Local Linkage Disequilibrium Research Articles

P0040 Binding of carbamylated peptides to alleles associated with susceptibility and resistance to rheumatoid arthritis

Aim HLA-DRB1 is a strong genetic component of RA and also strongly correlates with the presence of antibodies against citrullinated proteins. Additionally, antibodies against carbamylated proteins are also detected in the RA synovium, and often these antibodies cross-react between citrullinated and carbamylated antigens. We have previously demonstrated the importance of individual shared epitope amino acids in RA susceptibility and resistance. Our aim is to examine the potential contribution of carbamylation to RA through peptide binding analysis of carbamylated peptides to alleles associated with RA susceptibility and resistance. Methods We measured binding of native, citrullinated and carbamylated forms of vimentin 66–78 and fibrinogen; and native and carbamylated type II collagen 259–273 , to alleles associated with RA susceptibility (DRB1 ∗ 04:01) and resistance (DRB1 ∗ 04:02 and ∗ 08:01). Additionally, we measured peptide binding to alleles of loci in linkage disequilibrium with DRB1, as they may be contributing cis elements to disease development. Results Carbamylated vimentin, fibrinogen and collagen were bound effectively by susceptible allele ∗ 04:01. DRB1 ∗ 04:02 was similarly able to bind carbamylated vimentin and fibrinogen, but unable to bind any form of collagen. DRB1 ∗ 08:01 was able to bind both native and carbamylated forms of vimentin and fibrinogen, but lacked collagen binding. DRB4 ∗ 01:01, a locus in linkage disequilibrium with DRB1 ∗ 04:01, exhibited the strongest preference for carbamylated fibrinogen and vimentin. Conclusions Based on the preference for carbamylated peptides, it is possible that DRB4 ∗ 01:01 plays a role in RA pathogenesis that has not been appreciated due to linkage. Download high-res image (188KB) Download full-size image

Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

Structure and genetic diversity of natural Brazilian pepper populations (Schinus terebinthifolius Raddi).

In the face of a possible loss of genetic diversity in plants due the environmental changes, actions to ensure the genetic variability are an urgent necessity. The extraction of Brazilian pepper fruits is a cause of concern because it results in the lack of seeds in soil, hindering its distribution in space and time. It is important to address this concern and explore the species, used by riparian communities and agro-factories without considering the need for keeping the seeds for natural seed banks and for species sustainability. The objective of this study was to evaluate the structure and the genetic diversity in natural Brazilian pepper populations (Schinus terebinthifolius Raddi). Twenty-two alleles in 223 individuals were identified from eight forest remnants located in the states of Minas Gerais, Espírito Santo, and Sergipe. All populations presented loci in Hardy-Weinberg equilibrium deviation. Four populations presented six combinations of loci in linkage disequilibrium. Six exclusive alleles were detected in four populations. Analysis of molecular variance showed the absence of diversity between regions and that between the populations (GST) was 41%. Genetic diversity was structured in seven clusters (ΔK7). Brazilian pepper populations were not structured in a pattern of isolation by distance and present genetic bottleneck. The populations São Mateus, Canastra, Barbacena, and Ilha das Flores were identified as management units and may support conservation projects, ecological restoration and in implementation of management plans for Brazilian pepper in the State of Sergipe.

Exome Sequence Data From Multigenerational Families Implicate AMPA Receptor Trafficking in Neurocognitive Impairment and Schizophrenia Risk

Schizophrenia is a mental disorder characterized by impairments in behavior, thought, and neurocognitive performance. We searched for susceptibility loci at a quantitative trait locus (QTL) previously reported for abstraction and mental flexibility (ABF), a cognitive function often compromised in schizophrenia patients and their unaffected relatives. Exome sequences were determined for 134 samples in 8 European American families from the original linkage study, including 25 individuals with schizophrenia or schizoaffective disorder. At chromosome 5q32-35.3, we analyzed 407 protein-altering variants for association with ABF and schizophrenia status. For replication, significant, Bonferroni-corrected findings were tested against cognitive traits in Mexican American families (n = 959), as well as interrogated for schizophrenia risk using GWAS results from the Psychiatric Genomics Consortium (PGC). From the gene SYNPO, rs6579797 (MAF = 0.032) shows significant associations with ABF (P = .015) and schizophrenia (P = .040), as well as jointly (P = .0027). In the Mexican American pedigrees, rs6579797 exhibits significant associations with IQ (P = .011), indicating more global effects on neurocognition. From the PGC results, other SYNPO variants were identified with near significant effects on schizophrenia risk, with a local linkage disequilibrium block displaying signatures of positive selection. A second missense variant within the QTL, rs17551608 (MAF = 0.19) in the gene WWC1, also displays a significant effect on schizophrenia in our exome sequences (P = .038). Remarkably, the protein products of SYNPO and WWC1 are interaction partners involved in AMPA receptor trafficking, a brain process implicated in synaptic plasticity. Our study reveals variants in these genes with significant effects on neurocognition and schizophrenia risk, identifying a potential pathogenic mechanism for schizophrenia spectrum disorders.

