Genome-wide Association Approach Research Articles

Identification of single-nucleotide variants associated with susceptibility to Salmonella in pigs using a genome-wide association approach

BackgroundSalmonella enterica serovars are a major cause of foodborne illness and have a substantial impact on global human health. In Canada, Salmonella is commonly found on swine farms and the increasing concern about drug use and antimicrobial resistance associated with Salmonella has promoted research into alternative control methods, including selecting for pig genotypes associated with resistance to Salmonella. The objective of this study was to identify single-nucleotide variants in the pig genome associated with Salmonella susceptibility using a genome-wide association approach. Repeated blood and fecal samples were collected from 809 pigs in 14 groups on farms and tonsils and lymph nodes were collected at slaughter. Sera were analyzed for Salmonella IgG antibodies by ELISA and feces and tissues were cultured for Salmonella. Pig DNA was genotyped using a custom 54 K single-nucleotide variant oligo array and logistic mixed-models used to identify SNVs associated with IgG seropositivity, shedding, and tissue colonization.ResultsVariants in/near PTPRJ (p = 0.0000066), ST6GALNAC3 (p = 0.0000099), and DCDC2C (n = 3, p < 0.0000086) were associated with susceptibility to Salmonella, while variants near AKAP12 (n = 3, p < 0.0000358) and in RALGAPA2 (p = 0.0000760) may be associated with susceptibility.ConclusionsFurther study of the variants and genes identified may improve our understanding of neutrophil recruitment, intracellular killing of bacteria, and/or susceptibility to Salmonella and may help future efforts to reduce Salmonella on-farm through genetic approaches.

A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank.

BackgroundCommon types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK.MethodsA genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication.ResultsWe identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10−11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10−10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10−8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively).ConclusionsWe have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

Identify New Genetic Variants on Chromosome 6 Associated with Mortality after Heart Transplantation

Graft failure in heart transplant recipients is still the leading cumulative cause of death, rejection related injuries likely being an important contributor. In this study we used a genome-wide association approach using whole-genome data from chromosome 6 to analyze genetic associations with survival after heart transplantation. The study included recipient samples from patients who had undergone heart transplantation at Skane University Hospital, Lund, Sweden, between 1988 and 2009. Patients with at least one grade 3 rejection episode and/or survival <10 years were included, as well as individuals in control group with no grade 3 rejection episodes or survival >10 years. Endomyocardial biopsies were sent to the Broad Institute for DNA extraction and whole-genome sequencing. Variant calling and variant recalibration and filtering was conducted with the Genome Analysis Toolkit (GATK). A genome-wide association analysis using PLINK utilizing allelic association using chi-square test was performed. Genome-wide association analysis was conducted on a total of 34 patients using 470502 single nucleotide variants on chromosome 6. Thirteen associations yielded p > 1 × 10-5. We found 3 variants associated with mortality and after heart transplantation, rs66723041 (1.88 × 10-6), rs68123256 (6.28 × 10-6) and rs66758173 (6.28 × 10-6) in the gene HLA-DRB6. This first of its kind genome-wide association analysis demonstrates genetic variants associated with mortality and survival after heart transplantation. No association attained genome-wide significance, but several intriguing findings emerged. Notably, a cluster of low p-value SNVs were observed at HLA-DRB6 associated with mortality after heart transplantation. Genetic approaches such as these may lead to the identification of novel biological pathways and the development of new pharmaceutical targets and biomarkers.

Importance of genetic polymorphisms in liver transplantation outcomes.

Although, liver transplantation serves as the only curative treatment for patients with end-stage liver diseases, it is burdened with complications, which affect survival rates. In addition to clinical risk factors, contribution of recipient and donor genetic prognostic markers has been extensively studied in order to reduce the burden and improve the outcomes. Determination of single nucleotide polymorphisms (SNPs) is one of the most important tools in development of personalized transplant approach. To provide a better insight in recent developments, we review the studies published in the last three years that investigated an association of recipient or donor SNPs with most common issues in liver transplantation: Acute cellular rejection, development of new-onset diabetes mellitus and non-alcoholic fatty liver disease, hepatocellular carcinoma recurrence, and tacrolimus concentration variability. Reviewed studies confirmed previously established SNP prognostic factors, such as PNPLA3 rs738409 for non-alcoholic fatty liver disease development, or the role of CYP3A5 rs776746 in tacrolimus concentration variability. They also identified several novel SNPs, with a reasonably strong association, which have the potential to become useful predictors of post-transplant complications. However, as the studies were typically conducted in one center on relatively low-to-moderate number of patients, verification of the results in other centers is warranted to resolve these limitations. Furthermore, of 29 reviewed studies, 28 used gene candidate approach and only one implemented a genome wide association approach. Genome wide association multicentric studies are needed to facilitate the development of personalized transplant medicine.

