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At least 973 records · Page 54Linked to original sources
PubMed2025

ClinGen recuration of hearing loss-associated genes demonstrates significant changes in gene-disease validity over time.

PURPOSE: The Clinical Genome Resource (ClinGen) Hearing Loss Gene Curation Expert Panel was assembled in 2016 and has since curated 174 gene-disease relationships (GDRs) using ClinGen's semiquantitative framework. ClinGen mandates the timely recuration of all GDRs classified as Disputed, Limited, Moderate, and Strong every 2 to 3 years. METHODS: Thirty-five GDRs met the criteria for recuration within 2 years of original curation. Previous evidence was reevaluated using the latest curation guidelines, and a comprehensive literature review was performed to obtain new evidence. Recurations were approved by the Gene Curation Expert Panel and published on the ClinGen website (www.clinicalgenome.org). RESULTS: Eight of 35 GDRs (22%) changed their classification. Two Moderate and 5 Strong GDRs were upgraded to Definitive because of new case evidence. One Strong was subsumed under another Definitive GDR after evaluation of the lumping/splitting of disease entities. Twenty-seven of 35 patients remained unchanged, with little to no new evidence reported. CONCLUSION: Genes classified as Moderate and Strong were likely to build evidence and change their classification over time, whereas Limited were unlikely to gain evidence. These findings highlight the critical role of recuration in ensuring that genetic tests and research studies incorporate the most recent evidence into their efforts.

Humans↗
PubMed2005

A genome-wide linkage and association study using COGA data.

BACKGROUND: Genome-wide association will soon be available to use as an adjunct to traditional linkage analysis. We studied alcoholism in 119 families collected by the Collaborative Study on the Genetics of Alcoholism and made available in Genetic Analysis Workshop 14, using genome-wide linkage and association analyses. METHODS: Genome-wide linkage analysis was first performed using microsatellite markers and a region with the strongest linkage evidence was further analyzed using single-nucleotide polymorphisms (SNPs). Family based genome-wide association test was also conducted using the SNPs. RESULTS: Nonparametric linkage analysis revealed weak linkage evidence on chromosome 7, and association analysis identified SNP tsc0515272 on chromosome 3 as significantly associated with alcoholism. CONCLUSION: Linkage analysis may require large sample sizes and high quality genotyping and marker maps to adequately improve power, while association analysis could hold more promise in efforts to identify variants responsible for complex traits.

Alcoholism↗
PubMed2006

SequenceLDhot: detecting recombination hotspots.

MOTIVATION: There is much local variation in recombination rates across the human genome--with the majority of recombination occurring in recombination hotspots--short regions of around approximately 2 kb in length that have much higher recombination rates than neighbouring regions. Knowledge of this local variation is important, e.g. in the design and analysis of association studies for disease genes. Population genetic data, such as that generated by the HapMap project, can be used to infer the location of these hotspots. We present a new, efficient and powerful method for detecting recombination hotspots from population data. RESULTS: We compare our method with four current methods for detecting hotspots. It is orders of magnitude quicker, and has greater power, than two related approaches. It appears to be more powerful than HotspotFisher, though less accurate at inferring the precise positions of the hotspot. It was also more powerful than LDhot in some situations: particularly for weaker hotspots (10-40 times the background rate) when SNP density is lower (< 1/kb). AVAILABILITY: Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.

Algorithms↗
PubMed2003

A gene-coexpression network for global discovery of conserved genetic modules.

To elucidate gene function on a global scale, we identified pairs of genes that are coexpressed over 3182 DNA microarrays from humans, flies, worms, and yeast. We found 22,163 such coexpression relationships, each of which has been conserved across evolution. This conservation implies that the coexpression of these gene pairs confers a selective advantage and therefore that these genes are functionally related. Many of these relationships provide strong evidence for the involvement of new genes in core biological functions such as the cell cycle, secretion, and protein expression. We experimentally confirmed the predictions implied by some of these links and identified cell proliferation functions for several genes. By assembling these links into a gene-coexpression network, we found several components that were animal-specific as well as interrelationships between newly evolved and ancient modules.

Animals↗
PubMed2005

Potentials and pitfalls of DNA array analysis of the endothelial stress response.

Endothelial cells respond to inflammatory stimuli with complex genetic alterations that determine the immune response and the outcome of the inflammatory process. An additional layer of complexity is added by the different phenotypes and functional heterogeneity of endothelial cells in the various tissues. To understand these complex gene response patterns and the regulatory pathways involved, many investigators increasingly use DNA microarray analysis. There are, however, many potential pitfalls in the use of microarrays that can result in false data and erroneous conclusions. This review surveys the principles of DNA microarray technology and its applications in endothelial cell research. We also attempt to outline some of the caveats and standard criteria that have to be considered in order to realize the full potential of microarrays in inflammation research.

