Myungguen Chung

ZIFIBI: Prediction of DNA binding sites for zinc finger proteins

The cis-regulatory region of target genes is key elements in the transcriptional regulation of gene expression. Many of these cis-regulatory regions have not been identified by either biological experiments or computational methods. Recently, a few additional C(2)H(2) zinc finger transcription factor binding sites have been discovered. The majority of the zinc finger binding sites, however, are still unknown. In this study, we used publically available data to evaluate possible interaction patterns between nucleotides and the amino acids of zinc finger domains. We calculated the most probable state path of three nucleotides sequences using a Hidden Markov Model (HMM). We used these computations to predict C(2)H(2) zinc finger transcription factor binding sites in cis-regulatory regions of their target genes (http://bioinfo.hanyang.ac.kr/ZIFIBI/frameset.php).

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.

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

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.

Construction of a Transcriptome-Driven Network at the Early Stage of Infection with Influenza A H1N1 in Human Lung Alveolar Epithelial Cells

We aimed to understand the molecular changes in host cells that accompany infection by the seasonal influenza A H1N1 virus because the initial response rapidly changes owing to the fact that the virus has a robust initial propagation phase. Human epithelial alveolar A549 cells were infected and total RNA was extracted at 30 min, 1 h, 2 h, 4 h, 8 h, 24 h, and 48 h post infection (h.p.i.). The differentially expressed host genes were clustered into two distinct sets of genes as the infection progressed over time. The patterns of expression were significantly different at the early stages of infection. One of the responses showed roles similar to those associated with the enrichment gene sets to known ‘gp120 pathway in HIV.’ This gene set contains genes known to play roles in preventing the progress of apoptosis, which infected cells undergo as a response to viral infection. The other gene set showed enrichment of ‘Drug Metabolism Enzymes (DMEs).’ The identification of two distinct gene sets indicates that the virus regulates the cell’s mechanisms to create a favorable environment for its stable replication and protection of gene metabolites within 8 h.

Genome-wide association study of biochemical traits based on eQTL-SNPs in Korean

Summary form only given. Most of genome-wide association studies consider genes that are located closest to single nucleotide polymorphisms (SNPs) that are highly significant association loci; however, the significance of the associations between SNPs and candidate genes has not been fully determined. Fortunately, recent achievements of ENCODE project provide the information of genomewide functional variants (i.e. RegulomeDB websites) such as expression quantitative trait loci (eQTL-SNPs). 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 study subjects (n=8,842) were previously reported in the KARE consortium and were tested the associations between eQTL-SNPs (n=24,235) and 10 biochemical measures (fasting glucose levels, BUN, serum albumin levels, AST, ALT, gamma GTP, total cholesterol, HDL cholesterol, triglycerides, and LDL cholesterol) by linear regression analysis. As results, we identified that a total of 17 eQTL-SNPs were significantly associated with the biochemical traits after the multiple comparison p-values adjusted by Bonferroni correction. The each alternative allele of the 17 eQTL-SNPs is likely to correlate with one of the following gene expression changes in more than one tissue or cell lines: B3GALT4, CPSF7, NRG3, MYL2, FAM169A. Conclusively, we could identify the functionally linked genes in expression levels the biochemical traits, and those eQTL-SNPs discovered from GWAS analysis might be applied to other genome-wide association studies.

A case-control genome-wide association study of metabolic syndrome in Korean

Metabolic syndrome (METS) constitutes several metabolic disorders including central obesity, dyslipidemia, glucose intolerances, and elevated blood pressure. METS is known to increase the risk of developing cardiovascular disease and diabetes. Genome-wide association study (GWAS) for 2,657 cases and 5,917 controls in Korean populations was performed to discover the genetic risk factors of METS. As a result, we identified 2 SNPs with genome-wide significance level p-values(<;5×10-8), 8SNPs with genome-wide suggestive p-values (5×10-8≤p-values<;1×10-5), and 2SNPs of more functional variants with borderline p-values (5×10-5≤p-values<;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 5000 SNPs based on the proportion of phenotypic variance explained by genotypic variance. In total, 159 eQTLs and 18 nsSNPs were presented in the top 5000 SNPs. Although they should be replicated in other independent populations, 6eQTLs and 2nsSNP 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 genome-wide association studies.

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

BackgroundA number of alignment tools have been developed to align sequencing reads to the human reference genome. The scale of information from next-generation sequencing (NGS) experiments, however, is increasing rapidly. Recent studies based on NGS technology have routinely produced exome or whole-genome sequences from several hundreds or thousands of samples. To accommodate the increasing need of analyzing very large NGS data sets, it is necessary to develop faster, more sensitive and accurate mapping tools.ResultsHIA uses two indices, a hash table index and a suffix array index. The hash table performs direct lookup of a q-gram, and the suffix array performs very fast lookup of variable-length strings by exploiting binary search. We observed that combining hash table and suffix array (hybrid index) is much faster than the suffix array method for finding a substring in the reference sequence. Here, we defined the matching region (MR) is a longest common substring between a reference and a read. And, we also defined the candidate alignment regions (CARs) as a list of MRs that is close to each other. The hybrid index is used to find candidate alignment regions (CARs) between a reference and a read. We found that aligning only the unmatched regions in the CAR is much faster than aligning the whole CAR. In benchmark analysis, HIA outperformed in mapping speed compared with the other aligners, without significant loss of mapping accuracy.ConclusionsOur experiments show that the hybrid of hash table and suffix array is useful in terms of speed for mapping NGS sequencing reads to the human reference genome sequence. In conclusion, our tool is appropriate for aligning massive data sets generated by NGS sequencing.

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.

AKAPDB: A-Kinase Anchoring Proteins Database

Abstract A-kinase-anchoring proteins (AKAPs) are scaffold pro-teins which compartmentalize protein kinase A (PKA, cAMP-dependent protein kinase) and other enzymes to specific subcellular sites. The spatiotemporal control of these enzymes by AKAPs is important for cellular func-tion like cell growth and development etc. Hence, it is important to understand the basic function of AKAPs and their functional domains. However, diverse names, function, cellular localizations and many members of AKAPs increase difficulties when researchers search ap-propriate AKAPs for their experimental purpose. Nevertheless, there was no previous AKAPs-related da-tabase regardless of their important cellular functions and difficulty of finding appropriate AKAPs. So, we de-veloped AKAPs database (AKAPDB), which contains their sequence information, functions and other in-formation derived from prediction programs and other databases. Therefore, we propose that AKAPDB can be an important tool to researchers in the related fields. AKAPDB is available via the internet at http://pla-za3.snu.ac.kr/akapdb/ Keywords: a-kinase anchoring protein, database

Image Preprocessing for cDNA Microarray Using Deconvolution Method

The image of cDNA microarray does not print actual intensity value because cDNA microarray methods are one of the methods using fluorescence dye. In scanning process for detecting emission of fluorescence light, the intensity of Cy3 (RED) and Cy5 (GREEN) are not identical in same conditions. We know that experiment for detecting emission of fluorescence light have several faults in itself. All of experiment using fluorescence detection have same problem. In actually, the function which calculates intensity for fluorescence light is not linear function but sigmoid function. Sigmoid function is mistaken in high or low level intensity. In this phenomenon is occurred by the character of PMT tube. If we take a detail information about above sigmoid function, we can do reverse trace step for recalculation original intensity. It is called ‘Deconvolution’. Then, Deconvolution method can apply several image processing step, recalculation original intensity step and dye-swap problem.