Alleles to Enhance Antioxidant Content in Maize-A Genome-Wide Association Approach.

The interest in antioxidant compound breeding in maize (Zea mays L.), a major food crop, has increased in recent years. However, breeding of antioxidant compounds in maize can be hampered, given the complex genetic nature of these compounds. In this work, we followed a genome-wide association approach, using a unique germplasm collection (containing Portuguese germplasm), to study the genetic basis of several antioxidants in maize. Sixty-seven genomic regions associated with seven antioxidant compounds and two color-related traits were identified. Several significant associations were located within or near genes involved in the carotenoid (Zm00001d036345) and tocopherol biosynthetic pathways (Zm00001d017746). Some indications of a negative selection against α-tocopherol levels were detected in the Portuguese maize germplasm. The strongest single nucleotide polymorphism (SNP)-trait associations and the SNP alleles with larger effect sizes were pinpointed and set as priority for future validation studies; these associations detected now constitute a benchmark for developing molecular selection tools for antioxidant compound selection in maize.

Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering.

When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred “Flint-Dent” panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.

Genetic architecture of photosynthesis energy partitioning as revealed by a genome-wide association approach.

The photosynthesis process is determined by the intensity level and spectral quality of the light; therefore, leaves need to adapt to a changing environment. The incident energy absorbed can exceed the sink capability of the photosystems, and, in this context, photoinhibition may occur in both photosystem II (PSII) and photosystem I (PSI). Quantum yield parameters analyses reveal how the energy is managed. These parameters are genotype-dependent, and this genotypic variability is a good opportunity to apply mapping association strategies to identify genomic regions associated with photosynthesis energy partitioning. An experimental and mathematical approach is proposed for the determination of an index which estimates the energy per photon flux for each spectral bandwidth (Δλ) of the light incident (QI index). Based on the QI, the spectral quality of the plant growth, environmental lighting, and the actinic light of PAM were quantitatively very similar which allowed an accurate phenotyping strategy of a rice population. A total of 143 genomic single regions associated with at least one trait of chlorophyll fluorescence were identified. Moreover, chromosome 5 gathers most of these regions indicating the importance of this chromosome in the genetic regulation of the photochemistry process. Through a GWAS strategy, 32 genes of rice genome associated with the main parameters of the photochemistry process of photosynthesis in rice were identified. Association between light-harvesting complexes and the potential quantum yield of PSII, as well as the relationship between coding regions for PSI-linked proteins in energy distribution during the photochemical process of photosynthesis is analyzed.

Genetics of Circadian and Sleep Measures in Adults: Implications for Sleep Medicine

In this review, we comprehensively discuss recent reports of heritability and genetic associations using candidate gene and genome-wide association (GWA) approaches in circadian and sleep phenotypes in adults, including chronotype (morningness-eveningness), sleep duration and daytime sleepiness, circadian rhythm sleep-wake disorders, and insomnia. Recent findings derive from GWA studies with objective measures and candidate gene studies examining the role of genetic ancestry and health disparities for sleep and circadian measures. The discovery of key, novel genetic markers using various methods has critical implications for future research in terms of identification, treatment, and countermeasures in the field of sleep medicine.

Identifying Drug Sensitivity Subnetworks with NETPHIX

Phenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. One of the important challenges in the area is to predict drug response on a personalized level and to understand the causes of different responses. The pathway-centric view of cancer significantly advanced the understanding of genotype-phenotype relationships. However, most network module identification methods in cancer focus on identifying subnetworks that include general cancer drivers, hence cannot be applied directly for the analysis of continuous features like drug response. On the other hand, existing genome wide association approaches or drug response prediction algorithms do not fully utilize the complex properties of cancer mutational landscape and cannot pinpoint the genetic alterations that are causal to drug sensitivity. To address these challenges, we developed a computational method, named NETPHIX (NETwork-to-PHenotype assocIation with eXclusivity), which aims to identify subnetworks of genes whose genetic alterations are associated with a continuous cancer phenotype. Leveraging the properties of cancer mutations and the interactions among genes, we formulate the problem as an integer linear program and solve it optimally to obtain a subnetwork of associated genes. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with drug responses. Utilizing interaction in formation among genes, NETPHIX modules are functionally coherent, and can thus provide important insights into drug action.

