• Molecules and Cells
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• 제39권5호
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• pp.395-402
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• 2016

Identifying Hoxc8 target genes is at the crux of understanding the Hoxc8-mediated regulatory networks underlying its roles during development. However, identification of these genes remains difficult due to intrinsic factors of Hoxc8, such as low DNA binding specificity, context-dependent regulation, and unknown cofactors. Therefore, as an alternative, the present study attempted to test whether the roles of Hoxc8 could be inferred by simply analyzing genes frequently coexpressed with Hoxc8, and whether these genes include putative target genes. Using archived gene expression datasets in which Hoxc8 was differentially expressed, we identified a total of 567 genes that were positively coexpressed with Hoxc8 in at least four out of eight datasets. Among these, 23 genes were coexpressed in six datasets. Gene sets associated with extracellular matrix and cell adhesion were most significantly enriched, followed by gene sets for skeletal system development, morphogenesis, cell motility, and transcriptional regulation. In particular, transcriptional regulators, including paralogs of Hoxc8, known Hox co-factors, and transcriptional remodeling factors were enriched. We randomly selected Adam19, Ptpn13, Prkd1, Tgfbi, and Aldh1a3, and validated their coexpression in mouse embryonic tissues and cell lines following $TGF-{\beta}2$ treatment or ectopic Hoxc8 expression. Except for Aldh1a3, all genes showed concordant expression with that of Hoxc8, suggesting that the coexpressed genes might include direct or indirect target genes. Collectively, we suggest that the coexpressed genes provide a resource for constructing Hoxc8-mediated regulatory networks.

• IMMUNE NETWORK
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• 제11권3호
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• pp.135-154
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• 2011

The great discovery of microRNAs (miRNAs) has revolutionized current cell biology and medical science. miRNAs are small conserved non-coding RNA molecules that post-transcriptionally regulate gene expression by targeting the 3' untranslated region of specific messenger RNAs for degradation or translational repression. New members of the miRNA family are being discovered on a daily basis and emerging evidence has demonstrated that miRNAs play a major role in a wide range of developmental process including cell proliferation, cell cycle, cell differentiation, metabolism, apoptosis, developmental timing, neuronal cell fate, neuronal gene expression, brain morphogenesis, muscle differentiation and stem cell division. Moreover, a large number of studies have reported links between alterations of miRNA homeostasis and pathological conditions such as cancer, psychiatric and neurological diseases, cardiovascular disease, and autoimmune disease. Interestingly, in addition, miRNA deficiencies or excesses have been correlated with a number of clinically important diseases ranging from cancer to myocardial infarction. miRNAs can repress the gene translation of hundreds of their targets and are therefore well-positioned to target a multitude of cellular mechanisms. As a consequence of extensive participation in normal functions, it is quite logical to ask the question if abnormalities in miRNAs should have importance in human diseases. Great discoveries and rapid progress in the past few years on miRNAs provide the hope that miRNAs will in the near future have a great potential in the diagnosis and treatment of many diseases. Currently, an explosive literature has focussed on the role of miRNA in human cancer and cardiovascular disease. In this review, I briefly summarize the explosive current studies about involvement of miRNA in various human cancers and cardiovascular disease.

• 한국정보과학회논문지:시스템및이론
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• 제36권2호
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• pp.60-67
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• 2009

단백질 상호작용 네트워크는 어떤 단백질들 간에 상호 작용 관계가 있는지를 네트워크 형태로 나타낸 것이며 단백질 상호작용을 발견하거나 분석하는 것은 생명 공학에서 중요한 연구분야이다. 본 논문에서는 방대한 단백질 상호작용 데이터를 유전자 온톨로지와 연계한 시각화를 통하여 효과적으로 직관을 얻을 수 있는 효율적인 단백질 상호작용 네트워크 분석시스템을 다룬다. 단백질 상호작용 네트워크는 데이터 양이 매우 방대하기 때문에 이를 효율적으로 분석하는 방법과 효과적인 시각화 기법이 요구된다. 본 연구에서는 이를 위하여 동적이고 상호작용 가능한 그래프와 관심 노드와 그 주변 노드를 표시하며 점진적으로 탐색할 수 있는 컨텍스트 기반 탐색 기법을 도입하였다. 이 밖에도 특화된 기능으로써 단백질 상호작용과 유전자 온톨로지 간의 빠르고 자유로운 상호참조 기능과 최소 공통 조상을 사용한 유전자 온톨로지 분석 기능 등을 지원한다. 인터페이스 측면에서는 상호참조 기능을 효과적으로 사용하게 하기 위하여 유전자 온톨로지 그래프와 단백질 상호작용의 시각화 결과를 2차원 윈도우로 나란히 보여주는 인터페이스를 디자인 하였다.

