scholarly journals Epistatic Effects on Abdominal Fat Content in Chickens: Results from a Genome-Wide SNP-SNP Interaction Analysis

PLoS ONE ◽  
2013 ◽  
Vol 8 (12) ◽  
pp. e81520 ◽  
Author(s):  
Fangge Li ◽  
Guo Hu ◽  
Hui Zhang ◽  
Shouzhi Wang ◽  
Zhipeng Wang ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Abdominal Fat ◽  
Fat Content ◽  
Epistatic Effects ◽  
Genome Wide ◽  
A Genome ◽  
Snp Interaction

scholarly journals A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content

BMC Genomics ◽  
2012 ◽  
Vol 13 (1) ◽  
pp. 704 ◽  
Author(s):  
Hui Zhang ◽  
Shou-Zhi Wang ◽  
Zhi-Peng Wang ◽  
Yang Da ◽  
Ning Wang ◽  
...  
Keyword(s):  
Broiler Chicken ◽  
Abdominal Fat ◽  
Fat Content ◽  
Selective Sweeps ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Scan

Abstract 178: RCBTB1 Genotypes Modulate Smoking Effect on Carotid Intima-Media Thickness: A Finding from a Genome-Wide Interaction Analysis

2012 ◽  
Vol 32 (suppl_1) ◽  
Author(s):  
Chuanhui Dong ◽  
Liyong Wang ◽  
Digna Cabral ◽  
Ashley Beecham ◽  
Susan H Blanton ◽  
...  
Keyword(s):  
Cigarette Smoking ◽  
Interaction Analysis ◽  
Intima Media Thickness ◽  
Carotid Intima Media Thickness ◽  
Carotid Imt ◽  
Media Thickness ◽  
Genome Wide ◽  
Cigarette Pack ◽  
A Genome ◽  
Snp Interaction

Objective: Smoking is an established risk factor for atherosclerotic disease. However, the degree of the cigarette smoking-induced damage varies from individual to individual, partly due to the between-individual difference in genetic makeup. The aim of this study was to identify genetic loci influencing the effect of cigarette smoking on carotid intima-media thickness (IMT) by performing a genome-wide association smoking-by-SNP interaction analysis. Methods and results: Genome-wide genotyping was performed using the Affymetrix SNP array 6.0 among 1,010 individuals who underwent B-mode ultrasound examination of carotid IMT from the population-based Northern Manhattan Study. Cigarette pack-years was calculated as number of years smoked multiplied by number of cigarettes smoked per day, then divided by 20. After quality control, a total of 722,379 single nucleotide polymorphisms (SNPs) were included in the final analysis. Generalized linear modeling was conducted to look for smoking-by-SNP interaction on carotid IMT while controlling for age, sex, hypertension, diabetes, dyslipidemia, body mass index, waist-to-hip ratio, and the top 3 principal components estimated to capture ancestry by EIGENSTRAT. Ten SNPs near or within 5 genes showed an interactive effect with cigarette smoking on IMT with a p value <1.0E-5. Among them, 3 SNPs (including 1 exonic splice enhancer SNP rs3751283, P=8.3E-7) are near or within regulator of chromosome condensation and BTB domain containing protein 1 (RCBTB1) gene on 13q14. Specifically, for SNP rs3751283, the mean IMT was substantially increased among CC-carriers (0.70 mm, 0.76 mm, 0.81 mm for 0, <20, and ≥20 cigarette pack-years, respectively, P=2.6E-6), slightly increased with smoking pack-years among TC-carriers (0.72 mm, 0.74 mm, 0.75 mm for 0, <20, and ≥20 cigarette pack-years, respectively, P=0.03), but very similar (0.73 mm) among TT-carriers for the three smoking groups (P=0.84). Conclusion: Our genome-wide interaction analysis reveals multiple genes, especially RCBTB1, that may modify the effect of smoking on carotid IMT. These genes will be further evaluated in our full dataset with additional genotyping. Also, larger independent studies are needed to validate these findings.

scholarly journals Detection of genome-wide copy number variations in two chicken lines divergently selected for abdominal fat content

