Efficient Mixed-model Association eXpedited Research Articles

A metabolomics study in citrus provides insight into bioactive phenylpropanoid metabolism.

Abstract Citrus fruits are widely consumed worldwide in juices or as fresh and provide a broad range of phytonutrients that are important for human health. Here, a citrus multi-omics resource is presented: comprehensive metabolic profiling of various citrus species was performed and metabolic profiles were compared among species, with a focus on the phenylpropanoid metabolic pathway. A metabolite-based genome-wide association analysis (mGWAS) of 154 pummelo accessions was performed using factored spectrally transformed linear mixed models (FaST-LMM) and efficient mixed-model association eXpedited (EMMAX), and the genetic and biochemical basis of metabolomic variation was comprehensively analysed. A metabolite-single nucleotide polymorphism-gene (metabolite-SNP-gene) interaction network was constructed for pummelo, and many candidate loci controlling the synthesis and regulation of bioactive compounds were identified; among these loci, three BAHD malonyltransferases were involved in the malonylation of flavonoid glycosides. Further investigation revealed that an R2R3-MYB transcription factor CgMYB1 positively controls the metabolism of phenylpropanoid molecules, particularly the flavonoid derivatives. This study provides valuable data resources on the metabolic regulatory networks of bioactive components in citrus, in addition to demonstrating an efficient method for metabolic pathway dissection and providing targets for future breeding work with the aim of improving nutritional value.

Genome-wide association study of feed conversion ratio in turbot (Scophthalmus maximus) based on genome resequencing

The feed conversion rate (FCR) is a crucial economic trait in aquaculture fish, as feed costs account for the vast majority of aquaculture costs. Given the importance of this trait, there have little efforts to unravel the genomic architecture of FCR and identify key genes or genomic regions useful as selection makers. This situation may stem from the inherent swimming behavior of fish, which presents challenges in obtaining individual FCRs. In this work, we developed a specialized small cage culture system. Through this system, the Feed Conversion Ratio (FCR) of 300 individuals was successfully determined, marking the first successful determination of individual FCRs for turbot. The results revealed a range of FCR values from 35.3% to 192.6%, with an average of 126.5% ± 23.5%. On this basis, a genome-wide association study (GWAS) was conducted to identify single nucleotide polymorphisms (SNP) associated with FCR. A total of 2613,115 SNPs on 22 chromosomes were selected for GWAS analysis by Efficient Mixed-Model Association eXpedited (EMMAX) software. A linear mixed model was employed to test the association between each SNP and FCR, considering population structure and genetic relatedness among individuals. Two significant SNPs on Chr6 were identified to be correlated with FCR. According to their localization in genome, four candidate genes were identified on Chr6, including uncharacterized protein KIAA1755, Kinesin Family Member 21B (KIF21B), Discs large homolog-associated protein 4B (DLGAP4B), and Copine 5B (CPNE5B), all of which are closely located in the genome and exhibit significant functional similarities. Our results will facilitate the implementation of marker-assisted selection in breeding programs and serve as a foundation for future research in this area.

GWAS resolves molecular mechanisms underlying natural variation for carotenoids in Cucurbita maxima Duchesne

Carotenoid levels and composition are essential nutraceutical traits in Cucurbita maxima influencing the fruit flesh and rind colors. In this study, Mr Fugly, Boston Marrow, Baby Green Hubbard, Chicago Warted Hubbard, Golden Hubbard, and Bush Buttercup of USA; Australian Butter (Australia); Marmellata and Marina di Chioggia of Italy contained the highest carotenoid content. EMMAX (Efficient Mixed-Model Association eXpedited) was employed for a Genome-wide association study (GWAS) to identify associated genomic regions underlying the regulation of carotenoids. Here, we profiled the contents of α-carotene, β-carotene, β-cryptoxanthin, lutein, and zeaxanthin from a diversity panel of C. maxima consisting of classical horticulture groups including buttercup, turban, banana, zapallito, hubbard, mammoth and australian. Lutein and β-carotene were the major carotenoids among C. maxima accessions. Furthermore, we used genotyping by sequencing to identify 12,996 single nucleotide polymorphisms (SNPs) that were used to resolve population structure with three primary clusters and their admixed genotypes. Our GWAS revealed several SNPs related to 289 genes involved in plastid biogenesis, protein ubiquitination, transcriptional regulation at the carotenoid biosynthesis level, fruit ripening, and regulation of carotenoid transport. Together, these results contribute to a better understanding of the molecular mechanisms of carotenoid biosynthesis in fruit flesh and would facilitate breeding for enhanced carotenoids in winter squashes.

