Identification of genes associated with quantitative traits involved in cardiovascular disease and lipoprotein metabolism

Cardiovascular disease (CVD) is a threat to public health. It has been reported to be the leading cause of death in United States. The invention of next generation sequencing (NGS) technology has revolutionized the biomedical research. To investigate NGS data of CVD related quantitative traits would contribute to address the unknown etiology and disease mechanism of CVD. NHLBI's Exome Sequencing Project (ESP) contains CVD related phenotypes and their associated NGS exomes sequence data. Initially, a subset of next generation sequencing data consisting of 13 CVD-related quantitative traits was investigated. Only 6 traits, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, platelet counts, waist circumference, and weight, were analyzed by functional linear model (FLM) and 7 currently existing methods. FLM outperformed all currently existing methods by identifying the highest number of significant genes and had identified 96, 139, 756, 1162, 1106, and 298 genes associated with SBP, DBP, Height, Platelet, Waist, and Weight respectively. ^

Contrasting quantitative traits and neutral genetic markers for genetic resource assessment of Mesoamerican Cedrela odorata

We compared within-population variability and degree of population differentiation for neutral genetic markers (RAPDS) and eight quantitative traits in Central American populations of the endangered tree, Cedrela odorata. Whilst population genetic diversity for neutral markers (Shannon index) and quantitative traits (heritability, coefficient of additive genetic variation) were uncorrelated, both marker types revealed strong differentiation between populations from the Atlantic coast of Costa Rica and the rest of the species' distribution. The degree of interpopulation differentiation was higher for RAPD markers (F-ST 0.67 for the sampled Mesoamerican range) than for quantitative traits (Q(ST) = 0.30). Hence, the divergence in quantitative traits was lower than could have been achieved by genetic drift alone, suggesting that balancing selection for similar phenotypes in different populations of this species. Nevertheless, a comparison of pair-wise estimates of population differentiation in neutral genetic markers and quantitative traits revealed a strong positive correlation (r = 0.66) suggesting that, for C. odorata, neutral marker divergence could be used as a surrogate for adaptive gene divergence for conservation planning. The utility of this finding and suggested further work are discussed.

Nonparametric Evaluation of Quantitative Traits in Population-Based Association Studies when the Genetic Model is Unknown

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits.

Metabolic homeostasis is achieved by complex molecular and cellular networks that differ significantly among individuals and are difficult to model with genetically engineered lines of mice optimized to study single gene function. Here, we systematically acquired metabolic phenotypes by using the EUMODIC EMPReSS protocols across a large panel of isogenic but diverse strains of mice (BXD type) to study the genetic control of metabolism. We generated and analyzed 140 classical phenotypes and deposited these in an open-access web service for systems genetics (www.genenetwork.org). Heritability, influence of sex, and genetic modifiers of traits were examined singly and jointly by using quantitative-trait locus (QTL) and expression QTL-mapping methods. Traits and networks were linked to loci encompassing both known variants and novel candidate genes, including alkaline phosphatase (ALPL), here linked to hypophosphatasia. The assembled and curated phenotypes provide key resources and exemplars that can be used to dissect complex metabolic traits and disorders.

Quantitative and qualitative differences in morphological traits revealed between diploid Fragaria species

Background and Aims: The aims of this investigation were to highlight the qualitative and quantitative diversity apparent between nine diploid Fragaria species and produce interspecific populations segregating for a large number of morphological characters suitable for quantitative trait loci analysis. Methods: A qualitative comparison of eight described diploid Fragaria species was performed and measurements were taken of 23 morphological traits from 19 accessions including eight described species and one previously undescribed species. A principal components analysis was performed on 14 mathematically unrelated traits from these accessions, which partitioned the species accessions into distinct morphological groups. Interspecific crosses were performed with accessions of species that displayed significant quantitative divergence and, from these, populations that should segregate for a range of quantitative traits were raised. Key Results: Significant differences between species were observed for all 23 morphological traits quantified and three distinct groups of species accessions were observed after the principal components analysis. Interspecific crosses were performed between these groups, and F2 and backcross populations were raised that should segregate for a range of morphological characters. In addition, the study highlighted a number of distinctive morphological characters in many of the species studied. Conclusions: Diploid Fragaria species are morphologically diverse, yet remain highly interfertile, making the group an ideal model for the study of the genetic basis of phenotypic differences between species through map-based investigation using quantitative trait loci. The segregating interspecific populations raised will be ideal for such investigations and could also provide insights into the nature and extent of genome evolution within this group.

