Genome-wide Quantitative Trait Locus Analysis Research Articles

Cardiac Troponin I-Interacting Kinase Affects Cardiomyocyte S-Phase Activity but Not Cardiomyocyte Proliferation.

Identifying genetic variants that affect the level of cell cycle reentry and establishing the degree of cell cycle progression in those variants could help guide development of therapeutic interventions aimed at effecting cardiac regeneration. We observed that C57Bl6/NCR (B6N) mice have a marked increase in cardiomyocyte S-phase activity after permanent coronary artery ligation compared with infarcted DBA/2J (D2J) mice. Cardiomyocyte cell cycle activity after infarction was monitored in D2J, (D2J×B6N)-F1, and (D2J×B6N)-F1×D2J backcross mice by means of bromodeoxyuridine or 5-ethynyl-2'-deoxyuridine incorporation using a nuclear-localized transgenic reporter to identify cardiomyocyte nuclei. Genome-wide quantitative trait locus analysis, fine scale genetic mapping, whole exome sequencing, and RNA sequencing analyses of the backcross mice were performed to identify the gene responsible for the elevated cardiomyocyte S-phase phenotype. (D2J×B6N)-F1 mice exhibited a 14-fold increase in cardiomyocyte S-phase activity in ventricular regions remote from infarct scar compared with D2J mice (0.798±0.09% versus 0.056±0.004%; P<0.001). Quantitative trait locus analysis of (D2J×B6N)-F1×D2J backcross mice revealed that the gene responsible for differential S-phase activity was located on the distal arm of chromosome 3 (logarithm of the odds score=6.38; P<0.001). Additional genetic and molecular analyses identified 3 potential candidates. Of these, Tnni3k (troponin I-interacting kinase) is expressed in B6N hearts but not in D2J hearts. Transgenic expression of TNNI3K in a D2J genetic background results in elevated cardiomyocyte S-phase activity after injury. Cardiomyocyte S-phase activity in both Tnni3k-expressing and Tnni3k-nonexpressing mice results in the formation of polyploid nuclei. These data indicate that Tnni3k expression increases the level of cardiomyocyte S-phase activity after injury.

Linkage analysis identifies novel genetic modifiers of microbiome traits in families with inflammatory bowel disease

ABSTRACT Dysbiosis of the gut microbiome is a hallmark of inflammatory bowel disease (IBD) and both, IBD risk and microbiome composition, have been found to be associated with genetic variation. Using data from families of IBD patients, we examined the association between genetic and microbiome similarity in a specific IBD context, followed by a genome-wide quantitative trait locus (QTL) linkage analysis of various microbiome traits using the same data. SNP genotypes as well as gut microbiome and phenotype data were obtained from the Kiel IBD family cohort (IBD-KC). The IBD-KC is an ongoing prospective study in Germany currently comprising 256 families with 455 IBD patients and 575 first- and second-degree relatives. Initially focusing upon known IBD risk loci, we noted a statistically significant (FDR<0.05) association between genetic similarity at SNP rs11741861 and overall microbiome dissimilarity among pairs of relatives discordant for IBD. In a genome-wide QTL analysis, 12 chromosomal regions were found to be linked to the abundance of one of seven microbial genera, namely Barnesiella (chromosome 4, region spanning 10.34 cM), Clostridium_XIVa (chr4, 3.86 cM; chr14, two regions spanning 7.05 and 13.02 cM respectively), Pseudoflavonifractor (chr7, 12.80 cM) Parasutterella (chr14, 8.26 cM), Ruminococcus (chr16, two overlapping regions spanning 8.01 and 16.87 cM, respectively), Roseburia (chr19, 7.99 cM), and Odoribacter (chr22, three regions spanning 0.89, 5.57 and 1.71 cM, respectively), as well as the Shannon index of α diversity (chr3, 1.47 cM). Our study thus shows that, in families of IBD patients, pairwise genetic similarity for at least one IBD risk locus is associated with overall microbiome dissimilarity among discordant pairs of relatives, and that hitherto unknown genetic modifiers of microbiome traits are located in at least 12 human genomic regions.

