A simple method to localise pleiotropic susceptibility loci using univariate linkage analyses of correlated traits

Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y ps) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

Identification of multiple quantitative trait loci linked to prion disease incubation period in mice

Polymorphisms in the prion protein gene are known to affect prion disease incubation times and susceptibility in humans and mice. However, studies with inbred lines of mice show that large differences in incubation times occur even with the same amino acid sequence of the prion protein, suggesting that other genes may contribute to the observed variation. To identify these loci we analyzed 1,009 animals from an F2 intercross between two strains of mice, CAST/Ei and NZW/OlaHSd, with significantly different incubation periods when challenged with RML scrapie prions. Interval mapping identified three highly significantly linked regions on chromosomes 2, 11, and 12; composite interval mapping suggests that each of these regions includes multiple linked quantitative trait loci. Suggestive evidence for linkage was obtained on chromosomes 6 and 7. The sequence conservation between the mouse and human genome suggests that identification of mouse prion susceptibility alleles may have direct relevance to understanding human susceptibility to bovine spongiform encephalopathy (BSE) infection, as well as identifying key factors in the molecular pathways of prion pathogenesis. However, the demonstration of other major genetic effects on incubation period suggests the need for extreme caution in interpreting estimates of variant Creutzfeldt–Jakob disease epidemic size utilizing existing epidemiological models.

When does female multiple mating evolve to adjust inbreeding? : Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait

Peer reviewed

When does female multiple mating evolve to adjust inbreeding? : Effects of inbreeding depression, direct costs, mating constraints, and polyandry as a threshold trait

Ackowledgements: This work was funded by a European Research Council Starting Grant to JMR. All simulations were performed using the Maxwell computing cluster at the University of Aberdeen

Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores

ABSTRACT Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Likert-type items, and the aim of the analysis is to estimate participants' scores on the corresponding latent traits. We propose a new approach to deal with missing responses in such a situation that is based on (1) multiple imputation of non-responses and (2) simultaneous rotation of the imputed datasets. We applied the approach in a real dataset where missing responses were artificially introduced following a real pattern of non-responses, and a simulation study based on artificial datasets. The results show that our approach (specifically, Hot-Deck multiple imputation followed of Consensus Promin rotation) was able to successfully compute factor score estimates even for participants that have missing data.

On the prediction of simultaneous inbreeding coefficients at multiple loci

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.

Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci

Objective: To perform a 1-stage meta-analysis of genome-wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci. Methods: We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta-analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease. Results: We meta-analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934T at 3p24.1 (odds ratio [OR], 1.17; p ¼ 1.6 � 10�8) near EOMES, rs2150702G in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p ¼ 3.3 � 10�8), and rs6718520A in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p ¼ 3.4 � 10�8). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 � 10�6, some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1). Interpretation: We have performed a meta-analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS.

Coping strategies used by ballet dancers : effects of individual differences in competitive trait anxiety

The purpose of the present investigation was to examine relationships between coping strategies and competitive trait anxiety among ballet dancers. Participants were 104 classical ballet dancers from three professional ballet companies, two private dance schools, and two full-time, university dance courses in Australia. Coping strategies were assessed using the Modified COPE scale (MCOPE: Crocker & Graham, 1995), while competitive trait anxiety was assessed using the Sport Anxiety Scale (SAS: Smith, Smoll, & Schutz, 1990). Standard multiple regression analyses showed that trait anxiety scores were significant predictors of seven of the 12 coping strategies, with moderate to large effect sizes. High trait anxious dancers reported more frequent use of all categories of coping strategies. A two-way MANOVA showed no main effects for gender nor status (professional versus students) and no significant interaction effect. The present results emphasize the need for the effectiveness of specific coping strategies to be considered during the process of preparing young classical dancers for a career in professional ballet.