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.

A quantitative-trait genome-wide association study of alcoholism risk in the community: findings and implications

BACKGROUND Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. METHODS Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. RESULTS No findings reached genome-wide significance (p = 8.4 x 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 x 10(-7). Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. CONCLUSIONS We conclude that: - 1) meta-analyses of consumption data may contribute usefully to gene discovery; - 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging, and; - 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).

Within-family outliers: Segregating alleles or environmental effects? A linkage analysis of height from 5815 sibling pairs

Most information in linkage analysis for quantitative traits comes from pairs of relatives that are phenotypically most discordant or concordant. Confounding this, within-family outliers from non-genetic causes may create false positives and negatives. We investigated the influence of within-family outliers empirically, using one of the largest genome-wide linkage scans for height. The subjects were drawn from Australian twin cohorts consisting of 8447 individuals in 2861 families, providing a total of 5815 possible pairs of siblings in sibships. A variance component linkage analysis was performed, either including or excluding the within-family outliers. Using the entire dataset, the largest LOD scores were on chromosome 15q (LOD 2.3) and 11q (1.5). Excluding within-family outliers increased the LOD score for most regions, but the LOD score on chromosome 15 decreased from 2.3 to 1.2, suggesting that the outliers may create false negatives and false positives, although rare alleles of large effect may also be an explanation. Several regions suggestive of linkage to height were found after removing the outliers, including 1q23.1 (2.0), 3q22.1 (1.9) and 5q32 (2.3). We conclude that the investigation of the effect of within-family outliers, which is usually neglected, should be a standard quality control measure in linkage analysis for complex traits and may reduce the noise for the search of common variants of modest effect size as well as help identify rare variants of large effect and clinical significance. We suggest that the effect of within-family outliers deserves further investigation via theoretical and simulation studies.

