Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

A multilevel approach to understanding circadian rhythmicity : social and sleep-dependent effects in ants and mice

Résumé françaisLa majorité des organismes vivants sont soumis à l'alternance du jour et de la nuit, conséquence de la rotation de la terre autour de son axe. Ils ont développé un système interne de mesure du temps, appelé horloge circadienne, leur permettant de s'adapter et de synchroniser leur comportement et leur physiologie aux cycles de lumière. Cette dernière est considérée comme étant le signal majeur entraînant l'horloge interne et. par conséquent, les rythmes journaliers d'éveil et de sommeil. Outre sa régulation circadienne, le sommeil est contrôlé par un processus homéostatique qui détermine son besoin. La contribution de ces deux processus dans le fonctionnement cellulaire du cerveau n'a pas encore été investiguée. La mesure de l'amplitude ainsi que de la prévalence des ondes delta de l'EEG (activité delta) constitue un index très fiable du besoin de sommeil. Il a été démontré que cette activité est génétiquement déterminée et associée à un locus de trait quantitatif situé sur le chromosome 13 de la souris.Grâce à des expériences de privation de sommeil et d'analyses de transcriptome du cerveau dans trois souches de souris présentant diverses réponses à la privation de sommeil, nous avons trouvé que Homerla, localisé dans la région d'intérêt du chromosome 13, est le meilleur marqueur du besoin de sommeil. Homerla est impliqué dans la récupération de l'hyperactivité neuronale induite par le glutamate, grâce à son effet tampon sur le calcium intracellulaire. Une fonction fondamentale du sommeil pourrait donc être de protéger le cerveau et de lui permettre de récupérer après une hyperactivité neuronale imposée par une veille prolongée.De plus, nous avons montré que 2032 transcrits sont exprimés rythmiqueraent dans le cerveau de la souris, parmi lesquels seulement 391 le restent après que les animaux aient été privés de sommeil à différents moments au cours des 24 heures. Cette observation montre clairement que la plupart des changements rythmiques au niveau du transcriptome dépendent du sommeil et non de l'horloge circadienne et souligne ainsi l'importance du sommeil dans la physiologie des mammifères.La plupart des expériences concernant les rythmes circadiens ont été réalisées sur des individus isolés en négligeant l'effet du contexte social sur les comportements circadiens. Les espèces sociales, telles que les fourmis, se caractérisent par une division du travail où une répartition des tâches s'effectue entre ses membres. De plus, certaines d'entre elles doivent être pratiquées en continu comme les soins au couvain tandis que d'autres requièrent une activité rythmique comme le fourragement. Ainsi la fourmi est un excellent modèle pour l'étude de 1 influence du contexte social sur les rythmes circadiens.A ces fins, nous avons décidé d'étudier les rythmes circadiens chez une espèce de fourmi Camponotus fellah et de caractériser au niveau moléculaire son horloge circadienne. Nous avons ainsi développé un système vidéo permettant de suivre l'activité locomotrice de tous les individus d'une colonie. Nos résultats montrent que, bien que la plupart des fourmis soient arythmiques à l'intérieur de la colonie, elles développent d'amples rythmes d'activité en isolation. De plus, ces rythmes disparaissent presque aussitôt que la fourmi est réintroduite dans la colonie. Cette rythmicité observée en isolation semble être générée par l'horloge circadienne car elle persiste en condition constante (obscurité totale). Nous avons ensuite regardé si cette apparente arythmie observée dans la colonie résultait d'un effet masquant des interactions sociales sur les rythmes circadiens d'activité. Nos résultats suggèrent que l'horloge interne est fonctionnelle dans la colonie mais que l'expression de ses rythmes au niveau comportemental est inhibée par les interactions sociales. Les analyses moléculaires du statut de l'horloge dans différents contextes sociaux sont actuellement en cours. Le contexte social semble donc un déterminant majeur du comportement circadien chez la fourmi.AbstractAlmost all living organisms on earth are subjected to the alternance of day and night re-sulting from the rotation of the earth around its axis. They have evolved with an internal timing system, termed the circadian clock, enabling them to adapt and synchronize their behavior and physiology to the daily changes in light and related environmental parame¬ters. Light is thought to be the major cue entraining the circadian clock and consequently the rhythms of rest/activity. In addition to its circadian dependent timing, sleep is reg¬ulated by a homeostatic process that determines its need. The contribution of these two processes in the cellular functioning of the brain has not yet been considered. A highly reliable index of the homeostatic process of sleep is the measure of the amplitude and prevalence of the EEG delta waves (delta activity). It has been shown that sleep need, measured by delta activity, is genetically determined and associated with a Quantitative Trait Locus (QTL) located on the mouse chromosome 13. By using sleep deprivation and brain transcriptome profiling in three inbred mouse strains showing different responses to sleep loss, we found that Homerla, localized within this QTL region is the best transcrip¬tional marker of sleep need. Interestingly Homerla is primarily involved in the recovery from glutamate-induced neuronal hyperactivity by its buffering effect on intracellular cal¬cium. A fundamental function of sleep may therefore reside in the protection and recovery of the brain from a neuronal hyperactivity imposed by prolonged wakefulness.Moreover, time course gene expression experiments showed that 2032 brain tran¬scripts present a rhythmic variation, but only 391 of those remain rhythmic when mice are sleep deprived at four time points around the clock. This finding clearly suggests that most changes in gene transcription over the day are sleep-wake dependent rather than clock dependent and underlines the importance of sleep in mammalian physiology.In the second part of this PhD, I was interested in the social influence on circadian behavior. Most experiments done in the circadian field have been performed on isolated individuals and have therefore ignored the effect of the social context on circadian behav-ior. Eusocial insect species such as ants are characterized by a division of labor: colony tasks are distributed among individuals, some of them requiring continuous activity such as nursing or rhythmic ones such as foraging. Thus ants represent a suitable model to study the influence of the social context on the circadian clock and its output rhythms.The aim of this part was to address the effect of social context on circadian rhythms in the ant species Camponotus fellah and to characterize its circadian clock at the molecu¬lar level. We therefore developed a video tracking system to follow the locomotor activity of all individuals in a colony. Our results show that most ants are arrhythmic within the colony, but develop, when subjected to social isolation, strong rhythms of activity that intriguingly disappear when individuals are reintroduced into the colony. The rhythmicity observed in isolated ants seems to be driven by the circadian clock as it persists under constant conditions (complete darkness). We then tested whether the apparent arrhyth- micity in the colony stemmed from a masking effect of social interactions on circadian rhythms. Indeed, we found that circadian clocks of ants in the colony are functional but their expression at the behavioral level is inhibited by social interactions. The molecular assessment of the circadian clock functional state in the different social context is still under investigation. Our results suggest that social context is a major determinant of circadian behavior in ants.