Coping strategies used by ballet dancers : effects of individual differences in competitive trait anxiety

The world of classical ballet exerts considerable physical and psychological stress upon those who participate, and yet the process of coping with such stressors is not well understood. The purpose of the present investigation was to examine relationships between coping strategies and competitive trait anxiety among ballet dancers. Participants were 104 classical dancers (81 females and 23 males) ranging in age from 15 to 35 years (M = 19.4 yr., SD = 3.8 yr.) from three professional ballet companies, two private dance schools, and two full-time, university dance courses in Australia. Participants had a mean of 11.5 years of classical dance training (SD = 5.2 yr.), having started dance training at 6.6 years of age (SD = 3.4 yr.). Coping strategies were assessed using the Modified COPE scale (MCOPE: Crocker & Graham, 1995), a 48-item measure comprising 12 coping subscales (Seeking Social Support for Instrumental Reasons, Seeking Social Support for Emotional Reasons, Behavioral Disengagement, Planning, Suppression of Competing Activities, Venting of Emotions, Humor, Active Coping, Denial, Self-Blame, Effort, and Wishful Thinking). Competitive trait anxiety was assessed using the Sport Anxiety Scale (SAS: Smith, Smoll, & Schutz, 1990), a 21-item measure comprising three anxiety subscales (Somatic Anxiety, Worry, Concentration Disruption). Standard multiple regression analyses showed that trait anxiety scores, in particular for Somatic Anxiety and Worry, were significant predictors of seven of the 12 coping strategies (Suppression of Competing Activities: R2 = 27.1%; Venting of Emotions: R2 = 23.2%; Active Coping: R2 = 14.3%; Denial: R2 = 17.7%; Self-Blame: R2 = 35.7%; Effort: R2 = 16.6%; Wishful Thinking: R2 = 42.3%). High trait anxious dancers reported more frequent use of all categories of coping strategies. A separate two-way MANOVA showed no significant main effect for gender nor status (professional versus students) and no significant interaction effect. The present findings are generally consistent with previous research in the sport psychology domain (Crocker & Graham, 1995; Giacobbi & Weinberg, 2000) which has shown that high trait anxious athletes tend, in particular, to use more maladaptive, emotion-focused coping strategies when compared to low trait anxious athletes; a tendency which has been proposed to lead to negative performance effects. The present results emphasize the need for the effectiveness of specific coping strategies to be considered during the process of preparing young classical dancers for a career in professional ballet. In particular, the results suggest that dancers who are, by nature, anxious about performance may need special attention to help them to learn to cope with performance-related stress. Given the absence of differences in coping strategies between student and professional dancers and between males and females, it appears that such educational efforts should begin at an early career stage for all dancers.

Genetic analyses in a sample of individuals with high or low BMD shows association with multiple Wnt pathway genes

INTRODUCTION Although the high heritability of BMD variation has long been established, few genes have been conclusively shown to affect the variation of BMD in the general population. Extreme truncate selection has been proposed as a more powerful alternative to unselected cohort designs in quantitative trait association studies. We sought to test these theoretical predictions in studies of the bone densitometry measures BMD, BMC, and femoral neck area, by investigating their association with members of the Wnt pathway, some of which have previously been shown to be associated with BMD in much larger cohorts, in a moderate-sized extreme truncate selected cohort (absolute value BMD Z-scores = 1.5-4.0; n = 344). MATERIALS AND METHODS Ninety-six tag-single nucleotide polymorphism (SNPs) lying in 13 Wnt signaling pathway genes were selected to tag common genetic variation (minor allele frequency [MAF] > 5% with an r(2) > 0.8) within 5 kb of all exons of 13 Wnt signaling pathway genes. The genes studied included LRP1, LRP5, LRP6, Wnt3a, Wnt7b, Wnt10b, SFRP1, SFRP2, DKK1, DKK2, FZD7, WISP3, and SOST. Three hundred forty-four cases with either high or low BMD were genotyped by Illumina Goldengate microarray SNP genotyping methods. Association was tested either by Cochrane-Armitage test for dichotomous variables or by linear regression for quantitative traits. RESULTS Strong association was shown with LRP5, polymorphisms of which have previously been shown to influence total hip BMD (minimum p = 0.0006). In addition, polymorphisms of the Wnt antagonist, SFRP1, were significantly associated with BMD and BMC (minimum p = 0.00042). Previously reported associations of LRP1, LRP6, and SOST with BMD were confirmed. Two other Wnt pathway genes, Wnt3a and DKK2, also showed nominal association with BMD. CONCLUSIONS This study shows that polymorphisms of multiple members of the Wnt pathway are associated with BMD variation. Furthermore, this study shows in a practical trial that study designs involving extreme truncate selection and moderate sample sizes can robustly identify genes of relevant effect sizes involved in BMD variation in the general population. This has implications for the design of future genome-wide studies of quantitative bone phenotypes relevant to osteoporosis.