Asymmetric linkage disequilibrium: Tools for assessing multiallelic LD

Standard measures of linkage disequilibrium (LD) provide an incomplete description of the correlation between two loci. Recently, Thomson and Single (2014) described a new asymmetric pair of LD measures (ALD) that give a more complete description of LD. The ALD measures are symmetric and equivalent to the correlation coefficient r when both loci are bi-allelic. When the numbers of alleles at the two loci differ, the ALD measures capture this asymmetry and provide additional detail about the LD structure. In disease association studies the ALD measures are useful for identifying additional disease genes in a genetic region, by conditioning on known effects. In evolutionary genetic studies ALD measures provide insight into selection acting on individual amino acids of specific genes, or other loci in high LD (see Thomson and Single (2014) for these examples). Here we describe new software for computing and visualizing ALD. We demonstrate the utility of this software using haplotype frequency data from the National Marrow Donor Program (NMDP). This enhances our understanding of LD patterns in the NMDP data by quantifying the degree to which LD is asymmetric and also quantifies this effect for individual alleles.

Genetic properties of 240 maize inbred lines and identity-by-descent segments revealed by high-density SNP markers

Characterization of the genetic properties of maize inbred lines is beneficial not only for increasing knowledge of genetic diversity, but also for maize breeding. In the present study, a panel of 240 maize inbred lines commonly used in China, including three foundation parents Dan340, Mo17, and Huangzao4, and their derivatives, was genotyped using the MaizeSNP50 BeadChip, which contains 56,110 single-nucleotide polymorphism (SNP) markers. As a result, 40,757 SNPs with unique physical positions were successfully recalled in this panel with an average coverage of 50 kb per SNP. Five subgroups including Lan, LRC, PB, Reid, and SPT were inferred using 4000 SNPs with minor allele frequency ≥0.200, a result that was largely consistent with the pedigree information for these 240 inbred lines. With a cutoff value of r 2 < 0.100, linkage disequilibrium (LD) decay distances along the ten chromosomes of maize ranged from 397 to 819 kb, with an average of 643 kb. A subtotal of 26, 35, and 23 identity-by-descent segments, which were longer than both the average LD decay distance on the corresponding chromosomes and the local LD decay distance of r 2 < 0.100, were identified in the Dan340, Huangzao4, and Mo17 derivatives, respectively. Three lower peaks for Tajima’s D overlapped with three major quantitative trait loci (qkrn7, scmv1, and qHS2.09) in these derivatives. Elucidating the genetic properties of this panel provides information for investigating the genetic architecture of agronomic traits and heterotic grouping during maize breeding.

Genomic best linear unbiased prediction method reflecting the degree of linkage disequilibrium.

The degree of linkage disequilibrium (LD) between markers differs depending on the location of the genome; this difference biases genetic evaluation by genomic best linear unbiased prediction (GBLUP). To correct this bias, we used three GBLUP methods reflecting the degree of LD (GBLUP-LD). In the three GBLUP-LD methods, genomic relationship matrices were conducted from single nucleotide polymorphism markers weighted according to local LD levels. The predictive abilities of GBLUP-LD were investigated by estimating variance components and assessing the accuracies of estimated breeding values using simulation data. When quantitative trait loci (QTL) were located at weak LD regions, the predictive abilities of the three GBLUP-LD methods were superior to those of GBLUP and Bayesian lasso except when the number of QTL was small. In particular, the superiority of GBLUP-LD increased with decreasing trait heritability. The rates of QTL at weak LD regions would increase when selection by GBLUP continues; this consequently decreases the predictive ability of GBLUP. Thus, the GBLUP-LD could be applicable for populations selected by GBLUP for a long time. However, if QTL were located at strong LD regions, the accuracies of three GBLUP-LD methods were lower than GBLUP and Bayesian lasso.

