Genetic Loci ; Humans ; Obesity ; genetics

No abstract available.
Genetic Loci* ; Loss of Heterozygosity* ; Stomach Neoplasms*

Overwhelming evidences supports the idea that inflammatory bowel disease (IBD) is caused by a complex interplay between genetic alterations of multiple genes and an aberrant interaction with environmental factors. There is growing evidence that epigenetic factors can play a significant part in the pathogenesis of IBD. Significant effort has been invested in uncovering genetic and epigenetic factors, which may increase the risk of IBD, but progress has been slow, and few IBD-specific factors have been detected so far. It has been known for decades that DNA methylation is the most well studied epigenetic modification, and analysis of DNA methylation is leading to a new generation of cancer biomarkers. Therefore, in this review, we summarize the role of DNA methylation alteration in IBD pathogenesis, and discuss specific genes or genetic loci using recent molecular technology advances. Here, we suggest that DNA methylation should be studied in depth to understand the molecular pathways of IBD pathogenesis, and discuss epigenetic studies of IBD that may have a significant impact on the field of IBD research.
Biomarkers ; DNA Methylation ; Epigenomics* ; Genetic Loci ; Inflammatory Bowel Diseases*

Overwhelming evidences supports the idea that inflammatory bowel disease (IBD) is caused by a complex interplay between genetic alterations of multiple genes and an aberrant interaction with environmental factors. There is growing evidence that epigenetic factors can play a significant part in the pathogenesis of IBD. Significant effort has been invested in uncovering genetic and epigenetic factors, which may increase the risk of IBD, but progress has been slow, and few IBD-specific factors have been detected so far. It has been known for decades that DNA methylation is the most well studied epigenetic modification, and analysis of DNA methylation is leading to a new generation of cancer biomarkers. Therefore, in this review, we summarize the role of DNA methylation alteration in IBD pathogenesis, and discuss specific genes or genetic loci using recent molecular technology advances. Here, we suggest that DNA methylation should be studied in depth to understand the molecular pathways of IBD pathogenesis, and discuss epigenetic studies of IBD that may have a significant impact on the field of IBD research.
Biomarkers ; DNA Methylation ; Epigenomics* ; Genetic Loci ; Inflammatory Bowel Diseases*

The imputation of untyped SNPs enables researchers to validate association findings across SNP arrays and also enables them to test a large number of SNPs to reveal the fine structure of the association peak, facilitating interpretation of the results and the location of causal polymorphisms. In this study, we applied the imputation method to a genomewide association study and recapitulated the previously associated gene loci of blood pressure traits in Korean cohorts. A total of 1,827,004 SNPs were imputed by the IMPUTE program, and we conducted a genomewide association study for systolic and diastolic blood pressure. While no SNPs passed the Bonferroni correction p-value (p=2.74x10-8 for 1,827,004 SNPs), 12 novel loci for systolic blood pressure and 16 novel loci for diastolic blood pressure were detected by imputed SNPs, with 10-5genetic loci that were previously reported revealed that the imputed SNPs had lower p-values than those of genotyped SNPs. Moreover, a nonsynonymous SNP in the CSMD1 gene, one of the 14 genes, was found to be associated with systolic blood pressure (p<0.05). These results suggest that the imputation method can facilitate the discovery of novel SNPs as well as enhance the fine structure of the association peak in the loci.
Blood Pressure ; Cohort Studies ; Genetic Loci ; Polymorphism, Single Nucleotide

OBJECTIVETo evaluate the effect and profitability of using the quantitative trait loci (QTL)-linked direct marker (DR marker) in gene-assisted selection (GAS).

METHODSThree populations (100, 200, or 300 sows plus 10 boars within each group) with segregating QTL were simulated stochastically. Five economic traits were investigated, including number of born alive (NBA), average daily gain to 100 kg body weight (ADG), feed conversion ratio (FCR), back fat at 100 kg body weight (BF) and intramuscular fat (IMF). Selection was based on the estimated breeding value (EBV) of each trait. The starting frequencies of the QTL's favorable allele were 0.1, 0.3 and 0.5, respectively. The economic return was calculated by gene flow method.

RESULTSThe selection efficiency was higher than 100% when DR markers were used in GAS for 5 traits. The selection efficiency for NBA was the highest, and the lowest was for ADG whose QTL had the lowest variance. The mixed model applied DR markers and obtained higher extra genetic gain and extra economic returns. We also found that the lower the frequency of the favorable allele of the QTL, the higher the extra return obtained.

CONCLUSIONGAS is an effective selection scheme to increase the genetic gain and the economic returns in pig breeding.

Autism spectrum disorder (ASD) is one of the most complex behavioral disorders with a strong genetic influence. The objectives of this article are to review the current status of genetic research in ASD, and to provide information regarding the potential candidate genes, mutations, and genetic loci possibly related to pathogenesis in ASD. Investigations on monogenic causes of ASD, candidate genes among common variants, rare de novo mutations, and copy number variations are reviewed. The current possible clinical applications of the genetic knowledge and their future possibilities are highlighted.
Autistic Disorder* ; Child ; Autism Spectrum Disorder* ; Genetic Loci ; Genetic Research ; Genetics*

Quantitative trait loci (QTL) and their additive, dominance and epistatic effects play a critical role in complex trait variation. It is often infeasible to detect multiple interacting QTL due to main effects often being confounded by interaction effects. Positioning interacting QTL within a small region is even more difficult. We present a variance component approach nested in an empirical Bayesian method, which simultaneously takes into account additive, dominance and epistatic effects due to multiple interacting QTL. The covariance structure used in the variance component approach is based on combined linkage disequilibrium and linkage (LDL) information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously fine map interacting QTL using the proposed approach. The present method combined with LDL information can efficiently detect QTL and their dominance and epistatic effects, making it possible to simultaneously fine map main and epistatic QTL.
Chromosome Mapping ; Epistasis, Genetic ; Genetic Linkage ; Humans ; Linkage Disequilibrium ; Monte Carlo Method ; Quantitative Trait Loci ; genetics

OBJECTIVE: To investigate the statistical method of tri-allelic patterns of STR loci. METHODS: The DNAs of venous blood and blood stain samples from 8,846 unrelated individuals were extracted using magnetic bead method, and STR genotypes were determined by multiplex fluorescent amplification and capillary electrophoresis and analyzed using GeneMapper ID v3.2 software. The genotype frequency and allele frequency of trizonal were determined by direct counting and formula, respectively, in order to deduce the formula of trizonal in paternity test and individual recognition. RESULTS: Of the 8,846 individuals, four tri-alleles and three tri-genotypes were detected. The multiplying of allele frequency and actual rate showed significantly statistical difference. The formula of trizonal in paternity test and individual recognition was successfully deduced. CONCLUSION The frequency of the two alleles inherited as a whole in the population could be calculated by multiplying the frequencies of each allele in the tri-allelic patterns.
Alleles ; Gene Frequency ; Genetic Loci ; Genetics, Population ; Genotype ; Humans ; Microsatellite Repeats ; Polymorphism, Genetic

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome- wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.
Computer Simulation ; Data Mining ; Databases, Genetic ; Gene Regulatory Networks ; Genes, rel ; Genetic Loci ; Genetic Research ; Humans ; Polymorphism, Single Nucleotide ; Stroke