• Journal of Periodontal and Implant Science
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• 제50권5호
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• pp.313-326
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• 2020

Purpose: This study was conducted to analyze specific RNA expression profiles in gingival tissue and saliva samples in periodontitis patients and healthy individuals, and to determine their correlations in light of the potential use of microarray-based analyses of saliva samples as a periodontal monitoring tool. Methods: Gingival tissue biopsies and saliva samples from 22 patients (12 with severe periodontitis and 10 with a healthy periodontium) were analyzed using transcriptomic microarray analysis. Differential gene expression was assessed, and pathway and clustering analyses were conducted for the samples. The correlations between the results for the gingival tissue and saliva samples were analyzed at both the gene and pathway levels. Results: There were 621 differentially expressed genes (DEGs; 320 upregulated and 301 downregulated) in the gingival tissue samples of the periodontitis group, and 154 DEGs (44 upregulated and 110 downregulated) in the saliva samples. Nine of these genes overlapped between the sample types. The periodontitis patients formed a distinct cluster group based on gene expression profiles for both the tissue and saliva samples. Database for Annotation, Visualization and Integrated Discovery analysis revealed 159 enriched pathways from the tissue samples of the periodontitis patients, as well as 110 enriched pathways In the saliva samples. Thirty-four pathways overlapped between the sample types. Conclusions: The present results indicate the possibility of using the salivary transcriptome to distinguish periodontitis patients from healthy individuals. Further work is required to enhance the extraction of available RNA from saliva samples.

• Toxicological Research
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• 제26권1호
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• pp.21-28
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• 2010

As the frequency and the intensity of so called Asian dust (AD) events have increased, public concerns about the adverse health effects has spiked sharply over the last two decades. Despite the recent reports on the correlation between AD events and the risk for cardiovascular and respiratory disease, the nature of the toxicity and the degree of the risk are yet largely unknown. In the present study, we investigated the effects of the dichloromethane extract of AD (AD-X) and that of urban dust (NAD-X) collected during a non-AD period on gene expression in HL-60 cells using Illumina Sentrix HumanRef-8 Expression BeadChips. Global changes in gene expression were analyzed after 24 h of incubation with 50 or 100 ${\mu}g$/ml AD-X and NAD-X. By one-way analysis of variance (p < 0.05) and Benjamini-Hochberg multiple testing correction for false discovery rate of the results, 573 and 297 genes were identified as AD-X- and NAD-X-responsive, respectively. The genes were classified into three groups by Venn diagram analysis of their expression profile, i.e., 290 AD-X-specific, 14 NAD-X-specific, and 283 overlapping genes. Quantitative realtime PCR confirmed the changes in the expression levels of the selected genes. The expression patterns of five genes, namely SORL1, RABEPK, DDIT4, AZU1, and NUDT1 differed significantly between the two groups. Following rigorous validation process, these genes may provide information in developing biomarker for AD exposure.

• Parasites, Hosts and Diseases
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• 제53권1호
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• pp.43-49
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• 2015

The aim of the study was to explore the possible molecular markers of chloroquine resistance in Plasmodium vivax isolates in Thailand. A total of 30 P. vivax isolates were collected from a malaria endemic area along the Thai-Myanmar border in Mae Sot district of Thailand. Dried blood spot samples were collected for analysis of Pvmdr1 and Pvcrt-o polymorphisms. Blood samples ($100{\mu}l$) were collected by finger-prick for in vitro chloroquine susceptibility testing by schizont maturation inhibition assay. Based on the cut-off $IC_{50}$ of 100 nM, 19 (63.3%) isolates were classified as chloroquine resistant P. vivax isolates. Seven non-synonymous mutations and 2 synonymous were identified in Pvmdr1 gene. Y976F and F1076L mutations were detected in 7 (23.3%) and 16 isolates (53.3%), respectively. Analysis of Pvcrt-o gene revealed that all isolates were wild-type. Our results suggest that chloroquine resistance gene is now spreading in this area. Monitoring of chloroquine resistant molecular markers provide a useful tool for future control of P. vivax malaria.