Directional dominance on stature and cognition in diverse human populations

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

中国蔷薇属芹叶组（Rosa Sect. Pimpinellifoliae DC. ex Ser.）的分类学研究

本研究通过我国CDBI、 KUN、PE、SZ等主要标本馆约3, 500份馆藏标本的研究和野外考察相结合，对我国蔷薇属（Rosa L.）芹叶组(Sect. pimpinellifoliae DC. ex Ser.）植物以及相关组的一些种进行了性状特征、形态和微形态的研究，对该组的一些种的形态特征描述进行了补充，同时给出详细的地理和海拔范围分布图。综合花粉以及种子（瘦果）形态的研究结果重新制订了分种检索表，同时，对该组一些形态相近容易混淆的种进行了对比研究，特别对一直存在争议的绢毛复合体（绢毛蔷薇R. sericea Lindl.和峨眉蔷薇R. omeiensis Rolfe）进行了大量宏观形态特征的研究，并用光学显微镜（LM）和扫描电镜(SEM)对二者的花粉及种子形态、微形态进行对比研究和分析，主要研究内容包括： 1. 芹叶组孢粉研究 对芹叶组的10个种及相关的4个组共17个种（18个样品）的植物花粉进行了光镜和扫描电镜观察和比较研究。研究结果表明：蔷薇属植物花粉粒大小为中等偏小，极轴长23.98[21.82(R. graciliflora Rehd. et Wils.)～29.18(R. tsinglingensis Pax. et Hoffm.)] μm，赤道轴长28.65[24.15（R. graciliflora）～34.70(R. davidii Crép.)] μm；花粉属辐射对称等极单花粉，花粉形态赤道面观呈球形到超长球形；极面观为三裂圆形或近圆形,三孔沟，孔缘加厚,具中部突起的桥状盖。花粉外壁纹饰为条纹状，光镜下形态特征相差不大；在电镜下外壁条纹和脊沟内穿孔的形状、大小和频度等特征，常具组至种水平上的可见变异，可作为组至种水平划分的依据。 根据花粉外壁条纹特征及穿孔形状和数目等特征，本研究将这些植物的花粉归为5个类型，并编制了分组检索表。同时，根据条纹状的清晰度，排列方式、条纹形状、穿孔大小及其频度等方面的差异，各有特点，对该组的10个种编制了分种检索表。 2. 芹叶组种子形态研究 应用光学显微镜和扫描电镜对我国蔷薇属芹叶组14个种及相关组5个组共36种植物的种子宏观形态及种皮微形态特征进行了观察研究。结果显示，蔷薇属种子形态多样,形状分别为肾形、卵形或锥形等；种子颜色以淡棕色、褐色以及土黄色为主；种子大小种间相差悬殊，相对体积为（长×宽×厚）36.66（4.79～114.47) mm3。光镜下，种子宏观形态特征具组内一致性，在扫描电镜下种子表面结构特征因种而异，其纹饰以网纹为主，可分为3种类型，即近平滑型、负网纹型和网纹型。研究结果表明，蔷薇属种子表面纹饰与地理分布关系不大,具有组及种内稳定性。其种子形态、大小、表而纹饰类型等特征可作为蔷薇属组及种水平上的分类依据。 结合蔷薇属花粉形态研究结果，得出蔷薇属种皮微形态特征与花粉外壁纹饰特征相吻合，在代表组及种的特征上具相关性的结论。同时根据种子形态、微形态结构特征的组间区别和种间差异编制了分组及芹叶组14个种的分种检索表。 3. 绢毛蔷薇复合体的研究 通过对大量标本的研究、野外观察以及扫描电镜对绢毛蔷薇复合体的花粉形态和种皮表面结构进行研究，通过对小叶、花粉及种子的形态定量分析结果支持Rowley (1959)的观点，将峨眉蔷薇处理为绢毛蔷薇的一个变种。 综上研究结果得出，蔷薇属植物的小叶片数目、花被基数以及花粉及种子形态等性状是较为稳定的，这些特征可很好的作为分类学依据。 The morphology, pollen exine sculpture and seed coat structure of the species of Rosa sect. Pimpinellifoliae and related sections were studied.About 3,500 herbarium specimens at CDBI, KUN, PE, and SZ were examined. Field work in Sichuan and Yunnan were conducted. Revisions of some species were carried out and a new key to species of sect. Pimpinellifoliae was proposed based on morphology, pollen exine sculpture and seed coat structure, Detailed morphological descriptions, geographical distributions and the altitudinal ranges of some taxa are given. The systematics of the species complex, the Rosa sericea complex (R. sericea Lindl. & R. omeiensis Rolfe), was emphasized. This thesis focused on the following three aspects: 1. Pollen morphology of Rosa sect. Pimpinellifoliae The pollen morphology of 18 samples representing 10 species of the Eurasian Rosa sect. Pimpinellifoliae and 7 additional species of related sections was investigated under LM and SEM. The pollen grains are monadic, actinomorphic, equipolar, medium-sized, spheroidal to perprolate in equatorial view, 3-lobed circular or semi-circular in polar view, crassimarginate, pontoperculate, and with striate exine sculpture. The striate sculpture varies among sections and species. The equatorial axis ranges from 17.97 μm (R. sikangensis) to 29.18 μm (R. tsinglingensis) with an average of 23.98 μm in length, while polar axis varies from 24.15 μm (R. gracilifolra) to 34.70 μm (R. davidii) with an average of 28.65 μm in length. The pollens can be divided into five types based on striate sculpture and a key to the sections sampled was proposed accordingly. The pollen morphology of species of sect. Pimpinellifoliae is more homogeneous and different from other sections sampled and did not support the two-series subdivisions in sect. Pimpinellifoliae. A key is also provided based on characers of pollen morphology among species in sect. Pimpinellifoliae. 2. Seed coat structure of Rosa sect. Pimpinellifoliae The seed coat structure of 39 samples representing 14 species of Rosa sect. Pimpinellifoliae and 12 additional species of related sections was investigated under LE and SEM. The seed relative volume (Length × width × thickness) ranges from 4.79 to 114.47 mm3 with an average of 36.66. mm3. The seeds are reniform, ovate or oblong in shape, with orange-brown, light brown or deep brown color. Seed coat sculpture was reticulate or striate-like reticulate. There was no difference in sculpture character of various speices under LM, while three types of seed coat sculpture were identified under SEM and a key to species based on the seed coat sculpture was provided. The three types of seed coat sculpture were nearly smooth, areolate and reticulate. The study of the seed coat sculpture of same species sampled from different populations showed that characters on the seed coat are stable, and thus the size, shape and seed coat sculpture can be used in species level identification. Interestingly, characters in the seed coat sculpture and the pollen morphology in sect. Pimpinellifoliae are consistent at in specific or sectional levels. A key to the 14 species sampled was given based on seed coat sculpture. 3. The study on Rosa sericea complex The Rosa sericea complex contains R. omeiensis and R. sericea. They are morphologically similar to one another and the systematic status of R. omeiensis has been controversial. In this study we examined large numbers of herbarium specimens of R. omeiensis and R. sericea and conducted field observations in the Hengduan Mts.. We also performed SEM study of pollen morphology and seed coat structure of R. omeiensis and R. sericea. We further carried out intensive morphometric study on the leaflet, pollen, and seed morphology. Our results showed that R. omeiensis should be sunk to be a variety of R. sericea, just as Rowley’s treatment in 1959. In conclusion, the features in the number of leaflet and petal, and the morphological character on pollen and seed are relatively stable. Therefore these characters are very useful in taxon delimition.

