• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5767-5772
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• 2015

Background: Polymorphisms in the MDM2 309 (T>G) and TP53 72 (G>C) genes are reported to increase the susceptibility to head and neck cancer (HNC) in various populations. The risk for HNC is also strongly associated with etiologic habits such as smoking, alcohol consumption and/or chewing of betel quid (BQ). In a case-control study, we investigated the significance of the above polymorphisms alone, and upon interaction with one another as well as with various etiologic habits in determining HNC risk in a Northeast Indian population. Materials and Methods: Genotyping at 309 MDM2 and 72 TP53 in 122 HNC patients and 86 cancer free healthy controls was performed by PCR using allele specific primers, and the results were confirmed by DNA sequencing. Results: Individuals with the GG mutant allele of MDM2 showed a higher risk for HNC in comparison to those with the TT wild type allele (OR=1.9, 95%CI: 1.1-3.3) (p=0.022). The risk was further increased in females by ~4-fold (OR=4.6, 95% CI: 1.1-19.4) (P=0.04). TP53 polymorphism did not contribute to HNC risk alone; however, interaction between the TP53 GC and MDM2 GG genotypes resulted in significant risk (OR=4.9, 95% CI: 0.2-105.1) (p=0.04). Smokers, BQ- chewers and alcohol consumers showed statistically significant and dose-dependent increase in HNC risk, irrespective of the MDM2 genotype. Conclusions: MDM2 genotype could serve as an important predictive biomarker for HNC risk in the population of Northeast India.

• Journal of Forest and Environmental Science
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• v.39 no.1
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• pp.27-39
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• 2023

Twenty-five Eucalyptus clones (14 E. camaldulensis - EC and 11 interspecific eucalypt hybrid clones - EH) grown in three contrasting sites were evaluated for the growth and few wood traits at 4 years of age. The stability, genotype-site interaction and suitability of these clones for pulp and solid wood industry sectors were studied. Growth of eucalypt clones was significantly higher at site 1 with higher rainfall, but wood density did not differ significantly from lower rainfall sites. Kraft pulp yield (KPY) decreased from sites 1 to 3 based on moisture availability, but not between two groups of clones. Volumetric shrinkage (VS) was significantly higher in EC clones at site 3 with lowest rainfall, but there was no specific trend at other two sites with maximum (site 1) and intermediate (site 2) rainfall. The mechanical traits modulus of rupture (MOR) and modulus of elasticity (MOE) were at par in sites 1 and 2, but significantly lower at the driest site 3. The growth rate had a significant positive correlation with KPY, MOR and MOE and a negative correlation with VS, but no significant impact on wood density in both groups of clones. Genotype×environment interaction (G×E) was evident in most traits due to the difference in response of clones to moisture availability. Since wood density was negatively correlated to KPY, it has to be kept at an optimum level for the profitability of pulp industry. There was no significant difference between EC and EH clones for most traits except VS at site 3. Stability of clones varied across sites in different traits, and hence clones may be selected for deployment at each site by screening for growth, followed by wood density, considering the relationship of growth and density with other traits required by pulp and solid wood industry sectors.

• Horticultural Science & Technology
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• v.35 no.3
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• pp.361-372
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• 2017

Bred and grown around the world, tomato (Solanum spp.) has highly valuable fruits containings various anti-oxidants such as lycopene, flavonoids, glutamine, and ${\beta}-carotene$. Several studies have explored, way in which to enhance the growth, management and quality of tomato, we focus on the management of growth for yield rather than quality. The expression of superior agronomic traits depends on where cultivars are grown. We evaluated 10 cultivars grown in three environment for their lycopene. HTL3137 ($70.48mg{\cdot}kg^{-1}$), which was grown in Yoeju in spring/summer, contained the highest lycopene content, while HTL10256 ($20.9mg{\cdot}kg^{-1}$), which was grown in Suwon in spring/summer, contain the least lycopene.Correlations between color components and lycopene content varied according to growing location and season. In spring/summer-grown tomatoes from Suwon, no significant correlation was observed between any color component (redness [R], greenness [G], blueness [B], luminosity, $L^*$, $a^*$, $b^*$, hue and chroma) and lycopene content. A correlation was observed between B and lycopene content in tomatoes grown in Yeoju during the same season. In tomatoes grown in Yeoju in fall/winter, significant correlations were found between lycopene content and G, luminosity, $L^*$, and hue. Variance in interactions between genotype, environment, and genotype ${\times}$ environment (G ${\times}$ E) using Minimum Norm Quadratic Unbiased Estimate (MINQUE) analysis indicated that lycopene content depends on genotype (51.33%), environment (49.13%), and G ${\times}$ E (21.43%). However, when the Additive Main Effects and Multiplicative Interaction (AMMI) was used, the G ${\times}$ E value was highest.

• Genomics & Informatics
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• v.7 no.1
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• pp.20-25
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• 2009

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that is characterized by inflammation of the synovial tissue and deterioration of the joint and bone. A recent study reported a potential gene-environment interaction between HLA-DR and smoking. The present study investigated whether a specific gene was related to the association between smoking and the severity of RA (rheumatoid factor levels > 20 IU/ml). We used the resources of the NARAC family collection of GAW 15 databases, and 1139 subjects with RF>20 IU/ml were included in the current analysis. The linkage panel contained 5858 SNP markers, and 5744 SNPs passed quality control criteria. Linear regression analyses, using PLINK software and generalized estimating equation regression models, were used to test for associations between the SNPs and the severity of RA according to smoking groups. Two major findings were established. First, the severity of RA in smokers was associated with rs703618 (p=$6{\times}10^{-5}$), which lies in the intronic region of the stabilin 2 (STAB2) gene on chromosome 12. Second, there were significant differences in the levels of RF between 'ever smokers' and 'never smokers' according to the rs703618 genotype (G/G, A/G, A/A). We investigated whether a specific gene acts as a mediator between smoking and the severity of RA and found that the STAB2 gene could affect this relationship. Our finding indicates that smoking may mediate RA severity by affecting the expression level of a specific gene.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.677-684
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• 2008

Accurate estimation of dry matter intake (DMI) is a prerequisite to meet animal performance targets without penalizing animal health and the environment. The objective of the current study was to evaluate some of the existing models in order to predict DMI when lactating dairy cows were offered a total mixed ration containing a high level of concentrates and locally produced agricultural by-products. Six popular models were chosen for DMI prediction (Brown et al., 1977; Rayburn and Fox, 1993; Agriculture Forestry and Fisheries Research Council Secretariat, 1999; National Research Council (NRC), 2001; Cornell Net Carbohydrate and Protein System (CNCPS), Fox et al., 2003; Fuentes-Pila et al., 2003). Databases for DMI comparison were constructed from two different sources: i) 12 commercial farm investigations and ii) a controlled dairy cow experiment. The model evaluation was performed using two different methods: i) linear regression analysis and ii) mean square error prediction analysis. In the commercial farm investigation, DMI predicted by Fuentes-Pila et al. (2003) was the most accurate when compared with the actual mean DMI, whilst the CNCPS prediction showed larger mean bias (difference between mean predicted and mean observed values). Similar results were observed in the controlled dairy cow experiment where the mean bias by Fuentes-Pila et al. (2003) was the smallest of all six chosen models. The more accurate prediction by Fuentes-Pila et al. (2003) could be attributed to the inclusion of dietary factors, particularly fiber as these factors were not considered in some models (i.e. NRC, 2001; CNCPS (Fox et al., 2003)). Linear regression analysis had little meaningful biological significance when evaluating models for prediction of DMI in this study. Further research is required to improve the accuracy of the models, and may recommend more mechanistic approaches to investigate feedstuffs (common to the Asian region), animal genotype, environmental conditions and their interaction, as the majority of the models employed are based on empirical approaches.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.210-210
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• 2017

Sorghum is rich source of various phytochemicals including phenolic acids that have potential to significantly impact human health. Phytochemical production may be induced by not only genotype but a number of environmental factors including temperatures and amount of sunshine. The objective of this study was to determine the effect of planting date and harvesting stage on the agronomic and quality traits of 'Donganme' grain sorghum variety developed to produce high antioxidant activity. 'Donganme' were planted in three locations at four dates from early May to early July. Each planted fractions were harvested five times 35, 40, 45, 50, 55 days after head shooting date, respectively. Significant difference existed between the growth period and the agronomic traits. The interaction effects planting date and harvesting date was significant for plant height, tiller production, grain yield and antioxidant activity, indicating that low temperature and integrated sunshine influence on that traits. The result showed that antioxidant activity production occurred when the sorghum crop was grown in late season although the yield is lower. To produce antioxidant activity from sorghum grain need to consider the relation between the yield and nutrition component simultaneously.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5037-5042
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• 2012

Background: Tobacco contains agents which generate various potent DNA adducts that can cause gene mutations. Production of DNA adducts may be neutralized by glutathione S transferase (GST) along with other phase I and phase II enzyme systems. The existence of null type of GST among the population increases the susceptibility to various disorders and diseases. The present study focuses on the impact of high tobacco usage and possible null type mutation in GST loci. Methods: Genotypes of GST were detected by multiplex polymerase chain reaction in unrelated 504 volunteers of high tobacco using natives of Gujarat. Allelic frequencies were calculated using Statistical Package for Social Studies-16 software. Hardy Weinberg Equilibrium (HWE) was calculated using Chi square test. Two sided Fisher's significance test was used to compare allelic frequencies of different populations. Results: The frequency of homozygous null genotype of GSTM1 and GSTT1 were 20% (95% CI 16.7-23.9) and 35.5% (95% CI 31.4-39.9) respectively. The GSTM1 and GSTT1 null allele frequency distribution in the Gujarat population was significantly deviating from HWE. GSTT1 null frequency of Gujaratians was significantly higher and different to all reported low tobacco using Indian ethnics, while GSTM1 was not differing significantly. Conclusion: Tobacco usage significantly influences the rate of mutation and frequency of GSTT1 and M1 null types among the habituates. The rate of mutation in GSTT1 loci was an undeviating response to the dose of tobacco usage among the population. This mutational impact of tobacco on GSTT1 postulates the possible gene - environment interaction and selection of null genotype among the subjects to prone them under susceptible status for various cancers and even worst to cure the population with GSTT1 dependent drugs.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6673-6680
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• 2013

Objective: Insulin resistance (IR) is an established risk factor for colorectal cancer (CRC). Given that CRC and IR physiologically overlap and the calpain-10 gene (CAPN10) is a candidate for IR, we explored the association between CAPN10 and CRC risk. Methods: Blood samples of 400 case-control pairs were genotyped, and the lifestyle and dietary habits of these pairs were recorded and collected. Unconditional logistic regression (LR) was used to assess the effects of CAPN10 SNP43 and SNP19, and environmental factors. Both generalized multifactor dimensionality reduction (GMDR) and the classification and regression tree (CART) were used to test gene-environment interactions for CRC risk. Results: The GA+AA genotype of SNP43 and the Del/Ins+Ins/Ins genotype of SNP19 were marginally related to CRC risk (GA+AA: OR = 1.35, 95% CI = 0.92-1.99; Del/Ins+Ins/Ins: OR = 1.31, 95% CI = 0.84-2.04). Notably, a high-order interaction was consistently identified by GMDR and CART analyses. In GMDR, the four-factor interaction model of SNP43, SNP19, red meat consumption, and smoked meat consumption was the best model, with a maximum cross-validation consistency of 10/10 and testing balance accuracy of 0.61 (P < 0.01). In LR, subjects with high red and smoked meat consumption and two risk genotypes had a 6.17-fold CRC risk (95% CI = 2.44-15.6) relative to that of subjects with low red and smoked meat consumption and null risk genotypes. In CART, individuals with high smoked and red meat consumption, SNP19 Del/Ins+Ins/Ins, and SNP43 GA+AA had higher CRC risk (OR = 4.56, 95%CI = 1.94-10.75) than those with low smoked and red meat consumption. Conclusions: Though the single loci of CAPN10 SNP43 and SNP19 are not enough to significantly increase the CRC susceptibility, the combination of SNP43, SNP19, red meat consumption, and smoked meat consumption is associated with elevated risk.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.6
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• pp.765-772
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• 2017

Objective: This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score) of Hanwoo. Methods: To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms) were excluded from the model. Results: The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP) in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion: The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.