Chronic Periodontitis Genome-wide Association Studies

Recent genome-wide association studies (GWAS) of chronic periodontitis (CP) offer rich data sources for the investigation of candidate genes, functional elements, and pathways. We used GWAS data of CP (n = 4,504) and periodontal pathogen colonization (n = 1,020) from a cohort of adult Americans of European descent participating in the Atherosclerosis Risk in Communities study and employed a MAGENTA approach (i.e., meta-analysis gene set enrichment of variant associations) to obtain gene-centric and gene set association results corrected for gene size, number of single-nucleotide polymorphisms, and local linkage disequilibrium characteristics based on the human genome build 18 (National Center for Biotechnology Information build 36). We used the Gene Ontology, Ingenuity, KEGG, Panther, Reactome, and Biocarta databases for gene set enrichment analyses. Six genes showed evidence of statistically significant association: 4 with severe CP (NIN, p = 1.6 × 10−7; ABHD12B, p = 3.6 × 10−7; WHAMM, p = 1.7 × 10−6; AP3B2, p = 2.2 × 10−6) and 2 with high periodontal pathogen colonization (red complex–KCNK1, p = 3.4 × 10−7; Porphyromonas gingivalis–DAB2IP, p = 1.0 × 10−6). Top-ranked genes for moderate CP were HGD (p = 1.4 × 10−5), ZNF675 (p = 1.5 × 10−5), TNFRSF10C (p = 2.0 × 10−5), and EMR1 (p = 2.0 × 10−5). Loci containing NIN, EMR1, KCNK1, and DAB2IP had showed suggestive evidence of association in the earlier single-nucleotide polymorphism–based analyses, whereas WHAMM and AP2B2 emerged as novel candidates. The top gene sets included severe CP (“endoplasmic reticulum membrane,” “cytochrome P450,” “microsome,” and “oxidation reduction”) and moderate CP (“regulation of gene expression,” “zinc ion binding,” “BMP signaling pathway,” and “ruffle”). Gene-centric analyses offer a promising avenue for efficient interrogation of large-scale GWAS data. These results highlight genes in previously identified loci and new candidate genes and pathways possibly associated with CP, which will need to be validated via replication and mechanistic studies.

The peopling of Greenland: further insights from the analysis of genetic diversity using autosomal and X-chromosomal markers.

The peopling of Greenland has a complex history shaped by population migrations, isolation and genetic drift. The Greenlanders present a genetic heritage with components of European and Inuit groups; previous studies using uniparentally inherited markers in Greenlanders have reported evidence of a sex-biased, admixed genetic background. This work further explores the genetics of the Greenlanders by analysing autosomal and X-chromosomal data to obtain deeper insights into the factors that shaped the genetic diversity in Greenlanders. Fourteen Greenlandic subsamples from multiple geographical settlements were compared to assess the level of genetic substructure in the Greenlandic population. The results showed low levels of genetic diversity in all sets of the genetic markers studied, together with an increased number of X-chromosomal loci in linkage disequilibrium in relation to the Danish population. In the broader context of worldwide populations, Greenlanders are remarkably different from most populations, but they are genetically closer to some Inuit groups from Alaska. Admixture analyses identified an Inuit component in the Greenlandic population of approximately 80%. The sub-populations of Ammassalik and Nanortalik are the least diverse, presenting the lowest levels of European admixture. Isolation-by-distance analyses showed that only 16% of the genetic substructure of Greenlanders is most likely to be explained by geographic barriers. We suggest that genetic drift and a differentiated settlement history around the island explain most of the genetic substructure of the population in Greenland.

Evidence of substantial recombination among Trypanosoma cruzi II strains from Minas Gerais