Detection and use of QTL for complex traits in multiple environments.

QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.

QTL mapping of multiple foliar disease and root-lesion nematode resistances in wheat.

A genetic linkage map, based on a cross between the synthetic hexaploid CPI133872 and the bread wheat cultivar Janz, was established using 111 F1-derived doubled haploid lines. The population was phenotyped in multiple years and/or locations for seven disease resistance traits, namely, Septoria tritici blotch (Mycosphaeralla graminicola), yellow leaf spot also known as tan spot (Pyrenophora tritici-repentis), stripe rust (Puccinia striiformis f. sp. tritici), leaf rust (Puccinia triticina), stem rust (Puccinia graminis f. sp. tritici) and two species of root-lesion nematode (Pratylenchyus thornei and P. neglectus). The DH population was also scored for coleoptile colour and the presence of the seedling leaf rust resistance gene Lr24. Implementation of a multiple-QTL model identified a tightly linked cluster of foliar disease resistance QTL in chromosome 3DL. Major QTL each for resistance to Septoria tritici blotch and yellow leaf spot were contributed by the synthetic hexaploid parent CPI133872 and linked in repulsion with the coincident Lr24Sr24/ locus carried by parent Janz. This is the first report of linked QTL for Septoria tritici blotch and yellow leaf spot contributed by the same parent. Additional QTL for yellow leaf spot were detected in 5AS and 5BL. Consistent QTL for stripe rust resistance were identified in chromosomes 1BL, 4BL and 7DS, with the QTL in 7DS corresponding to the Yr18Lr34/ region. Three major QTL for P. thornei resistance (2BS, 6DS, 6DL) and two for P. neglectus resistance (2BS, 6DS) were detected. The recombinants combining resistance to Septoria tritici blotch, yellow leaf spot, rust diseases and root-lesion nematodes from parents CPI133872 and Janz constitute valuable germplasm for the transfer of multiple disease resistance into new wheat cultivars.

Quantitative Trait Loci for CD4:CD8 Lymphocyte Ratio Are Associated with Risk of Type 1 Diabetes and HIV-1 Immune Control

Abnormal expansion or depletion of particular lymphocyte subsets is associated with clinical manifestations such as HIV progression to AIDS and autoimmune disease. We sought to identify genetic predictors of lymphocyte levels and reasoned that these may play a role in immune-related diseases. We tested 2.3 million variants for association with five lymphocyte subsets, measured in 2538 individuals from the general population, including CD4+ T cells, CD8+ T cells, CD56+ natural killer (NK) cells, and the derived measure CD4:CD8 ratio. We identified two regions of strong association. The first was located in the major histocompatibility complex (MHC), with multiple SNPs strongly associated with CD4:CD8 ratio (rs2524054, p = 2.1 × 10−28). The second region was centered within a cluster of genes from the Schlafen family and was associated with NK cell levels (rs1838149, p = 6.1 × 10−14). The MHC association with CD4:CD8 replicated convincingly (p = 1.4 × 10−9) in an independent panel of 988 individuals. Conditional analyses indicate that there are two major independent quantitative trait loci (QTL) in the MHC region that regulate CD4:CD8 ratio: one is located in the class I cluster and influences CD8 levels, whereas the second is located in the class II cluster and regulates CD4 levels. Jointly, both QTL explained 8% of the variance in CD4:CD8 ratio. The class I variants are also strongly associated with durable host control of HIV, and class II variants are associated with type-1 diabetes, suggesting that genetic variation at the MHC may predispose one to immune-related diseases partly through disregulation of T cell homeostasis.

On the probability of dizygotic twins being concordant for two alleles at multiple polymorphic loci

Accurate determination of same-sex twin zygosity is important for medical, scientific and personal reasons. Determination may be based upon questionnaire data, blood group, enzyme isoforms and fetal membrane examination, but assignment of zygosity must ultimately be confirmed by genotypic data. Here methods are reviewed for calculating average probabilities of correctly concluding a twin pair is monozygotic, given they share the same genotypes across all loci for commonly utilized multiplex short tandem repeat (STR) kits.