Although there have been plenty of dominance deviation analysis, few studies have dealt with multiple phenotypes. Because researchers focused on multiple phenotypes (final weight and backfat thickness) of Landrace pigs, the classification of the genes was possible. With genome-wide association studies (GWASs), we analyzed the additive and dominance effects of the single nucleotide polymorphisms (SNPs). The classification of the pig genes into four categories (overdominance in final weight, overdominance in backfat thickness and overdominance in final weight, underdominance in backfat thickness, etc.) can enable us not only to analyze each phenotype's dominant effects, but also to illustrate the gene ontology (GO) analysis with different aspects. We aimed to determine the additive and dominant effect in backfat thickness and final weight and performed GO analysis. Using additive model and dominance deviation analysis in GWASs, Landrace pigs' overdominant and underdominant SNP effects in final weight and backfat thickness were surveyed. Then through GO analysis, we investigated the genes that were classified in the GWASs. The major GO terms of the underdominant effects in final weight and overdominant effects in backfat thickness were ion transport with the SLC8A3, KCNJ16, P2RX7 and TRPC3 genes. Interestingly, the major GO terms in the underdominant effects in the final weight and the underdominant effects in the backfat thickness were the regulation of ion transport with the STAC, GCK, TRPC6, UBASH3B, CAMK2D, CACNG4 and SCN4B genes. These results demonstrate that ion transport and ion transport regulation genes have distinct dominant effects. Through GWASs using the mode of linear additive model and dominance deviation, overdominant effects and underdominant effects in backfat thickness was contrary to each other in GO terms (ion transport and ion transport regulation, respectively). Additionally, because ion transport and ion transport regulation genes are associative with adipose tissue accumulation, we could infer that these two groups of genes had to do with unique fat accumulation mechanisms in Landrace pigs.
Objective: The Bayesian first-order antedependence models, which specified single nucleotide polymorphisms (SNP) effects as being spatially correlated in the conventional BayesA/B, had more accurate genomic prediction than their corresponding classical counterparts. Given advantages of $BayesC{\pi}$ over BayesA/B, we have developed hyper-$BayesC{\pi}$, ante-$BayesC{\pi}$, and ante-hyper-$BayesC{\pi}$ to evaluate influences of the antedependence model and hyperparameters for $v_g$ and $s_g^2$ on $BayesC{\pi}$.Methods: Three public data (two simulated data and one mouse data) were used to validate our proposed methods. Genomic prediction performance of proposed methods was compared to traditional $BayesC{\pi}$, ante-BayesA and ante-BayesB. Results: Through both simulation and real data analyses, we found that hyper-$BayesC{\pi}$, ante-$BayesC{\pi}$ and ante-hyper-$BayesC{\pi}$ were comparable with $BayesC{\pi}$, ante-BayesB, and ante-BayesA regarding the prediction accuracy and bias, except the situation in which ante-BayesB performed significantly worse when using a few SNPs and ${\pi}=0.95$. Conclusion: Hyper-$BayesC{\pi}$ is recommended because it avoids pre-estimated total genetic variance of a trait compared with $BayesC{\pi}$ and shortens computing time compared with ante-BayesB. Although the antedependence model in $BayesC{\pi}$ did not show the advantages in our study, larger real data with high density chip may be used to validate it again in the future.
The retinal degenerative disease, progressive retinal atrophy (PRA) is a major reason of vision impairment in canine population. Canine PRA signifies an inherently dissimilar category of retinal dystrophies which has solid resemblances to human retinis pigmentosa. Even though much is known about the biology of PRA, the knowledge about the intricate connection among genetic loci, genes and pathways associated to this disease in dogs are still remain unknown. Therefore, we have performed a genome wide association study (GWAS) to identify susceptibility single nucleotide polymorphisms (SNPs) of PRA. The GWAS was performed using a case-control based association analysis method on PRA dataset of 129 dogs and 135,553 markers. Further, the gene-set and pathway analysis were conducted in this study. A total of 1,114 markers associations with PRA trait at p < 0.01 were extracted and mapped to 640 unique genes, and then selected significant (p < 0.05) enriched 35 gene ontology (GO) terms and 5 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways contain these genes. In particular, apoptosis process, homophilic cell adhesion, calcium ion binding, and endoplasmic reticulum GO terms as well as pathways related to focal adhesion, cyclic guanosine monophosphate)-protein kinase G signaling, and axon guidance were more likely associated to the PRA disease in dogs. These data could provide new insight for further research on identification of potential genes and causative pathways for PRA in dogs.
