Discovery and fine mapping of serum protein loci through transethnic meta-analysis.

Many disorders are associated with altered serum protein concentrations, including malnutrition, cancer, and cardiovascular, kidney, and inflammatory diseases. Although these protein concentrations are highly heritable, relatively little is known about their underlying genetic determinants. Through transethnic meta-analysis of European-ancestry and Japanese genome-wide association studies, we identified six loci at genome-wide significance (p < 5 × 10(-8)) for serum albumin (HPN-SCN1B, GCKR-FNDC4, SERPINF2-WDR81, TNFRSF11A-ZCCHC2, FRMD5-WDR76, and RPS11-FCGRT, in up to 53,190 European-ancestry and 9,380 Japanese individuals) and three loci for total protein (TNFRS13B, 6q21.3, and ELL2, in up to 25,539 European-ancestry and 10,168 Japanese individuals). We observed little evidence of heterogeneity in allelic effects at these loci between groups of European and Japanese ancestry but obtained substantial improvements in the resolution of fine mapping of potential causal variants by leveraging transethnic differences in the distribution of linkage disequilibrium. We demonstrated a functional role for the most strongly associated serum albumin locus, HPN, for which Hpn knockout mice manifest low plasma albumin concentrations. Other loci associated with serum albumin harbor genes related to ribosome function, protein translation, and proteasomal degradation, whereas those associated with serum total protein include genes related to immune function. Our results highlight the advantages of transethnic meta-analysis for the discovery and fine mapping of complex trait loci and have provided initial insights into the underlying genetic architecture of serum protein concentrations and their association with human disease.

CUBN is a gene locus for albuminuria.

Identification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10(-11)) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.

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.

Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs

Although Ca transport in plants is highly complex, the overexpression of vacuolar Ca2+ transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca2+ transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.

A quantitative nature of somatic embryogenesis in soybean

The objectives of this research were to investigate the genetic parameters associated with the in vitro formation of somatic embryos in soybean and to determine the effect of light intensity on the embryogenic capability of F-1, F-2, and backcross (RC1P1 and RC1P2) progenies derived from crosses between embryogenic (IAS-5 and Embrapa-1) and nonembryogenic (Parana) cultivars. Immature cotyledons (4-6 mm in length) derived from the parental lines, F-1, F-2, RC1P1, and RC1P2 were grown for 90 d on the inductive N10 medium, after which the number of somatic embryos was recorded. Chi-square tests for goodness of fit showed that the genetic component of the somatic embryogenesis trait is controlled in a quantitative manner by approximately 10 genes. A normal distribution for somatic embryo formation in the F-2 generations was observed reinforcing the quantitative nature of the trait. Variation in light intensity (8-12 and 27-33 mu mol m(-2) s(-1)) had no effect on somatic embryo formation in the parental material tested.

Strong selection against hybrids at a hybrid zone in the Ensatina ring species complex and its evolutionary implications

The analysis of interactions between lineages at varying levels of genetic divergence can provide insights into the process of speciation through the accumulation of incompatible mutations. Ring species, and especially the Ensatina eschscholtzii system exemplify this approach. The plethodontid salamanders E. eschscholtzii xanthoptica and E. eschscholtzii platensis hybridize in the central Sierran foothills of California. We compared the genetic structure across two transects (southern and northern Calaveras Co.), one of which was resampled over 20 years, and examined diagnostic molecular markers (eight allozyme loci and mitochondrial DNA) and a diagnostic quantitative trait (color pattern). Key results across all studies were: (1) cline centers for all markers were coincident and the zones were narrow, with width estimates of 730 m to 2000 m; (2) cline centers at the northern Calaveras transect were coincident between 1981 and 2001, demonstrating repeatability over five generations; (3) there were very few if any putative F1s, but a relatively high number of backcrossed individuals in the central portion of transects: and (4) we found substantial linkage disequilibrium in all three studies and strong heterozygote deficit both in northern Calaveras, in 2001, and southern Calaveras. Both linkage disequilibrium and heterozygote deficit showed maximum values near the center of the zones. Using estimates of cline width and dispersal, we infer strong selection against hybrids. This is sufficient to promote accumulation of differences at loci that are neutral or under divergent selection, but would still allow for introgression of adaptive alleles. The evidence for strong but incomplete isolation across this centrally located contact is consistent with theory suggesting a gradual increase in postzygotic incompatibility between allopatric populations subject to divergent selection and reinforces the value of Ensatina as a system for the study of divergence and speciation at multiple stages. © 2005 The Society for the Study of Evolution. All rights reserved.