BMC Genomics ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 517 ◽  
Author(s):  
Hui Zhang ◽  
Zhi-Qiang Du ◽  
Jia-Qiang Dong ◽  
Hai-Xia Wang ◽  
Hong-Yan Shi ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Variations ◽  
Abdominal Fat ◽  
Fat Content ◽  
Genome Wide

scholarly journals Genome Wide Analysis Approach Suggests Chromosome 2 Locus to be Associated with Thiazide and Thiazide Like-Diuretics Blood Pressure Response

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sonal Singh ◽  
Caitrin W. McDonough ◽  
Yan Gong ◽  
Kent R. Bailey ◽  
Eric Boerwinkle ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Protein Interaction ◽  
Interaction Analysis ◽  
Inositol Phosphate ◽  
Meta Analysis ◽  
Hypertensive Patients ◽  
Protein Protein Interaction ◽  
Genome Wide ◽  
A Genome ◽  
Β Blockers

AbstractChlorthalidone (CTD) is more potent than hydrochlorothiazide (HCTZ) in reducing blood pressure (BP) in hypertensive patients, though both are plagued with BP response variability. However, there is a void in the literature regarding the genetic determinants contributing to the variability observed in BP response to CTD. We performed a discovery genome wide association analysis of BP response post CTD treatment in African Americans (AA) and European Americans (EA) from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) study and replication in an independent cohort of AA and EA treated with HCTZ from the PEAR study, followed by a race specific meta-analysis of the two studies. Successfully replicated SNPs were further validated in beta-blocker treated participants from PEAR-2 and PEAR for opposite direction of association. The replicated and validated signals were further evaluated by protein-protein interaction network analysis. An intronic SNP rs79237970 in the WDR92 (eQTL for PPP3R1) was significantly associated with better DBP response to CTD (p = 5.76 × 10−6, β = −15.75) in the AA cohort. This SNP further replicated in PEAR (p = 0.00046, β = −9.815) with a genome wide significant meta-analysis p-value of 8.49 × 10−9. This variant was further validated for opposite association in two β-blockers treated cohorts from PEAR-2 metoprolol (p = 9.9 × 10−3, β = 7.47) and PEAR atenolol (p = 0.04, β = 4.36) for association with DBP. Studies have implicated WDR92 in coronary artery damage. PPP3R1 is the regulatory subunit of the calcineurin complex. Use of calcineurin inhibitors is associated with HTN. Studies have also shown polymorphisms in PPP3R1 to be associated with ventricular hypertrophy in AA hypertensive patients. Protein-protein interaction analysis further identified important hypertension related pathways such as inositol phosphate-mediated signaling and calcineurin-NFAT signaling cascade as important biological process associated with PPP3R1 which further strengthen the potential importance of this signal. These data collectively suggest that WDR92 and PPP3R1 are novel candidates that may help explain the genetic underpinnings of BP response of thiazide and thiazide-like diuretics and help identify the patients better suited for thiazide and thiazide-like diuretics compared to β-blockers for improved BP management. This may further help advance personalized approaches to antihypertensive therapy.

scholarly journals A Time-dependent Genome-Wide SNP-SNP Interaction Analysis of Chicken Body Weight

2019 ◽  
Author(s):  
Fang-Ge Li ◽  
Hui Li
Keyword(s):  
Body Weight ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Genetic Network ◽  
Time Dependent ◽  
Model Organisms ◽  
Multiple Time ◽  
Genome Wide ◽  
Snp Interaction

Abstract Background The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. Results We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (BW) (n=475) at multiple time points (day of hatch (BW0) and one, three, five, and seven weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67×10 −12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. Conclusions With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

scholarly journals A time-dependent genome-wide SNP-SNP interaction analysis of chicken body weight

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Fang-Ge Li ◽  
Hui Li
Keyword(s):  
Body Weight ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Genetic Network ◽  
Time Dependent ◽  
Model Organisms ◽  
Multiple Time ◽  
Genome Wide ◽  
Snp Interaction

Abstract Background The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. Results We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (BW) (n = 475) at multiple time points (day of hatch (BW0) and 1, 3, 5, and 7 weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67 × 10− 12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. Conclusions With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

scholarly journals A sex-stratified genome-wide association study of tuberculosis using a multi-ethnic genotyping array