• Genomics & Informatics
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• 제8권1호
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• pp.28-33
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• 2010

Increased exposure of human to RF fields has raised concerns for its potential adverse effects on our health. To address the biological effects of RF radiation, we used genome wide gene expression as the indicator. We exposed normal WI-38 human fibroblast cells to 1763 MHz mobile phone RF radiation at a specific absorption rate (SAR) of 60 W/kg with an operating cooling system for 24 h. There were no alterations in cell numbers or morphology after RF exposure. Through microarray analysis, we identified no differentially expressed genes (DEGs) at the 0.05 significance level after controlling for multiple testing errors with the Benjaminiochberg false discovery rate (BH FDR) method. Meanwhile, 82 genes were differentially expressed between RF-exposed cells and controls when the significance level was set at 0.01 without correction for multiple comparisons. We found that 24 genes (0.08% of the total genes examined) were changed by more than 1.5-fold on RF exposure. However, significant enrichment of any gene set or pathway was not observed from the functional annotation analysis. From these results, we did not find any evidence that non-thermal RF radiation at a 60-W/kg SAR significantly affects cell proliferation or gene expression in WI-38 cells.

• Asian-Australasian Journal of Animal Sciences
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• 제18권8호
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• pp.1088-1097
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• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.438-441
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• 2007

Recently, due to molecular biology and engineering technology, DNA microarray makes people watch thousands of genes and the state of variation from the tissue samples of living body. With DNA Microarray, it is possible to construct a genetic group that has similar expression patterns and grasp the progress and variation of gene. This paper practices Cluster Analysis which purposes the discovery of biological subgroup or class by using gene expression information. Hence, the purpose of this paper is to predict a new class which is unknown, open leukaemia data are used for the experiment, and MCL (Markov CLustering) algorithm is applied as an analysis method. The MCL algorithm is based on probability and graph flow theory. MCL simulates random walks on a graph using Markov matrices to determine the transition probabilities among nodes of the graph. If you look at closely to the method, first, MCL algorithm should be applied after getting the distance by using Euclidean distance, then inflation and diagonal factors which are tuning modulus should be tuned, and finally the threshold using the average of each column should be gotten to distinguish one class from another class. Our method has improved the accuracy through using the threshold, namely the average of each column. Our experimental result shows about 70% of accuracy in average compared to the class that is known before. Also, for the comparison evaluation to other algorithm, the proposed method compared to and analyzed SOM (Self-Organizing Map) clustering algorithm which is divided into neural network and hierarchical clustering. The method shows the better result when compared to hierarchical clustering. In further study, it should be studied whether there will be a similar result when the parameter of inflation gotten from our experiment is applied to other gene expression data. We are also trying to make a systematic method to improve the accuracy by regulating the factors mentioned above.

• Animal Bioscience
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• 제34권1호
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• pp.134-142
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• 2021

Objective: To understand the athletic characteristics of Thoroughbreds, high-throughput analysis has been conducted using horse muscle tissue. However, an in vitro system has been lacking for studying and validating genes from in silico data. The aim of this study is to validate genes from differentially expressed genes (DEGs) of our previous RNA-sequencing data in vitro. Also, we investigated the effects of exercise-induced stress including heat, oxidative, hypoxic and cortisol stress on horse skeletal muscle derived cells with the top six upregulated genes of DEGs. Methods: Enriched pathway analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool with upregulated genes in horse skeletal muscle tissue after exercise. Among the candidates, the top six genes were analysed through geneMANIA to investigate gene networks. Muscle cells derived from neonatal horse skeletal tissue were maintained and subjected to exercise-related stressors. Transcriptional changes in the top six genes followed by stressors were investigated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Results: The inflammation response pathway was the most commonly upregulated pathway after horse exercise. Under non-cytotoxic conditions of exercise-related stressors, the transcriptional response of the top six genes was different among types of stress. Oxidative stress yielded the most similar expression pattern to DEGs. Conclusion: Our results indicate that transcriptional change after horse exercise in skeletal muscle tissue strongly relates to stress response. The qRT-PCR results showed that stressors contribute differently to the transcriptional regulation. These results would be valuable information to understand horse exercise in the stress aspect.