Genetic and phenotypic architecture of metabolic syndrome-associated components in dyslipidemic and normolipidemic subjects: the GEMS Study.

Atherogenic dyslipidemia, manifest by low HDL-cholesterol and high TG levels, is an important component of ATP-III defined metabolic syndrome. Here, we dissected the phenotypic and genetic architecture of these traits by assessing their relationships with other metabolically relevant measures, including plasma adipo-cytokines, highly sensitive C-reactive protein (hsCRP) and LDL particle size, in a large family data set (n=2800) and in an independent set of dyslipidemic cases (n=716) and normolipidemic controls (n=1073). We explored the relationships among these phenotypes using variable clustering and then estimated their genetic heritabilities and cross-trait correlations. In families, four clusters explained 61% of the total variance, with one adiposity-related cluster (including hsCRP), one BP-related cluster, and two lipid-related clusters (HDL-C, TG, adiponectin and LDL particle size; apoB and non-HDL-C). A similar structure was observed in dyslipidemic cases and normolipidemic controls. The genetic correlations in the families largely paralleled the phenotype clustering results, suggesting that common genes having pleiotropic effects contributed to the correlations observed. In summary, our analyses support a model of metabolic syndrome with two major components, body fat and lipids, each with two subcomponents, and quantifies their degree of overlap with each other and with metabolic-syndrome related measures (adipokines, LDL particle size and hsCRP).

Genome-wide association study of co-occurring anxiety in major depression.

