970 resultados para quantitative trait loci (QTLs)


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quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

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Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

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Detecting the action of selection in natural populations can be achieved using the QST-FST comparison that relies on the estimation of FST with neutral markers, and QST using quantitative traits potentially under selection. QST higher than FST suggests the action of directional selection and thus potential local adaptation. In this article, we apply the QST-FST comparison to four populations of the hermaphroditic freshwater snail Radix balthica located in a floodplain habitat. In contrast to most studies published so far, we did not detect evidence of directional selection for local optima for any of the traits we measured: QST calculated using three different methods was never higher than FST. A strong inbreeding depression was also detected, indicating that outcrossing is probably predominant over selfing in the studied populations. Our results suggest that in this floodplain habitat, local adaptation of R. balthica populations may be hindered by genetic drift, and possibly altered by uneven gene flow linked to flood frequency.

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Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 × 10(-3)), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 × 10(-4)). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 × 10(-4)) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other.

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Les traits quantitatifs complexes sont des caractéristiques mesurables d’organismes vivants qui résultent de l’interaction entre plusieurs gènes et facteurs environnementaux. Les locus génétiques liés à un caractère complexe sont appelés «locus de traits quantitatifs » (QTL). Récemment, en considérant les niveaux d’expression tissulaire de milliers de gènes comme des traits quantitatifs, il est devenu possible de détecter des «QTLs d’expression» (eQTL). Alors que ces derniers ont été considérés comme des phénotypes intermédiaires permettant de mieux comprendre l’architecture biologique des traits complexes, la majorité des études visent encore à identifier une mutation causale dans un seul gène. Cette approche ne peut remporter du succès que dans les situations où le gène incriminé a un effet majeur sur le trait complexe, et ne permet donc pas d’élucider les situations où les traits complexes résultent d’interactions entre divers gènes. Cette thèse propose une approche plus globale pour : 1) tenir compte des multiples interactions possibles entre gènes pour la détection de eQTLs et 2) considérer comment des polymorphismes affectant l’expression de plusieurs gènes au sein de groupes de co-expression pourraient contribuer à des caractères quantitatifs complexes. Nos contributions sont les suivantes : Nous avons développé un outil informatique utilisant des méthodes d’analyse multivariées pour détecter des eQTLs et avons montré que cet outil augmente la sensibilité de détection d’une classe particulière de eQTLs. Sur la base d’analyses de données d’expression de gènes dans des tissus de souris recombinantes consanguines, nous avons montré que certains polymorphismes peuvent affecter l’expression de plusieurs gènes au sein de domaines géniques de co-expression. En combinant des études de détection de eQTLs avec des techniques d’analyse de réseaux de co-expression de gènes dans des souches de souris recombinantes consanguines, nous avons montré qu’un locus génétique pouvait être lié à la fois à l’expression de plusieurs gènes au niveau d’un domaine génique de co-expression et à un trait complexe particulier (c.-à-d. la masse du ventricule cardiaque gauche). Au total, nos études nous ont permis de détecter plusieurs mécanismes par lesquels des polymorphismes génétiques peuvent être liés à l’expression de plusieurs gènes, ces derniers pouvant eux-mêmes être liés à des traits quantitatifs complexes.

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Recurrent spontaneous abortion (RSA) is defined as the loss of three or more consecutive pregnancies during the first trimester of embryonic intrauterine development. This kind of human infertility is frequent among the general population since it affects 1 to 5% of women. In half of the cases the etiology remains unelucidated. In the present study, we used interspecific recombinant congenic mouse strains (IRCS) in the aim to identify genes responsible for embryonic lethality. Applying a cartographic approach using a genotype/phenotype association, we identified a minimal QTL region, of about 6 Mb on chromosome 1, responsible for a high rate of embryonic death (,30%). Genetic analysis suggests that the observed phenotype is linked to uterine dysfunction. Transcriptomic analysis of the uterine tissue revealed a preferential deregulation of genes of this region compared to the rest of the genome. Some genes from the QTL region are associated with VEGF signaling, mTOR signaling and ubiquitine/proteasome-protein degradation pathways. This work may contribute to elucidate the molecular basis of a multifactorial and complex human disorder as RSA.