Mapping QTLs for Breast Muscle Weight in an F2 Intercross between Native Japanese Nagoya and White Plymouth Rock Chicken Breeds.

Nagoya (NAG), a native Japanese chicken breed, has high quality meat but low meat yield, whereas White Plymouth Rock (WPR), a parental breed of commercial broilers, has rapid growth but high body fat. We previously reported three quantitative trait loci (QTLs) for early postnatal growth in 239 F2 chickens between NAG and WPR breeds. In this study, using the same F2 chickens at 4 weeks of age, we performed genome-wide QTL analysis for breast muscle weight, fat weight and serum and liver levels of biochemical parameters. Two significant QTLs for pectoralis minor and/or major weights were revealed on chromosome 2 between 108 Mb and 127 Mb and chromosome 4 between 10 Mb and 68 Mb. However, no QTL for the other traits was detected. The two QTLs explained 7.0–11.1% of the phenotypic variances, and their alleles derived from WPR increased muscle weights. The chromosome 2 QTL may be a novel locus, whereas the chromosome 4 QTL coincided with a known QTL for meat quality. The findings provide information that is beneficial for genetic improvement of meat yield for the lean NAG breed and, furthermore, provide a better understanding of the genetic basis of chicken muscle development.

Regression based fast multi-trait genome-wide QTL analysis.

Multivariate simple interval mapping (SIM) is one of the most popular approaches for multiple quantitative trait locus (QTL) analysis. Both maximum likelihood (ML) and least squares (LS) multivariate regression (MVR) are widely used methods for multi-trait SIM. ML-based MVR (MVR-ML) is an expectation maximization (EM) algorithm based iterative and complex time-consuming approach. Although the LS-based MVR (MVR-LS) approach is not an iterative process, the calculation of likelihood ratio (LR) statistic in MVR-LS is also a time-consuming complex process. We have introduced a new approach (called FastMtQTL) for multi-trait QTL analysis based on the assumption of multivariate normal distribution of phenotypic observations. Our proposed method can identify almost the same QTL positions as those identified by the existing methods. Moreover, the proposed method takes comparatively less computation time because of the simplicity in the calculation of LR statistic by this method. In the proposed method, LR statistic is calculated only using the sample variance-covariance matrix of phenotypes and the conditional probability of QTL genotype given the marker genotypes. This improvement in computation time is advantageous when the numbers of phenotypes and individuals are larger, and the markers are very dense resulting in a QTL mapping with a bigger dataset.

A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma.

Molecular quantitative trait locus (QTL) analyses are increasingly popular to explore the genetic architecture of complex traits, but existing studies do not leverage shared regulatory patterns and suffer from a large multiplicity burden, which hampers the detection of weak signals such as trans associations. Here, we present a fully multivariate proteomic QTL (pQTL) analysis performed with our recently proposed Bayesian method LOCUS on data from two clinical cohorts, with plasma protein levels quantified by mass-spectrometry and aptamer-based assays. Our two-stage study identifies 136 pQTL associations in the first cohort, of which >80% replicate in the second independent cohort and have significant enrichment with functional genomic elements and disease risk loci. Moreover, 78% of the pQTLs whose protein abundance was quantified by both proteomic techniques are confirmed across assays. Our thorough comparisons with standard univariate QTL mapping on (1) these data and (2) synthetic data emulating the real data show how LOCUS borrows strength across correlated protein levels and markers on a genome-wide scale to effectively increase statistical power. Notably, 15% of the pQTLs uncovered by LOCUS would be missed by the univariate approach, including several trans and pleiotropic hits with successful independent validation. Finally, the analysis of extensive clinical data from the two cohorts indicates that the genetically-driven proteins identified by LOCUS are enriched in associations with low-grade inflammation, insulin resistance and dyslipidemia and might therefore act as endophenotypes for metabolic diseases. While considerations on the clinical role of the pQTLs are beyond the scope of our work, these findings generate useful hypotheses to be explored in future research; all results are accessible online from our searchable database. Thanks to its efficient variational Bayes implementation, LOCUS can analyze jointly thousands of traits and millions of markers. Its applicability goes beyond pQTL studies, opening new perspectives for large-scale genome-wide association and QTL analyses.Diet, Obesity and Genes (DiOGenes) trial registration number: NCT00390637.