2018 ◽  
Author(s):  
Haiko Schurz ◽  
Craig J Kinnear ◽  
Chris Gignoux ◽  
Genevieve Wojcik ◽  
Paul D van Helden ◽  
...  
Keyword(s):  
Association Study ◽  
X Chromosome ◽  
Complex Disease ◽  
Genome Wide Association Study ◽  
Interaction Analysis ◽  
Genome Wide Association ◽  
Genotyping Array ◽  
Association Testing ◽  
Genome Wide ◽  
A Genome

AbstractTuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease with a known human genetic component. Males seem to be more affected than females and in most countries the TB notification rate is twice as high in males as in females. While socio-economic status, behaviour and sex hormones influence the male bias they do not fully account for it. Males have only one copy of the X chromosome, while diploid females are subject to X chromosome inactivation. In addition, the X chromosome codes for many immune-related genes, supporting the hypothesis that X-linked genes could contribute to TB susceptibility in a sex-biased manner. We report the first TB susceptibility genome-wide association study (GWAS) with a specific focus on sex-stratified autosomal analysis and the X chromosome. Individuals from an admixed South African population were genotyped using the Illumina Multi Ethnic Genotyping Array, specifically designed as a suitable platform for diverse and admixed populations. Association testing was done on the autosome and X chromosome in a sex stratified and combined manner. SNP association testing was not statistically significant using a stringent cut-off for significance but revealed likely candidate genes that warrant further investigation. A genome wide interaction analysis detected 16 significant interactions. Finally, the results highlight the importance of sex-stratified analysis as strong sex-specific effects were identified on both the autosome and X chromosome.

scholarly journals Large-Scale, Genome-Wide Gene-Diet Interaction Testing for HbA1c Using Derived Dietary Patterns in the UK Biobank

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1280-1280
Author(s):  
Kenneth Westerman ◽  
Ye Chen ◽  
Han Chen ◽  
Jose Florez ◽  
Joanne Cole ◽  
...  
Keyword(s):  
Principal Components ◽  
Dietary Patterns ◽  
Genetic Variants ◽  
Interaction Analysis ◽  
European Ancestry ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Gene Level ◽  
The Uk

Abstract Objectives Gene-diet interaction analysis can inform the development of precision nutrition for diabetes by uncovering genetic variants whose effects on glycemic traits vary across dietary behaviors. However, due to noise in dietary datasets and the low statistical power inherent in interaction analysis, there is a lack of confident, well-replicated gene-diet interactions for glycemic traits. Emerging computationally-efficient software tools have made it feasible to conduct well-powered, genome-wide interaction analysis in hundreds of thousands of individuals. Here, our objective was to conduct a genome-wide gene-diet interaction analysis for glycated hemoglobin (HbA1c; a measure of hyperglycemia), leveraging the large sample size of the UK Biobank cohort and data-driven dietary patterns to discover genetic variants whose effect is modulated by diet. Methods Food frequency questionnaires were previously used to derive empirical dietary patterns using principal components analysis (FFQ-PCs) in the UK Biobank. FFQ-PCs were used in genome-wide interaction analysis for HbA1c levels in unrelated, non-diabetic individuals of European ancestry (N = 331,610), adjusting for age, sex, and 10 genetic principal components. P-values were calculated for both the interaction (P-int) and a joint test (significance of the variant-HbA1c association combining the main and interaction effects) and the MAGMA tool was used to calculate gene-level enrichment statistics. Results Preliminary results from the first two FFQ-PCs confirmed known genetic loci for HbA1c using the joint test, such as at G6PC2 and GCK. Though no interaction tests reached genome-wide significance, suggestive signals (P-int &lt; 1e-5) emerged at the variant level (including one near TPSD1, which codes for a tryptase and has been linked to red blood cell traits) and the gene level (such as for GTF3C2, which has previously been shown to interact with sleep in impacting lipid traits). Conclusions We have conducted the largest genome-wide study of gene-diet interactions for glycemic traits to-date and identified regions in the genome whose effect on HbA1c may be modulated by dietary intake, suggesting that this approach has the potential to reveal new insights into the genetics of glycemic traits and inform individualized dietary guidelines for diabetes prevention and management. Funding Sources NHLBI.

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