Identification Of Disease Genes Research Articles

Genetic analysis of skeletal dysplasia: recent advances and perspectives in the post-genome-sequence era

Skeletal dysplasia is a group of disorders of the skeleton that result from derangement of growth, development and/or differentiation of the skeleton. Nearly 300 disorders are included; most of them are monogenic diseases. Responsible genes for skeletal dysplasia have been identified in more than 150 diseases mainly through positional cloning. Identification of disease genes would improve patient care through genetic diagnosis as well as improving our understanding of the diseases and molecular mechanism of skeletal tissue formation. Studies of skeletal dysplasia would also help identify disease genes for common diseases affecting bones and joints. In this study, the author reviews recent advances and the current status of the genetic analysis of skeletal dysplasia and its impacts on research into skeletal biology.

Systematic identification of human mitochondrial disease genes through integrative genomics

The majority of inherited mitochondrial disorders are due to mutations not in the mitochondrial genome (mtDNA) but rather in the nuclear genes encoding proteins targeted to this organelle. Elucidation of the molecular basis for these disorders is limited because only half of the estimated 1,500 mitochondrial proteins have been identified. To systematically expand this catalog, we experimentally and computationally generated eight genome-scale data sets, each designed to provide clues as to mitochondrial localization: targeting sequence prediction, protein domain enrichment, presence of cis-regulatory motifs, yeast homology, ancestry, tandem-mass spectrometry, coexpression and transcriptional induction during mitochondrial biogenesis. Through an integrated analysis we expand the collection to 1,080 genes, which includes 368 novel predictions with a 10% estimated false prediction rate. By combining this expanded inventory with genetic intervals linked to disease, we have identified candidate genes for eight mitochondrial disorders, leading to the discovery of mutations in MPV17 that result in hepatic mtDNA depletion syndrome. The integrative approach promises to better define the role of mitochondria in both rare and common human diseases.

The impact of data quality on the identification of complex disease genes: experience from the Family Blood Pressure Program

The application of genome-wide linkage scans to uncover susceptibility loci for complex diseases offers great promise for the risk assessment, treatment, and understanding of these diseases. However, for most published studies, linkage signals are typically modest and vary considerably from one study to another. The multicenter Family Blood Pressure Program has analyzed genome-wide linkage scans of over 12 000 individuals. Based on this experience, we developed a protocol for large linkage studies that reduces two sources of data error: pedigree structure and marker genotyping errors. We then used the linkage signals, before and after data cleaning, to illustrate the impact of missing and erroneous data. A comprehensive error-checking protocol is an important part of complex disease linkage studies and enhances gene mapping. The lack of significant and reproducible linkage findings across studies is, in part, due to data quality.

The systematic functional characterisation of Xq28 genes prioritises candidate disease genes

BackgroundWell known for its gene density and the large number of mapped diseases, the human sub-chromosomal region Xq28 has long been a focus of genome research. Over 40 of approximately 300 X-linked diseases map to this region, and systematic mapping, transcript identification, and mutation analysis has led to the identification of causative genes for 26 of these diseases, leaving another 17 diseases mapped to Xq28, where the causative gene is still unknown. To expedite disease gene identification, we have initiated the functional characterisation of all known Xq28 genes.ResultsBy using a systematic approach, we describe the Xq28 genes by RNA in situ hybridisation and Northern blotting of the mouse orthologs, as well as subcellular localisation and data mining of the human genes. We have developed a relational web-accessible database with comprehensive query options integrating all experimental data. Using this database, we matched gene expression patterns with affected tissues for 16 of the 17 remaining Xq28 linked diseases, where the causative gene is unknown.ConclusionBy using this systematic approach, we have prioritised genes in linkage regions of Xq28-mapped diseases to an amenable number for mutational screens. Our database can be queried by any researcher performing highly specified searches including diseases not listed in OMIM or diseases that might be linked to Xq28 in the future.

Gene-Based Single Nucleotide Polymorphisms and Linkage Disequilibrium Patterns of 29 Asthma Candidate Genes in the Chromosome 5q31–33 Region in Koreans

Background and Methods: Numerous genetic studies have mapped asthma susceptibility genes to a region on chromosome 5q31–33 in several populations. This region contains a cluster of cytokines and other immune-related genes important in immune response. In the present study, to determine the genetic variations and patterns of linkage disequilibrium (LD), we resequenced all the exons and promoter regions of the 29 asthma candidate genes in the chromosome 5q31–33 region. Results: We identified a total of 314 genetic variants, including 289 single nucleotide polymorphisms (SNPs), 22 insertion/deletion polymorphisms and 3 microsatellites. Standardized variance data for allele frequency revealed substantial differences in SNP allele frequencies among different ethnic groups. Interestingly, significant ethnic differences were observed mainly in intron SNPs. LD block analysis using 174 common SNPs with a frequency of >10% disclosed strong LD within most candidate genes. No significant LD was observed across genes, except for one LD block (CD14-IK block). Gene-based haplotype analyses showed that 1–5 haplotype-tagging SNPs may be used to define the six or fewer common haplotypes with a frequency of >5%, regardless of the number of SNPs. Conclusion: Overall, our results provide useful information for the identification of immune-mediated disease genes in the chromosome 5q31–33 region, as well as valuable evidence for gene-based haplotype analysis in disease association studies.

Significance of Murine Retroviral Mutagenesis for Identification of Disease Genes in Human Acute Myeloid Leukemia

Retroviral insertion mutagenesis is considered a powerful tool to identify cancer genes in mice, but its significance for human cancer has remained elusive. Moreover, it has recently been debated whether common virus integrations are always a hallmark of tumor cells and contribute to the oncogenic process. Acute myeloid leukemia (AML) is a heterogeneous disease with a variable response to treatment. Recurrent cytogenetic defects and acquired mutations in regulatory genes are associated with AML subtypes and prognosis. Recently, gene expression profiling (GEP) has been applied to further risk stratify AML. Here, we show that mouse leukemia genes identified by retroviral insertion mutagenesis are more frequently differentially expressed in distinct subclasses of adult and pediatric AML than randomly selected genes or genes located more distantly from a virus integration site. The candidate proto-oncogenes showing discriminative expression in primary AML could be placed in regulatory networks mainly involved in signal transduction and transcriptional control. Our data support the validity of retroviral insertion mutagenesis in mice for human disease and indicate that combining these murine screens for potential proto-oncogenes with GEP in human AML may help to identify critical disease genes and novel pathogenetic networks in leukemia.

Prioritizing regions of candidate genes for efficient mutation screening

The availability of the complete sequence of the human genome has dramatically facilitated the search for disease-causing sequence variations. In fact, the rate-limiting step has shifted from the discovery and characterization of candidate genes to the actual screening of human populations and the subsequent interpretation of observed variations. In this study we tested the hypothesis that some segments of candidate genes are more likely than others to contain disease-causing variations and that these segments can be predicted bioinformatically. A bioinformatic technique, prioritization of annotated regions (PAR), was developed to predict the likelihood that a specific coding region of a gene will harbor a disease-causing mutation based on conserved protein functional domains and protein secondary structures. This method was evaluated by using it to analyze 710 genes that collectively harbor 4,498 previously identified mutations. Nearly 50% of the genes were recognized as disease-associated after screening only 9% of the complete coding sequence. The PAR technique identified 90% of the genes as containing at least one mutation, with less than 40% of the screening resources that traditional approaches would require. These results suggest that prioritization strategies such as PAR can accelerate disease-gene identification through more efficient use of screening resources.

Using Inbred Mouse Strains to Identify Genes for Complex Diseases

In recent years, genetic studies in humans have identified a handful of genes that are associated with common disorders, but our understanding of such diseases at the genetic level remains relatively rudimentary. The use of mice to dissect the complex genetic etiology of common disorders offers a viable alternative to human studies since experimental parameters, such as environmental influences, breeding scheme, and detailed phenotyping can be controlled. This review focuses on the utility of mouse genetics for identification of complex disease genes. Atherosclerosis is used as a representative example, followed by an overview for the prospects of successful gene discovery in the future.

Bioinformatics methods for identifying candidate disease genes

With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information is the usual strategy by which candidate disease genes are selected. Enrichment for candidate disease genes, however, depends on the skills of the operating researcher. Over the past few years, a number of bioinformatics methods that enrich for the most likely candidate disease genes have been developed. Such in silico prioritisation methods may further improve by completion of datasets, by development of standardised ontologies across databases and species and, ultimately, by the integration of different strategies.

Interactive visual analysis of SNP data for rapid autozygosity mapping in consanguineous families

Autozygosity mapping of recessive disorders using small numbers of highly inbred families is a powerful tool for disease gene identification. With the advent of cheap rapid methods for whole-genome SNP genotyping, data analysis, rather than laboratory work, has become rate-limiting for this approach. Here, we describe AutoSNPa, a computer program used for handling and visually presenting large amounts of SNP data, in such a way as to facilitate the rapid identification and subsequent scrutiny of autozygous regions.