Biotechnology↗
PubMed2006

Molecular approaches in the diagnosis of primary immunodeficiency diseases.

Over 120 inherited primary immunodeficiency diseases (PIDs) are known to exist. The genes responsible for many of these diseases have also been identified. Recent advances in diagnostic procedures have enabled these to be identified earlier and appropriately treated. While a number of approaches are available to identify mutations, direct sequencing remains the gold standard. This approach identifies the exact genetic change with substantial precision. We suggest that a sensitive and economical approach to mutation detection could be the direct sequencing of cDNA followed by the confirmatory sequencing of the corresponding exon. While screening techniques such as single-stranded conformation polymorphism (SSCP), heteroduplex analysis (HA), denaturing gradient gel electrophoresis (DGGE), and denaturing high-performance liquid chromatography (dHPLC) have proven useful, each has inherent advantages and disadvantages. We discuss these advantages and disadvantages and also discuss the potential of future sequencing technologies such as pyrosequencing, combinatorial sequencing-by-hybridization, multiplex polymerase colony (polony), and resequencing arrays as tools for future mutation detection. In addition we briefly discuss several high-throughput SNP detection technologies.

Algorithms↗
PubMed2006

Status of clinical gene sequencing data reporting and associated risks for information loss.

Clinical gene sequencing is growing in importance and cost-effectiveness. In the past two years, the number of genes associated with disease has grown by roughly 25%. Knowledge of genetic variations will soon guide drug selection and dosages, predict risks from toxin exposures, and inform nutritional needs. Despite the significance of sequencing, methods for reporting results are problematic. Frequent use of paper and infrequent use of naming standards impede data exchange and make incorporation into the electronic medical record difficult. Reports often describe only variations found, rather than all data (all patient bases sequenced). Also, reports frequently do not describe reference data used to define variations. These practices create risks for loss of both data and information. Standardized electronic reporting of all data (all bases sequenced and all reference data) and electronic record systems capable of storing these results would both prevent data loss and simplify the preservation of information those data provide.

Computer Security↗
PubMed2005

Critical values and variation in type I error along chromosomes in the COGA dataset using the applied pseudo-trait method.

BACKGROUND: By analyzing a "pseudo-trait," a trait not linked or associated with any of the markers tested, the distribution of the test statistic under the null hypothesis can provide the critical value for the appropriate percentile of the distribution. In addition, the anecdotal observation that p-values tend to be more significant near the telomeres was investigated. RESULTS: The applied pseudo-trait (APT) method was applied to the Affymetrix and Illumina SNPs in the Collaborative Study on the Genetics of Alcoholism dataset to determine appropriate critical values for regression of offspring on mid-parent (ROMP) and Haseman-Elston association and linkage analyses, investigating the occurrence of type I errors in different chromosomal locations, and the extent to which the critical values obtained depend on the type of pseudo-trait used. CONCLUSION: On average, the 5 percentile critical values obtained for this study were less than the expected 0.05. The distribution of p-values does not seem to depend on chromosomal position for ROMP association analysis methods, but does in some cases for Haseman-Elston linkage analysis. Results vary with different pseudo-traits.

Alcoholism↗
PubMed2003

Development of an integrated laboratory information management system for the maize mapping project.

MOTIVATION: The development of an integrated genetic and physical map for the maize genome involves the generation of an enormous amount of data. Managing this data requires a system to aid in genotype scoring for different types of markers coming from both local and remote users. In addition, researchers need an efficient way to interact with genetic mapping software and with data files from automated DNA sequencing. They also need ways to manage primer data for mapping and sequencing and provide views of the integrated physical and genetic map and views of genetic map comparisons. RESULTS: The MMP-LIMS system has been used successfully in a high-throughput mapping environment. The genotypes from 957 SSR, 1023 RFLP, 189 SNP, and 177 InDel markers have been entered and verified via MMP-LIMS. The system is flexible, and can be easily modified to manage data for other species. The software is freely available. AVAILABILITY: To receive a copy of the iMap or cMap software, please fill out the form on our website. The other MMP-LIMS software is freely available at http://www.maizemap.org/bioinformatics.htm.

Chromosome Mapping↗
PubMed2005

Linkage analysis of GAW14 simulated data: comparison of multimarker, multipoint, and conditional approaches.

