• The Journal of Natural Sciences
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• v.11 no.1
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• pp.45-54
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• 1999

In epistatic grouping of uvs genes in A. nidulans based on the sensitivities to 4-NQO, the same epistatic grouping was obtained as those for UV and MMS-sensitivities. Based on the MMS-sensitivities, uvsA demonstrated synergistic interactions to uvsF and uvsH, the UvsF group genes, but exhibited epistatic interactions to uvsB and uvsC. The same epistatic grouping was also seen for uvsI when UV was irradiated after 4h germination of conidia, showing synergistic interactions to uvsH, uvsC, and uvsB. However, epistatic interactions were observed with uvsF, which were different from those obtained in quiescent conidia by UV. Intergenic and intragenic recombination frequencies were normal in uvsI compared with wild type.

• Korean Journal of Poultry Science
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• v.48 no.2
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• pp.51-58
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• 2021

Fatty acid composition is an important economic trait that affects meat flavor. Several genes that influence fatty acid composition in meat have been investigated. In a previous study, we identified 51 significant SNP × SNP interactions (P≤0.05) between nine SNPs of six candidate genes (DEGS1, ELOVL6, FABP3, FABP4, FASN, and SCD) on meat fatty acid composition in Korean native chicken. This study further investigated the patterns of the SNP × SNP interactions to understand how they affect the fatty acid content in thigh and breast meat of Korean native chicken. The significant epistatic effects of SNP combinations showed various patterns for each fatty acid trait. The results of this study suggest that the respective additive effects of each SNP on polygenic traits, such as fatty acid composition, should be considered in combination with the epistatic effect of SNP combinations in animal breeding programs. The findings of this study have provided new genetic information for improving meat quality, especially the fatty acid composition, of Korean native chicken.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.267-267
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• 2022

Glutinous rice is a key grain quality trait occupying an important part during rice processing in most rice growing areas. Amylose content (AC) of rice determine eating quality which is one of the major traits in rice breeding program. In this study, a gene pyramiding approach was used to introduce two dull genes, responsible for low amylose contents, for glutinous rice breeding using marker assisted selection (MAS). Two dull genes were located on chromosome 6 (wx-mq, AC: 12.7 %) and chromosome 10 (du1, AC: 10.3%), respectively. To test whether these two dull genes have an epistatic interaction, we developed an F₂ population by crossing two nearly isogenic lines(NILs) harboring wx-mq and du1. Gene based marker and KASP marker were used to select NILs(NIL-nor, NIL-wxmq, NIL-du1, and NIL-wxmq/du1) from the F2 population. A two-way ANOVA revealed an epistatic interaction between the two genes in the F2 population. The mean of Amylose contents for NIL-nor, NIL-wxwq, NIL-(du1, and NIL-wxmq/du1 were 17.3%, 12.5%, 9.7%, and 7.2%, respectively. This interaction was confirmed by an analysis of NILs indicating that both genes are involved in the same genetic mechanism controlling amylose contents. This result will be useful for rice breeding related to amylose content.

• Animal Bioscience
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• v.37 no.4
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• pp.622-630
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• 2024

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

• Journal of Plant Biotechnology
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• v.44 no.4
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• pp.349-355
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• 2017

The amino acid composition of rice is a major concern of rice breeders because amino acids are among the most important nutrient components in rice. In this study, a genetic map was constructed with a population of 134 recombinant inbred lines (RILs) from a cross between Dasanbyeo (Tongil-type indica) and TR22183 (temperate japonica), as a means to detect the main and epistatic effect quantitative trait loci (QTLs) for the amino acid content (AAC). Using a linkage map which covered a total of 1458 cM based on 239 molecular marker loci, a total of six main-effect QTLs (M-QTLs) was identified for the content of six amino acids that were mapped onto chromosome 3. For all the M-QTLs, the TR22183 allele increased the trait values. The QTL cluster (flanked by id3015453 and id3016090) on chromosome 3 was associated with the content of five amino acids. The phenotypic variation, explained by the individual QTLs located in this cluster, ranged from 10.2 to 12.4%. In addition, 26 epistatic QTLs (Ep-QTLs) were detected and the 25 loci involved in this interaction were distributed on all nine chromosomes. Both the M-QTLs and Ep-QTLs detected in this study will be useful in breeding programs which target the development of rice with improved amino acid composition.

