• Korean Journal of Biological Psychiatry
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• v.17 no.2
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• pp.65-69
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• 2010

Gene-environment interactions are important in pathogenesis of suicide or suicidal behavior. Twin and adoption studies and family studies show that genetic factors play a critical role in suicide or suicidal behavior. Given the strong association between serotonergic neurotransmission and suicide, recent molecular genetic studies have focused on polymorphisms of serotonin genes, especially on serotonin transporter and tryptophan hydroxylase genes. Some studies have revealed a significant interaction between s allele of the serotonin transporter gene and the risk of suicide attempt associated with childhood trauma. In addition, the polymorphism of brain-derived neurotrophic factor gene also may influence the effect of childhood trauma in relation to the risk of attempting suicide. Future studies should explore genetic and environmental factors in suicide or suicidal behavior and examine for gene and environment interaction.

• Genomics & Informatics
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• v.14 no.4
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

• Communications for Statistical Applications and Methods
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• v.17 no.5
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• pp.667-678
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• 2010

It is important to detect the gene-gene interaction in GWAS(Genome-Wide Association Study). There are many studies about detecting gene-gene interaction. The one is Multifactor dimensionality reduction method. But MDR method is not applied continuous data and expanded multifactor dimensionality reduction(E-MDR) method is suggested. The goal of this study is to evaluate the power of E-MDR for identifying gene-gene interaction by simulation. Also we applied the method on the identify interaction e ects of single nucleotid polymorphisms(SNPs) responsible for economic traits in a Korean cattle population (real data).

• The Plant Pathology Journal
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• v.24 no.4
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• pp.384-391
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• 2008

Rice blast disease, caused by the pathogenic fungus Magnaporthe grisea, is a serious issue in rice (Oryza sativa L.) growing regions of the world. Transcript profiling in rice inoculated with the fungus has been investigated using the transcriptomics technology, serial analysis of gene expression (SAGE). Short sequence tags containing sufficient information which are ten base-pairs representing the unique transcripts were identified by SAGE technology. We identified a total of 910 tag sequences via the GenBank database, and the resulting genes were shown to be up-regulated in all functional categories under the fungal biotic stress. Compared to the compatible interaction, the stress and defense genes in the incompatible interaction appear to be more up-regulated. Particularly, thaumatin-like gene (TLP) was investigated in determining the gene and protein expression level utilizing Northern and Western blotting analyses, resulting in an increase in both the gene and the protein expression level which arose earlier in the incompatible interaction than in the compatible interaction.

• Genomics & Informatics
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• v.16 no.4
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• pp.37.1-37.3
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• 2018

Gene-gene interaction is a key factor for explaining missing heritability. Many methods have been proposed to identify gene-gene interactions. Multifactor dimensionality reduction (MDR) is a well-known method for the detection of gene-gene interactions by reduction from genotypes of single-nucleotide polymorphism combinations to a binary variable with a value of high risk or low risk. This method has been widely expanded to own a specific objective. Among those expansions, fuzzy-MDR uses the fuzzy set theory for the membership of high risk or low risk and increases the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as a new membership function in empirical fuzzy MDR (EFMDR). However, EFMDR is relatively slow, because it is implemented by R script language. Therefore, in this study, we implemented EFMDR using RCPP ($c^{{+}{+}}$ package) for faster executions. Our implementation for faster EFMDR, called EMMDR-Fast, is about 800 times faster than EFMDR written by R script only.

• Genomics & Informatics
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• v.13 no.2
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• pp.45-52
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• 2015