Hyun Jeong Cho;Akinkunmi Paul Okekunle ;Ga-Eun Yie ;Jiyoung Youn ;Moonil Kang;Taiyue Jin;Joohon Sung;Jung Eun Lee
Nutrition Research and Practice
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v.17
no.4
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pp.789-802
/
2023
BACKGROUND/OBJECTIVES: Habitual coffee consumption was inversely associated with type 2 diabetes (T2D) and hyperglycemia in observational studies, but the causality of the association remains uncertain. This study tested a causal association of genetically predicted coffee consumption with T2D using the Mendelian randomization (MR) method. SUBJECTS/METHODS: We used five single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with habitual coffee consumption in a previous genome-wide association study among Koreans. We analyzed the associations between IVs and T2D, fasting blood glucose (FBG), 2h-postprandial glucose (2h-PG), and glycated haemoglobin (HbA1C) levels. The MR results were further evaluated by standard sensitivity tests for possible pleiotropism. RESULTS: MR analysis revealed that increased genetically predicted coffee consumption was associated with a reduced prevalence of T2D; ORs per one-unit increment of log-transformed cup per day of coffee consumption ranged from 0.75 (0.62-0.90) for the weighted mode-based method to 0.79 (0.62-0.99) for Wald ratio estimator. We also used the inverse-variance-weighted method, weighted median-based method, MR-Egger method, and MR-PRESSO method. Similarly, genetically predicted coffee consumption was inversely associated with FBG and 2h-PG levels but not with HbA1c. Sensitivity measures gave similar results without evidence of pleiotropy. CONCLUSIONS: A genetic predisposition to habitual coffee consumption was inversely associated with T2D prevalence and lower levels of FBG and 2h-PG profiles. Our study warrants further exploration.
Purpose: This study focused on identifying the interaction effects of genetic and lifestyle-environmental factors on the development of type 2 diabetes mellitus (T2D). Methods: Study subjects were selected from the Korean Genome and Epidemiology Study (KoGES) from 2001 to 2014. Data on genetic variations, anthropometric measurements, biochemical data, and seven lifestyle factors (diet, physical activity, alcohol drinking, smoking, sleep, depression, and stress) were obtained from 4,836 Koreans aged between 40 and 59 years, including those with T2D at baseline (n = 1,209), newly developed T2D (n= 1,298) and verified controls (n = 3,538). The genetic risk score (GRS) was calculated by using 11 single-nucleotide polymorphisms (SNPs) related to T2D development and the second quartile was used as the reference category. A Cox proportional hazards regression model was used to evaluate the associations of GRS and lifestyle factors with T2D risk, controlling for covariates. Results: Multivariate regression analysis revealed that GRS was the strongest risk factor for T2D, and body mass index (BMI), smoking, drinking, and spicy food preference also increased the risk. Lifestyle/environmental factors that showed significant interactions with GRS were BMI, current smoking, current drinking, fatty food preference, and spicy food preference. Conclusions: Interactions between genetic factors and lifestyle/environmental factors were associated with an increased risk of T2D. The results will be useful to provide a new perspective on genetic profiling for the earlier detection of T2D risk and clues for personalized interventions, which might be more effective prevention strategies or therapies in individuals with a genetic predisposition to T2D.
Thisarani Kalhari Ediriweera;Prabuddha Manjula;Jaewon Kim;Jin Hyung Kim;Seonju Nam;Minjun Kim;Eunjin Cho;Mohammad Shamsul Alam Bhuiyan;Md. Abdur Rashid;Jun Heon Lee
Animal Bioscience
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v.37
no.5
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pp.826-831
/
2024
Objective: The major histocompatibility complex in chicken demonstrates a great range of variations within varities, breeds, populations and that can eventually influence their immuneresponses. The preset study was conducted to understand the major histocompatibility complex-B (MHC-B) variability in five major populations of Bangladesh native chicken: Aseel, Hilly, Junglefowl, Non-descript Deshi, and Naked Neck. Methods: These five major populations of Bangladesh native chicken were analyzed with a subset of 89 single nucleotide polymorphisms (SNPs) in the high-density MHC-B SNP panel and Kompetitive Allele-Specific polymerase chain reaction genotyping was applied. To explore haplotype diversity within these populations, the results were analyzed both manually and computationally using PHASE 2.1 program. The phylogenetic investigations were also performed using MrBayes program. Results: A total of 136 unique haplotypes were identified within these five Bangladesh chicken populations, and only one was shared (between Hilly and Naked Neck). Phylogenetic analysis showed no distinct haplotype clustering among the five populations, although they were shared in distinct clades; notably, the first clade lacked Naked Neck haplotypes. Conclusion: The present study discovered a set of unique MHC-B haplotypes in Bangladesh chickens that could possibly cause varied immune reponses. However, further investigations are required to evaluate their relationships with global chicken populations.
