• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3431-3436
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• 2012

Objective: X-ray cross-complementing group 4 (XRCC4) is a major repair gene for DNA double-strand breaks (DSB) in the non-homologous end-joining (NHEJ) pathway. Several potentially functional polymorphisms of the XRCC4 gene have been implicated in breast cancer risk, but individually published studies showed inconclusive results. The aim of this meta-analysis was to investigate the association between XRCC4 polymorphisms and the risk of breast cancer. Methods: The MEDLINE, EMBASE, Web of science and CBM databases were searched for all relevant articles published up to June 20, 2012. Potential associations were assessed with comparisons of the total mutation rate (TMR), complete mutation rate (CMR) and partial mutation rate (PMR) in cases and controls. Statistical analyses were performed using RevMan 5.1.6 and STATA 12.0 software. Results: Five studies were included with a total of 5,165 breast cancer cases and 4,839 healthy controls. Meta-analysis results showed that mutations of rs2075686 (C>T) and rs6869366 (G>T) in the XRCC4 gene were associated with increased risk of breast cancer, while rs2075685 (G>T) and rs10057194 (A>G) might decrease the risk of breast cancer. However, rs1805377 (A>G), rs1056503 (G>T), rs28360317 (ins>del) and rs3734091 (A>G) polymorphisms of XRCC4 gene did not appear to have an influence on breast cancer susceptibility. Conclusion: Results from the current meta-analysis suggest that the rs2075685 (G>T) and rs6869366 (G>T) polymorphisms of the XRCC4 gene might increase the risk of breast cancer, whereas rs2075685 (G>T) and rs10057194 (A>G) might be protective factors.

• BMB Reports
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• v.49 no.4
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• pp.199-200
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• 2016

Gene regulation in the brain is essential for long-term plasticity and memory formation. Despite this established notion, the quantitative translational map in the brain during memory formation has not been reported. To systematically probe the changes in protein synthesis during memory formation, our recent study exploited ribosome profiling using the mouse hippocampal tissues at multiple time points after a learning event. Analysis of the resulting database revealed novel types of gene regulation after learning. First, the translation of a group of genes was rapidly suppressed without change in mRNA levels. At later time points, the expression of another group of genes was downregulated through reduction in mRNA levels. This reduction was predicted to be downstream of inhibition of ESR1 (Estrogen Receptor 1) signaling. Overexpressing Nrsn1, one of the genes whose translation was suppressed, or activating ESR1 by injecting an agonist interfered with memory formation, suggesting the functional importance of these findings. Moreover, the translation of genes encoding the translational machineries was found to be suppressed, among other genes in the mouse hippocampus. Together, this unbiased approach has revealed previously unidentified characteristics of gene regulation in the brain and highlighted the importance of repressive controls.

• Interdisciplinary Bio Central
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• v.3 no.2
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• pp.8.1-8.6
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• 2011

Background: Thanks to the development of the mathematical/statistical reverse engineering and the high-throughput measuring biotechnology, lots of biologically meaningful genegene interaction networks have been revealed. Steady-state analysis of these systems provides an important clue to understand and to predict the systematic behaviours of the biological system. However, modeling such a complex and large-scale system is one of the challenging difficulties in systems biology. Results: We introduce a new stochastic modeling approach that can describe gene regulatory mechanisms by dividing two (DNA and protein) layers. Simple queuing system is employed to explain the DNA layer and the protein layer is modeled using G-networks which enable us to account for the post-translational protein interactions. Our method is applied to a transcription repression system and an active protein degradation system. The steady-state results suggest that the active protein degradation system is more sensitive but the transcription repression system might be more reliable than the transcription repression system. Conclusions: Our two layer stochastic model successfully describes the long-run behaviour of gene regulatory networks which consist of various mRNA/protein processes. The analytic solution of the G-networks enables us to extend our model to a large-scale system. A more reliable modeling approach could be achieved by cooperating with a real experimental study in synthetic biology.

• Research in Plant Disease
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• v.30 no.1
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• pp.50-59
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• 2024

Charcoal rot disease, caused by the fungus Macrophomina phaseolina, is one of the most important diseases of Sesame (Sesamum indicum) all over the world. However, the population biology of M. phaseolina is poorly understood. In this study, M. phaseolina isolates from five different regions of Iran (Khuzestan, Fars, Bushehr, Hormozgan, and Kohgiluyeh & Boyer-Ahmad provinces) (n=200) were analyzed for genetic variation using inter simple sequence repeats marker. In total, 152 unique haplotypes were identified among the 200 M. phaseolina isolates, and gene diversity (H=0.46-0.84) and genotypic diversity were high in each of the regions. The structure analysis clustered five Iranian populations into two distinct groups, the individuals from group 1 were assigned to the Bushehr population and the individuals from Khuzestan, Fars, Hormozgan and Kohgiluyeh & Boyer-Ahmad were aggregated and formed group 2. The results matched with genetic differentiation and gene flow among regions. Analyses of the distribution of gene diversity within and among five Iranian populations were 61% and 39%, respectively. Our results showed that infected seeds are thought to be the dominant mechanism responsible for the spreading of the pathogen in southern parts of Iran. In summary, it is essential to have local quarantine and prevent seed exchanges between geographical populations to restrict the dispersal of pathogen over long distances and provide certified seeds in Iran.

• Molecular & Cellular Toxicology
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• v.4 no.4
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• pp.323-330
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• 2008

Surrogate tissue analysis incorporating -omics technologies has emerged as a potential alternative method for evaluating toxic effect of the tissues which are not accessible for sampling. Among the recent applications, blood including whole blood, peripheral blood lymphocytes and peripheral blood mononuclear cells (PBMCs) was suggested as a suitable surrogate tissue in determining toxicant exposure and effect at the pre- or early clinical stage. In this application, we investigated transcriptomic profiles in astemizole treated Cynomolgus monkey's PBMCs. PBMCs were isolated from 4-6 years old male monkeys at 24 hr after administration45 Helvetica Light (10 mg/kg, 30 mg/kg). Gene expression profiles of astemizole treated monkey's PBMCs were determined using Affymetrix $GeneChip^{(R)}$ Human Genome U133 plus 2.0 arrays. The expression levels of 724 probe sets were significantly altered in PBMCs at 10 or 30 mg/kg after astemizole administration following determination of paired t-test using statistical criteria of ${\geq}$$1.5-fold changes at P<0.05. Gene expression patterns in PBMCs showed a considerable difference between astemizole 10 and 30 mg/kg administration groups in spite of an administration of the same chemical. However, close examination using Ingenuity Pathway Analysis (IPA) software revealed that several gene sets related to cardiotoxicity were deregulated at astemizole 10 and 30 mg/kg administration groups. The deregulation of cardiac hypertrophy related genes such as TXN, GNAQ, and MAP3K5 was observed at 10 mg/kg group. In astemizole 30 mg/kg group, genes involved in cardiotoxicity including cardiac necrosis/cell death, dilation, fibrosis, and hypertrophy were also identified. These results suggest that toxicogenomic approach using PBMCs as surrogate tissues will contribute to assess toxicant exposures and identify biomarkers at the pre-clinical stage.

• Biomedical Science Letters
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• v.18 no.2
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• pp.139-145
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• 2012

RFLP of PGC-$1{\alpha}$ gene of 285 Korean women was analyzed by PCR and HpaII restriction. We evaluated the correlation between PGC 1 genotypes and biochemical results, using the results of RFLP. Study subjects were divided into 3 groups: normal group (who has been average value of serum biochemical analysis), upper group (who has been higher value than average value), and low group (who have been lower value than average value). The frequencies of $H_1H_1$, $H_1H_2$, and $H_2H_2$ genotypes were 92 (32%), 85 (32%), and 108 (38%) respectively, and the ratio between $H_1$ and $H_2$ alleles was 1:1.1. There were no meaningful differences between biochemical results and PGC-$1{\alpha}$ genotypes in the normal group. But, in upper group, there was significant difference in total cholesterol (P=0.04) level. In the result of Turkey multiple comparison test, the P value of $H_1H_1$ and $H_2H_2$ was 0.059. In upper group, there were noticeable differences also in triglyceride (P=0.034) level and glucose (P=0.043) level, respectively. There were important differences between $H_1H_1$ type and $H_1H_2$ type in triglyceride (P=0.029) level and between $H_1H_2$ type and $H_2H_2$ type in glucose (P=0.040) level. This study may provide the PGC-$1{\alpha}$ genotype patterns for the amounts of lipid and glucose in the serum. $H_2$ allele (Ser482) of PGC-$1{\alpha}$ gene may be related with upper group in Korean women.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.2363-2367
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• 2012