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Recurrent spontaneous abortion (RSA) is defined as the loss of three or more consecutive pregnancies during the first trimester of embryonic intrauterine development. This kind of human infertility is frequent among the general population since it affects 1 to 5% of women. In half of the cases the etiology remains unelucidated. In the present study, we used interspecific recombinant congenic mouse strains (IRCS) in the aim to identify genes responsible for embryonic lethality. Applying a cartographic approach using a genotype/phenotype association, we identified a minimal QTL region, of about 6 Mb on chromosome 1, responsible for a high rate of embryonic death (similar to 30%). Genetic analysis suggests that the observed phenotype is linked to uterine dysfunction. Transcriptomic analysis of the uterine tissue revealed a preferential deregulation of genes of this region compared to the rest of the genome. Some genes from the QTL region are associated with VEGF signaling, mTOR signaling and ubiquitine/proteasome-protein degradation pathways. This work may contribute to elucidate the molecular basis of a multifactorial and complex human disorder as RSA.

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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.

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Calcium (Ca) and magnesium (Mg) are the most abundant group II elements in both plants and animals. Genetic variation in shoot Ca and shoot Mg concentration (shoot Ca and Mg) in plants can be exploited to biofortify food crops and thereby increase dietary Ca and Mg intake for humans and livestock. We present a comprehensive analysis of within-species genetic variation for shoot Ca and Mg, demonstrating that shoot mineral concentration differs significantly between subtaxa (varietas). We established a structured diversity foundation set of 376 accessions to capture a high proportion of species-wide allelic diversity within domesticated Brassica oleracea, including representation of wild relatives (C genome, 1n = 9) from natural populations. These accessions and 74 modern F-1 hybrid cultivars were grown in glasshouse and field environments. Shoot Ca and Mg varied 2- and 2.3-fold, respectively, and was typically not inversely correlated with shoot biomass, within most subtaxa. The closely related capitata (cabbage) and sabauda (Savoy cabbage) subtaxa consistently had the highest mean shoot Ca and Mg. Shoot Ca and Mg in glasshouse-grown plants was highly correlated with data from the field. To understand and dissect the genetic basis of variation in shoot Ca and Mg, we studied homozygous lines from a segregating B. oleracea mapping population. Shoot Ca and Mg was highly heritable (up to 40). Quantitative trait loci (QTL) for shoot Ca and Mg were detected on chromosomes C2, C6, C7, C8, and, in particular, C9, where QTL accounted for 14 to 55 of the total genetic variance. The presence of QTL on C9 was substantiated by scoring recurrent backcross substitution lines, derived from the same parents. This also greatly increased the map resolution, with strong evidence that a 4-cM region on C9 influences shoot Ca. This region corresponds to a 0.41-Mb region on Arabidopsis (Arabidopsis thaliana) chromosome 5 that includes 106 genes. There is also evidence that pleiotropic loci on C8 and C9 affect shoot Ca and Mg. Map-based cloning of these loci will reveal how shoot-level phenotypes relate to Ca 21 and Mg 21 uptake and homeostasis at the molecular level.

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Background and Aims: Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus. Methods: Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus 'Tapidor' x 'Ningyou 7' (TNDH) using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP. Key Results: In general, root and biomass traits were highly correlated under LP and HP conditions. 'Ningyou 7' had greater LRL, LRN and LRD than 'Tapidor', at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06. Conclusions: High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection.

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Key message We have identified QTLs for stomatal characteristics on chromosome II of faba bean by applying SNPs derived from M. truncatula , and have identified candidate genes within these QTLs using synteny between the two species. Abstract Faba bean (Vicia faba L.) is a valuable food and feed crop worldwide, but drought often limits its production, and its genome is large and poorly mapped. No information is available on the effects of genomic regions and genes on drought adaptation characters such as stomatal characteristics in this species, but the synteny between the sequenced model legume, Medicago truncatula, and faba bean can be used to identify candidate genes. A mapping population of 211 F5 recombinant inbred lines (Mélodie/2 × ILB 938/2) were phenotyped to identify quantitative trait loci (QTL) affecting stomatal morphology and function, along with seed weight, under well-watered conditions in a climate-controlled glasshouse in 2013 and 2014. Canopy temperature (CT) was evaluated in 2013 under water-deficit (CTd). In total, 188 polymorphic single nucleotide polymorphisms (SNPs), developed from M. truncatula genome data, were assigned to nine linkage groups that covered ~928 cM of the faba bean genome with an average inter-marker distance of 5.8 cM. 15 putative QTLs were detected, of which eight (affecting stomatal density, length and conductance and CT) co-located on chromosome II, in the vicinity of a possible candidate gene—a receptor-like protein kinase found in the syntenic interval of M. truncatula chromosome IV. A ribose-phosphate pyrophosphokinase from M. truncatula chromosome V, postulated as a possible candidate gene for the QTL for CTd, was found some distance away in the same chromosome. These results demonstrate that genomic information from M. truncatula can successfully be translated to the faba bean genome.

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A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

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

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Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

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