Detect of Novel Alternative Form at Development Stages in Brain

this paper, we use the development information of ESTs to detect novel alternative form in Brain. We explain the expression pattern of gene for each development stage. Moreover, we expect that specific splice variants are associated with mouse disease of brain specifi

Replication of Interactions between Genome-Wide Genetic Variants and Body Mass Index in Fasting Glucose and Insulin Levels

The genetic regulation of glucose and insulin levels might be modified by adiposity. With regard to the genetic factors that are altered by adiposity, a large meta-analysis on the interactions between genetic variants and body mass index with regard to fasting glucose and insulin levels was reported by the Meta-Analyses of Glucose- and Insulin-related trait Consortium (MAGIC), based on European ancestry. Because no replication study has been performed in other ethnic groups, we first examined the link between reported single-nucleotide polymorphisms (SNPs) and fasting glucose and insulin levels in a large Korean cohort (Korean Genome and Epidemiology Study cohort [KoGES], n = 5,814). The MAGIC study reported 7 novel SNPs for fasting glucose levels and 6 novel SNPs for fasting insulin levels. In this study, we attempted to replicate the association of 5 SNPs with fasting glucose levels and 5 SNPs with fasting insulin levels. One SNP (rs2293941) in PDX1 was identified as a significant obesity-modifiable factor in Koreans. Our results indicate that the novel loci that were identified by MAGIC are poorly replicated in other ethnic groups, although we do not know why

MOESM1 of HIA: a genome mapper using hybrid index-based sequence alignment

Additional file 1. It includes the test datasets, all tested results, and information of all used tools

Genome-Wide Association Study of Metabolic Syndrome in Koreans

Metabolic syndrome (METS) is a disorder of energy utilization and storage and increases the risk of developing cardiovascular disease and diabetes. To identify the genetic risk factors of METS, we carried out a genome-wide association study (GWAS) for 2,657 cases and 5,917 controls in Korean populations. As a result, we could identify 2 single nucleotide polymorphisms (SNPs) with genome-wide significance level p-values (<5 × 10-8), 8 SNPs with genome-wide suggestive p-values (5 × 10-8 ≤ p < 1 × 10-5), and 2 SNPs of more functional variants with borderline p-values (5 × 10-5 ≤ p < 1 × 10-4). On the other hand, the multiple correction criteria of conventional GWASs exclude false-positive loci, but simultaneously, they discard many true-positive loci. To reconsider the discarded true-positive loci, we attempted to include the functional variants (nonsynonymous SNPs [nsSNPs] and expression quantitative trait loci [eQTL]) among the top 5,000 SNPs based on the proportion of phenotypic variance explained by genotypic variance. In total, 159 eQTLs and 18 nsSNPs were presented in the top 5,000 SNPs. Although they should be replicated in other independent populations, 6 eQTLs and 2 nsSNP loci were located in the molecular pathways of LPL, APOA5, and CHRM2, which were the significant or suggestive loci in the METS GWAS. Conclusively, our approach using the conventional GWAS, reconsidering functional variants and pathway-based interpretation, suggests a useful method to understand the GWAS results of complex traits and can be expanded in other genomewide association studies

MOESM2 of HIA: a genome mapper using hybrid index-based sequence alignment

Additional file 2. It contains the jar file of HIA. HIA can be used without restriction

Association between Expression Quantitative Trait Loci and Metabolic Traits in Two Korean Populations

<div><p>Most genome-wide association studies consider genes that are located closest to single nucleotide polymorphisms (SNPs) that are highly significant for those studies. However, the significance of the associations between SNPs and candidate genes has not been fully determined. An alternative approach that used SNPs in expression quantitative trait loci (eQTL) was reported previously for Crohn’s disease; it was shown that eQTL-based preselection for follow-up studies was a useful approach for identifying risk loci from the results of moderately sized GWAS. In this study, we propose an approach that uses eQTL SNPs to support the functional relationships between an SNP and a candidate gene in a genome-wide association study. The genome-wide SNP genotypes and 10 biochemical measures (fasting glucose levels, BUN, serum albumin levels, AST, ALT, gamma GTP, total cholesterol, HDL cholesterol, triglycerides, and LDL cholesterol) were obtained from the Korean Association Resource (KARE) consortium. The eQTL SNPs were isolated from the SNP dataset based on the RegulomeDB eQTL-SNP data from the ENCODE projects and two recent eQTL reports. A total of 25,658 eQTL SNPs were tested for their association with the 10 metabolic traits in 2 Korean populations (Ansung and Ansan). The proportion of phenotypic variance explained by eQTL and non-eQTL SNPs showed that eQTL SNPs were more likely to be associated with the metabolic traits genetically compared with non-eQTL SNPs. Finally, via a meta-analysis of the two Korean populations, we identified 14 eQTL SNPs that were significantly associated with metabolic traits. These results suggest that our approach can be expanded to other genome-wide association studies.</p></div

In silico annotation of eQTLs.

<p>Note. CHR: chromosome, BP: base position based on the human genome (NCBI36/hg18), SNP: single-nucleotide polymorphism, eQTL: expression quantitative trait loci, TF: Transcription factor binding in liver or pancreas cells, DHS: DNase1 Hypersensitive site in liver or pancreas cells.</p><p>In silico annotation of eQTLs.</p

Clinical characteristics of the Ansung and Ansan cohorts and the exclusion criteria for each biochemical trait.

<p>Clinical characteristics of the Ansung and Ansan cohorts and the exclusion criteria for each biochemical trait.</p

Significantly associated SNPs in the Ansung and Ansan cohorts and meta-analysis results.

<p>Note. CHR: chromosome, SNP: single-nucleotide polymorphism, BP: base position based on the human genome (NCBI36/hg18), A1: minor allele, MAF: minor allele frequency, Beta: effect size, SE: standard error, FDR: adjusted p-value by false discovery rate, BONF: adjusted p-value by bonferroni correction.</p><p>Significantly associated SNPs in the Ansung and Ansan cohorts and meta-analysis results.</p

Estimated genetic variance explained by eQTL SNPs and non-eQTL SNPs.

<p>Note. H2: previously reported heritability of the trait, Vg: estimated genetic variance, Vp: estimated phenotypic variance, Vg/Vp: percent of estimated genetic variance explained by SNPs for each trait.</p><p>Estimated genetic variance explained by eQTL SNPs and non-eQTL SNPs.</p