Genome-wide hierarchical mixed model association analysis.

In genome-wide mixed model association analysis, we stratified the genomic mixed model into two hierarchies to estimate genomic breeding values (GBVs) using the genomic best linear unbiased prediction and statistically infer the association of GBVs with each SNP using the generalized least square. The hierarchical mixed model (Hi-LMM) can correct confounders effectively with polygenic effects as residuals for association tests, preventing potential false-negative errors produced with genome-wide rapid association using mixed model and regression or an efficient mixed-model association expedited (EMMAX). Meanwhile, the Hi-LMM performs the same statistical power as the exact mixed model association and the same computing efficiency as EMMAX. When the GBVs have been estimated precisely, the Hi-LMM can detect more quantitative trait nucleotides (QTNs) than existing methods. Especially under the Hi-LMM framework, joint association analysis can be made straightforward to improve the statistical power of detecting QTNs.

Identifying Loci Associated With Bovine Corona Virus Infection and Bovine Respiratory Disease in Dairy and Feedlot Cattle

Bovine coronavirus (BCoV) is associated with respiratory and enteric infections in both dairy and beef cattle worldwide. It is also one of a complex of pathogens associated with bovine respiratory disease (BRD), which affects millions of cattle annually. The objectives of this study were to identify loci and heritability estimates associated with BCoV infection and BRD in dairy calves and feedlot cattle. Dairy calves from California (n = 1,938) and New Mexico (n = 647) and feedlot cattle from Colorado (n = 915) and Washington (n = 934) were tested for the presence of BCoV when classified as BRD cases or controls following the McGuirk scoring system. Two comparisons associated with BCoV were investigated: (1) cattle positive for BCoV (BCoV+) were compared to cattle negative for BCoV (BCoV−) and (2) cattle positive for BCoV and affected with BRD (BCoV+BRD+) were compared to cattle negative for BCoV and BRD (BCoV−BRD−). The Illumina BovineHD BeadChip was used for genotyping, and genome-wide association analyses (GWAA) were performed using EMMAX (efficient mixed-model association eXpedited). The GWAA for BCoV+ identified 51 loci (p < 1 × 10−5; 24 feedlot, 16 dairy, 11 combined) associated with infection with BCoV. Three loci were associated with BCoV+ across populations. Heritability estimates for BCoV+ were 0.01 for dairy, 0.11 for feedlot cattle, and 0.03 for the combined population. For BCoV+BRD+, 80 loci (p < 1 × 10−5; 26 feedlot, 25 dairy, 29 combined) were associated including 14 loci across populations. Heritability estimates for BCoV+BRD+ were 0.003 for dairy, 0.44 for feedlot cattle, and 0.07 for the combined population. Several positional candidate genes associated with BCoV and BRD in this study have been associated with other coronaviruses and respiratory infections in humans and mice. These results suggest that selection may reduce susceptibility to BCoV infection and BRD in cattle.

Genome-Wide Association Study (GWAS) of dental caries in diverse populations

BackgroundDental caries is one of the most common chronic diseases and is influenced by a complex interplay of genetic and environmental factors. Most previous genetic studies of caries have focused on identifying genes that contribute to dental caries in specific ethnic groups, usually of European descent.MethodsThe aim of this study is to conduct a genome-wide association study (GWAS) to identify associations affecting susceptibility to caries in a large multiethnic population from Argentina, the Philippines, Guatemala, Hungary, and the USA, originally recruited for studies of orofacial clefts (POFC, N = 3686). Ages of the participants ranged from 2 to 12 years for analysis of the primary dentition, and 18–60 years for analysis of the permanent dentition. For each participant, dental caries was assessed by counts of decayed and filled teeth (dft/DFT) and genetic variants (single nucleotide polymorphisms, SNPs) were genotyped or imputed across the entire genome. Caries was analyzed separately for the primary and permanent dentitions, with age, gender, and presence/absence of any type of OFC treated as covariates. Efficient Mixed-Model Association eXpedited (EMMAX) was used to test genetic association, while simultaneously accounting for relatedness and stratification.ResultsWe identified several suggestive loci (5 × 10−8 < P < 5 × 10−6) within or near genes with plausible biological roles for dental caries, including a cluster of taste receptor genes (TAS2R38, TAS2R3, TAS2R4, TASR25) on chromosome 7 for the permanent dentition analysis, and DLX3 and DLX4 on chromosome 17 for the primary dentition analysis. Genome-wide significant results were seen with SNPs in the primary dentition only; however, none of the identified genes near these variants have known roles in cariogenesis.ConclusionThe results of this study warrant further investigation and may lead to a better understanding of cariogenesis in diverse populations, and help to improve dental caries prediction, prevention, and/or treatment in future.

Accounting for Population Structure and Phenotypes From Relatives in Association Mapping for Farm Animals: A Simulation Study.

Population structure or genetic relatedness should be considered in genome association studies to avoid spurious association. The most used methods for genome-wide association studies (GWAS) account for population structure but are limited to genotyped individuals with phenotypes. Single-step GWAS (ssGWAS) can use phenotypes from non-genotyped relatives; however, its ability to account for population structure has not been explored. Here we investigate the equivalence among ssGWAS, efficient mixed-model association expedited (EMMAX), and genomic best linear unbiased prediction GWAS (GBLUP-GWAS), and how they differ from the single-SNP analysis without correction for population structure (SSA-NoCor). We used simulated, structured populations that mimicked fish, beef cattle, and dairy cattle populations with 1040, 5525, and 1,400 genotyped individuals, respectively. Larger populations were also simulated that had up to 10-fold more genotyped animals. The genomes were composed by 29 chromosomes, each harboring one QTN, and the number of simulated SNPs was 35,000 for the fish and 65,000 for the beef and dairy cattle populations. Males and females were genotyped in the fish and beef cattle populations, whereas only males had genotypes in the dairy population. Phenotypes for a trait with heritability varying from 0.25 to 0.35 were available in both sexes for the fish population, but only for females in the beef and dairy cattle populations. In the latter, phenotypes of daughters were projected into genotyped sires (i.e., deregressed proofs) before applying EMMAX and SSA-NoCor. Although SSA-NoCor had the largest number of true positive SNPs among the four methods, the number of false negatives was two–fivefold that of true positives. GBLUP-GWAS and EMMAX had a similar number of true positives, which was slightly smaller than in ssGWAS, although the difference was not significant. Additionally, no significant differences were observed when deregressed proofs were used as pseudo-phenotypes in EMMAX compared to daughter phenotypes in ssGWAS for the dairy cattle population. Single-step GWAS accounts for population structure and is a straightforward method for association analysis when only a fraction of the population is genotyped and/or when phenotypes are available on non-genotyped relatives.

Hierarchical mixed-model expedites genome-wide longitudinal association analysis.

A hierarchical random regression model (Hi-RRM) was extended into a genome-wide association analysis for longitudinal data, which significantly reduced the dimensionality of repeated measurements. The Hi-RRM first modeled the phenotypic trajectory of each individual using a RRM and then associated phenotypic regressions with genetic markers using a multivariate mixed model (mvLMM). By spectral decomposition of genomic relationship and regression covariance matrices, the mvLMM was transformed into a multiple linear regression, which improved computing efficiency while implementing mvLMM associations in efficient mixed-model association expedited (EMMAX). Compared with the existing RRM-based association analyses, the statistical utility of Hi-RRM was demonstrated by simulation experiments. The method proposed here was also applied to find the quantitative trait nucleotides controlling the growth pattern of egg weights in poultry data.

RMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool for Genome-wide Association Study

Along with the development of high-throughput sequencing technologies, both sample size and SNP number are increasing rapidly in genome-wide association studies (GWAS), and the associated computation is more challenging than ever. Here, we present a memory-efficient, visualization-enhanced, and parallel-accelerated R package called “rMVP” to address the need for improved GWAS computation. rMVP can 1) effectively process large GWAS data, 2) rapidly evaluate population structure, 3) efficiently estimate variance components by Efficient Mixed-Model Association eXpedited (EMMAX), Factored Spectrally Transformed Linear Mixed Models (FaST-LMM), and Haseman-Elston (HE) regression algorithms, 4) implement parallel-accelerated association tests of markers using general linear model (GLM), mixed linear model (MLM), and fixed and random model circulating probability unification (FarmCPU) methods, 5) compute fast with a globally efficient design in the GWAS processes, and 6) generate various visualizations of GWAS-related information. Accelerated by block matrix multiplication strategy and multiple threads, the association test methods embedded in rMVP are significantly faster than PLINK, GEMMA, and FarmCPU_pkg. rMVP is freely available at https://github.com/xiaolei-lab/rMVP.

10 Can single-step genome-wide association analysis (ssGWAA) account for population structure?

Abstract Several methods are available for genome-wide association analysis, including the classical GWAA (cGWAA) based on fixed, single-SNP regression; efficient mixed-model association expedited (EMMAX) that fits single-SNP regressions together with a relationship matrix to account for population structure; and single-step GWAA (ssGWAA) where all data, including non-genotyped animals, are used. The objectives of this study were to: 1) investigate the ability of ssGWAA to account for population structure and correctly identify quantitative trait nucleotides (QTN); and 2) compare ssGWAA with cGWAA and EMMAX. Three simulated datasets were used, which mimic fish, beef cattle, and dairy cattle populations. The fish population was composed of 2,040 fish, out of which 1,040 were genotyped and had phenotypes for a trait with heritability of 0.25. The beef cattle population had 6,010 animals in the pedigree, but only 1,500 with phenotypes (h2 = 0.35) and genotypes. Lastly, the dairy cattle population had 40,800 pedigreed animals, of which 20,000 females had phenotypes (h2 = 0.32) and 2,400 males were genotyped. All phenotypes, pedigree, and genotypes were used in ssGWAA, whereas only genotypes and phenotypes were used in cGWAA and EMMAX for the fish and beef cattle analyses. For the dairy cattle analysis using the last two methods, deregressed proofs had to be used instead of phenotypes. The ability to correctly identify QTN and the number of statistically significant SNP (P &amp;lt; 0.05/number of SNP) was assessed among methods. In all populations, cGWAA was able to identify some of the strongest QTN but showed a large number of false positives. EMMAX and ssGWAA did not show false associations and correctly identified the top QTN, with more signals observed in ssGWAA. The ssGWAA accounts for population structure and is a proper association method, especially for livestock populations where sparse genotyping is a reality and phenotypes may not be recorded in genotyped animals.

Loci Associated With Antibody Response in Feral Swine (Sus scrofa) Infected With Brucella suis.

Feral swine (Sus scrofa) are a destructive invasive species widespread throughout the United States that disrupt ecosystems, damage crops, and carry pathogens of concern for the health of domestic stock and humans including Brucella suis—the causative organism for swine brucellosis. In domestic swine, brucellosis results in reproductive failure due to abortions and infertility. Contact with infected feral swine poses spillover risks to domestic pigs as well as humans, companion animals, wildlife, and other livestock. Genetic factors influence the outcome of infectious diseases; therefore, genome wide association studies (GWAS) of differential immune responses among feral swine can provide an understanding of disease dynamics and inform management to prevent the spillover of brucellosis from feral swine to domestic pigs. We sought to identify loci associated with differential antibody responses among feral swine naturally infected with B. suis using a case-control GWAS. Tissue, serum, and genotype data (68,516 bi-allelic single nucleotide polymorphisms) collected from 47 feral swine were analyzed in this study. The 47 feral swine were culture positive for Brucella spp. Of these 47, 16 were antibody positive (cases) whereas 31 were antibody negative (controls). Single-locus GWAS were performed using efficient mixed-model association eXpedited (EMMAX) methodology with three genetic models: additive, dominant, and recessive. Eight loci associated with seroconversion were identified on chromosome 4, 8, 9, 10, 12, and 18. Subsequent bioinformatic analyses revealed nine putative candidate genes related to immune function, most notably phagocytosis and induction of an inflammatory response. Identified loci and putative candidate genes may play an important role in host immune responses to B. suis infection, characterized by a detectable bacterial presence yet a differential antibody response. Given that antibody tests are used to evaluate brucellosis infection in domestic pigs and for disease surveillance in invasive feral swine, additional studies are needed to fully understand the genetic component of the response to B. suis infection and to more effectively translate estimates of Brucella spp. antibody prevalence among feral swine to disease control management action.

Natural variation in OsGASR7 regulates grain length in rice.

Natural variation in OsGASR7 regulates grain length in rice.

Identification of loci associated with conception rate in primiparous Holstein cows

BackgroundSubfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472).ResultsThe CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10− 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10− 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production.ConclusionsThe identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.

Validation of 46 loci associated with female fertility traits in cattle

BackgroundSubfertility is one challenge facing the dairy industry as the average Holstein heifer conception rate (HCR), the proportion of heifers that conceive and maintain a pregnancy per breeding, is estimated at 55–60%. Of the loci associated with HCR, few have been validated in an independent cattle population, limiting their usefulness for selection or furthering our understanding of the mechanisms involved in successful pregnancy. Therefore, the objectives here were to identify loci associated with HCR: 1) to the first artificial insemination (AI) service (HCR1), 2) to repeated AI services required for a heifer to conceive (TBRD) and 3) to validate loci previously associated with fertility. Breeding and health records from 3359 Holstein heifers were obtained after heifers were bred by AI at observed estrus, with pregnancy determined at day 35 via palpation. Heifer DNA was genotyped using the Illumina BovineHD BeadChip, and genome-wide association analyses (GWAA) were performed with additive, dominant and recessive models using the Efficient Mixed Model Association eXpedited (EMMAX) method with a relationship matrix for two phenotypes. The HCR1 GWAA compared heifers that were pregnant after the first AI service (n = 497) to heifers that were open following the first AI service (n = 405), which included those that never conceived. The TBRD GWAA compared only those heifers which did conceive, across variable numbers of AI service (n = 712). Comparison of loci previously associated with fertility, HCR1 or TBRD were considered the same locus for validation when in linkage disequilibrium (D’ > 0.7).ResultsThe HCR1 GWAA identified 116, 187 and 28 loci associated (P < 5 × 10− 8) in additive, dominant and recessive models, respectively. The TBRD GWAA identified 235, 362, and 69 QTL associated (P < 5 × 10− 8) with additive, dominant and recessive models, respectively. Loci previously associated with fertility were in linkage disequilibrium with 22 loci shared with HCR1 and TBRD, 5 HCR1 and 19 TBRD loci.ConclusionsLoci associated with HCR1 and TBRD that have been identified and validated can be used to improve HCR through genomic selection, and to better understand possible mechanisms associated with subfertility.

Genetics of heart rate in heart failure patients (GenHRate)

BackgroundElevated resting heart rate (HR) is a risk factor and therapeutic target in patients with heart failure (HF) and reduced ejection fraction (HFrEF). Previous studies indicate a genetic contribution to HR in population samples but there is little data in patients with HFrEF.MethodsPatients who met Framingham criteria for HF and had an ejection fraction < 50% were prospectively enrolled in a genetic HF registry (2007–2015, n = 1060). All participants donated blood for DNA and underwent genome-wide genotyping with additional variants called via imputation. We performed testing of previously identified variant “hits” (43 loci) as well as a genome-wide association (GWAS) of HR, adjusted for race, using Efficient Mixed-Model Association Expedited (EMMAX).ResultsThe cohort was 35% female, 51% African American, and averaged 68 years of age. There was a 2 beats per minute (bpm) difference in HR by race, AA being slightly higher. Among 43 candidate variants, 4 single nucleotide polymorphisms (SNPs) in one gene (GJA1) were significantly associated with HR. In genome-wide testing, one statistically significant association peak was identified on chromosome 22q13, with strongest SNP rs535263906 (p = 3.3 × 10−8). The peak is located within the gene Cadherin EGF LAG Seven-Pass G-Type Receptor 1 (CELSR1), encoding a cadherin super-family cell surface protein identified in GWAS of other phenotypes (e.g., stroke). The highest associated SNP was specific to the African American population.ConclusionsThese data confirm GJA1 association with HR in the setting of HFrEF and identify novel candidate genes for HR in HFrEF patients, particularly CELSR1. These associations should be tested in additional cohorts.

Genomic variations and association study of agronomic traits in flax

BackgroundFlax (Linum usitatissimum. L) is an ancient oilseed and natural fiber crop. It could be divided into three categories by use, namely oil flax, fiber flax and oil-fiber dual purpose (OF). Cultivated flax is widely used in the food and textile industry. It is of great significance to elucidate the genetic characteristics of flax collections for accelerating the process of breeding improvement in this dual purpose crop. With the development of next-generation sequencing, we can use new methods, such as SLAF-seq (specific-locus amplified fragment sequencing), to decode unknown genomes of species. In this study, a high-through sequencing of flax collections using SLAF-seq was conducted. The evolutionary tendency was defined and candidate genes associated with agronomic traits of flax species were identified by Genome-Wide Association Studying (GWAS).ResultsA flax collection consisting of 224 varieties were sequenced by SLAF-seq. In total, 346,639 SLAF tags were developed from all accessions, with an average sequencing depth of 7.19 for each accession. A total of 584,987 SNPs (single nucleotide polymorphism) with an MAF > 0.05 were identified from these SLAFs. The population structure division and phylogenetic analysis indicated a strong divergence among three kinds of flax groups. The genome-wide variation uncovered that oil flax had the highest genetic diversity and was considered to be the ancestor of fiber flax and oil-fiber flax. Sixteen associated peak SNPs for six traits were obtained by GWAS of oil-related traits using EMMAX (efficient mixed-model association eXpedited). Candidate genes and their related pathway were evaluated. A new GWAS was developed for fiber properties using the GLM (General linear model) model and a number of loci were identified.ConclusionsTo our knowledge, this is the first study on discovery multiple loci for important agronomic traits of flax species using GWAS strategy. These results will provide the highest possibility of incorporating both high fiber and good oil traits in a single variety.

A family-based genome-wide association study of chronic rhinosinusitis with nasal polyps implicates several genes in the disease pathogenesis.

BackgroundThe pathogenesis of chronic rhinosinusitis with nasal polyps is largely unknown. Previous studies have given valuable information about genetic variants associated with this disease but much is still unexplained. Our goal was to identify genetic markers and genes associated with susceptibility to chronic rhinosinusitis with nasal polyps using a family-based genome-wide association study.Methods427 patients (293 males and 134 females) with CRSwNP and 393 controls (175 males and 218 females) were recruited from several Swedish hospitals. SNP association values were generated using DFAM (implemented in PLINK) and Efficient Mixed Model Association eXpedited (EMMAX). Analyses of pathway enrichment, gene expression levels and expression quantitative trait loci were then performed in turn.ResultsNone of the analysed SNPs reached genome wide significant association of 5.0 x 10−8. Pathway analyses using our top 1000 markers with the most significant association p-values resulted in 138 target genes. A comparison between our target genes and gene expression data from the NCBI Gene Expression Omnibus database showed significant overlap for 36 of these genes. Comparisons with data from expression quantitative trait loci showed the most skewed allelic distributions in cases with chronic rhinosinusitis with nasal polyps compared with controls for the genes HLCS, HLA-DRA, BICD2, VSIR and SLC5A1.ConclusionOur study indicates that HLCS, HLA-DRA, BICD2, VSIR and SLC5A1 could be involved in the pathogenesis of chronic rhinosinusitis with nasal polyps. HLA-DRA has been associated with chronic rhinosinusitis with nasal polyps in previous studies and HLCS, BICD2, VSIR and SLC5A1 may be new targets for future research.