Application of a rank-based genetic association test to age-at-onset data from the Collaborative Study on the Genetics of Alcoholism study.

Association studies of quantitative traits have often relied on methods in which a normal distribution of the trait is assumed. However, quantitative phenotypes from complex human diseases are often censored, highly skewed, or contaminated with outlying values. We recently developed a rank-based association method that takes into account censoring and makes no distributional assumptions about the trait. In this study, we applied our new method to age-at-onset data on ALDX1 and ALDX2. Both traits are highly skewed (skewness > 1.9) and often censored. We performed a whole genome association study of age at onset of the ALDX1 trait using Illumina single-nucleotide polymorphisms. Only slightly more than 5% of markers were significant. However, we identified two regions on chromosomes 14 and 15, which each have at least four significant markers clustering together. These two regions may harbor genes that regulate age at onset of ALDX1 and ALDX2. Future fine mapping of these two regions with densely spaced markers is warranted.

How trophic interaction strength depends on traits

A key problem in community ecology is to understand how individual-level traits give rise to population-level trophic interactions. Here, we propose a synthetic framework based on ecological considerations to address this question systematically. We derive a general functional form for the dependence of trophic interaction coefficients on trophically relevant quantitative traits of consumers and resources. The derived expression encompasses-and thus allows a unified comparison of-several functional forms previously proposed in the literature. Furthermore, we show how a community's, potentially low-dimensional, effective trophic niche space is related to its higher-dimensional phenotypic trait space. In this manner, we give ecological meaning to the notion of the "dimensionality of trophic niche space." Our framework implies a method for directly measuring this dimensionality. We suggest a procedure for estimating the relevant parameters from empirical data and for verifying that such data matches the assumptions underlying our derivation. © Springer Science+Business Media B.V. 2009.


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Estimation des corrélations phylogénétiques entre paramètres d'évolution moléculaire et Traits d'histoire de vie

Depuis quelques années, l'évolution moléculaire cherche à caractériser les variations et l'intensité de la sélection grâce au rapport entre taux de substitution synonyme et taux de substitution non-synonyme (dN/dS). Cette mesure, dN/dS, a permis d'étudier l'histoire de la variation de l'intensité de la sélection au cours du temps ou de détecter des épisodes de la sélection positive. Les liens entre sélection et variation de taille efficace interfèrent cependant dans ces mesures. Les méthodes comparatives, quant a elle, permettent de mesurer les corrélations entre caractères quantitatifs le long d'une phylogénie. Elles sont également utilisées pour tester des hypothèses sur l'évolution corrélée des traits d'histoire de vie, mais pour être employées pour étudier les corrélations entre traits d'histoire de vie, masse, taux de substitution ou dN/dS. Nous proposons ici une approche combinant une méthode comparative basée sur le principe des contrastes indépendants et un modèle d'évolution moléculaire, dans un cadre probabiliste Bayésien. Intégrant, le long d'une phylogénie, sur les reconstructions ancestrales des traits et et de dN/dS nous estimons les covariances entre traits ainsi qu'entre traits et paramètres du modèle d'évolution moléculaire. Un modèle hiérarchique, a été implémenté dans le cadre du logiciel coevol, publié au cours de cette maitrise. Ce modèle permet l'analyse simultané de plusieurs gènes sans perdre la puissance donnée par l'ensemble de séquences. Un travail deparallélisation des calculs donne la liberté d'augmenter la taille du modèle jusqu'à l'échelle du génome. Nous étudions ici les placentaires, pour lesquels beaucoup de génomes complets et de mesures phénotypiques sont disponibles. À la lumière des théories sur les traits d'histoire de vie, notre méthode devrait permettre de caractériser l'implication de groupes de gènes dans les processus biologique liés aux phénotypes étudiés.