OBJECTIVES: Co-morbidity between depression and anxiety disorders is common. In this study we define a quantitative measure of anxiety by summating four anxiety items from the SCAN interview in a large collection of major depression (MDD) cases to identify genes contributing to this complex phenotype. METHODS: A total of 1522 MDD cases dichotomised according to those with at least one anxiety item scored (n = 1080) and those without anxiety (n = 442) were analysed, and also compared to 1588 healthy controls at a genome-wide level, to identify genes that may contribute to anxiety in MDD. RESULTS: For the quantitative trait, suggestive evidence of association was detected for two SNPs, and for the dichotomous anxiety present/absent ratings for three SNPs at genome-wide level. In the genome-wide analysis of MDD cases with co-morbid anxiety and healthy controls, two SNPs attained P values of < 5 × 10⁻⁶. Analysing candidate genes, P values ≤ 0.0005 were found with three SNPs for the quantitative trait and three SNPs for the dichotomous trait. CONCLUSIONS: This study provides an initial genome-wide assessment of possible genetic contribution to anxiety in MDD. Although suggestive evidence of association was found for several SNPs, our findings suggest that there are no common variants strongly associated with anxious depression.

Genes mirror geography within Europe.

Understanding the genetic structure of human populations is of fundamental interest to medical, forensic and anthropological sciences. Advances in high-throughput genotyping technology have markedly improved our understanding of global patterns of human genetic variation and suggest the potential to use large samples to uncover variation among closely spaced populations. Here we characterize genetic variation in a sample of 3,000 European individuals genotyped at over half a million variable DNA sites in the human genome. Despite low average levels of genetic differentiation among Europeans, we find a close correspondence between genetic and geographic distances; indeed, a geographical map of Europe arises naturally as an efficient two-dimensional summary of genetic variation in Europeans. The results emphasize that when mapping the genetic basis of a disease phenotype, spurious associations can arise if genetic structure is not properly accounted for. In addition, the results are relevant to the prospects of genetic ancestry testing; an individual's DNA can be used to infer their geographic origin with surprising accuracy-often to within a few hundred kilometres.

Mobile gibberellin directly stimulates Arabidopsis hypocotyl xylem expansion.

Secondary growth of the vasculature results in the thickening of plant structures and continuously produces xylem tissue, the major biological carbon sink. Little is known about the developmental control of this quantitative trait, which displays two distinct phases in Arabidopsis thaliana hypocotyls. The later phase of accelerated xylem expansion resembles the secondary growth of trees and is triggered upon flowering by an unknown, shoot-derived signal. We found that flowering-dependent hypocotyl xylem expansion is a general feature of herbaceous plants with a rosette growth habit. Flowering induction is sufficient to trigger xylem expansion in Arabidopsis. By contrast, neither flower formation nor elongation of the main inflorescence is required. Xylem expansion also does not depend on any particular flowering time pathway or absolute age. Through analyses of natural genetic variation, we found that ERECTA acts locally to restrict xylem expansion downstream of the gibberellin (GA) pathway. Investigations of mutant and transgenic plants indicate that GA and its signaling pathway are both necessary and sufficient to directly trigger enhanced xylogenesis. Impaired GA signaling did not affect xylem expansion systemically, suggesting that it acts downstream of the mobile cue. By contrast, the GA effect was graft transmissible, suggesting that GA itself is the mobile shoot-derived signal.

Dissecting the genetic heterogeneity of depression through age at onset.

Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P < 5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P = 0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder. © 2012 Wiley Periodicals, Inc.

Mutation screening of the urocortin gene: identification of new single nucleotide polymorphisms and association studies with obesity in French Caucasians.

A linkage between obesity-related phenotypes and the 2p21-23 locus has been reported previously. The urocortin (UCN) gene resides at this interval, and its protein decreases appetite behavior, suggesting that UCN may be a candidate gene for susceptibility to obesity. We localized the UCN gene by radiation hybrid mapping, and the surrounding markers were genotyped in a collection of French families. Evidence for linkage was shown between the marker D2S165 and leptin levels (LOD score, 1.34; P = 0.006) and between D2S2247 and the z-score of body mass index (LOD score, 1.829; P = 0.0019). The gene was screened for SNPs in 96 obese patients. Four new variants were established. Two single nucleotide polymorphisms were located in the promoter (-535 A-->G, -286 G-->A), one in intron 1 (+31 C-->G), and one in the 3'-untranslated region (+34 C-->T). Association studies in cohorts of 722 unrelated obese and 381 control subjects and transmission disequilibrium tests, performed for the two frequent promoter polymorphisms, in 120 families (894 individuals) showed that no association was present between these variants and obesity, obesity-related phenotypes, and diabetes. Thus, our analyses of the genetic variations of the UCN gene suggest that, at least in French Caucasians, they do not represent a major cause of obesity.