Muhammad Ma'ruf;Lalu Muhammad Irham;Wirawan Adikusuma;Made Ary Sarasmita;Sabiah Khairi;Barkah Djaka Purwanto;Rockie Chong;Maulida Mazaya;Lalu Muhammad Harmain Siswanto
Genomics & Informatics
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v.21
no.4
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pp.48.1-48.8
/
2023
Liver cancer is the fourth leading cause of death worldwide. Well-known risk factors include hepatitis B virus and hepatitis C virus, along with exposure to aflatoxins, excessive alcohol consumption, obesity, and type 2 diabetes. Genomic variants play a crucial role in mediating the associations between these risk factors and liver cancer. However, the specific variants involved in this process remain under-explored. This study utilized a bioinformatics approach to identify genetic variants associated with liver cancer from various continents. Single-nucleotide polymorphisms associated with liver cancer were retrieved from the genome-wide association studies catalog. Prioritization was then performed using functional annotation with HaploReg v4.1 and the Ensembl database. The prevalence and allele frequencies of each variant were evaluated using Pearson correlation coefficients. Two variants, rs2294915 and rs2896019, encoded by the PNPLA3 gene, were found to be highly expressed in the liver tissue, as well as in the skin, cell-cultured fibroblasts, and adipose-subcutaneous tissue, all of which contribute to the risk of liver cancer. We further found that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. Positive associations with the prevalence rate were more frequent in East Asian and African populations. We highlight the utility of this population-specific PNPLA3 genetic variant for genetic association studies and for the early prognosis and treatment of liver cancer. This study highlights the potential of integrating genomic databases with bioinformatic analysis to identify genetic variations involved in the pathogenesis of liver cancer. The genetic variants investigated in this study are likely to predispose to liver cancer and could affect its progression and aggressiveness. We recommend future research prioritizing the validation of these variations in clinical settings.
Recently, it was reported that certain polymorphisms in the growth hormone secretagogue receptor gene (GHSR) are associated with the growth of chickens. However, the correlation between GHSR polymorphisms and economic traits has not been investigated in Korean native chickens (KNCs). Therefore, the objective of this study was to confirm the suitability of the GHSR gene as a candidate for genomic selection and identify a genetic marker for KNCs. A total of 220 KNCs from six breeds raised at the National Institute of Animal Science were genotyped for the c.739+726 SNP in the GHSR gene using polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), and the sequence for a subset of 30 birds was analyzed using direct sequencing. The association between the SNP genotypes and the economic traits of the KNCs was analyzed using the statistical package for the social science (SPSS) software program. The association analysis between the c.739+726T>C SNP and economic traits revealed that the SNP was significantly associated with body weight at 150 and 270 days (BW150 and BW270, respectively) in all KNCs (p<0.01), BW150 in KNC (Gary) (p<0.05), and egg production number in KNC (White, p<0.05). In addition, the SNPs discovered using direct sequencing (513A>G, 517A>T) had a significant effect on the body weight and egg production traits (p<0.05). In conclusion, these results might be useful as a basis for studies on the improvement of KNC breeds. Furthermore, these results suggest that the SNPs (c.739+726T>C, 513A>G, and 517A>T) located in the GHSR gene could be useful molecular genetic markers for KNCs.
Cho, Hee Yeon;Choi, Hyun Jin;Lee, So Hee;Lee, Hyun Kyung;Kang, Hee Kyung;Ha, Il Soo;Choi, Yong;Cheong, Hae Il
Clinical and Experimental Pediatrics
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v.52
no.11
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pp.1260-1266
/
2009
Purpose : Idiopathic nephrotic syndrome (NS) can be clinically classified as steroid-sensitive and steroid-resistant. The detailed mechanism of glucocorticoid action in NS is currently unknown. Methods : In this study, we investigated 3 known single nucleotide polymorphisms (SNPs) (ER22/23EK, N363S, and BclI) of the glucocorticoid receptor gene (the NR3C1 gene) in 190 children with NS using polymerase chain reaction-restriction fragment length polymorphism and analyzed the correlation between the genotypes and clinicopathologic features of the patients. Results : Eighty patients (42.1%) were initial steroid nonresponders, of which 31 (16.3% of the total) developed end-stage renal disease during follow-up. Renal biopsy findings of 133 patients were available, of which 36 (31.9%) showed minimal changes in NS and 77 (68.1%) had focal segmental glomerulosclerosis. The distribution of the BclI genotypes was comparable between the patient and control groups, and the G allele frequencies in both the groups were almost the same. The ER22/23EK and N363S genotypes were homogenous as ER/ER and NN, respectively, in all the patients and in 100 control subjects. The BclI genotype showed no correlation with the NS onset age, initial steroid responsiveness, renal pathologic findings, or progression to end-stage renal disease. Conclusion : These data suggested that the ER22/23EK, N363S, and BclI SNPs in the NR3C1 gene do not affect the development of NS, initial steroid responsiveness, renal pathologic lesion, and progression to end-stage renal disease in Korean children with NS.
Study the gene about economical characteristic of human disease or domestic animal is a matter of grave interest, preserve and elevation of gene of Korea cattle is key subject. Studies have been done on the gene of Korea cattle using EST based SNP map, but it is based on statistical model, therefore there are difference between real position and statistical position. These problems are solved using both EST_based SNP map and Gene on sequence by Lee et al. (2009b). We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, method is suggested E-MDR method using CART algorithm. Also we identified interaction effects of single nucleotide polymorphisms(SNPs) responsible for average daily gain(ADG) and marbling score(MS) using E-MDR method.
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