Will the real disease gene please stand up?

A common dilemma arising in linkage studies of complex genetic diseases is the selection of positive signals, their follow-up with association studies and discrimination between true and false positive results. Several strategies for overcoming these issues have been devised. Using the Genetic Analysis Workshop 14 simulated dataset, we aimed to apply different analytical approaches and evaluate their performance in discerning real associations. We considered a) haplotype analyses, b) different methods adjusting for multiple testing, c) replication in a second dataset, and d) exhaustive genotyping of all markers in a sufficiently powered, large sample group. We found that haplotype-based analyses did not substantially improve over single-point analysis, although this may reflect the low levels of linkage disequilibrium simulated in the datasets provided. Multiple testing correction methods were in general found to be over-conservative. Replication of nominally positive results in a second dataset appears to be less stringent, resulting in the follow-up of false positives. Performing a comprehensive assay of all markers in a large, well-powered dataset appears to be the most effective strategy for complex disease gene identification.

Genetic dissection of inflammatory bowel disease: unravelling etiology and improving diagnostics

Over the past 10 years, remarkable advances in the mapping and identification of genes involved in susceptibility to inflammatory bowel disease have been witnessed. Most notable among these advances has been the discovery of variants in the CARD15, DLG5, SLC22A4 and SLC22A5 genes, which are associated with increased risk of inflammatory bowel disease or specifically Crohn’s disease. These discoveries have provided critical new insights into the molecular pathophysiology of inflammatory bowel disease and the pathways wherein genetic and environmental factors such as enteric bacterial flora may interact to trigger immune dysregulation and intestinal inflammation. This review will outline the discovery of these inflammatory bowel disease-related genes, describe future prospects for further inflammatory bowel disease gene identification, and consider the impact of a genetic understanding of inflammatory bowel disease on future clinical practice.

Identification of disease genes by whole genome CGH arrays

Small, submicroscopic, genomic deletions and duplications (1 kb to 10 Mb) constitute up to 15% of all mutations underlying human monogenic diseases. Novel genomic technologies such as microarray-based comparative genomic hybridization (array CGH) allow the mapping of genomic copy number alterations at this submicroscopic level, thereby directly linking disease phenotypes to gene dosage alterations. At present, the entire human genome can be scanned for deletions and duplications at over 30,000 loci simultaneously by array CGH ( approximately 100 kb resolution), thus entailing an attractive gene discovery approach for monogenic conditions, in particular those that are associated with reproductive lethality. Here, we review the present and future potential of microarray-based mapping of genes underlying monogenic diseases and discuss our own experience with the identification of the gene for CHARGE syndrome. We expect that, ultimately, genomic copy number scanning of all 250,000 exons in the human genome will enable immediate disease gene discovery in cases exhibiting single exon duplications and/or deletions.

Therapeutics development for triplet repeat expansion diseases

The underlying genetic mutations for many inherited neurodegenerative disorders have been identified in recent years. One frequent type of mutation is trinucleotide repeat expansion. Depending on the location of the repeat expansion, the mutation might result in a loss of function of the disease gene, a toxic gain of function or both. Disease gene identification has led to the development of model systems for investigating disease mechanisms and evaluating treatments. Examination of experimental findings reveals similarities in disease mechanisms as well as possibilities for treatment.

Genetic Association, Post-translational Modification, and Protein-Protein Interactions in Type 2 Diabetes Mellitus

Type 2 diabetes mellitus is a complex disorder with a strong genetic component. Inherited complex disease susceptibility in humans is most commonly associated with single nucleotide polymorphisms. The mechanisms by which this occurs are still poorly understood. Here we focus on analyzing the effect of a set of disease-causing missense variations of the monogenetic form of Type 2 diabetes mellitus and a set of disease-associated nonsynonymous variations in comparison with that of nonsynonymous variations without any experimental evidence for association with any disease. Analysis of different properties such as evolutionary conservation status, solvent accessibility, secondary structure, etc. suggests that disease-causing variations are associated with extreme changes in the value of the parameters relating to evolutionary conservation and/or protein stability. Disease-associated variations are rather moderately conserved and have a milder effect on protein function and stability. The majority of the genes harboring these variations are clustered in or near the insulin signaling network. Most of these variations are identified as potential sites for post-translational modifications; certain predictions have already reported experimental evidence. Overall our results indicate that Type 2 diabetes mellitus may result from a large number of single nucleotide polymorphisms that impair modular domain function and post-translational modifications involved in signaling. Our emphasis is more on conserved corresponding residues than the variation alone. We believe that the approach of considering a stretch of peptide sequence involving a polymorphism would be a better method of defining the role of the polymorphism in the manifestation of this disease. Because most of the variations associated with the disease are rare, we hypothesize that this disease is a "mosaic model" of interaction between a large number of rare alleles and a small number of common alleles along with the environment, which is little contrary to the existing common disease common variant model.

Die Genetik der retinalen Dystrophien — ein Überblick

Vision requires complex retinal functions, involving multiple genes with different functions. Retinal degeneration results from disturbance of retina-specific processes such as the visual transduction cascade, but also from defects in basic functions such as pre-mRNA splicing and nucleotide synthesis. As a consequence, the retinal dystrophies are genetically extremely heterogeneous (as shown in the table). Thanks to the Human Genome Project, the identification of retinal disease genes and additional loci has skyrocketed. Today, a typical search for the causative gene in a disease-linked genomic interval starts at the computer. Genes from a particular region can be displayed, and multiple gene-specific data such as expression patterns are immediately accessible. Candidate genes can then be investigated in DNA from affected individuals.

Recent advances in the identification of genes for human hypertension

It is a well-established fact that genes are involved in the etiology of hypertension. However, identification of the gene variants still remains a challenge. Over the years, different approaches and technologies, including genome-wide scans, case-control association studies, experiments on inbred rodent models and expression profiling, have been utilized to elucidate hypertension susceptibility genes, but so far the results have been equivocal. During the last year, further chromosomal regions harboring blood pressure loci have been identified, and transcriptomics has been applied to aid the identification of disease genes. There are great expectations for the future with regards to further advancements in transcriptomics and proteomics. This review reports primarily on work that has been carried out in the last 12 months in the field, and considers its contribution towards a better understanding of the genetic mechanisms involved in blood pressure regulation and hypertension.

Bipolar affective disorder in a male with a deletion of Y chromosome – a case report

We report on a 25-year-old male with bipolar disorder, dysmorphic features and a deletion of the long arm of Y chromosome. A potential association between sex chromosome abnormalities and a susceptibility to major psychiatric disorders has been documented. However there have been very few reports on the coincidence of Y chromosome aberrations with bipolar disorder. Cytogenetic studies have contributed to the identification of several disease genes. Karyotyping of patients with bipolar disorder in order to identify candidate regions for linkage studies has been recommended.

PENDEKATAN FARMAKOGENOMIK DALAM PENGEMBANGAN OBAT BARU

The human population is heterogeneous and consists of populations of immense ethnic diversity. There are considerable allelic differences between human popula-tions as well as individuals within each ethnic group as a result of molecular hetero-geneity of the genome. This, in turn, is responsible for differential allelic expression of genes endowing them with polymorphic characters. The molecular diversity within genes is responsible amongst others, of disease resistance or susceptibility or for that matter drug response. Pharmacogenomics is the key to the understanding of differ-ential drug response in different patients in relation to genetic constitution. The revelation of such information at the molecular level would assist the pharmaceuti-cal industry to address a therapy directed to each individual. The objective of this article is to understand the nuances of the genetic repertoire and correlate it with disease gene identification, genes that have been or can be used as drug targets, identify candidate genes for drug development and recent trends in drug discovery.

TPMD: a database and resources of microsatellite marker genotyped in Taiwanese populations

Taiwan Polymorphic Marker Database (TPMD) (http://tpmd.nhri.org.tw/) is a marker database designed to provide experimental details and useful marker information allelotyped in Taiwanese populations accompanied by resources and technical supports. The current version deposited more than 372 000 allelotyping data from 1425 frequently used and fluorescent-labeled microsatellite markers with variation types of dinucleotide, trinucleotide and tetranucleotide. TPMD contains text and map displays with searchable and retrievable options for marker names, chromosomal location in various human genome maps and marker heterozygosity in populations of Taiwanese, Japanese and Caucasian. The integration of marker information in map display is useful for the selection of high heterozygosity and commonly used microsatellite markers to refine mapping of diseases locus followed by identification of disease gene by positional candidate cloning. In addition, our results indicated that the number of markers with heterozygosity over 0.7 in Asian populations is lower than that in Caucasian. To increase accuracy and facilitate genetic studies using microsatellite markers, we also list markers with genotyping difficulty due to ambiguity of allele calling and recommend an optimal set of microsatellite markers for genotyping in Taiwanese, and possible extension of genotyping in other Mongoloid populations.