Mapping Quantitative Trait Loci onto Chromosome-Scale Pseudomolecules in Flax.

Quantitative trait loci (QTL) are genomic regions associated with phenotype variation of quantitative traits. To date, a total of 313 QTL for 31 quantitative traits have been reported in 14 studies on flax. Of these, 200 QTL from 12 studies were identified based on genetic maps, the scaffold sequences, or the pre-released chromosome-scale pseudomolecules. Molecular markers for QTL identification differed across studies but the most used ones were simple sequence repeats (SSRs) or single nucleotide polymorphisms (SNPs). To uniquely map the SSR and SNP markers from different references onto the recently released chromosome-scale pseudomolecules, methods with several scripts and database files were developed to locate PCR- and SNP-based markers onto the same reference, co-locate QTL, and scan genome-wide candidate genes. Using these methods, 195 out of 200 QTL were successfully sorted onto the 15 flax chromosomes and grouped into 133 co-located QTL clusters; the candidate genes that co-located with these QTL clusters were also predicted. The methods and tools presented in this article facilitate marker re-mapping to a new reference, genome-wide QTL analysis, candidate gene scanning, and breeding applications in flax and other crops.

Genome-Wide Analysis Reveals Four Novel Loci for Attention-Deficit Hyperactivity Disorder in Korean Youths.

Objectives:The molecular mechanisms underlying attention-deficit hyperactivity disorder (ADHD) remain unclear. Therefore, this study aimed to identify the genetic susceptibility loci for ADHD in Korean children with ADHD. We performed a case-control and a family-based genome-wide association study (GWAS), as well as genome-wide quantitative trait locus (QTL) analyses, for two symptom traits.Methods:A total of 135 subjects (71 cases and 64 controls), for the case-control analysis, and 54 subjects (27 probands and 27 unaffected siblings), for the family-based analysis, were included.Results:The genome-wide QTL analysis identified four single nucleotide polymorphisms (SNPs) (rs7684645 near APELA, rs12538843 near YAE1D1 and POU6F2, rs11074258 near MCTP2, and rs34396552 near CIDEA) that were significantly associated with the number of inattention symptoms in ADHD. These SNPs showed possible association with ADHD in the family-based GWAS, and with hyperactivity-impulsivity in genome-wide QTL analyses. Moreover, association signals in the family-based QTL analysis for the number of inattention symptoms were clustered near genes IL10, IL19, SCL5A9, and SKINTL.Conclusion:We have identified four QTLs with genome-wide significance and several promising candidates that could potentially be associated with ADHD (CXCR4, UPF1, SETD5, NALCN-AS1, ERC1, SOX2-OT, FGFR2, ANO4, and TBL1XR1). Further replication studies with larger sample sizes are needed.

Genetic regulation of IL1RL1 methylation and IL1RL1-a protein levels in asthma.

Interleukin-1 receptor-like 1 (IL1RL1) is an important asthma gene. (Epi)genetic regulation of IL1RL1 protein expression has not been established. We assessed the association between IL1RL1 single nucleotide polymorphisms (SNPs), IL1RL1 methylation and serum IL1RL1-a protein levels, and aimed to identify causal pathways in asthma.Associations of IL1RL1 SNPs with asthma were determined in the Dutch Asthma Genome-wide Association Study cohort and three European birth cohorts, BAMSE (Children/Barn, Allergy, Milieu, Stockholm, an Epidemiological survey), INMA (Infancia y Medio Ambiente) and PIAMA (Prevention and Incidence of Asthma and Mite Allergy), participating in the Mechanisms of the Development of Allergy study. We performed blood DNA IL1RL1 methylation quantitative trait locus (QTL) analysis (n=496) and (epi)genome-wide protein QTL analysis on serum IL1RL1-a levels (n=1462). We investigated the association of IL1RL1 CpG methylation with asthma (n=632) and IL1RL1-a levels (n=548), with subsequent causal inference testing. Finally, we determined the association of IL1RL1-a levels with asthma and its clinical characteristics (n=1101).IL1RL1 asthma-risk SNPs strongly associated with IL1RL1 methylation (rs1420101; p=3.7×10-16) and serum IL1RL1-a levels (p=2.8×10-56). IL1RL1 methylation was not associated with asthma or IL1RL1-a levels. IL1RL1-a levels negatively correlated with blood eosinophil counts, whereas there was no association between IL1RL1-a levels and asthma.In conclusion, asthma-associated IL1RL1 SNPs strongly regulate IL1RL1 methylation and serum IL1RL1-a levels, yet neither these IL1RL1-methylation CpG sites nor IL1RL1-a levels are associated with asthma.

Verticillium dahliae Disease Resistance and the Regulatory Pathway for Maturity and Tuberization in Potato.

Kleb. is a pathogenic fungus causing wilting, chlorosis, and early dying in potato ( L.). Genetic mapping of resistance to was done using a diploid population of potato. The major quantitative trait locus (QTL) for resistance was found on chromosome 5. The gene, controlling earliness of maturity and tuberization, was mapped within the interval. Another QTL on chromosome 9 co-localized with the wilt resistance gene marker. Epistasis analysis indicated that the loci on chromosomes 5 and 9 had a highly significant interaction, and that functioned downstream of The alleles were sequenced and found to encode StCDF1.1 and StCDF1.3. Interaction between the resistance allele and the was demonstrated, but not for Genome-wide expression QTL (eQTL) analysis was performed and genes with eQTL at the and loci were both found to have similar functions involving the chloroplast, including photosynthesis, which declines in both maturity and wilt. Among the gene ontology (GO) terms that were specific to genes with eQTL at the , but not the locus, were those associated with fungal defense. These results suggest that controls fungal defense and reduces early dying in wilt through affecting genetic pathway controlling tuberization timing.

Genome-wide QTL analysis for anxiety trait in bipolar disorder type I

BackgroundGenetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. MethodsWe assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). ResultsWe identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). LimitationsSince confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. ConclusionsWe conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety.

Genome-wide QTL and eQTL analyses using Mendel.

Pedigree genome-wide association studies (GWAS) (Option 29) in the current version of the Mendel software is an optimized subroutine for performing large-scale genome-wide quantitative trait locus (QTL) analysis. This analysis (a) works for random sample data, pedigree data, or a mix of both; (b) is highly efficient in both run time and memory requirement; (c) accommodates both univariate and multivariate traits; (d) works for autosomal and x-linked loci; (e) correctly deals with missing data in traits, covariates, and genotypes; (f) allows for covariate adjustment and constraints among parameters; (g) uses either theoretical or single nucleotide polymorphism (SNP)–based empirical kinship matrix for additive polygenic effects; (h) allows extra variance components such as dominant polygenic effects and household effects; (i) detects and reports outlier individuals and pedigrees; and (j) allows for robust estimation via the t-distribution. This paper assesses these capabilities on the genetics analysis workshop 19 (GAW19) sequencing data. We analyzed simulated and real phenotypes for both family and random sample data sets. For instance, when jointly testing the 8 longitudinally measured systolic blood pressure and diastolic blood pressure traits, it takes Mendel 78 min on a standard laptop computer to read, quality check, and analyze a data set with 849 individuals and 8.3 million SNPs. Genome-wide expression QTL analysis of 20,643 expression traits on 641 individuals with 8.3 million SNPs takes 30 h using 20 parallel runs on a cluster. Mendel is freely available at http://www.genetics.ucla.edu/software.

Genome-Wide SNP Linkage Mapping and QTL Analysis for Fiber Quality and Yield Traits in the Upland Cotton Recombinant Inbred Lines Population.