Objective: To investigate the association between the connexin 37 C1019T polymorphism and Helicobacter pylori infection in patients with gastric cancer. Methods: 388 patients with gastric cancer (GC), 204 with chronic superficial gastritis (CSG) were studied. H. pylori was detected by gastric mucosal biopsies biopsy dyeing method. Connexin 37 gene polymorphism 1019 site genotypes were determined by gene sequencing technology. Genotypes and alleles frequencies were compared. Results: (1) Connexin37 gene 1019 site distribution frequency (CC type, TC type, TT type) in the CSG group was 18.1%, 45.1% and 36.8%; in the stomach cancer group it was 35.1%, 45.9% and 19.%, conforming to the Hardy-Weinberg euilibrium. (2) In comparison with CSG group, the frequency of Connexin37 C allele was higher in the gastric cancer group (58.0% vs 40.7%, OR = 2.01, 95%CI = 1.58-2.57, P < 0.01). The prevalence of gastric cancer risk was significantly increased in the carriers of C allele (CC+TC) than in TT homozygote (OR = 2.47, 5%CI = 1.68- 3.610. (3) Gastric cancer patients complicated with Hp infection 211 cases, gastric cancer group of the male patients with HP positive patients with 187 cases, 40 cases of female patients with negative patients, 24 cases were HP positive, negative in 137 cases, control group male patients, 28 cases were Hp positive, negative in 95 patients, female patients with Hp positive 6 cases, 75 cases were negative. On hierarchical analysis, the male group OR value was 15.9 (95%CI to 9.22-27.3), and the female OR was 2.19 (95%CI 0.88-5.59), indicating a greater contribution in males (P <0.01). After elimination of gender effects, positive HP and gastric cancer were closely related (OR 8.82, 95% CI: 5.45-14.3). (4) The distribution frequency of C allele in patients with Hp infection was much higher than that in Hp negative cases in the GC group (64.5% vs 47.0%, OR = 2.05, 95%CI = 1.54-2.74, P < 0.01). Compared with TT homozygotes, (CC+TC) genotype prevalence of gastric cancer risk increased significantly (OR = 2.96, 5%CI = 1.76-2.99 ). Conclusion: The T allele in the connexin37 gene might not only be associated with gastric cancer but also with H. pylori infection.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2439-2442
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• 2013

We investigated the possible association of interleukin-10 (IL-10) single nucleotide polymorphisms (SNPs) and susceptibility to acute myeloid leukemia (AML) in 115 patients and 137 healthy controls. Genetic analysis of IL-10 SNPs at -819 and -592 was carried out with the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) approach. The IL-10 mRNA expression of AML patients and controls with different genotype was detected by real-time quantitative polymerase chain reaction (RT-PCR). Genetic analysis of IL-10 revealed that the -819AA genotype frequencies and the -819A allele frequencies in the AML group were higher than in the controls (59.1% vs 40.9%; 75.6% vs 63.9%, respectively); there were remarkable differences in -819T/C and -592A/C gene distribution (P<0.05) and the TA haploid frequencies were higher in the AML group (75.6% vs 63.9%, P<0.05). IL-10 mRNA expression in incipient AML patients was obvious higher than the non-tumor group and the remission group ($7.78{\times}10^{-3}$ vs $2.43{\times}10^{-3}$, $3.64{\times}10^{-3}$, P<0.05).The study suggested that the haploid TA and genotype TA/TA may be associated with AML in Han people in Hunan province.The IL-10 SNPs at -819 and -592 sites were associated with AML and may affect IL-10 mRNA expression in AML patients.

• The Korea Journal of Herbology
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• v.28 no.5
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• pp.1-6
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• 2013

Objectives : This study was conducted to identify the original Sinomini Caulis et Rhizoma plant among Stephania tetrandra, Cocculus trilobus, and Aristolochiae fangchi to develop the genetic marker for Sinomini Caulis et Rhizoma. Methods : Sinomenium acutum was identified by the classification and identification committee of the National Center for Standardization of Herbal Medicines. The chloroplast ndhF gene was amplified. We performed sequences alignment analysis of Sinomenium acutum, Stephania tetrandra, C. trilobus, and A. fangchi using BioEdit program. The SFR markers designed were consisted of SF01, SR04, and SR05 primers. Results : Many variations of Sinomeni Caulis et Rhizoma are currently commercialized as herbal medicine. We compared the base sequences of the ndhF intergenic space of chloroplast DNA with Sinomenium acutum, Stephania tetrandra, C. trilobus, and A. fangchi. According to the results, it showed that the nucleotide variations were seen in 30 genes of four species. Phylogenetic analysis revealed that 4 species were classified into five groups based on an inter-group divergence in nucleotide sequence of 9%. We developed SFR marker nucleotides enough to authenticate respective species and confirmed its application on the band size at 419 base pair. These sequence differences at corresponding positions were available genetic markers to identity the Sinomeni Caulis et Rhizoma. Conclusions : Base on these results, the ndhF region was effective in distinguishing Sinomini Caulis et Rhizoma The SFR genetic marker was useful for identifying Sinomini Caulis et Rhizoma with other species.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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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.