Germline Variation Predicts Treatment Response in Multiple Myeloma

Background: Multiple myeloma (MM) treatment has advanced considerably with proteasome inhibitors, immunomodulatory drugs (IMiDs), and, most recently, monoclonal antibodies. However, treatment response is quite heterogeneous, and many patients still progress even with novel combination therapies. Thus, understanding the factors that underlie response to treatment is a priority. Several somatic genomic aberrations and mutations predict poor response to therapy. However, germline variation has not previously been investigated as a predictor of treatment response in MM. We used genome-wide association and transcriptome-wide association approaches to identify germline genetic predictors of treatment response in MM. Methods: We included 510 MM patients from Mayo Clinic and 324 MM patients from UCSF diagnosed from 1999-2015. Basic demographics, laboratory values and pathology at diagnosis, type of initial therapy, duration of therapy, and follow-up were ascertained by chart review. Patients were grouped into categories of treatment based on their first line therapy: proteasome inhibitor-based regimen, IMiD based regimen, combination proteasome and IMiD based regimen, or other. Response was assessed using International Myeloma Working Group (IMWG) response criteria after 4-6 cycles of induction. As such, response was categorized into progressive disease (PD), minimal response (MR), partial response (PR), very good partial response (VGPR), or complete response (CR). Germline samples were genotyped using Illumina or Affymetrix arrays and were imputed based on the Haplotype Reference Consortium (HRC). For the genome-wide association study (GWAS), we included all SNPs with minor allele frequency &gt;0.01 and imputation r2 of &gt;0.5. We tested each SNP for association with treatment response using a linear regression model that adjusted for age, gender, and genetic ancestry (from principal components analysis (PCA)). To perform the transcriptome-wide association study (TWAS), we calculated predicted gene expression data using PREDIXCAN software on a reference cohort of 922 individuals with genotype and RNA expression data from peripheral blood. We then tested the association between predicted gene expression and response to therapy using linear regression models. Both the GWAS and TWAS were performed on subgroups of patients who received either proteasome inhibitors or IMiD therapies. The analyses of patients on proteasome inhibitors were adjusted for IMiD use as a covariate and analyses of patients on IMiDs were adjusted for proteasome inhibitor use. The threshold for genome-wide significance loci was set at P = 5 x 10-8 and the threshold for suggestive loci was set at P = 10-6. The threshold for significance for TWAS was set at P = 4 x 10-6 by using a Bonferroni correction for the number of genes for which genetic models of expression could be developed by PREDIXCAN. Results: Overall, 42.7% (59 of 138) of patients on proteasome inhibitors alone, 32.5% (66 of 203) of patients on IMiDs alone, and 58.1% (50 of 86) of patients on combination achieved at least a VGPR. There were no significant differences in response across centers in analyses that adjusted for age, sex and types of therapy. There were no genome wide significant loci to predict for response. We identified 8 suggestive SNPs associated with proteasome inhibitor response and 4 suggestive SNPs associated with IMiD response. TWAS identified ZNF622 as a candidate genetic modifier of proteasome inhibitor effect that was significant after correction for multiple hypothesis testing (P = 1.6 x 10-6). Higher genetically predicted expression was associated with improved response to proteasome inhibitor therapy. Among patients above the median of predicted expression of ZNF622 on proteasome inhibitors, 62.6% achieved at least VGPR; among patients at or below the median of expression, only 37.6% achieved at least VGPR. Conclusions: We identified an association between predicted expression of ZNF622 and clinical response to proteasome inhibitor therapy among MM patients. ZNF622 is a zinc finger binding protein which is known to be co-activator of B Myb activity and to affect apoptosis in response to oxidative stress. Our work highlights the potential importance of pharmacogenetic modifiers of treatment response in MM. Disclosures Shah: Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Indapta Therapeutics: Equity Ownership; University of California, San Francisco: Employment; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding; Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Poseida: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wong:Celgene: Research Funding; Janssen: Research Funding; Roche: Research Funding; Fortis: Research Funding. Martin:Roche and Juno: Consultancy; Amgen, Sanofi, Seattle Genetics: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding.

Lentivirus Susceptibility in Iranian and German Sheep Assessed by Determination of TMEM154 E35K.

Simple SummaryThere are no data on the effect of the transmembrane protein 154 (TMEM154) E35K variants on susceptibility to small ruminant lentivirus (SRLV) infection in Iranian sheep breeds, and only limited data for German sheep flocks. This study aimed at investigating the association of TMEM154 variants and SRLV infection status in Iranian and German sheep flocks and breeds. Three out of the four analyzed sheep flocks/breeds showed a significant association between TMEM154 variants and SRLV prevalence. A complementary analysis was carried out based on regression analysis to test the relationship between frequency of the TMEM154 E allele and SRLV prevalence in different flocks/breeds. Results showed that the TMEM154 E allele frequencies could be useful for predicting genetic susceptibility to SRLV infection in a sheep flock or breed. Finally, the genetic susceptibility of different Iranian and German sheep breeds was compared based on the frequency of the TMEM154 E allele.Small ruminant lentiviruses (SRLVs) cause maedi-visna disease in sheep and are prevalent in Iran and Germany. The association of the transmembrane protein 154 (TMEM154) variants with SRLV infection has been previously identified by a genome-wide association (GWAS) approach and subsequent analyses, and validated in some US, German, and Turkish sheep flocks. We aimed at evaluating these findings for the first time in Iranian, and in some more German sheep flocks/breeds. Also, we aimed at comparing the SRLV susceptibility in Iranian and German sheep based on the frequency of the TMEM154 E35 allele. About 800 blood samples were collected from 21 Iranian and German sheep flocks/breeds for different purposes: (1) The association of TMEM154 E35K with SRLV infection status was tested in four sheep breeds and found to be significant in Kermani, Merinoland, and Brown Hair. (2) The usefulness of the TMEM154 E35 frequency for predicting SRLV susceptibility was evaluated by regression analysis, combining data from this study and some already published data. Results showed a significant association between E35 frequency and SRLV prevalence. (3) SRLV susceptibility was compared based on E35 frequency in Iranian and German sheep. Altogether, findings of this study provide valuable information on SRLV susceptibility, using TMEM154 E35, in Iranian and German sheep.

Genome-Wide Signatures of Selection in Colletotrichum kahawae Reveal Candidate Genes Potentially Involved in Pathogenicity and Aggressiveness.

Plants and their pathogens are engaged in continuous evolutionary battles, with pathogens evolving to circumvent plant defense mechanisms and plants responding through enhanced protection to prevent or mitigate damage induced by pathogen attack. Managed ecosystems are composed of genetically identical populations of crop plants with few changes from year to year. These environments are highly conducive to the emergence and dissemination of pathogens and they exert selective pressure for both qualitative virulence factors responsible for fungal pathogenicity, and quantitative traits linked to pathogen fitness, such as aggressiveness. In this study, we used a comparative genome-wide approach to investigate the genomic basis underlying the pathogenicity and aggressiveness of the fungal coffee pathogen Colletotrichum kahawae infecting green coffee berries. The pathogenicity was investigated by comparing genomic variation between C. kahawae and its non-pathogenic sibling species, while the aggressiveness was studied by a genome-wide association approach with groups of isolates with different phenotypic profiles. High genetic differentiation was observed between C. kahawae and the most closely related species with 5,560 diagnostic SNPs identified, in which a significant enrichment of non-synonymous mutations was detected. Functional annotation of these non-synonymous mutations revealed a significant enrichment mainly in two gene ontology categories, “oxidation–reduction process” and “integral component of membrane.” Finally, the annotation of several genes potentially under-selection revealed that C. kahawae’s pathogenicity may be a complex biological process, in which important biological functions, such as, detoxification and transport, regulation of host and pathogen gene expression, and signaling are involved. On the other hand, the genome-wide association analyses for aggressiveness were able to identify 10 SNPs and 15 SNPs of small effect in single and multi-association analysis, respectively, from which 7 were common, giving in total 18 SNPs potentially associated. The annotation of these genomic regions allowed the identification of four candidate genes encoding F-box domain-containing, nitrosoguanidine resistance, Fungal specific transcription factor domain-containing and C6 transcription factor that could be associated with aggressiveness. This study shed light, for the first time, on the genetic mechanisms of C. kahawae host specialization.

Genome-Wide Analyses Reveal Footprints of Divergent Selection and Drought Adaptive Traits in Synthetic-Derived Wheats.

Crop-wild introgressions have long been exploited without knowing the favorable recombination points. Synthetic hexaploid wheats are one of the most exploited genetic resources for bread wheat improvement. However, despite some QTL with major effects, much less is known about genome-wide patterns of introgressions and their effects on phenotypes. We used two genome-wide association approaches: SNP-GWAS and haplotype-GWAS to identify SNPs and haplotypes associated with productivity under water-limited conditions in a synthetic-derived wheat (SYN-DER) population. Haplotype-GWAS further enriched and identified 20 more genomic regions associated with drought adaptability that did not overlap with SNP-GWAS. Since GWAS is biased to the phenotypes in the study and may fail to detect important genetic diversity during breeding, we used five complementary analytical approaches (t-test, Tajima’s D, nucleotide diversity (π), Fst, and EigenGWAS) to identify divergent selections in SYN-DER compared to modern bread wheat. These approaches consistently pinpointed 89 ‘selective sweeps’, out of which 30 selection loci were identified on D-genome. These key selections co-localized with important functional genes of adaptive traits such as TaElf3-D1 (1D) for earliness per se (Eps), TaCKX-D1 (3D), TaGS1a (6D) and TaGS-D1 (7D) for grain size, weight and morphology, TaCwi-D1 (5D) influencing drought tolerance, and Vrn-D3 (7D) for vernalization. Furthermore, 55 SNPs and 23 haplotypes of agronomic and physiological importance such as grain yield, relative water content and thousand grain weight in SYN-DER, were among the top 5% of divergent selections contributed by synthetic hexaploid wheats. These divergent selections associated with improved agronomic performance carry new alleles that have been introduced to wheat. Our results demonstrated that GWAS and selection sweep analyses are powerful approaches for investigating favorable introgressions under strong selection pressure and the use of crop-wild hybridization to assist the improvement of wheat yield and productivity under moisture limiting environments.

Resolving Phylogenetic Relationships for Streptococcus mitis and Streptococcus oralis through Core- and Pan-Genome Analyses.

Taxonomic and phylogenetic relationships of Streptococcus mitis and Streptococcus oralis have been difficult to establish biochemically and genetically. We used core-genome analyses of S. mitis and S. oralis, as well as the closely related species Streptococcus pneumoniae and Streptococcus parasanguinis, to clarify the phylogenetic relationships between S. mitis and S. oralis, as well as within subclades of S. oralis. All S. mitis (n = 67), S. oralis (n = 89), S. parasanguinis (n = 27), and 27 S. pneumoniae genome assemblies were downloaded from NCBI and reannotated. All genes were delineated into homologous clusters and maximum-likelihood phylogenies built from putatively nonrecombinant core gene sets. Population structure was determined using Bayesian genome clustering, and patristic distance was calculated between populations. Population-specific gene content was assessed using a phylogenetic-based genome-wide association approach. Streptococcus mitis and S. oralis formed distinct clades, but species mixing suggests taxonomic misassignment. Patristic distance between populations suggests that S. oralis subsp. dentisani is a distinct species, whereas S. oralis subsp. tigurinus and subsp. oralis are supported as subspecies, and that S. mitis comprises two subspecies. None of the genes within the pan-genomes of S. mitis and S. oralis could be statistically correlated with either, and the dispensable genomes showed extensive variation among isolates. These are likely important factors contributing to established overlap in biochemical characteristics for these taxa. Based on core-genome analysis, the substructure of S. oralis and S. mitis should be redefined, and species assignments within S. oralis and S. mitis should be made based on whole-genome analysis to be robust to misassignment.

Genome-wide association study suggests impact of chromosome 10 rs139401390 on kidney function in patients with coronary artery disease

Chronic kidney disease (CKD) is an independent risk factor for onset and progression of coronary artery disease (CAD). Discovery of predisposing loci for kidney function in CAD patients was performed using a genome-wide association approach. Inclusion criteria were CAD with ≥50% stenosis (≥1 coronary artery) and a creatinine-based estimated glomerular filtration rate (eGFR) of 30–75 ml/min/1.73 m2. An association of rs139401390 located to a region 58.8 kb upstream of renalase (RNLS) with eGFR was detected in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study (n = 499, p = 7.88 × 10−9, mean eGFR 60.7 ml/min/1.73 m2). Direct genotyping of rs139401390A > G suggested increased eGFR by 12.0 ml/min/1.73 m2 per A allele (p = 0.000004). Genome-wide replication of rs139401390A > G in the Coronary Artery Disease and Renal Failure (CAD-REF) registry with a mean eGFR of 47.8 ml/min/1.73 m2 (n = 574, p = 0.033) was only nominally significant. Comparison of rs139401390 genotypes for risk of reduced kidney function in the overall LURIC study revealed higher adjusted odds ratios (OR) for eGFR <60 ml/min/1.73 m2 for CAD patients (n = 1992, OR = 2.36, p = 0.008, G/A + G/G vs A/A) compared to patients with/without CAD (n = 2908, OR = 1.97, p = 0.014, G/A + G/G vs A/A). No significant risk elevation was detected in patients without CAD (n = 948, p = 0.571). rs139401390 may affect kidney function in CAD patients with mild reduction in eGFR.

Genome-wide association study of berry-related traits in grape [Vitis vinifera L.] based on genotyping-by-sequencing markers

ABSTRACTDeciphering the genetic control of grape berry traits is crucial for optimizing yield, fruit quality, and consumer acceptability. In this study, an association panel of 179 grape genotypes comprising a mixture of ancient cultivars, landraces, and modern varieties collected worldwide were genotyped with genotyping-by-sequencing using a genome-wide association approach based on 32,311 single-nucleotide polymorphism (SNP) markers. Genome-wide efficient mixed-model association was selected as the optimal statistical model based on the results of known control loci of grape berry color traits. Many of the associated SNPs identified in this study were in accordance with the previous QTL analyses using biparental mapping. The grape skin color locus was found to be associated with a mybA transcription factor on chromosome 2. Two strong and distinct association signals associated with berry development periods were found on chromosome 16. Most candidate genes of the interval were highlighted as receptor-like protein kinase. For berry weight, significant association loci were identified on chromosome 18, as previously known, and on chromosome 19 and chromosome 17, as newly mapped. Berry flesh texture was newly located on chromosome 16; candidate genes in the interval were related to calcium. Berry flavor was determined on chromosome 5. Genomic regions were further investigated to reveal candidate genes. In this work, we identified interesting genetic determinants of grape berry-related traits. The identification of the markers closely associated with these berry traits may be useful for grape molecular breeding.

Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes.

Although oat cultivation around the Mediterranean basin is steadily increasing, its yield in these regions lags far behind those of Northern Europe. This results mainly from the poor adaptation of current oat cultivars to Mediterranean environments. Local landraces may act as reservoirs of favorable traits that could contribute to increase oat resilience in this region. To aid selection of suitable agro-climate adapted genotypes we integrated genome-wide association approaches with analysis of field assessed phenotypes of genetic variants and of the weight of associated markers across different environmental variables. Association models accounting for oat population structure were applied on either arithmetic means or best linear unbiased prediction (BLUPs) to ensure robust identification of associations with the agronomic traits evaluated. The meta-analysis of the six joint environments (mega-environment) identified several markers associated with several agronomic traits and crown rust severity. Five of these associated markers were located within expressed genes. These associations were only mildly influenced by climatic variables indicating that these markers are good candidates to improve the genetic potential of oat under Mediterranean conditions. The models also highlighted several marker-trait associations, strongly affected by particular climatic variables including high rain pre- or post-heading dates and high temperatures, revealing strong potential for oat adaptation to specific agro-climatic conditions. These results will contribute to increase oat resilience for particular climatic conditions and facilitate breeding for plant adaptation to a wider range of climatic conditions in the current scenario of climate change.

Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes

Genome wide association (GWA) analysis of brain imaging phenotypes can advance our understanding of the genetic basis of normal and disorder-related variation in the brain. GWA approaches typically use linear mixed effect models to account for non-independence amongst subjects due to factors, such as family relatedness and population structure. The use of these models with high-dimensional imaging phenotypes presents enormous challenges in terms of computational intensity and the need to account multiple testing in both the imaging and genetic domain. Here we present a method that makes mixed models practical with high-dimensional traits by a combination of a transformation applied to the data and model, and the use of a non-iterative variance component estimator. With such speed enhancements permutation tests are feasible, which allows inference on powerful spatial tests like the cluster size statistic.

Pleiotropic effects of regulatory variation in tan result in correlation of two pigmentation traits in Drosophila melanogaster.

Traits with a common genetic basis frequently display correlated phenotypic responses to selection or environmental conditions. In Drosophila melanogaster, pigmentation of the abdomen and a trident‐shaped region on the thorax are genetically correlated. Here, we used a pooled replicated genomewide association approach (Pool‐GWAS) to identify the genetic basis of variation in thoracic trident pigmentation in two Drosophila melanogaster populations. We confirmed the previously reported large effect of ebony and the association of the cosmopolitan inversion In(3R)Payne. For the first time, we identified tan as another major locus contributing to variation in trident pigmentation. Intriguingly, the regulatory variants of tan that were most strongly associated with female abdominal pigmentation also showed a strong association with trident pigmentation. We validated this common genetic basis in transgenic assays and found qualitatively similar effects on trident and abdominal pigmentation. Further work is required to determine whether this genetic correlation is favoured by natural selection or reflects a neutral by‐product of a shared regulatory architecture.

A Genetic Locus on Chromosome 2q24 Predicting Peripheral Neuropathy Risk in Type 2 Diabetes

Diabetic peripheral neuropathy (DPN) is a significant contributor to the increased morbidity associated with type 2 diabetes (T2D). However, the risk of developing DPN varies among T2D patients, possibly due to genetic factors. We aimed to identify genetic predictors of DPN using an unbiased genome-wide association (GWAS) approach in Action to Control Cardiovascular Risk in Diabetes (ACCORD)—a large trial of intensive glycemic control in subjects with T2D and high CVD risk. Occurrence of DPN was defined as a clinical Michigan Neuropathy Screening Instrument (MNSI) score &amp;gt;2.0 at baseline or during follow-up. Using logistic regression, we conducted a GWAS, testing 6.8 million common single nucleotide polymorphisms (SNPs) among 4,384 DPN cases and 784 DPN-negative controls of white origin for whom genetic data were available. A locus on chromosome 2q24 reached GWAS significance (p=1.9×10-9). The minor allele of the lead SNP (rs13417783, minor allele frequency=0.14) decreased DPN odds by 36% (OR 0.64, 95% CI 0.59-0.69)—an effect not influenced by the glycemic treatment assignment (p for interaction=0.6). Adjacent to this SNP lies a cluster of genes coding for human voltage-gated sodium channels (SCN1A, SCN2A, SCN3A, SCN7A, and SCN9A) that are expressed in neurons and are mutated in monogenic forms of peripheral neuropathy and epilepsy. In an expression quantitative trait locus (eQTL) analysis, the minor (protective) allele of this SNP was associated with higher expression of SCN2A (P=0.0009) in tibial nerve. Other loci reaching notable significance (p≤1×10-6) were 8p23 in the gene CSMD1, previously implicated in epilepsy, and 11q25 in OPCML, an opioid-binding protein. In summary, we have discovered a novel genetic locus predicting DPN risk. Pending further investigation, these findings may provide better mechanistic insights into the pathophysiology of DPN, hopefully leading to the development of novel pharmacological interventions to prevent or treat this diabetic complication. Disclosure Y. Tang: None. J. Mychaleckyj: None. B.A. Perkins: Advisory Panel; Self; Boehringer Ingelheim GmbH. Research Support; Self; Boehringer Ingelheim GmbH, Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Abbott. Speaker's Bureau; Self; Abbott, Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Insulet Corporation. Speaker's Bureau; Self; Insulet Corporation, Dexcom, Inc. R. Pop-Busui: Research Support; Self; AstraZeneca. M.J. Wagner: None. A. Motsinger-Reif: None. J.B. Buse: Other Relationship; Self; ADOCIA, AstraZeneca, Dexcom, Inc., Elcelyx Therapeutics, Inc., Eli Lilly and Company, Fractyl Laboratories, Inc., Intarcia Therapeutics, Inc., Lexicon Pharmaceuticals, Inc., Metavention, NovaTarg, Novo Nordisk A/S, Sanofi, VTV Therapeutics. Research Support; Self; Boehringer Ingelheim GmbH, Johnson &amp; Johnson Services, Inc., Theracos, Inc.. Other Relationship; Self; Shenzhen Hightide Biopharmaceutical, Ltd.. Research Support; Self; National Heart, Lung, and Blood Institute, National Center for Advancing Translational Sciences. Other Relationship; Self; National Institute of Diabetes and Digestive and Kidney Diseases, American Diabetes Association. Research Support; Self; Patient-Centered Outcomes Research Institute. Other Relationship; Self; National Institute of Environmental Health Sciences. H. Shah: None. A. Doria: Research Support; Self; Sanofi-Aventis.