Abstract 1290: Association of common genetic variants with TMPRSS2 ERG fusion status in prostate cancer

Abstract Introduction and Objectives: Oncogenic activation of ERG resulting from prevalent gene fusions is present in two thirds of prostate cancer (CaP) patients of European Ancestry including Caucasian Americans (CA). Our laboratory and others have recently reported that major cancer driver genes, including ERG, show significant racial/ethnic differences in CaP with lower frequencies in African Americans (AA), Africans and Asians. Racial differences of CaP associated SNPs have also been extensively described. However, there is limited data on germline association with ERG fusion status. The goal of this study is to identify germline molecular determinants associating with ERG status of CaP. Methods: Blood derived genomic DNA samples were prepared from 270 AA men and 129 CA men treated by radical prostatectomy at Walter Reed National Military Medical Center (WRNMMC). ERG status was determined in whole mounted prostate specimens by immuno-histochemistry (IHC) for ERG protein expression as a surrogate for the TMPRSS2-ERG fusion. Blinded blood samples were genotyped for SNPs on the Illumina Golden Gate platform using Infinium Oncoarray, a 500K genome wide BeadChip kit from Illumina. Data analysis approaches included association analyses based on logistic regression, Principal Component Analysis (PCA) and Efficient Mixed-Model Association eXpedited (EMMAX) analysis. Genotype imputation analysis is being performed by IMPUTE2 program. Results: After applying rigorous sample and SNP QC steps on the datasets, SNP genotyping analysis was performed in 321 patients with 478,299 SNPs. Logistic regression, principal component analysis by EIGENSTRAT and a variance component approach, EMMAX analysis were performed to account for population structure. By EMMAX we identified SNPs associated with ERG status. The SNPs most significantly (&amp;lt;10-5) associated with ERG fusion status included rs6698333, an intron variant of Kruppel-like factor 17 (KLF17) and two SNPs (rs1889877, rs3798999) in the intron of adhesion G protein-coupled receptor B3 (ADGRB3). Fine-mapping of SNPs is underway by genotype imputation analysis (IMPUTE2) using the 1000 Genomes reference dataset, followed by independent validation. Conclusions: This study identified SNPs differentially associated with ERG status of CaP, a major driver oncogene in CaP. Although the biological significance as it relates to ERG status of CaP still needs to be determined, these SNPs, with independent validation, may help as markers in stratifying patients early (even before CaP is detected) for targeted prevention and treatment options. Citation Format: Indu Kohaar, Lakshmi Ravindranath, Denise Young, Amina Ali, Qiyuan Li, Albert Dobi, David McLeod, Inger L. Rosner, Isabell Sesterhenn, Matthew Freedman, Shiv Srivastava, Gyorgy Petrovics. Association of common genetic variants with TMPRSS2 ERG fusion status in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1290. doi:10.1158/1538-7445.AM2017-1290

Rapid Communication: Subclinical bovine respiratory disease - loci and pathogens associated with lung lesions in feedlot cattle.

ABSTRACTBovine respiratory disease (BRD) is an economically important disease of feedlot cattle that is caused by viral and bacterial pathogen members of the BRD complex. Many cases of subclinical BRD go untreated and are not detected until slaughter, when lung lesions are identified. The objectives of this study were to identify which BRD pathogens were associated with the presence of lung lesions at harvest and to identify genomic loci that were associated with susceptibility to lung lesions as defined by consolidation of the lung and/or the presence of fibrin tissue. Steers from a Colorado feedlot (n = 920) were tested for the presence of viral and bacterial pathogens using deep pharyngeal and mid-nasal swabs collected on entry into the study. Pathogen profiles were compared between cattle with or without lung consolidation (LC), fibrin tissue in the lung (FT), a combination of LC and FT in the same lung (lung lesions [LL]), and hyperinflated lungs (HIF) at harvest. Genotyping was conducted using the Illumina BovineHD BeadChip. Genomewide association analyses (GWAA) were conducted using EMMAX (efficient mixed-model association eXpedited), and pseudoheritabilities were estimated. The pathogen profile comparisons revealed that LC (P = 0.01, odds ratio [OR] = 3.37) and LL cattle (P = 0.04, OR = 4.58) were more likely to be infected with bovine herpes virus-1 and that HIF cattle were more likely to be infected with Mycoplasma spp. (P = 0.04, OR = 4.33). Pseudoheritability estimates were 0.25 for LC, 0.00 for FT, 0.28 for LL, and 0.13 for HIF. Because pseudoheritability for FT was estimated to be 0, GWAA results for FT were not reported. There were 4 QTL that were moderately associated (P < 1 × 10−5) with only LC, 2 that were associated with only LL, and 1 that was associated with LC and LL. Loci associated with HIF included 12 that were moderately associated and 3 that were strongly associated (uncorrected P < 5 × 10−7). A 24-kb region surrounding significant lead SNP was investigated to identify positional candidate genes. Many positional candidate genes underlying or flanking the detected QTL have been associated with signal transduction, cell adhesion, or gap junctions, which have functional relevance to the maintenance of lung health. The identification of pathogens and QTL associated with the presence of lung abnormalities in cattle exhibiting subclinical BRD allows the identification of loci that may not be detected through manifestation of clinical disease alone.

Genomewide association mapping and pathway analysis of meat tenderness in Polled Nellore cattle1

Brazil is one of the world's largest beef exporters, although the product has a low price due to quality issues. The meat exported by Brazil is considered medium and low quality by international buyers, mainly due to lack of tenderness. The predominant Zebu breeds (80% Nellore) are known for producing tougher beef than taurine breeds. Nonetheless, some studies have shown that there is substantial genetic variability for tenderness within the Nellore breed, although it is a difficult trait to improve by conventional selection methods. Therefore, the aim of this study was to perform a genomewide association study (GWAS) and a gene set enrichment analysis to identify genomic regions and biologically relevant pathways associated with meat tenderness in Polled Nellore cattle. Data consisted of Warner-Bratzler shear force values of LM from 427 Polled Nellore animals divided into 3 experimental slaughters (years 2005, 2008, and 2010). The animals were genotyped with either the Illumina BovineHD BeadChip (777k, on 61 samples) or the GGP Indicus HD chip (77k, on 366 samples). Single nucleotide polymorphisms were excluded when the call rate was <90%, the Hardy-Weinberg proportions -value was <1% (Fisher exact test, Bonferroni adjusted), and the minor allele frequency was <1%. Imputation from the GGP Indicus HD chip to the Illumina BovineHD BeadChip was performed using the FImput program. Genomewide association analysis was performed using the Efficient Mixed Model Association eXpedited (EMMAx) and the population parameters previously determined (P3D) methods. The GWAS was complemented with a gene set enrichment analysis performed using the FatiGO procedure. Significant markers ( < 0.0001) explaining a larger proportion of variation than other significant SNPs were located on chromosomes 3, 13, 17, 20, 21, and 25, indicating QTL associated with meat tenderness throughout the genome. Additionally, gene set analysis identified 22 Gene Ontology functional terms and 2 InterPro entries that showed significant enrichment of genes associated with tenderness. The functional categories included protein tyrosine and serine/threonine kinase activity, calcium ion binding, lipid metabolic process, and growth factors, among others. These results help to elucidate the genetic architecture and metabolic pathways underlying this trait, which is of extreme economic and social importance to Brazil, because Nellore is the dominant beef cattle breed in the country.