Due to the scarcity of evidence of sexuality in Trypanosoma cruzi, the causative agent of Chagas disease, it has been general accepted that the parasite reproduction is essentially clonal with infrequent genetic recombination. This assumption is mainly supported by indirect evidence, such as Hardy–Weinberg imbalances, linkage disequilibrium and a strong correlation between independent sets of genetic markers of T. cruzi populations. However, because the analyzed populations are usually isolated from different geographic regions, the possibility of population substructuring as generating these genetic marker imbalances cannot be eliminated. To investigate this possibility, we firstly compared the allele frequencies and haplotype networks using seven different polymorphic loci (two from mitochondrial and five from different nuclear chromosomes) in two groups of TcII strains: one including isolates obtained from different regions in Latin America and the other including isolates obtained only from patients of the Minas Gerais State in Brazil. Our hypothesis was that if the population structure is essentially clonal, Hardy–Weinberg disequilibrium and a sharp association between the clusters generated by analyzing independent markers should be observed in both strain groups, independent of the geographic origin of the samples. The results demonstrated that the number of microsatellite loci in linkage disequilibrium decreased from 4 to 1 when only strains from Minas Gerais were analyzed. Moreover, we did not observed any correlation between the clusters when analyzing the nuclear and mitochondrial loci, suggesting independent inheritance of these markers among the Minas Gerais strains. Besides, using a second subset of five physically linked microsatellite loci and the Minas Gerais strains, we could also demonstrate evidence of homologous recombination roughly proportional to the relative distance among them. Taken together, our results do not support a clonal population structure for T. cruzi, particularly in TcII, which coexists in the same geographical area, suggesting that genetic exchanges among these strains may occur more frequently than initially expected.

A commentary on Pitfalls of predicting complex traits from SNPs

In their recent Opinion article (Pitfalls of predicting complex traits from SNPs. Nature Rev. Genet. 14, 507–515 (2013))1, Wray and co-authors discuss prediction of complex traits using single-nucleotide polymorphisms (SNPs). We would like to further elaborate and qualify some topics. As stated by Wray and co-authors1, knowing the proportion of variance of a trait that is explained by regression on markers in the population (h2M) is relevant because, in principle, h2M represents the maximum prediction accuracy (R2TST) that is achievable in testing (TST) data if marker effects were known2. Following one study3, Wray and co-authors1 suggest estimating h2M using a ratio of variance components that are inferred from a G-BLUP analysis (h2G-BLUP). However, the realized proportions of allele sharing at markers and at causal loci can be very different4 owing to, for example, imperfect marker–causal loci linkage disequilibrium (LD). Consequently, the marker-based model may largely misrepresent the data-generating process; this is exacerbated with unrelated individuals5. Under these conditions, it is not clear that the finite sample estimate of h2G-BLUP is an unbiased estimate of h2M (REF. 5), conseqeuenty, it is not obvious that R2TST can achieve values equal to the finite sample estimate of h2G-BLUP. In a recent article5, we studied the R2TST of G-BLUP and its relationship with h2G-BLUP. We show analytically that mis-specification of the training–testing (TRN–TST) genomic relationships (owing to, for example, imperfect marker–causal loci LD) can impose a large-sample upper bound on R2TST that is considerably lower than the finite sample estimate of h2G-BLUP. The same study5 also presents simulation scenarios with nominally unrelated individuals, where R2TST can be extremely low in situations with markedly different h2G-BLUP, suggesting a tenuous relationship between h2G-BLUP and R2TST, even with moderately large TRN samples.

Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region

Genome-wide association studies have successfully identified associations between common diseases and a large number of single nucleotide polymorphisms (SNPs) across the genome. We investigate the effectiveness of several statistics, including p-values, likelihoods, genetic map distance and linkage disequilibrium between SNPs, in filtering SNPs in several disease-associated regions. We use simulated data to compare the efficacy of filters with different sample sizes and for causal SNPs with different minor allele frequencies (MAFs) and effect sizes, focusing on the small effect sizes and MAFs likely to represent the majority of unidentified causal SNPs. In our analyses, of all the methods investigated, filtering on the ranked likelihoods consistently retains the true causal SNP with the highest probability for a given false positive rate. This was the case for all the local linkage disequilibrium patterns investigated. Our results indicate that when using this method to retain only the top 5% of SNPs, even a causal SNP with an odds ratio of 1.1 and MAF of 0.08 can be retained with a probability exceeding 0.9 using an overall sample size of 50,000.