Genome-wide association with residual body weight gain in Bos indicus cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relationship of short tandem repeats flanking leptin-melanocortin pathway genes with anthropometric profile and leptinemia in Brazilian individuals

Objective: To investigate the relationship of short tandem repeats (STR) near genes involved in the leptin-melanocortin pathway with body mass index (BMI) and leptinemia. Subjects and methods: Anthropometric variables and leptinemia were measured in 100 obese and 110 non-obese individuals. D1S200, D2S1788, DS11912, and D18S858 loci were analyzed by PCR and high-resolution electrophoresis. Results: Overall STR allele frequencies were similar between the obese and non-obese group (p > 0.05). Individual alleles D1S200 (17), D11S912 (43), D18S858 (11/12) were associated with obesity (p < 0.05). Individuals carrying these alleles showed higher BMI than non-carriers (p < 0.05). Moreover, a relationship between D18S858 11/12 alleles and increased waist circumference was found (p = 0.040). On the other hand, leptinemia was not influenced by the studied STRs (p > 0.05). Conclusions: D1S200, D11S912, and D18S858 loci are associated with increased BMI and risk for obesity in this sample. Arq Bras Endocrinol Metab. 2012;56(1):47-53

Evidence of neutral and adaptive genetic divergence between European trout populations sampled along altitudinal gradients

Species with a wide geographical distribution are often composed of distinct subgroups which may be adapted to their local environment. European trout (Salmo trutta species complex) provide an example of such a complex consisting of several genetically and ecologically distinct forms. However, trout populations are strongly influenced by human activities, and it is unclear to what extent neutral and adaptive genetic differences have persisted. We sampled 30 Swiss trout populations from heterogeneous environments along replicated altitudinal gradients in three major European drainages. More than 850 individuals were genotyped at 18 microsatellite loci which included loci diagnostic for evolutionary lineages and candidate markers associated with temperature tolerance, reproductive timing and immune defence. We find that the phylogeographic structure of Swiss trout populations has not been completely erased by stocking. Distinct genetic clusters corresponding to the different drainages could be identified, although nonindigenous alleles were clearly present, especially in the two Mediterranean drainages. We also still detected neutral genetic differentiation within rivers which was often associated with the geographical distance between populations. Five loci showed evidence of divergent selection between populations with several drainage-specific patterns. Lineage-diagnostic markers, a marker linked to a quantitative trait locus for upper temperature tolerance in other salmonids and a marker linked to the major histocompatibility class I gene were implicated in local adaptation and some patterns were associated with altitude. In contrast, tentative evidence suggests a signal of balancing selection at a second immune relevant gene (TAP2). Our results confirm the persistence of both neutral and potentially adaptive genetic differences between trout populations in the face of massive human-mediated dispersal.

Evolution of dominance under frequency-dependent intraspecific competition

A population-genetic analysis is performed of a two-locus two-allele model, in which the primary locus has a major effect on a quantitative trait that is under frequency-dependent disruptive selection caused by intraspecific competition for a continuum of resources. The modifier locus determines the degree of dominance at the trait level. We establish the conditions when a modifier allele can invade and when it becomes fixed if sufficiently frequent. In general, these are not equivalent because an unstable internal equilibrium may exist and the condition for successful invasion of the modifier is more restrictive than that for eventual fixation from already high frequency. However, successful invasion implies global fixation, i.e., fixation from any initial condition. Modifiers of large effect can become fixed, and also invade, in a wider parameter range than modifiers of small effect. We also study modifiers with a direct, frequency-independent deleterious fitness effect. We show that they can invade if they induce a sufficiently high level of dominance and if disruptive selection on the ecological trait is strong enough. For deleterious modifiers, successful invasion no longer implies global fixation because they can become stuck at an intermediate frequency due to a stable internal equilibrium. Although the conditions for invasion and for fixation if sufficiently frequent are independent of the linkage relation between the two loci, the rate of spread depends strongly on it. The present study provides further support to the view that evolution of dominance may be an efficient mechanism to remove unfit heterozygotes that are maintained by balancing selection. It also demonstrates that an invasion analysis of mutants of very small effect is insufficient to obtain a full understanding of the evolutionary dynamics under frequency-dependent selection.