The purposes of this study were 1) to examine the performance of a new multimarker regression approach for model-free linkage analysis in comparison to a conventional multipoint approach, and 2) to determine the whether a conditioning strategy would improve the performance of the conventional multipoint method when applied to data from two interacting loci. Linkage analysis of the Kofendrerd Personality Disorder phenotype to chromosomes 1 and 3 was performed in three populations for all 100 replicates of the Genetic Analysis Workshop 14 simulated data. Three approaches were used: a conventional multipoint analysis using the Zlr statistic as calculated in the program ALLEGRO; a conditioning approach in which the per-family contribution on one chromosome was weighted according to evidence for linkage on the other chromosome; and a novel multimarker regression approach. The multipoint and multimarker approaches were generally successful in localizing known susceptibility loci on chromosomes 1 and 3, and were found to give broadly similar results. No advantage was found with the per-family conditioning approach. The effect on power and type I error of different choices of weighting scheme (to account for different numbers of affected siblings) in the multimarker approach was examined.

Chromosome Mapping↗
PubMed2005

Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data.

We applied three approaches for the identification of polymorphisms explaining the linkage evidence to the Genetic Analysis Workshop 14 simulated data: 1) the genotype-IBD sharing test (GIST); 2) an approach suggested by Horikawa and colleagues; and 3) the homozygote sharing test (HST). These tests were compared with a family-based association test. Two linked regions with highest nonparametric linkage scores were selected to apply these methods. In the first region, Horikawa's method identified the most SNPs within the region containing the disease susceptibility locus, while HST performed best in the second region. However, Horikawa's method also had the most type I errors. These methods show potential as additional tools to complement family-based association tests for the identification of disease susceptibility variants.

Chromosomes, Human, Pair 1↗
PubMed2004

Combining biological networks to predict genetic interactions.

Genetic interactions define overlapping functions and compensatory pathways. In particular, synthetic sick or lethal (SSL) genetic interactions are important for understanding how an organism tolerates random mutation, i.e., genetic robustness. Comprehensive identification of SSL relationships remains far from complete in any organism, because mapping these networks is highly labor intensive. The ability to predict SSL interactions, however, could efficiently guide further SSL discovery. Toward this end, we predicted pairs of SSL genes in Saccharomyces cerevisiae by using probabilistic decision trees to integrate multiple types of data, including localization, mRNA expression, physical interaction, protein function, and characteristics of network topology. Experimental evidence demonstrated the reliability of this strategy, which, when extended to human SSL interactions, may prove valuable in discovering drug targets for cancer therapy and in identifying genes responsible for multigenic diseases.

Animals↗
PubMed2007

Signatures of positive selection in genes associated with human skin pigmentation as revealed from analyses of single nucleotide polymorphisms.

Phenotypic variation between human populations in skin pigmentation correlates with latitude at the continental level. A large number of hypotheses involving genetic adaptation have been proposed to explain human variation in skin colour, but only limited genetic evidence for positive selection has been presented. To shed light on the evolutionary genetic history of human variation in skin colour we inspected 118 genes associated with skin pigmentation in the Perlegen dataset, studying single nucleotide polymorphisms (SNPs), and analyzed 55 genes in detail. We identified eight genes that are associated with the melanin pathway (SLC45A2, OCA2, TYRP1, DCT, KITLG, EGFR, DRD2 and PPARD) and presented significant differences in genetic variation between Europeans, Africans and Asians. In six of these genes we detected, by means of the EHH test, variability patterns that are compatible with the hypothesis of local positive selection in Europeans (OCA2, TYRP1 and KITLG) and in Asians (OCA2, DCT, KITLG, EGFR and DRD2), whereas signals were scarce in Africans (DCT, EGFR and DRD2). Furthermore, a statistically significant correlation between genotypic variation in four pigmentation candidate genes and phenotypic variation of skin colour in 51 worldwide human populations was revealed. Overall, our data also suggest that light skin colour is the derived state and is of independent origin in Europeans and Asians, whereas dark skin color seems of unique origin, reflecting the ancestral state in humans.

Asian People↗
PubMed2005

Mining the probiotic genome: advanced strategies, enhanced benefits, perceived obstacles.

Recent advances in DNA sequencing has made it possible to accurately decipher the entire genetic complement of a probiotic bacterium. Increases in sequencing capabilities have been enhanced through improved computer software that can annotate, or identify, the majority of genes encoded by the sequence. The availability of annotated genome sequence will be important in defining the capabilities of the individual strains of probiotic bacteria. It will also form the platform for microarray and proteomic technologies that allow real-time analysis of RNA and protein expression in the bacterial cell. Investigation of probiotic organisms with these new and potentially powerful tools will facilitate the development of the bacteria as therapeutic agents, and provide the mechanisms to produce advanced probiotic strains. This paper addresses the core technologies in the rapidly growing area of genomics, and their application to the molecular characterisation of probiotic bacteria and host-microbe interactions.

