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Marc A van Driel

Publications and source records attributed to Marc A van Driel.

8 recordsLinked to original sources
PubMed2006

Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.

Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases.

Computational Biology↗
PubMed2006

A text-mining analysis of the human phenome.

A number of large-scale efforts are underway to define the relationships between genes and proteins in various species. But, few attempts have been made to systematically classify all such relationships at the phenotype level. Also, it is unknown whether such a phenotype map would carry biologically meaningful information. We have used text mining to classify over 5000 human phenotypes contained in the Online Mendelian Inheritance in Man database. We find that similarity between phenotypes reflects biological modules of interacting functionally related genes. These similarities are positively correlated with a number of measures of gene function, including relatedness at the level of protein sequence, protein motifs, functional annotation, and direct protein-protein interaction. Phenotype grouping reflects the modular nature of human disease genetics. Thus, phenotype mapping may be used to predict candidate genes for diseases as well as functional relations between genes and proteins. Such predictions will further improve if a unified system of phenotype descriptors is developed. The phenotype similarity data are accessible through a web interface at http://www.cmbi.ru.nl/MimMiner/.

Chromosome Mapping↗
PubMed2006

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.

Computational Biology↗
PubMed2003

Novel types of mutation in the choroideremia ( CHM) gene: a full-length L1 insertion and an intronic mutation activating a cryptic exon.

Choroideremia (CHM) is a progressive chorioretinal degeneration caused by mutations in the widely expressed CHM gene on chromosome Xq21. The product of this gene, Rab escort protein (REP)-1, is involved in the posttranslational lipid modification and subsequent membrane targeting of Rab proteins, small GTPases that play a key role in intracellular trafficking. We have searched for mutations of the CHM gene in patients with choroideremia by analysis of individual CHM exons and adjacent intronic sequences PCR-amplified from genomic DNA and by reverse transcription (RT)-PCR analysis of the coding region of the CHM mRNA. In 35 patients, at least 21 different causative CHM defects were identified. These included two partial CHM gene deletions and an insertion of a full-length L1 retrotransposon into the coding region of the CHM gene, a type of mutation that has not been previously reported as a cause of CHM. We also detected nine different nonsense mutations, five of which are recurrent, a small deletion, a small insertion, and at least five distinct splice site mutations, one of which has been described previously. Moreover, we report for the first time the identification of an intronic mutation remote from the exon-intron junctions that creates a strong acceptor splice site and leads to the inclusion of a cryptic exon into the CHM mRNA. Finally, in an affected male who did not have a mutation in any of the CHM exons or their splice sites, the deletion of a complete exon from the CHM mRNA was observed.

Adaptor Proteins, Signal Transducing↗
PubMed2003

A new web-based data mining tool for the identification of candidate genes for human genetic disorders.

To identify the gene underlying a human genetic disorder can be difficult and time-consuming. Typically, positional data delimit a chromosomal region that contains between 20 and 200 genes. The choice then lies between sequencing large numbers of genes, or setting priorities by combining positional data with available expression and phenotype data, contained in different internet databases. This process of examining positional candidates for possible functional clues may be performed in many different ways, depending on the investigator's knowledge and experience. Here, we report on a new tool called the GeneSeeker, which gathers and combines positional data and expression/phenotypic data in an automated way from nine different web-based databases. This results in a quick overview of interesting candidate genes in the region of interest. The GeneSeeker system is built in a modular fashion allowing for easy addition or removal of databases if required. Databases are searched directly through the web, which obviates the need for data warehousing. In order to evaluate the GeneSeeker tool, we analysed syndromes with known genesis. For each of 10 syndromes the GeneSeeker programme generated a shortlist that contained a significantly reduced number of candidate genes from the critical region, yet still contained the causative gene. On average, a list of 163 genes based on position alone was reduced to a more manageable list of 22 genes based on position and expression or phenotype information. We are currently expanding the tool by adding other databases. The GeneSeeker is available via the web-interface (http://www.cmbi.kun.nl/GeneSeeker/).

Computational Biology↗
PubMed2003

Autosomal dominant rhegmatogenous retinal detachment associated with an Arg453Ter mutation in the COL2A1 gene.

PURPOSE: To investigate the clinical features and molecular causes of autosomal dominant rhegmatogenous retinal detachment (RRD) in two large families. METHODS: Clinical examination and linkage analysis of both families using markers flanking the COL2A1 gene associated with Stickler syndrome type 1, the loci for Wagner disease/erosive vitreoretinopathy (5q14.3), high myopia (18p11.31 and 12q21-q23), and nonsyndromic congenital retinal nonattachment (10q21). RESULTS: Fifteen individuals from family A and 12 individuals from family B showed RRD or retinal tears with minimal (family A) or no (family B) systemic characteristics of Stickler syndrome and no ocular features of Wagner disease or erosive vitreoretinopathy. The RRD cosegregated fully with a chromosomal region harboring the COL2A1 gene with maximum lod scores of 6.09 (family A) and 4.97 (family B). In family B, an Arg453Ter mutation was identified in exon 30 of the COL2A1 gene, that was previously described in a patient with classic Stickler syndrome. In family A, DNA sequence analysis revealed no mutation in the coding region and at the splice sites of the COL2A1 gene. CONCLUSIONS: In two large families with RRD, linkage was found at the COL2A1 locus. In one of these families an Arg453Ter mutation was identified, which is surprising, because all predominantly ocular Stickler syndrome cases until now have been associated with protein-truncating mutations in exon 2, an exon subject to alternative splicing. In contrast, the Arg453Ter mutation and other protein-truncating mutations in the helical domain of COL2A1 have been associated until now with classic Stickler syndrome.

Adolescent↗
PubMed2002

Genomic structure and assessment of the retinally expressed RFamide-related peptide gene in dominant cystoid macular dystrophy.

PURPOSE: Computer-assisted sampling of EST data contained within the UniGene human sequences collection is being used to establish a catalog of novel genes that are expressed exclusively or predominantly in the human retina. This provides a valuable source for candidate genes possibly involved in retinal degeneration. In this report we present the characterization of the C7orf9 gene locus encoding RFamide-related peptides (RFRPs) and its evaluation in dominant cystoid macular dystrophy (CYMD). METHODS: Bioinformatics and cDNA library screening were used to isolate the full-length cDNA sequence and to determine the genomic organization of C7orf9. Expression profiling was done by RT-PCR and Northern blot analysis. C7orf9 was evaluated as a candidate gene for CYMD by DNA sequencing and Southern blot analysis in two affected individuals from an extended Dutch CYMD family. RESULTS: The C7orf9 cDNA transcript consists of 1190 bp and is organized into 3 exons on the short arm of chromosome 7 within the critical region for CYMD. The transcript is specifically expressed in the retina but not in a large range of other human tissues. No disease-causing mutations or larger gene rearrangements were found. CONCLUSIONS: We provide the genomic organization of the RFamide-related peptide gene, C7orf9, which encodes a precursor protein for at least two small neuropeptides, referred to as NPSF (alias RFRP-1) and NPVF (alias RFRP-3) and show that it is abundantly expressed in the human retina. Results of our comprehensive mutation analysis suggests that C7orf9 is not the CYMD gene.

Amino Acid Sequence↗