Enhanced Localization of Genetic Samples through Linkage-Disequilibrium Correction

Characterizing the spatial patterns of genetic diversity in human populations has a wide range of applications, from detecting genetic mutations associated with disease to inferring human history. Current approaches, including the widely used principal-component analysis, are not suited for the analysis of linked markers, and local and long-range linkage disequilibrium (LD) can dramatically reduce the accuracy of spatial localization when unaccounted for. To overcome this, we have introduced an approach that performs spatial localization of individuals on the basis of their genetic data and explicitly models LD among markers by using a multivariate normal distribution. By leveraging external reference panels, we derive closed-form solutions to the optimization procedure to achieve a computationally efficient method that can handle large data sets. We validate the method on empirical data from a large sample of European individuals from the POPRES data set, as well as on a large sample of individuals of Spanish ancestry. First, we show that by modeling LD, we achieve accuracy superior to that of existing methods. Importantly, whereas other methods show decreased performance when dense marker panels are used in the inference, our approach improves in accuracy as more markers become available. Second, we show that accurate localization of genetic data can be achieved with only a part of the genome, and this could potentially enable the spatial localization of admixed samples that have a fraction of their genome originating from a given continent. Finally, we demonstrate that our approach is resistant to distortions resulting from long-range LD regions; such distortions can dramatically bias the results when unaccounted for.

Genetic structure of the Atlantic Rainforest tree species Luehea divaricata (Malvaceae)

The Atlantic Rain Forest is one of the most important Brazilian biomes and a hotspot for biodiversity that is characterized by its high level of endemism, where new species are still being described. Luehea divaricata (Malvaceae) is commonly found in riparian forests areas of the Atlantic forest. Because of the importance of this species in reforestation programs, we used nine pairs of microsatellite loci to study the genetic variability of this species along its distribution area and verify if fragmentation is compromising the survival of these populations. A total of 50 alleles were obtained with an average observed and expected heterozygosity of 0.53 and 0.67, respectively. Seven of the nine populations studied showed a heterozygosity deficit. Most of the genetic diversity was found within populations; while the level of genetic differentiation was moderated (6.84) between populations. Different levels of gene flow between the populations were detected. Positive and significant values of Fis were found for seven populations. The signal test for excess of heterozygosity indicated that a recent genetic bottleneck occurred in the fragmented populations. The dendrogram constructed by the UPGMA method revealed the formation of seven clusters, which was confirmed by the Bayesian analysis for number of K clusters. The presence of several pairs of loci in linkage disequilibrium confirms that these populations experienced a loss of genetic diversity caused by genetic drift. The results showed that it is necessary to develop management strategies for the conservation of these populations of L. divaricata as the viability of the next generations are severely compromised.

A Connected Set of Genes Associated with Programmed Cell Death Implicated in Controlling the Hypersensitive Response in Maize

Rp1-D21 is a maize auto-active resistance gene conferring a spontaneous hypersensitive response (HR) of variable severity depending on genetic background. We report an association mapping strategy based on the Mutant Assisted Gene Identification and Characterization approach to identify naturally occurring allelic variants associated with phenotypic variation in HR. Each member of a collection of 231 diverse inbred lines of maize constituting a high-resolution association mapping panel were crossed to a parental stock heterozygous for Rp1-D21, and the segregating F(1) generation testcrosses were evaluated for phenotypes associated with lesion severity for 2 years at two locations. A genome-wide scan for associations with HR was conducted with 47,445 SNPs using a linear mixed model that controlled for spurious associations due to population structure. Since the ability to identify candidate genes and the resolution of association mapping are highly influenced by linkage disequilibrium (LD), we examined the extent of genome-wide LD. On average, marker pairs separated by >10 kbp had an r(2) value of <0.1. Genomic regions surrounding SNPs significantly associated with HR traits were locally saturated with additional SNP markers to establish local LD structure and precisely identify candidate genes. Six significantly associated SNPs at five loci were detected. At each locus, the associated SNP was located within or immediately adjacent to candidate causative genes predicted to play significant roles in the control of programmed cell death and especially in ubiquitin pathway-related processes.

Genome-wide and local pattern of linkage disequilibrium and persistence of phase for 3 Danish pig breeds

BackgroundThe extent of linkage disequilibrium (LD) is of critical importance for genomic selection and marker assisted selection. The primary purpose of this study is to examine patterns of LD in three Danish pig breeds (Duroc, Landrace and Yorkshire); we also examine patterns of persistence of phase between the breeds. We quantify local LD by fitting a model relating LD to physical distance between markers in sliding windows, and use this to visualize how LD varies according to physical position. We use a similar method to examine local persistence of phase.ResultsAverage LD decay over distance for Duroc was significantly different from Landrace and Yorkshire, that showed similar patterns. Persistence of phase between Landrace and Yorkshire was much higher than between these breeds and Duroc. Local r2 over the chromosomes showed more variation between breeds than average r2 decay across whole genome. Also local persistence of phase was higher between Landrace and Yorkshire than between these breeds and Duroc.ConclusionsThe results concerning genome-wide LD indicated that Duroc had “old inbreeding”, and confirmed the mixture history of Landrace and Yorkshire, which is also implied by the higher level of persistence of phase between Landrace and Yorkshire. The method to estimate and visualize local pattern of LD and persistence of phase provides insight into how these quantities vary along chromosomes and between breeds.