Databases, Genetic↗
PubMed2006

Genomewide screens for Escherichia coli genes affecting growth of T7 bacteriophage.

Use of bacteriophages as a therapy for bacterial infection has been attempted over the last century. Such an endeavor requires the elucidation of basic aspects of the host-virus interactions and the resistance mechanisms of the host. Two recently developed bacterial collections now enable a genomewide search of the genetic interactions between Escherichia coli and bacteriophages. We have screened >85% of the E. coli genes for their ability to inhibit growth of T7 phage and >90% of the host genes for their ability to be used by the virus. In addition to identifying all of the known interactions, several other interactions have been identified. E. coli CMP kinase is essential for T7 growth, whereas overexpression of the E. coli uridine/cytidine kinase inhibits T7 growth. Mutations in any one of nine genes that encode enzymes for the synthesis of the E. coli lipopolysaccharide receptor for T7 adsorption leads to T7 resistance. Selection of T7 phage that can recognize these altered receptors has enabled the construction of phage to which the host is 100-fold less resistant.

Bacteriophage T7↗
PubMed2004

Development and implementation of a database system to manage a large-scale mouse ENU-mutagenesis program.

A mouse ENU-mutagenesis program at RIKEN GSC has been initiated to conduct a large-scale, genome-wide, early- and late-onset phenotypic screen of mutant mice. We screened about a hundred mice every week with a comprehensive set of phenotype assays including behavioral tests based on a modified SHIRPA protocol, blood tests (both clinical biochemical testing and hemogram), and measurement of locomotor activity in their home cages. To manage the entire program, we developed a client/server architecture database system and named it MUSDB (Mutagenesis Universal Support DataBase). It manages mouse husbandry, mating protocols, procedures for ENU injection and phenotypic screens, phenotype inheritance tests, preservation of sperm and organs, and other materials generated during the program. We have implemented MUSDB in quite a large-scale system that includes 150 client computers. It has, helped reduce typographical errors and provided simple and efficient operation via its front-end user interface. It significantly contributed to the communication within and between workgroups in the program and in the accumulation of various phenotypic and inheritance data.

Animals↗
PubMed2003

Genomic distribution and characterization of EST-derived resistance gene analogs (RGAs) in sugarcane.

A large sugarcane EST (expressed sequence tag) project recently gave us access to 261,609 EST sequences from sugarcane, assembled into 81,223 clusters. Among these, we identified 88 resistance gene analogs (RGAs) based on their homology to typical pathogen resistance genes, using a stringent BLAST search with a threshold e-value of e(-50). They included representatives of the three major groups of resistance genes with NBS/LRR, LRR or S/T KINASE domains. Fifty RGAs showed a total of 148 single-dose polymorphic RFLP markers, which could be located on the sugarcane reference genetic map (constructed in cultivar R570, 2n=approximately 115). Fifty-five SSR loci corresponding to 134 markers in R570 were also mapped to enable the classification of the various haplotypes into homology groups. Several RGA clusters were found. One cluster of two LRR-like loci mapped close to the only disease resistance gene known so far in sugarcane, which confers resistance to common rust. Detailed sequence comparison between two NBS/LRR RGA clusters in relation to their orthologs in rice and maize suggests their polyphyletic origins, and indicates that the degree of divergence between paralogous RGAs in sugarcane can be larger than that from an ortholog in a distant species.

Amino Acid Sequence↗
PubMed2025

Oncopacket: integration of cancer research data using GA4GH phenopackets.

SUMMARY: Lack of data integration remains a significant impediment to cancer research, and many analyses still require customized software to transform and prepare cancer data. We describe a software package to harmonize genetic and clinical cancer data into the GA4GH Phenopacket schema, an ISO standard for representing clinical case data. We integrated demographic, mutation, morphology, diagnosis, intervention, and survival data using case data from the National Cancer Institute for 12 cancer types. The Phenopacket standard provides a foundation for downstream use, including sophisticated statistical and AI/ML analyses. We demonstrate fitness for purpose by using the integrated data to recapitulate a known association between mutations in the gene encoding isocitrate dehydrogenase 1 and survival time in brain cancer patients. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at: https://github.com/monarch-initiative/oncopacket (archived at 10.5281/zenodo.15353125).

Humans↗