Acute myeloid leukemia is a well characterized blood cancer in which the unnatural growth of immature white blood cell takes place, where several genes transcription is regulated by the micro RNAs (miRNAs). Argonaute (AGO) protein is a protein family that binds to the miRNAs and mRNA complex where a strong binding affinity is crucial for its RNA silencing function. By understanding pattern recognition between the miRNAs-mRNA complex and its binding affinity with AGO protein, one can decipher the regulation of a particular gene and develop suitable siRNA for the same in disease condition. In the current work, HOXA9 gene has been selected from literature, whose deregulation is well-established in acute myeloid leukemia. Four miRNAs (mir-145, mir-126, let-7a, and mir-196b) have been selected to target mRNA of HOXA9 (NCBI accession No. NM_152739.3). The binding interaction between mRNAs and mRNA of HOXA9 gene was studied computationally. From result, it was observed mir-145 has highest affinity for HOXA9 gene. Furthermore, the interaction between miRNAs-mRNA duplex of all chosen miRNAs are docked with AGO protein (PDB ID: 3F73, chain A) to study their interaction at molecular level through an in silico approach. The residual interaction and hydrogen bonding are inspected in Discovery Studio 3.5 suites. The current investigation throws light on understanding of AGO-assisted miRNA based gene silencing mechanism in HOXA9 gene associated in acute myeloid leukemia computationally.

• BMB Reports
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• v.47 no.2
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• pp.92-97
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• 2014

We have examined the effect of bithorax complex genes on the expression of castor gene. During the embryonic stages 12-15, both Ultrabithorax and abdominal-A regulated the castor gene expression negatively, whereas Abdominal-B showed a positive correlation with the castor gene expression according to real-time PCR. To investigate whether ABD-B protein directly interacts with the castor gene, electrophoretic mobility shift assays were performed using the recombinant ABD-B homeodomain and oligonucleotides, which are located within the region 10 kb upstream of the castor gene. The results show that ABD-B protein directly binds to the castor gene specifically. ABD-B binds more strongly to oligonucleotides containing two 5'-TTAT-3' canonical core motifs than the probe containing the 5'-TTAC-3' motif. In addition, the sequences flanking the core motif are also involved in the protein-DNA interaction. The results demonstrate the importance of HD for direct binding to target sequences to regulate the expression level of the target genes.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.693-703
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• 2010

Diseases of human or economical traits of cattles are occured by interaction of genes. We introduce expanded multifactor dimensionality reduction(E-MDR), dummy multifactor dimensionality reduction(D-MDR) and SNPHarvester which are developed to find interaction of genes. We will select interaction of outstanding gene combinations and select final best genotype groups.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.360-370
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• 2009

Genetic factors clearly play a role in carcinogenesis, but migrant studies provide unequivocal evidence that environmental factors are critical in defining cancer risk. Therefore, one may expect that the lower availability of substrate for biochemical reactions leads to more genetic changes in enzyme function; for example, most studies have indicated the variant MTHFR genotype 677TT is related to biomarkers, such as homocysteine concentrations or global DNA methylation particularly in a low folate diet. The modification of a phenotype related to a genotype, particularly by dietary habits, could support the notion that some of inconsistencies in findings from molecular epidemiologic studies could be due to differences in the populations studied and unaccounted underlying characteristics mediating the relationship between genetic polymorphisms and the actual phenotypes. Given the evidence that diet can modify cancer risk, gene-diet interactions in cancer etiology would be anticipated. However, much of the evidence in this area comes from observational epidemiology, which limits the causal inference. Thus, the investigation of these interactions is essential to gain a full understanding of the impact of genetic variation on health outcomes. This report reviews current approaches to gene-diet interactions in epidemiological studies. Characteristics of gene and dietary factors are divided into four categories: one carbon metabolism-related gene polymorphisms and dietary factors including folate, vitamin B group and methionines; oxidative stress-related gene polymorphisms and antioxidant nutrients including vegetable and fruit intake; carcinogen-metabolizing gene polymorphisms and meat intake including heterocyclic amins and polycyclic aromatic hydrocarbon; and other gene-diet interactive effect on cancer.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.467-474
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• 2012

Human diseases and livestock economic traits are not typically the result of variation of a single genetic locus, but are rather the result of interplay between interactions among multiple genes and a variety of environmental exposures. We have used linear regression model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. Of course, we use 5 SNPs (single uncleotide polymorphism) which were studied recently by Oh et al. (2011). We apply the MDR (multifactor demensionality reduction) method on the identify major interaction effects of single nucleotide polymorphisms responsible for economic traits in a Korean cattle population.