Improved Heritability Estimation from Genome-wide SNPs

Estimation of narrow-sense heritability, h(2), from genome-wide SNPs genotyped in unrelated individuals has recently attracted interest and offers several advantages over traditional pedigree-based methods. With the use of this approach, it has been estimated that over half the heritability of human height can be attributed to the ~300,000 SNPs on a genome-wide genotyping array. In comparison, only 5%-10% can be explained by SNPs reaching genome-wide significance. We investigated via simulation the validity of several key assumptions underpinning the mixed-model analysis used in SNP-based h(2) estimation. Although we found that the method is reasonably robust to violations of four key assumptions, it can be highly sensitive to uneven linkage disequilibrium (LD) between SNPs: contributions to h(2) are overestimated from causal variants in regions of high LD and are underestimated in regions of low LD. The overall direction of the bias can be up or down depending on the genetic architecture of the trait, but it can be substantial in realistic scenarios. We propose a modified kinship matrix in which SNPs are weighted according to local LD. We show that this correction greatly reduces the bias and increases the precision of h(2) estimates. We demonstrate the impact of our method on the first seven diseases studied by the Wellcome Trust Case Control Consortium. Our LD adjustment revises downward the h(2) estimate for immune-related diseases, as expected because of high LD in the major-histocompatibility region, but increases it for some nonimmune diseases. To calculate our revised kinship matrix, we developed LDAK, software for computing LD-adjusted kinships.

Novel Putative Polymorphism in SERPINC1 Encoding Antithrombin III Is Implicated in Elevated Estimated Systolic Pulmonary Pressure in Patients with Chuvash Polycythemia.

AbstractAbstract 2869Chuvash polycythemia (CP) is characterized by homozygosity for the R200W mutation in the von Hippel Lindau gene (VHL). This rare genetic disorder causes elevated levels of hypoxia inducible factor (HIF)-1 and HIF-2 that trigger constitutive hypoxia responses at normoxia. Hypoxia is a recognized cause of pulmonary hypertension. We recently reported that systolic pulmonary artery pressure (SPAP) estimated by echocardiography-determined tricuspid regurgitation velocity (TRV) was elevated in 120 CP patients compared to 31 Chuvash controls (P = 0.005), and that increasing age (P = 0.001), increasing systemic pulse pressure (P = 0.003) and lower serum ferritin concentration (P = 0.009) were independent predictors of higher estimated SPAP in CP patients [Sable et al., 2012]. In this study, we profiled gene expression for 16,642 genes in peripheral blood mononuclear cells (PBMCs) derived from a cohort of 43 CP patients, and measured the TRV for these individuals. Based on a prospectively chosen criterion of TRV ≥2.5 m/sec, 20 patients were classified as having elevated level of estimated SPAP and 23 were normal. Gene expression level between these two SPAP groups appeared to be homogenous. However, we identified 4777 genes at false discovery rate (FDR) <0.05 that exhibit pulse pressure by SPAP group interaction, suggesting a profound difference in pulse pressure regulation between the two SPAP groups.Further analysis of probe level data revealed a potential genetic polymorphism located within exon 7 of SERPINC1, encoding antithrombin III, at a site where a disease-associated SNP has not been reported. The minor allele of this polymorphism, which we designated “B”, was highly enriched in the elevated estimated SPAP group (P=0.0009), and classification based on the putative SERPINC1 genotypes strengthens the interaction effect with pulse pressure. Analysis of the gene expression data for the 43 CP patients with an additive genetic model of SERPINC1 identified 1902 differential genes at FDR <0.05. The 1120 genes up-regulated by the B allele were highly enriched in the Reactome G-protein coupled receptor pathway (Padjusted < 8×10−10). Several genes involved in smooth muscle contraction, regulation of blood pressure, and angiogenesis were up-regulated by the putative B allele, for example, HTR5A (serotonin receptor 5A), TAC3 (tachykinin 3), ADRA1D (adrenergic alpha-1D- receptor), BDKRB1 (bradykinin receptor B1), BDKRB2 (bradykinin receptor B1), EDN2 (endothelin 2), PTGER1 (prostaglandin E receptor 1), PTGIR (prostaglandin I2 receptor), APLNR (apelin receptor), RAMP2 (receptor activity modifying protein 2), MYH6 (myosin heavy chain 6), MYH7 (myosin heavy chain 7), MYL2 (myosin light chain 2), MYLK2 (myosin light chain kinase 2), MYLK3 (myosin light chain kinase 3), ACE (angiotensin I converting enzyme 1), ATP2A1 (ATPase cardiac muscle fast twitch 1), ADCY4 (adenylate cyclase 4), and PRKAA2 (protein kinase AMP-activated alpha 2 catalytic subunit). On the other hand, genes whose malfunction has been associated with familial pulmonary hypertension, including BMPR2 (bone morphogenetic protein receptor, type II), SMAD5 (SMAD family member 5), and ACVR2A (activin A receptor, type IIA), were among the 782 genes down regulated by the B allele.These results suggest that alterations in SERPINC1 may be implicated in the development of elevated SPAP in patients with CP. Antithrombin III deficiency is a potential factor in chronic thromboembolic pulmonary hypertension, but our results suggest that the putative B polymorphism may have effects beyond the coagulation cascade. Whether this is due to the SERPINC1 polymorphism itself or to another locus in linkage disequilibrium will require our future planned studies, beginning with sequencing of SERPINC1 exon 7 and identification of the polymorphism. Disclosures:No relevant conflicts of interest to declare.

Effective size of a wild salmonid population is greatly reduced by hatchery supplementation

Many declining and commercially important populations are supplemented with captive-born individuals that are intentionally released into the wild. These supplementation programs often create large numbers of offspring from relatively few breeding adults, which can have substantial population-level effects. We examined the genetic effects of supplementation on a wild population of steelhead (Oncorhynchus mykiss) from the Hood River, Oregon, by matching 12 run-years of hatchery steelhead back to their broodstock parents. We show that the effective number of breeders producing the hatchery fish (broodstock parents; N(b)) was quite small (harmonic mean N(b)=25 fish per brood-year vs 373 for wild fish), and was exacerbated by a high variance in broodstock reproductive success among individuals within years. The low N(b) caused hatchery fish to have decreased allelic richness, increased average relatedness, more loci in linkage disequilibrium and substantial levels of genetic drift in comparison with their wild-born counterparts. We also documented a substantial Ryman-Laikre effect whereby the additional hatchery fish doubled the total number of adult fish on the spawning grounds each year, but cut the effective population size of the total population (wild and hatchery fish combined) by nearly two-thirds. We further demonstrate that the Ryman-Laikre effect is most severe in this population when (1) >10% of fish allowed onto spawning grounds are from hatcheries and (2) the hatchery fish have high reproductive success in the wild. These results emphasize the trade-offs that arise when supplementation programs attempt to balance disparate goals (increasing production while maintaining genetic diversity and fitness).

Reprioritizing Genetic Associations in Hit Regions Using LASSO‐Based Resample Model Averaging

Significance testing one SNP at a time has proven useful for identifying genomic regions that harbor variants affecting human disease. But after an initial genome scan has identified a “hit region” of association, single-locus approaches can falter. Local linkage disequilibrium (LD) can make both the number of underlying true signals and their identities ambiguous. Simultaneous modeling of multiple loci should help. However, it is typically applied ad hoc: conditioning on the top SNPs, with limited exploration of the model space and no assessment of how sensitive model choice was to sampling variability. Formal alternatives exist but are seldom used. Bayesian variable selection is coherent but requires specifying a full joint model, including priors on parameters and the model space. Penalized regression methods (e.g., LASSO) appear promising but require calibration, and, once calibrated, lead to a choice of SNPs that can be misleadingly decisive. We present a general method for characterizing uncertainty in model choice that is tailored to reprioritizing SNPs within a hit region under strong LD. Our method, LASSO local automatic regularization resample model averaging (LLARRMA), combines LASSO shrinkage with resample model averaging and multiple imputation, estimating for each SNP the probability that it would be included in a multi-SNP model in alternative realizations of the data. We apply LLARRMA to simulations based on case-control genome-wide association studies data, and find that when there are several causal loci and strong LD, LLARRMA identifies a set of candidates that is enriched for true signals relative to single locus analysis and to the recently proposed method of Stability Selection. Genet. Epidemiol. 36:451–462, 2012. © 2012 Wiley Periodicals, Inc.