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PubMedDate not supplied

Analytical resources for assessment of clinical genetics services in public health: current status and future prospects.

CONTEXT: Genetics services are not well integrated into the public health programs of most states, nor has there been effective use of clinical and program databases in the design, evaluation, and monitoring of public health genetics services at the state level. OBJECTIVE: To evaluate the availability and current use of population-based clinical genetics databases, including birth defects surveillance programs, in state-level public health genetics programs. DESIGN: Mail survey to state genetics coordinators in 50 states and 3 territories during 1996 with an update in 1997. RESULTS: Thirty states had birth defects surveillance programs; data from these resources were used in public health genetics program planning and management in only 15 states. Thirty states or territories had clinical genetics services databases. Most states had newborn screening program databases; few linked these records to vital statistics for programmatic purposes. Only 24 states had individual record databases for the Children with Special Health Care Needs program; 8 states had databases for maternal serum alpha-fetoprotein screening, and 7 had statewide cytogenetics registries. CONCLUSION: Population-based databases concerning aspects of public health genetics are largely unavailable at the state level. Where these databases exist, they are poorly integrated into state public health genetics program activities. More attention should be paid to the development and use of clinical data programs for the assessment, monitoring, and assurance of genetics issues with relevance to population health.

Child↗
PubMed2006

CancerGenes: a gene selection resource for cancer genome projects.

The genome sequence framework provided by the human genome project allows us to precisely map human genetic variations in order to study their association with disease and their direct effects on gene function. Since the description of tumor suppressor genes and oncogenes several decades ago, both germ-line variations and somatic mutations have been established to be important in cancer-in terms of risk, oncogenesis, prognosis and response to therapy. The Cancer Genome Atlas initiative proposed by the NIH is poised to elucidate the contribution of somatic mutations to cancer development and progression through the re-sequencing of a substantial fraction of the total collection of human genes-in hundreds of individual tumors and spanning several tumor types. We have developed the CancerGenes resource to simplify the process of gene selection and prioritization in large collaborative projects. CancerGenes combines gene lists annotated by experts with information from key public databases. Each gene is annotated with gene name(s), functional description, organism, chromosome number, location, Entrez Gene ID, GO terms, InterPro descriptions, gene structure, protein length, transcript count, and experimentally determined transcript control regions, as well as links to Entrez Gene, COSMIC, and iHOP gene pages and the UCSC and Ensembl genome browsers. The user-friendly interface provides for searching, sorting and intersection of gene lists. Users may view tabulated results through a web browser or may dynamically download them as a spreadsheet table. CancerGenes is available at http://cbio.mskcc.org/cancergenes.

Databases, Genetic↗
PubMed2006

Lotus japonicus as a platform for legume research.

The major role of 'model plants' is to provide knowledge and technologies obtained in related systems to researchers studying crop plants. Lotus japonicus was chosen as a model system first for legume genetics and then for legume genomics. A large number of L. japonicus mutants that have alterations in legume-specific phenomena have been generated and phenotypically characterized, and genomics has drastically accelerated the molecular characterization of these mutants. Substantial resources of information and experimental materials, including genomic and cDNA sequences, corresponding DNA libraries and high-density linkage maps demonstrate that L. japonicus is an excellent model system. Transfer of knowledge from L. japonicus to other legumes, especially crop legumes, is a matter for urgent consideration.

Chromosome Mapping↗
PubMed2005

Comparison of genotype- and haplotype-based approaches for fine-mapping of alcohol dependence using COGA data.

It is generally assumed that the detection of disease susceptibility genes via fine-mapping association study is facilitated by consideration of marker haplotypes. In this study, we compared the performance of genotype-based and haplotype-based association studies using the Collaborative Study of Genetics of Alcoholism dataset, on several chromosomal regions showing evidence for linkage with ALDX1. After correction for multiple testing, the most significant results were observed with the genotype-based analyses on two regions of chromosomes 2 and 7. Interestingly, the analyses results from this dataset showed that there was no advantage of the haplotype-based analyses over genotype-based (single-locus) analyses. However, caution should be taken when generalizing these results to other chromosomal regions or to other populations.