It is of significance to discover genes related to fiber quality and yield traits and tightly linked markers for marker-assisted selection (MAS) in cotton breeding. In this study, 188 F8 recombinant inbred lines (RILs), derived from a intraspecific cross between HS46 and MARCABUCAG8US-1-88 were genotyped by the cotton 63K single nucleotide polymorphism (SNP) assay. Field trials were conducted in Sanya, Hainan Province, during the 2014–2015 cropping seasons under standard conditions. Results revealed significant differences (P < 0.05) among RILs, environments and replications for fiber quality and yield traits. Broad-sense heritabilities of all traits including fiber length, fiber uniformity, micronaire, fiber elongation, fiber strength, boll weight, and lint percentage ranged from 0.26 to 0.66. A 1784.28 cM (centimorgans) linkage map, harboring 2618 polymorphic SNP markers, was constructed, which had 0.68 cM per marker density. Seventy-one quantitative trait locus (QTLs) for fiber quality and yield traits were detected on 21 chromosomes, explaining 4.70∼32.28% phenotypic variance, in which 16 were identified as stable QTLs across two environments. Meanwhile, 12 certain regions were investigated to be involved in the control of one (hotspot) or more (cluster) traits, mainly focused on Chr05, Chr09, Chr10, Chr14, Chr19, and Chr20. Nineteen pairs of epistatic QTLs (e-QTLs) were identified, of which two pairs involved in two additive QTLs. These additive QTLs, e-QTLs, and QTL clusters were tightly linked to SNP markers, which may serve as target regions for map-based cloning, gene discovery, and MAS in cotton breeding.

Genome-Wide Identification of QTL for Seed Yield and Yield-Related Traits and Construction of a High-Density Consensus Map for QTL Comparison in Brassica napus.

Seed yield (SY) is the most important trait in rapeseed, is determined by multiple seed yield-related traits (SYRTs) and is also easily subject to environmental influence. Many quantitative trait loci (QTLs) for SY and SYRTs have been reported in Brassica napus; however, no studies have focused on seven agronomic traits simultaneously affecting SY. Genome-wide QTL analysis for SY and seven SYRTs in eight environments was conducted in a doubled haploid population containing 348 lines. Totally, 18 and 208 QTLs for SY and SYRTs were observed, respectively, and then these QTLs were integrated into 144 consensus QTLs using a meta-analysis. Three major QTLs for SY were observed, including cqSY-C6-2 and cqSY-C6-3 that were expressed stably in winter cultivation area for 3 years and cqSY-A2-2 only expressed in spring rapeseed area. Trait-by-trait meta-analysis revealed that the 144 consensus QTLs were integrated into 72 pleiotropic unique QTLs. Among them, all the unique QTLs affected SY, except for uq.A6-1, including uq.A2-3, uq.C1-2, uq.C1-3, uq.C6-1, uq.C6-5, and uq.C6-6 could also affect more than two SYRTs. According to the constructed high-density consensus map and QTL comparison from literatures, 36 QTLs from five populations were co-localized with QTLs identified in this study. In addition, 13 orthologous genes were observed, including five each gene for SY and thousand seed weight, and one gene each for biomass yield, branch height, and plant height. The genomic information of these QTLs will be valuable in hybrid cultivar breeding and in analyzing QTL expression in different environments.

Genome-wide QTL analysis of meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs.

BackgroundWe conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F2 progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.ResultsWe identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10−55). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.ConclusionsOur results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-014-0080-6) contains supplementary material, which is available to authorized users.

Identification of a Racially Dimorphic Variant in the Human Platelet PAR4 Thrombin Receptor Altering Platelet Function and Pharmacologic Inhibition

Compared to whites, blacks have a 2-fold higher incidence of coronary heart disease (CHD), and black race is an independent predictor of worse survival after CHD events after accounting for other confounding variables (e.g., socioeconomic, demographic, etc.). However, there has been a paucity of literature considering racial differences in platelet function. We recently reported results from the Platelet RNA And eXpression-1 (PRAX1) study of platelets in healthy black (n=70) and white (n=84) subjects (Edelstein et al, Nat. Med 2013). Human platelets express two thrombin receptors, protease activated receptor (PAR) 1 and PAR4. We demonstrated 1) a 3.7-fold increased PAR4-mediated aggregation kinetics and greater calcium mobilization in platelets from black subjects compared to whites, and 2) phosphatidylcholine transfer protein (PC-TP) was a mediator of this racial difference. These findings have potential clinical significance because greater platelet-mediated thrombosis could contribute to the worse outcomes in blacks than whites after coronary events. Additionally, in the presence of vorapaxar (an FDA-approved PAR1 inhibitor for patients with coronary and peripheral vascular disease) PAR4 is the primary means by which thrombin activates platelets, and the risks and benefits of vorapaxar and other PAR inhibitors by race are unknown.Because PC-TP expression only accounted for 18% of the observed variance in PAR4 function, we have considered additional mechanisms to explain the racial difference in thrombin-induced PAR4-mediated platelet reactivity. Although platelets from blacks express 14% more PAR4 protein than whites, this difference does not explain the variance in platelet PAR4 function. Genome-wide quantitative trait locus analysis identified common 3 SNPs in the PAR4 gene (F2RL3) as associated with PAR4-induced platelet aggregation (P = 4.79 x 10-11). Importantly, the allele frequency of these SNPs differs by race in both the 1000 Genomes dataset and in PRAX1 (P= 4.31 x 10-16). One of these SNPs, rs773902, determines if residue 120 in PAR4 is an alanine (81% in whites vs. 37% in blacks) or a threonine (63% in blacks vs. 19% in whites). A second less frequent, non-synonymous F2RL3SNP, Phe296Val, was only observed in blacks and was associated with loss of PAR4 function. This variant appears to have a dominant negative effect since only one copy of PAR4-296Val abolished the enhanced PAR4-AP induced platelet aggregation associated with PAR4-Thr120.A proximal step in PAR4-induced platelet signal transduction is Gq activation leading to hydrolysis of phosphatidylinositol 4,5-biphosphate to IP3 and diacylglycerol, followed by increased cytoplasmic calcium. Platelets with the PAR4-Thr120 variant exhibited a 65% greater Ca2+ flux than PAR4-Ala120 homozygotes (P = 0.03). To eliminate other sources of inter-individual variation we cloned and expressed each variant in 293 cells, which lack endogenous PAR4 expression, and measured the generation of IP3 in response to PAR4-AP treatment. Compared to PAR4-Ala120 expressing cells, PAR4-Thr120 expressing cells generated 41% higher IP3 levels (P = 0.03).Because PAR inhibitors are either currently approved (vorapaxar) or in development, we examined platelet function in the presence of PAR1 and PAR4 antagonists. PAR4 genotype had no effect on vorapaxar inhibition of PAR1 signaling or PAR4 signaling in the presence of vorapaxar. YD-3, a selective inhibitor of PAR4 and not PAR1, was also tested. In stark contrast to vorapaxar, PAR4 genotype had a significant effect of the efficacy of PAR4 inhibition by the compound YD-3. Platelets from subjects homozygous for the PAR4-Thr120 were not inhibited by any tested concentration of YD-3 while PAR4-Ala120 homozygotes were inhibited in a dose-dependent manner (P = 6x10-8).In summary, we have identified variation in the PAR4 gene that alters PAR4 function and accounts for 48% of the observed racial difference in platelet PAR4 signaling. These results, couple with other racial data (Tourdot et al., submitted), have two critical clinical implications for anti-platelet therapy: (1) Patients expressing the PAR4-Thr120 variant (mostly black) may not be adequately protected on current anti-platelet drugs, and (2) PAR4 antagonists currently in development may not be effective in PAR4-Thr120 expressing platelets. This suggests a critical need for new and effective therapies for these patients. DisclosuresNo relevant conflicts of interest to declare.

Genomic regions of pufferfishes responsible for host specificity of a monogenean parasite, Heterobothrium okamotoi

The genetic mechanisms underlying host specificity of parasitic infections are largely unknown. After hatching, the larvae of the monogenean parasite, Heterobothrium okamotoi, attach to the gill filaments of hosts and the post-larval worms develop there by consuming nutrients from the host. The susceptibility to H. okamotoi infection differs markedly among fish species. While this parasite can grow on tiger pufferfish (also called fugu), Takifugu rubripes, it appears to be rejected by a close congener, grass pufferfish, Takifugu niphobles, after initial attachment to the gills. To determine the genetic architecture of the pufferfish responsible for this host specificity, we performed genome-wide quantitative trait loci analysis. We raised second generation (F2) hybrids of the two pufferfish species and experimentally infected them with the monogenean in vivo. To assess possible differences in host mechanisms between early and later periods of infection, we sampled fish three h and 21days after exposure. Genome scanning of fish from the 3h infection trial revealed suggestive quantitative trait loci on linkage groups 2 and 14, which affected the number of parasites on the gill. However, analysis of fish 21days p.i. detected a significant quantitative trait locus on linkage group 9 and three other suggestive quantitative trait loci on linkage groups 7, 18 and 22. These results indicated the polygenic nature of the host mechanisms involved in the infection/rejection of H. okamotoi. Moreover the analyses suggested that host factors may play a more important role during the growth period of the parasite than during initial host recognition at the time of attachment. Within the 95% confidence interval of the linkage group 9 quantitative trait locus in the fugu genome, there were 214 annotated protein-coding genes, including immunity-related genes such as Irak4, Muc2 and Muc5ac.

370 SYSTEMIC AND ORGAN-SPECIFIC GENETIC DETERMINANTS OF FIBROGENESIS IN LIVER AND HEART

Background: Various chronic human diseases result in organ fibrosis, i.e. excessive accumulation of extracellular matrix. Fibrosis is a multifactorial trait determined by both genetic and exogenous factors such as xenobiotics. Our aim is to compare fibrogenesis in liver and heart in a systemic fibrosis model to dissect common and organ-specific mechanisms of fibrosis. Furthermore, we employed a systems genetics approach to identify genetic modifiers of hepatic and cardiac fibrosis. Method: We tested the parental strains (C57BL/6J [B] and DBA/2J [D], 6/group) for the following fibrosis models: (i) N-nitro-Larginine-methylester (L-NAME), a NO synthase inhibitor, provided in drinking water (5 weeks, ad libitum); (ii) CCl4, administered i.p. (0.7mg/kg, 12 injections for 6 weeks). Collagen accumulation was quantified in histological liver and heart sections after Sirius red staining. The proliferation marker Ki-67 and fibroblast marker fibronectin were determined by immunohistochemistry. Thirty BxD recombinant inbred lines, genotyped for >13,000 markers, served as genetic reference population for the identification of genetic risk factors by genome-wide quantitative trait locus analysis (QTL). Results: Whereas L-NAME treatment did not induce hepatic fibrosis, CCl4 induced fibrosis in liver and heart, a hitherto unknown phenomenon. We observed marked differences for both hepatic and cardiac fibrosis between C57BL/6J and DBA/2J strains. Cardiac fibroblast proliferation and collagen accumulation was enhanced in DBA/2J mice (collagen area [%] in liver B =2.5%, D =7.2%, P = 0.0002; in heart: B = 0.6%, D =1.2%, P = 0.006). CCl4-challenged BxD lines also differed in fibrosis susceptibility. Collagen levels in livers and hearts of BxDs were correlated significantly (R = 0.39, P < 0.002). QTL analyses identified several tissue-specific loci as well as an overlap of fibrosis associated peaks on chromosome 18 in liver and heart. Conclusions: CCl4 induces systemic fibrosis in liver and heart and therefore meets the requirements as a fibrotic model to dissect common and organ specific modifiers of fibrogenesis. In the genetic reference population, hepatic and cardiac fibrosis susceptibility were correlated significantly, suggesting common genetic determinants of fibrogenesis. The overlap of tissue-specific QTL peaks on chromosome 18 supports the assumption of systemic profibrogenic core pathways.

Quantitative Trait Loci Affecting Rous Sarcoma Virus Induced Tumor Regression Trait in F2 Intercross Chickens

We performed a genome-wide linkage and quantitative trait locus (QTL) analysis to confirm the existence of QTL affecting Rous Sarcoma Virus (RSV) induced tumor regression, and to estimate their effects on phenotypic variance in an F2 resource population. The F2 population comprised 158 chickens obtained by crossing tumor regressive White Leghorn (WL) and tumor progressive Rhode Island Red (RIR) lines was measured for tumor formation after RSV inoculation. Forty-three tumor progressive and 28 tumor regressive chickens were then used for genome-wide linkage and QTL analysis using a total of 186 microsatellite markers. Microsatellite markers were mapped on 20 autosomal chromosomes. A significant QTL was detected with marker LEI0258 located within the MHC B region on chromosome 16. This QTL had the highest F ratio (9.8) and accounted for 20.1% of the phenotypic variation. Suggestive QTL were also detected on chromosomes 4, 7 and 10. The QTL on chromosome 4 were detected at the 1% chromosome-wide level explaining 17.5% of the phenotypic variation, and the QTLs on chromosome 7 and 10 were detected at the 5% chromosome-wide level and explained 11.1% and 10.5% of the phenotypic variation, respectively. These results indicate that the QTLs in the non-MHC regions play a significant role in RSV-induced tumor regression. The present study constitutes one of the first preliminary reports in domestic chickens for QTLs affecting RSV-induced tumor regression outside the MHC region. I .

Aberrant Genetic Control of Invariant TCR-Bearing NKT Cell Function in New Zealand Mouse Strains: Possible Involvement in Systemic Lupus Erythematosus Pathogenesis

Both suppressive and promoting roles of NKT cells have been reported in the pathogenesis of systemic lupus erythematosus (SLE). Herein, we found that although New Zealand mice have normal frequencies of NKT cells, their in vitro potential to produce IL-4 and IFN-gamma in response to alpha-galactosylceramide was remarkably impaired in New Zealand Black (NZB) mice prone to mild SLE, while production was highly up-regulated in nonautoimmune New Zealand White (NZW) mice and at intermediate levels in (NZB x NZW)F(1) mice, which are prone to severe SLE. Because this aberration is evident in young mice before disease onset, genetic mechanisms are thought to be involved. Genome-wide quantitative trait locus analysis and association studies revealed that a locus linked to D11Mit14 on chromosome 11 may be involved in the difference in cytokine-producing potential between NZB and NZW NKT cells. Additionally, (NZB x NZW)F(1) x NZB backcross progeny with the NZW genotype for D11Mit14 showed significantly increased frequencies of age-associated SLE phenotypes, such as high serum levels of IgG, IgG anti-DNA Abs, and lupus nephritis. In coculture studies, alpha-galactosylceramide-stimulated NKT cells from NZW and (NZB x NZW)F(1) mice, but not from NZB mice, showed significantly enhanced Ig synthesis by B cells. These findings suggest that the D11Mit14-linked NZW locus may contribute to the development of SLE in (NZB x NZW)F(1) mice through a mechanism that up-regulates NKT cell function. Thus, this NZW allele may be a candidate of the NZW modifiers that act to promote (NZB x NZW)F(1) disease.

Klk1 as One of the Genes Contributing to Hypertension in Dahl Salt-Sensitive Rat

A genome-wide quantitative trait loci analysis for blood pressure was performed using 107 male F2 rats derived from Dahl salt-sensitive and Lewis rats. Blood pressure was assessed by telemetry, and >400 microsatellite markers were used for genotyping. Two major quantitative trait loci for blood pressure were identified at chromosome 1 and chromosome 10. The expression levels of 366 transcripts around the chromosome 1 quantitative trait loci were assessed by RT-PCR, and we found that the Klk1 (kallikrein 1) and Ngfg (nerve growth factor gamma) mRNA levels were significantly reduced in the kidneys of Dahl salt-sensitive rats compared with those in Lewis rats. The expression levels of kallikrein 1 protein were also suppressed in Dahl salt-sensitive rats compared with those in Lewis rats. Because the kallikrein-kinin system has been shown to be involved in renal function, including salt homeostasis, it is likely that the reduced expression of Klk1 contributes to salt-sensitive hypertension in Dahl salt-sensitive rats.