The genetics of reproductive organ morphology in two Petunia species with contrasting pollination syndromes

Main conclusion Switches between pollination syndromes have happened frequently during angiosperm evolution. Using QTL mapping and reciprocal introgressions, we show that changes in reproductive organ morphology have a simple genetic basis. In animal-pollinated plants, flowers have evolved to optimize pollination efficiency by different pollinator guilds and hence reproductive success. The two Petunia species, P. axillaris and P. exserta, display pollination syndromes adapted to moth or hummingbird pollination. For the floral traits color and scent, genetic loci of large phenotypic effect have been well documented. However, such large-effect loci may be typical for shifts in simple biochemical traits, whereas the evolution of morphological traits may involve multiple mutations of small phenotypic effect. Here, we performed a quantitative trait locus (QTL) analysis of floral morphology, followed by an in-depth study of pistil and stamen morphology and the introgression of individual QTL into reciprocal parental backgrounds. Two QTLs, on chromosomes II and V, are sufficient to explain the interspecific difference in pistil and stamen length. Since most of the difference in organ length is caused by differences in cell number, genes underlying these QTLs are likely to be involved in cell cycle regulation. Interestingly, conservation of the locus on chromosome II in a different P. axillaris subspecies suggests that the evolution of organ elongation was initiated on chromosome II in adaptation to different pollinators. We recently showed that QTLs for pistil and stamen length on chromosome II are tightly linked to QTLs for petal color and volatile emission. Linkage of multiple traits will enable major phenotypic change within a few generations in hybridizing populations. Thus, the genomic architecture of pollination syndromes in Petunia allows for rapid responses to changing pollinator availability.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

A locus on chromosome 7 determines myocardial cell necrosis and calcification (dystrophic cardiac calcinosis) in mice.

Dystrophic cardiac calcinosis, an age-related cardiomyopathy that occurs among certain inbred strains of mice, involves myocardial injury, necrosis, and calcification. Using a complete linkage map approach and quantitative trait locus analysis, we sought to identify genetic loci determining dystrophic cardiac calcinosis in an F2 intercross of resistant C57BL/6J and susceptible C3H/HeJ inbred strains. We identified a single major locus, designated Dyscalc, located on proximal chromosome 7 in a region syntenic with human chromosomes 19q13 and 11p15. The statistical significance of Dyscalc (logarithm of odds score 14.6) was tested by analysis of permuted trait data. Analysis of BxH recombinant inbred strains confirmed the mapping position. The inheritance pattern indicated that this locus influences susceptibility of cells both to enter necrosis and to subsequently undergo calcification.

Genomewide significant linkage to migrainous Hheadache on chromosome 5q21

Familial typical migraine is a common, complex disorder that shows strong familial aggregation. Using latent-class analysis (LCA), we identified subgroups of people with migraine/severe headache in a community sample of 12,245 Australian twins (60% female), drawn from two cohorts of individuals aged 23-90 years who completed an interview based on International Headache Society criteria. We report results from genomewide linkage analyses involving 756 twin families containing a total of 790 independent sib pairs ( 130 affected concordant, 324 discordant, and 336 unaffected concordant for LCA-derived migraine). Quantitative-trait linkage analysis produced evidence of significant linkage on chromosome 5q21 and suggestive linkage on chromosomes 8, 10, and 13. In addition, we replicated previously reported typical-migraine susceptibility loci on chromosomes 6p12.2-p21.1 and 1q21-q23, the latter being within 3 cM of the rare autosomal dominant familial hemiplegic migraine gene (ATP1A2), a finding which potentially implicates ATP1A2 in familial typical migraine for the first time. Linkage analyses of individual migraine symptoms for our six most interesting chromosomes provide tantalizing hints of the phenotypic and genetic complexity of migraine. Specifically, the chromosome 1 locus is most associated with phonophobia; the chromosome 5 peak is predominantly associated with pulsating headache; the chromosome 6 locus is associated with activity-prohibiting headache and photophobia; the chromosome 8 locus is associated with nausea/vomiting and moderate/severe headache; the chromosome 10 peak is most associated with phonophobia and photophobia; and the chromosome 13 peak is completely due to association with photophobia. These results will prove to be invaluable in the design and analysis of future linkage and linkage disequilibrium studies of migraine.

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.