Alcoholism↗
PubMed2007

Hereditary chronic pancreatitis.

Hereditary chronic pancreatitis (HCP) is a very rare form of early onset chronic pancreatitis. With the exception of the young age at diagnosis and a slower progression, the clinical course, morphological features and laboratory findings of HCP do not differ from those of patients with alcoholic chronic pancreatitis. As well, diagnostic criteria and treatment of HCP resemble that of chronic pancreatitis of other causes. The clinical presentation is highly variable and includes chronic abdominal pain, impairment of endocrine and exocrine pancreatic function, nausea and vomiting, maldigestion, diabetes, pseudocysts, bile duct and duodenal obstruction, and rarely pancreatic cancer. Fortunately, most patients have a mild disease. Mutations in the PRSS1 gene, encoding cationic trypsinogen, play a causative role in chronic pancreatitis. It has been shown that the PRSS1 mutations increase autocatalytic conversion of trypsinogen to active trypsin, and thus probably cause premature, intrapancreatic trypsinogen activation disturbing the intrapancreatic balance of proteases and their inhibitors. Other genes, such as the anionic trypsinogen (PRSS2), the serine protease inhibitor, Kazal type 1 (SPINK1) and the cystic fibrosis transmembrane conductance regulator (CFTR) have been found to be associated with chronic pancreatitis (idiopathic and hereditary) as well. Genetic testing should only be performed in carefully selected patients by direct DNA sequencing and antenatal diagnosis should not be encouraged. Treatment focuses on enzyme and nutritional supplementation, pain management, pancreatic diabetes, and local organ complications, such as pseudocysts, bile duct or duodenal obstruction. The disease course and prognosis of patients with HCP is unpredictable. Pancreatic cancer risk is elevated. Therefore, HCP patients should strongly avoid environmental risk factors for pancreatic cancer.

Adult↗
PubMed2005

Use of genetic toxicology information for risk assessment.

Genetic toxicology data are used worldwide in regulatory decision-making. On the 25th anniversary of Environmental and Molecular Mutagenesis, we think it is important to provide a brief overview of the currently available genetic toxicity tests and to outline a framework for conducting weight-of-the-evidence (WOE) evaluations that optimize the utility of genetic toxicology information for risk assessment. There are two major types of regulatory decisions made by agencies such as the Environmental Protection Agency (EPA) and the Food and Drug Administration (FDA): (1) the approval and registration of pesticides, pharmaceuticals, medical devices, and medical-use products, and (2) the setting of standards for acceptable exposure levels in air, water, and food. Genetic toxicology data are utilized for both of these regulatory decisions. The current default assumption for regulatory decisions is that chemicals that are shown to be genotoxic in standard tests are, in fact, capable of causing mutations in humans (in somatic and/or germ cells) and that they contribute to adverse health outcomes via a "genotoxic/mutagenic" mode of action (MOA). The new EPA Guidelines for Carcinogen Risk Assessment [Guidelines for Carcinogen Risk Assessment, USEPA, 2005, EPA Publication No. EPA/630/P-03/001F] emphasize the use of MOA information in risk assessment and provide a framework to help identify a possible mutagenic and/or nonmutagenic MOA for potential adverse effects. An analysis of the available genetic toxicity data is now, more than ever, a key component to consider in the derivation of an MOA for characterizing observed adverse health outcomes such as cancer. We provide our perspective and a two-step strategy for evaluating genotoxicity data for optimal use in regulatory decision-making. The strategy includes integration of all available information and provides, first, for a WOE analysis as to whether a chemical is a mutagen, and second, whether an adverse health outcome is mediated via a mutagenic MOA.

Animals↗
PubMed2005

Facing the genetic heterogeneity in neuromuscular disorders: linkage analysis as an economic diagnostic approach towards the molecular diagnosis.

The identification of an ever increasing number of gene defects in patients with neuromuscular disorders has disclosed both marked phenotype and genotype variability and considerable disease overlap. In order to offer an economic strategy to characterise the molecular defect in patients with unclassified neuromuscular disorders, we designed DNA marker sets for linkage analysis of 62 distinct neuromuscular disorders gene loci, including all known muscular dystrophies, congenital myopathies, congenital myasthenic syndromes and myotonias. Genotyping of marker loci of 140 clinically well-characterised families with unclassified neuromuscular disorders reduced the number of candidates to one or two genes in 49 % of the families. Subsequent mutation analysis and genome-wide scans enabled the determination of the genetic defect in 31 % of the families including the identification of a new gene and a new mutation in an unexpected candidate gene. This highlights the effective application of this approach both for diagnostic strategies as well as for the identification of new loci and genes.

DNA Mutational Analysis↗
PubMed2002

Retroposed new genes out of the X in Drosophila.

New genes that originated by various molecular mechanisms are an essential component in understanding the evolution of genetic systems. We investigated the pattern of origin of the genes created by retroposition in Drosophila. We surveyed the whole Drosophila melanogaster genome for such new retrogenes and experimentally analyzed their functionality and evolutionary process. These retrogenes, functional as revealed by the analysis of expression, substitution, and population genetics, show a surprisingly asymmetric pattern in their origin. There is a significant excess of retrogenes that originate from the X chromosome and retropose to autosomes; new genes retroposed from autosomes are scarce. Further, we found that most of these X-derived autosomal retrogenes had evolved a testis expression pattern. These observations may be explained by natural selection favoring those new retrogenes that moved to autosomes and avoided the spermatogenesis X inactivation, and suggest the important role of genome position for the origin of new genes.

Animals↗
PubMed2006

OmicBrowse: a browser of multidimensional omics annotations.

UNLABELLED: OmicBrowse is a browser to explore multiple datasets coordinated in the multidimensional omic space integrating omics knowledge ranging from genomes to phenomes and connecting evolutional correspondences among multiple species. OmicBrowse integrates multiple data servers into a single omic space through secure peer-to-peer server communications, so that a user can easily obtain an integrated view of distributed data servers, e.g. an integrated view of numerous whole-genome tiling-array data retrieved from a user's in-house private-data server, along with various genomic annotations from public internet servers. OmicBrowse is especially appropriate for positional-cloning purposes. It displays both genetic maps and genomic annotations within wide chromosomal intervals and assists a user to select candidate genes by filtering their annotations or associated documents against user-specified keywords or ontology terms. We also show that an omic-space chart effectively represents schemes for integrating multiple datasets of multiple species. AVAILABILITY: OmicBrowse is developed by the Genome-Phenome Superbrain Project and is released as free open-source software under the GNU General Public License at http://omicspace.riken.jp.

Chromosome Mapping↗
PubMed2004

Elevated rates of protein secretion, evolution, and disease among tissue-specific genes.

Variation in gene expression has been held responsible for the functional and morphological specialization of tissues. The tissue specificity of genes is known to correlate positively with gene evolution rates. We show here, using large data sets, that when a gene is expressed highly in a small number of tissues, its protein is more likely to be secreted and more likely to be mutated in genetic diseases with Mendelian inheritance. We find that secreted proteins are evolving at faster rates than nonsecreted proteins, and that their evolutionary rates are highly correlated with tissue specificity. However, the impact of secretion on evolutionary rates is countered by tissue-specific constraints that have been held constant over the past 75 million years. We find that disease genes are underrepresented among intracellular and slowly evolving housekeeping genes. These findings illuminate major selective pressures that have shaped the gene repertoires expressed in different mammalian tissues.

Animals↗
PubMed2006

Tetranucleotide repeats in coding regions: no evidence for involvement in EMAST carcinogenesis.

Genetic instability is a hallmark of malignancy. In the majority of malignant tumors, chromosomal instability leads to major numerical and structural chromosomal aberrations. In contrast, some tumors have a deficient DNA mismatch repair system and accumulate mutations particularly in repetitive mono- and dinucleotide sequences, a phenomenon referred to as microsatellite instability (MSI). Recently, a novel phenotype of tumors presenting with elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) has been reported. To date, not much is known about the molecular mechanisms of EMAST tumorigenesis. In MSI tumors, instability at specific mono- and dinucleotide repeats leads to alteration of genes carrying these repeats and thus may contribute to MSI tumorigenesis. We hypothesized that, similarly to the MSI phenotype, development of EMAST cancers may be promoted by mutations affecting tetranucleotides located in coding regions of the genome. To test this hypothesis, we performed a genome-wide database search to identify tetranucleotides in gene-encoding regions. Only seven tetranucleotide repeats located in predicted gene-encoding regions were retrieved. Allele length analysis yielded three remaining candidates with a monomorphic pattern in healthy individuals. Mutation analysis revealed that none of these three candidates displayed mutations in EMAST-positive bladder cancers. These data suggest that mutational inactivation of tetranucleotide-containing genes is very unlikely to contribute to the progression of EMAST tumors.

Biomarkers, Tumor↗
PubMed2003

Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines.

Simultaneous multiclass classification of tumor types is essential for future clinical implementations of microarray-based cancer diagnosis. In this study, we have combined genetic algorithms (GAs) and all paired support vector machines (SVMs) for multiclass cancer identification. The predictive features have been selected through iterative SVMs/GAs, and recursive feature elimination post-processing steps, leading to a very compact cancer-related predictive gene set. Leave-one-out cross-validations yielded accuracies of 87.93% for the eight-class and 85.19% for the fourteen-class cancer classifications, outperforming the results derived from previously published methods.

Algorithms↗
PubMed2005

Blood rights: the body and information privacy.

Genetic and other medical technology makes blood, human tissue and other bodily samples an immediate and accessible source of comprehensive personal and health information about individuals. Yet, unlike medical records, bodily samples are not subject to effective privacy protection or other regulation to ensure that individuals have rights to control the collection, use and transfer of such samples. This article examines the existing coverage of privacy legislation, arguments in favour of baseline protection for bodily samples as sources of information and possible approaches to new regulation protecting individual privacy rights in bodily samples.

Australia↗
PubMed2006

Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes.

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray co-expressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown.

Computational Biology↗
PubMed2003

The Iranian Human Mutation Gene Bank: a data and sample resource for worldwide collaborative genetics research.

As Human Genome Project exploration continues, the necessity of having a broader spectrum of genomic DNA material from different nationalities to study various aspects of hereditary disease becomes more obvious. The existence of high genetic polymorphism within and between different communities in the world makes it necessary for the gene hunters to investigate many different populations. Iran, a large country with close to 66 million people, is a land of different nationalities, tribes, and religions that offers a highly heterogeneous gene pool to the genetics researcher. The purity of many different races in this country has been highly conserved by geographical borders and by an ancient culture that has always encouraged intrafamilial marriages. All these have created a population that is remarkably heterogeneous yet high in consanguinity rate. During the last five years of investigation we have established a DNA bank, the Iranian Human Mutation Gene Bank (www.IHMGB.com), which contains all genetic diseases studied in Iran that have the Mendelian mode of inheritance. Some of the samples are assigned to common or novel mutations and others belong to patients with clinical profiles associated with particular genetic diseases but undefined mutation. This bank stores samples of DNA from the patient and his/her first-degree relatives together with a comprehensive pedigree and clinical profile for each sample. To facilitate collaboration with other scientists around the world with the same interests, we decided to present our experimental projects online. This DNA bank provides opportunities for us to collaborate with scientists outside Iran. It offers a sample resource to research scientists around the world, at no charge, for the purpose of investigating the various aspects of genetic disorders from prenatal diagnosis to gene structure and function. It is strongly stressed that no commercial benefit is involved in the establishment of this DNA bank and the DNA samples are free of charge. However, to meet our goals and to respect ethical values, DNA samples can only be used under certain conditions stated in the User Consent Form.