Sex-linked inheritance, genetic correlations and sexual dimorphism in three melanin-based colour traits in the barn owl.

Theory states that genes on the sex chromosomes have stronger effects on sexual dimorphism than genes on the autosomes. Although empirical data are not necessarily consistent with this theory, this situation may prevail because the relative role of sex-linked and autosomally inherited genes on sexual dimorphism has rarely been evaluated. We estimated the quantitative genetics of three sexually dimorphic melanin-based traits in the barn owl (Tyto alba), in which females are on average darker reddish pheomelanic and display more and larger black eumelanic feather spots than males. The plumage traits with higher sex-linked inheritance showed lower heritability and genetic correlations, but contrary to prediction, these traits showed less pronounced sexual dimorphism. Strong offspring sexual dimorphism primarily resulted from daughters not expressing malelike melanin-based traits and from sons expressing femalelike traits to similar degrees as their sisters. We conclude that in the barn owl, polymorphism at autosomal genes rather than at sex-linked genes generate variation in sexual dimorphism in melanin-based traits.

Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait.

BACKGROUND AND AIMS: Although it is well known that fire acts as a selective pressure shaping plant phenotypes, there are no quantitative estimates of the heritability of any trait related to plant persistence under recurrent fires, such as serotiny. In this study, the heritability of serotiny in Pinus halepensis is calculated, and an evaluation is made as to whether fire has left a selection signature on the level of serotiny among populations by comparing the genetic divergence of serotiny with the expected divergence of neutral molecular markers (QST-FST comparison). METHODS: A common garden of P. halepensis was used, located in inland Spain and composed of 145 open-pollinated families from 29 provenances covering the entire natural range of P. halepensis in the Iberian Peninsula and Balearic Islands. Narrow-sense heritability (h(2)) and quantitative genetic differentiation among populations for serotiny (QST) were estimated by means of an 'animal model' fitted by Bayesian inference. In order to determine whether genetic differentiation for serotiny is the result of differential natural selection, QST estimates for serotiny were compared with FST estimates obtained from allozyme data. Finally, a test was made of whether levels of serotiny in the different provenances were related to different fire regimes, using summer rainfall as a proxy for fire regime in each provenance. KEY RESULTS: Serotiny showed a significant narrow-sense heritability (h(2)) of 0·20 (credible interval 0·09-0·40). Quantitative genetic differentiation among provenances for serotiny (QST = 0·44) was significantly higher than expected under a neutral process (FST = 0·12), suggesting adaptive differentiation. A significant negative relationship was found between the serotiny level of trees in the common garden and summer rainfall of their provenance sites. CONCLUSIONS: Serotiny is a heritable trait in P. halepensis, and selection acts on it, giving rise to contrasting serotiny levels among populations depending on the fire regime, and supporting the role of fire in generating genetic divergence for adaptive traits.

Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution.

Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻&supl;³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

The additive genetic variance after bottlenecks is affected by the number of loci involved in epistatic interactions.

We investigated the role of the number of loci coding for a neutral trait on the release of additive variance for this trait after population bottlenecks. Different bottleneck sizes and durations were tested for various matrices of genotypic values, with initial conditions covering the allele frequency space. We used three different types of matrices. First, we extended Cheverud and Routman's model by defining matrices of "pure" epistasis for three and four independent loci; second, we used genotypic values drawn randomly from uniform, normal, and exponential distributions; and third we used two models of simple metabolic pathways leading to physiological epistasis. For all these matrices of genotypic values except the dominant metabolic pathway, we find that, as the number of loci increases from two to three and four, an increase in the release of additive variance is occurring. The amount of additive variance released for a given set of genotypic values is a function of the inbreeding coefficient, independently of the size and duration of the bottleneck. The level of inbreeding necessary to achieve maximum release in additive variance increases with the number of loci. We find that additive-by-additive epistasis is the type of epistasis most easily converted into additive variance. For a wide range of models, our results show that epistasis, rather than dominance, plays a significant role in the increase of additive variance following bottlenecks.

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition.