scholarly journals Genome-wide Association Studies Reveal Similar Genetic Architecture with Shared and Unique QTL for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

2017 ◽  
Author(s):  
Roger L. Vallejo ◽  
Guangtu Gao ◽  
Sixin Liu ◽  
Breno O. Fragomeni ◽  
Alvaro G. Hernandez ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Cold Water ◽  
Association Studies ◽  
Snp Array ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Bacterial Cold Water Disease ◽  
Breeding Populations ◽  
Genome Wide ◽  
Two Populations

ABSTRACTBacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome physical map have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

Abstract P231: Gene-by-smoking Interaction Analyses of Kidney Traits in the NHLBI Candidate-gene Association Resources Care Cohorts

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Nora Franceschini ◽  
Ching-Ti Liu ◽  
W Linda Kao ◽  
Leslie Lange ◽  
Kari E North ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Association Studies ◽  
Snp Array ◽  
Genetic Effects ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Current Smoking ◽  
Genome Wide ◽  
Smoking Exposure ◽  
Smoking Interaction

Smoking is a known risk factor for progression of chronic kidney disease (CKD) but little is known of the role of smoking exposure on genetic effects of variants influencing kidney traits in the general population. We examined the evidence for effect modification of current smoking on the association of single nucleotide polymorphisms (SNP) with estimated glomerular filtration rate (eGFR) and urine albumin to creatinine ratio (UACR), two well established markers of kidney disease, in 23,767 white and 8,110 African American individuals from five studies genotyped using the custom SNP array ITMAT-Broad-CARe (IBC array) in the CARe consortium. We obtained study- and race-specific residuals from linear regression models of natural log-transformed eGFR or UACR regressed on age, sex and study site. We then stratified residuals by current smoking exposure and performed genome wide association analyses using additive genetic models adjusted for 10 principal components, and accounting for family structure using mixed models, if needed. Meta-analyses across smoking-specific strata within each self-reported race were performed using the inverse variance weighted fixed effect models. We assessed smoking interaction using a heterogeneity test (P<0.10) and I 2 metric. Among SNPs reaching the array wide specific significance threshold (2.0x10 -6 ) for association with eGFR or UACR, there was significant between smoking-strata heterogeneity for rs7422339 ( CPS1 , P=0.03, I 2 =77.7%) and rs13333226 ( UMOD , P=0.06, I 2 =71.1%) for eGFR in whites, with larger decreases in eGFR among current smokers compared to past/never smokers. For UACR, rs1801239 (missense variant of CUBN , between smoking-strata heterogeneity P=0.09, I 2 =64.8%) T allele showed less protective effect among current smokers than non-smokers in whites only. These loci have been previously identified in genome wide association studies. Our findings, if replicated, suggest possible important interactions of smoking exposure on the genetic effects of known loci associated with kidney traits. Funding(This research has received full or partial funding support from the American Heart Association, National Center)

A Genome Wide Association Study Identifies Novel Susceptibility Genes for Pediatric Venous Thrombosis,

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3336-3336 ◽  
Author(s):  
Astrid Arning ◽  
Milan Hiersche ◽  
Christoph Bidlingmaier ◽  
Monika Stoll ◽  
Ulrike Nowak-Gottl
Keyword(s):  
Venous Thrombosis ◽  
Association Studies ◽  
Snp Array ◽  
Independent Study ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Permutation Testing ◽  
Haplotype Association ◽  
Genome Wide ◽  
A Genome

Abstract Abstract 3336 Background: Genome wide association studies (GWAS) are the current method of choice to dissect the genetic basis of common complex diseases. Up-to-date, studies in families with a known first onset of symptomatic arterial or venous thrombosis (VT) in early childhood are lacking. Methods: Here, we performed a GWAS in a large family-based study sample comprising 241 nuclear families with pediatric VT using the Illumina 660W Infinium SNP array. The average genotype call rate was >99.5%, and the genomic inflation factor was a= 1.012. Single point and haplotype association was assessed using the Transmission Disequilibrium Test (TDT) as implemented in PLINK and FBAT, respectively, and corrected for multiple testing using permutation testing. In addition, associations were corrected for age, gender, and in a subsequent analysis for Factor VLeiden. Results and Conclusion: Four SNPs exceeded the threshold for genome wide significance in this dataset as determined by permutation testing using 100.000 bootstrap permutations (p<10−5), and are likely true associations. Among these, 2 SNPs reside in a region on chromosome 6q13 comprising the gene for beta-1,3-glucoronyltransferase 2 (B3GAT2), a member of the human natural killer 1 (HNK1) carbohydrate pathway are associated with pediatric VT with p-values for rs1304029 (p=3.42×10−6) and rs2748331 (p=6.92×10−6). The corresponding haplotype association test resulted in a p=5.37×10−6 for the GA-haplotype, further underlining the robustness of the association. The SNPs rs636434 on chromosome 6q12 and rs1565242 on chromosome 15 both reside within hypothetical genes and are associated with VT with a p=2.70×10−6 and p=8.24×10−6, respectively. Additional SNPs exceeding a p<10−5 are included in subsequent analyses looking at gene networks and replication in independent study samples including our second GWAS on pediatric thromboembolic stroke (TS). Future studies using larger study samples are warranted to validate these findings and to characterize the genetic architecture underlying VT and TS in children. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Genome-Wide Association Study of Meiotic Recombination Phenotypes

2016 ◽  
Vol 6 (12) ◽  
pp. 3995-4007 ◽  
Author(s):  
Ferdouse Begum ◽  
Reshmi Chowdhury ◽  
Vivian G Cheung ◽  
Stephanie L Sherman ◽  
Eleanor Feingold
Keyword(s):  
Meiotic Recombination ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Snp Array ◽  
Genome Wide Association ◽  
Chromosome 17 ◽  
Genome Wide Association Studies ◽  
Regulatory Variants ◽  
Genome Wide ◽  
Meta Analyses

Abstract Meiotic recombination is an essential step in gametogenesis, and is one that also generates genetic diversity. Genome-wide association studies (GWAS) and molecular studies have identified genes that influence of human meiotic recombination. RNF212 is associated with total or average number of recombination events, and PRDM9 is associated with the locations of hotspots, or sequences where crossing over appears to cluster. In addition, a common inversion on chromosome 17 is strongly associated with recombination. Other genes have been identified by GWAS, but those results have not been replicated. In this study, using new datasets, we characterized additional recombination phenotypes to uncover novel candidates and further dissect the role of already known loci. We used three datasets totaling 1562 two-generation families, including 3108 parents with 4304 children. We estimated five different recombination phenotypes including two novel phenotypes (average recombination counts within recombination hotspots and outside of hotspots) using dense SNP array genotype data. We then performed gender-specific and combined-sex genome-wide association studies (GWAS) meta-analyses. We replicated associations for several previously reported recombination genes, including RNF212 and PRDM9. By looking specifically at recombination events outside of hotspots, we showed for the first time that PRDM9 has different effects in males and females. We identified several new candidate loci, particularly for recombination events outside of hotspots. These include regions near the genes SPINK6, EVC2, ARHGAP25, and DLGAP2. This study expands our understanding of human meiotic recombination by characterizing additional features that vary across individuals, and identifying regulatory variants influencing the numbers and locations of recombination events.

scholarly journals Development of the catfish 250K SNP array for genome-wide association studies

2014 ◽  
Vol 7 (1) ◽  
pp. 135 ◽  
Author(s):  
Shikai Liu ◽  
Luyang Sun ◽  
Yun Li ◽  
Fanyue Sun ◽  
Yanliang Jiang ◽  
...  
Keyword(s):  
Association Studies ◽  
Snp Array ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Population structure and genome-wide association studies in bread wheat for phosphorus efficiency traits using 35 K Wheat Breeder’s Affymetrix array

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Preman R. Soumya ◽  
Amanda J. Burridge ◽  
Nisha Singh ◽  
Ritu Batra ◽  
Renu Pandey ◽  
...  
Keyword(s):  
Bread Wheat ◽  
Genome Wide Association Study ◽  
Polymorphic Information Content ◽  
Association Studies ◽  
Snp Array ◽  
Genome Wide Association ◽  
Phosphorus Efficiency ◽  
Genome Wide Association Studies ◽  
P Efficiency ◽  
Genome Wide

AbstractSoil bioavailability of phosphorus (P) is a major concern for crop productivity worldwide. As phosphatic fertilizers are a non-renewable resource associated with economic and environmental issues so, the sustainable option is to develop P use efficient crop varieties. We phenotyped 82 diverse wheat (Triticum aestivum L.) accessions in soil and hydroponics at low and sufficient P. To identify the genic regions for P efficiency traits, the accessions were genotyped using the 35 K-SNP array and genome-wide association study (GWAS) was performed. The high-quality SNPs across the genomes were evenly distributed with polymorphic information content values varying between 0.090 and 0.375. Structure analysis revealed three subpopulations (C1, C2, C3) and the phenotypic responses of these subpopulations were assessed for P efficiency traits. The C2 subpopulation showed the highest genetic variance and heritability values for numerous agronomically important traits as well as strong correlation under both P levels in soil and hydroponics. GWAS revealed 78 marker-trait associations (MTAs) but only 35 MTAs passed Bonferroni Correction. A total of 297 candidate genes were identified for these MTAs and their annotation suggested their involvement in several biological process. Out of 35, nine (9) MTAs were controlling polygenic trait (two controlling four traits, one controlling three traits and six controlling two traits). These multi-trait MTAs (each controlling two or more than two correlated traits) could be utilized for improving bread wheat to tolerate low P stress through marker-assisted selection (MAS).

scholarly journals Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods

2021 ◽  
Vol 12 ◽  
Author(s):  
Mohsen Yoosefzadeh-Najafabadi ◽  
Sepideh Torabi ◽  
Dan Tulpan ◽  
Istvan Rajcan ◽  
Milad Eskandari
Keyword(s):  
Data Integration ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Hierarchical Data ◽  
Hyperspectral Reflectance ◽  
Integration Strategy ◽  
Breeding Populations ◽  
Genome Wide ◽  
Genome Association

In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.

Sign in / Sign up

Export Citation Format

Share Document