Consanguinity↗
PubMed2006

Comparative genetic mutation frequencies based on amino acid composition differences.

Genetic variation inferred from large-scale amino acid composition comparisons among genomes and chromosomes of several species, Saccharomyces cerevisiae, Drosophila melanogaster, Ceanorhabditis elegans, H. sapiens, is shown to be correlated (highest, r(2)=0.9855, p<0.01) with reported mutation rates for various genes in these species. This study, based largely on pseudogene data, helps to establish reference mutation frequencies that are likely to be representative of overall genome mutation rates in each of the species examined, and provides further insight into heterogeneity of mutation rates among genomes.

Amino Acid Sequence↗
PubMed2004

Integration of the rat recombination and EST maps in the rat genomic sequence and comparative mapping analysis with the mouse genome.

Inbred strains of the laboratory rat are widely used for identifying genetic regions involved in the control of complex quantitative phenotypes of biomedical importance. The draft genomic sequence of the rat now provides essential information for annotating rat quantitative trait locus (QTL) maps. Following the survey of unique rat microsatellite (11,585 including 1648 new markers) and EST (10,067) markers currently available, we have incorporated a selection of 7952 rat EST sequences in an improved version of the integrated linkage-radiation hybrid map of the rat containing 2058 microsatellite markers which provided over 10,000 potential anchor points between rat QTL and the genomic sequence of the rat. A total of 996 genetic positions were resolved (avg. spacing 1.77 cM) in a single large intercross and anchored in the rat genomic sequence (avg. spacing 1.62 Mb). Comparative genome maps between rat and mouse were constructed by successful computational alignment of 6108 mapped rat ESTs in the mouse genome. The integration of rat linkage maps in the draft genomic sequence of the rat and that of other species represents an essential step for translating rat QTL intervals into human chromosomal targets.

Animals↗
PubMedDate not supplied

Knowledge-assisted recognition of cluster boundaries in gene expression data.

BACKGROUND AND MOTIVATION: DNA microarray technology has made it possible to determine the expression levels of thousands of genes in parallel under multiple experimental conditions. Genome-wide analyses using DNA microarrays make a great contribution to the exploration of the dynamic state of genetic networks, and further lead to the development of new disease diagnosis technologies. An important step in the analysis of gene expression data is to classify genes with similar expression patterns into the same groups. To this end, hierarchical clustering algorithms have been widely used. Major advantages of hierarchical clustering algorithms are that investigators do not need to specify the number of clusters in advance and results are presented visually in the form of a dendrogram. However, since traditional hierarchical clustering methods simply provide results on the statistical characteristics of expression data, biological interpretations of the resulting clusters are not easy, and it requires laborious tasks to unveil hidden biological processes regulated by members in the clusters. Therefore, it has been a very difficult routine for experts. OBJECTIVE: Here, we propose a novel algorithm in which cluster boundaries are determined by referring to functional annotations stored in genome databases. MATERIALS AND METHODS: The algorithm first performs hierarchical clustering of gene expression profiles. Then, the cluster boundaries are determined by the Variance Inflation Factor among the Gene Function Vectors, which represents distributions of gene functions in each cluster. Our algorithm automatically specifies a cutoff that leads to functionally independent agglomerations of genes on the dendrogram derived from similarities among gene expression patterns. Finally, each cluster is annotated according to dominant gene functions within the respective cluster. RESULTS AND CONCLUSIONS: In this paper, we apply our algorithm to two gene expression datasets related to cell cycle and cold stress response in budding yeast Saccharomyces cerevisiae. As a result, we show that the algorithm enables us to recognize cluster boundaries characterizing fundamental biological processes such as the Early G1, Late G1, S, G2 and M phases in cell cycles, and also provides novel annotation information that has not been obtained by traditional hierarchical clustering methods. In addition, using formal cluster validity indices, high validity of our algorithm is verified by the comparison through other popular clustering algorithms, K-means, self-organizing map and AutoClass.

Algorithms↗