invaluable tool in the hands of researchers who investigate genetic diseases. Databases of SNPs are growing at a very fast rate, and the ability to perform large-scale, high-resolution association studies is quickly becoming a reality. In this paper we describe SNPper, a web-based tool to search for SNPs in public databases. The system allows searching for all SNPs in a given set of genes (for candidate gene studies) or in a specified region of a chromosome. The information displayed for each gene or each SNP is fully annotated and linked to the leading bioinformatics web sites. The first release of SNPper is available on the web, and has received positive feedback from the genetic and bioinformatics community.

Databases, Genetic↗
PubMed2006

Bioinformatics for study of autoimmunity.

Recent years have witnessed an explosive growth in available biological data pertaining to autoimmunity research. This includes a tremendous quantity of sequence data (biological structures, genetic and physical maps, pathways, etc.) generated by genome and proteome projects plus extensive clinical and epidemiological data. Autoimmunity research stands to greatly benefit from this data so long as appropriate strategies are available to enable full access to and utilization of this data. The quantity and complexity of this biological data necessitates use of advanced bioinformatics strategies for its efficient retrieval, analysis and interpretation. Major progress has been made in development of specialized tools for storage, analysis and modeling of immunological data, and this has led to development of a whole new field know as immunoinformatics. With advances in novel high-throughput immunology technologies immunoinformatics is transforming understanding of how the immune system functions. This paper reviews advances in the field of immunoinformatics pertinent to autoimmunity research including databases, tools in genomics and proteomics, tools for study of B- and T-cell epitopes, integrative approaches, and web servers.

Allergy and Immunology↗
PubMed2003

Functional genomics and proteomics as a foundation for systems biology.

Developments in high-throughput measurement technologies for biological molecules have created a paradigm shift in modern life science research. The field of systems biology attempts to provide a systems-level understanding by systematically organising the genomic, functional genomic and proteomic data obtained from genetic and environmental perturbations of interest and using the data to build a descriptive and mechanistic model of the biological phenomena. The goal is to build a mathematical framework with some predictive abilities. This review highlights the need for system-level understanding, lists some of the high-throughput measurement tools of importance in systems biology, reviews various types of experimental and computational approaches being used in systems biology research and attempts to address some of the challenges facing this research community.

Animals↗
PubMed2006

FlyBase: genomes by the dozen.

FlyBase (http://flybase.org/) is the primary database of genetic and genomic data for the insect family Drosophilidae. Historically, Drosophila melanogaster has been the most extensively studied species in this family, but recent determination of the genomic sequences of an additional 11 Drosophila species opens up new avenues of research for other Drosophila species. This extensive sequence resource, encompassing species with well-defined phylogenetic relationships, provides a model system for comparative genomic analyses. FlyBase has developed tools to facilitate access to and navigation through this invaluable new data collection.

Animals↗
PubMed2004

Mouse inbred strain sequence information and yin-yang crosses for quantitative trait locus fine mapping.

The shared ancestry of mouse inbred strains, together with the availability of sequence and phenotype information, is a resource that can be used to map quantitative trait loci (QTL). The difficulty in using only sequence information lies in the fact that in most instances the allelic state of the QTL cannot be unambiguously determined in a given strain. To overcome this difficulty, the performance of multiple crosses between various inbred strains has been proposed. Here we suggest and evaluate a general approach, which consists of crossing the two strains used initially to map the QTL and any new strain. We have termed these crosses "yin-yang," because they are complementary in nature as shown by the fact that the QTL will necessarily segregate in only one of the crosses. We used the publicly available SNP database of chromosome 16 to evaluate the mapping resolution achievable through this approach. Although on average the improvement of mapping resolution using only four inbred strains was relatively small (i.e., reduction of the QTL-containing interval by half at most), we found a great degree of variability among different regions of chromosome 16 with regard to mapping resolution. This suggests that with a large number of strains in hand, selecting a small number of strains may provide a significant contribution to the fine mapping of QTL.

Alleles↗
PubMed2005

Integrating gene and protein expression data: pattern analysis and profile mining.

Proteomics and functional genomics are emerging new research fields devoted to the study of the entire collection of proteins and mRNA transcripts (collectively known as gene products) that define a biological system. DNA microarrays are now a popular platform for measuring changes in messenger RNA transcript levels on a genome-wide scale, while gel-free shotgun profiling methods based on tandem mass spectrometry are increasingly being used to determine the identity, modification states, and relative abundance of large numbers of proteins. By defining the behavior of entire biological pathways and networks under various physiological states, these studies aim to extend traditional reductionist molecular genetic approaches regarding the biological roles of the vast array of uncharacterized gene products. A key goal is to determine how the information encoded by the myriad of expressed gene products is integrated at the molecular, cellular, and even whole organism level to create the dynamic biochemical processes and complex physiological controls that sustain life. While comparison of the complementary information contained in proteomic and mRNA data sets poses considerable analytical challenges, these efforts should provide added insight into the fundamental mechanisms underlying physiology, development, and the emergence of disease. Here, we outline several analytical approaches, methods, and tools that have proven to be helpful in the face of this important challenge.

Algorithms↗
PubMed2006

Resources for genetic variation studies.

The rapid growth of genome-wide diversity databases, as well as ongoing large-scale resequencing projects targeting genes and other functional components of our genome, provide valuable resources of natural variation at the DNA sequence level. In this review, we briefly summarize the wealth of data on DNA polymorphisms in humans, the distribution of this diversity in the genome as well as among individuals, and the consequence of recombination on its organization. These data provide a set of powerful tools that can be used to better understand inherited phenotypic variation in humans. We discuss the implications for the design of studies investigating correlations between genotypes and phenotypes, both at the fundamental level of genome function and regulation, and for the mapping of disease genes.

Biomedical Research↗