• Journal of Microbiology
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• v.39 no.2
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• pp.102-108
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• 2001

DNA damage response has a central role in the maintenance of genomic integrity while mutations in related genes may result in a range of disorders including neoplasic formations. The uvsZl characterized in this report is a navel uvs mutation in Aspergillus nidulans, resulting in a nucleotide excision repair (NER) phenotype: UV-sensitivity before DNA synthesis (quiescent cells), high UV-induced mutation frequency and probable absence of involvement with mitotic and meiotic recombinations. The mutation is recessive and nan-allelic to the previously characterized uvsA101 mutation, also located on the paba-y interval on chromosome I. uvsZl skewed wild-type sensitivity to MMS, which suggests non-involvement of this mutation with BER. Epitasis tests showed that the uvsZ gene product is probably involved in the same repair pathways as UVSB or UVSH proteins. Although mutations in these proteins result in an NER phenotype, UVSB is related with cell cycle control and UVSH is associated with the post-replicational repair pathway. The epistatic interaction among uvsZl and uvsB413 and uvsH77 mutations indicates that different repair systems may be related with the common steps of DNA damage response in Aspergillus nidulans.

• Genomics & Informatics
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• v.12 no.4
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• pp.216-224
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• 2014

Gastritis is a common but a serious disease with a potential risk of developing carcinoma. Helicobacter pylori infection is reported as the most common cause of gastritis, but other genetic and genomic factors exist, especially single-nucleotide polymorphisms (SNPs). Association studies between SNPs and gastritis disease are important, but results on epistatic interactions from multiple SNPs are rarely found in previous genome-wide association (GWA) studies. In this study, we performed computational GWA case-control studies for gastritis in Korea Associated Resource (KARE) data. By transforming the resulting SNP epistasis network into a gene-gene epistasis network, we also identified potential gene-gene interaction factors that affect the susceptibility to gastritis.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Molecules and Cells
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• v.25 no.3
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• pp.417-427
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• 2008

Comparison of maps and QTLs between populations may provide us with a better understanding of molecular maps and the inheritance of traits. We developed and used two reciprocal $BC_1F_1$ populations, IP/DS//IP and IP/DS//DS, for QTL analysis. DS (Dasanbyeo) is a Korean tongil-type cultivar (derived from an indica x japonica cross and similar to indica in its genetic make-up) and IP (Ilpumbyeo) is a Korean japonica cultivar. We constructed two molecular linkage maps corresponding to each backcross population using 196 markers for each map. The length of each chromosome was longer in the IP/DS//IP population than in the IP/DS//DS population, indicating that more recombinants were produced in the IP/DS//IP population. Distorted segregation was observed for 44 and 19 marker loci for the IP/DS//IP and IP/DS//DS populations, respectively; these were mostly skewed in favor of the indica alleles. A total of 36 main effect QTLs (M-QTLs) and 15 digenic epistatic interactions (E-QTLs) were detected for the seven traits investigated. The phenotypic variation explained (PVE) by M-QTLs ranged from 3.4% to 88.2%. Total PVE of the M-QTLs for each trait was significantly higher than that of the E-QTLs. The total number of M-QTLs identified in the IP/DS//IP population was higher than in the IP/DS//DS population. However, the total PVE by the M-QTLs and E-QTLs together for each trait was similar in the two populations, suggesting that the two $BC_1F_1$ populations are equally useful for QTL analysis. Maps and QTLs in the two populations were compared. Eleven new QTLs were identified for SN, SF, GL, and GW in this study, and they will be valuable in marker-assisted selection, particularly for improving grain traits in tongil-type varieties.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7955-7958
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• 2014

Breast cancer is the most common cancer among women in the world. In Iran, the incidence of breast cancer is on the increase. We here studied the association of rs1219648 in FGFR2 and rs1042522 in TP53 and their interaction in development of early onset sporadic breast cancer in Iranian Azeri population to evaluate epistatic effects on the risk of mammary neoplasia. We genotyped the two polymorphisms in 100 women with early onset breast cancer and 100 healthy women by PCR-RFLP. Allele frequency differences were tested using $chi^2$-test with 95% confident intervals. Our results indicated a statistically significant association (p<0.05) between rs1219648, but not rs1042522, and risk of breast cancer. We also found that the combination of FGFR2 major genotype and TP53 hetero genotype had protective effects against breast cancer, while the hetero allele of FGFR2 in combination with the minor genotype of TP53 was associated with a high risk. This study revealed an important crosstalk between two polymorphisms in FGFR2 and TP53 in development of breast cancer. These candidates risk variants should be further evaluated in studies with a larger sample size.