quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

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.

Evolutionary aspects of population structure for molecular and quantitative traits in the freshwater snail Radix balthica.

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.

Modularisation épistatique des loci à trait quantitatif associés à la pression artérielle et identification de gènes candidats pour l’hypertension

Problématique: L’hypertension artérielle essentielle, facteur de risque majeur dans le développement des maladies cardiovasculaires, est un trait multigénique complexe dont les connaissances sur le déterminisme génétique nécessitent d’être approfondies. De nombreux loci à trait quantitatif (QTLs); soit des gènes responsables de faire varier la pression artérielle (PA), ont été identifiés chez l’humain et le modèle animal. Cependant, le mystère plane encore sur la façon dont ces gènes fonctionnent ensemble pour réguler la PA. Hypothèse et objectif: Plutôt qu’une addition de QTLs ayant chacun une action infinitésimale sur la PA, une interaction épistatique entre les gènes serait responsable du phénotype hypertendu. Ainsi, l’étude de cette épistasie entre les gènes impliqués, directement ou indirectement, dans l’homéostasie de la PA nous permettrait d’explorer de nouvelles voies de régulation moléculaire en cause dans cette maladie. Méthodes: Via la réalisation de souches congéniques de rats, où un segment chromosomique provenant d’une souche receveuse hypertendue (Dahl Salt Sensitive, SS/Jr) est remplacé par son homologue provenant d’une souche donneuse normotendue (Lewis, LEW), des QTLs peuvent être mis en évidence. Dans ce contexte, la combinaison de QTLs via la création de doubles ou multiples congéniques constitue la première démonstration fonctionnelle des interactions intergéniques. Résultats: Vingt-sept combinaisons au total nous ont menés à l’appréciation d’une modularisation des QTLs. Ces derniers ont été catégorisés selon deux principaux modules épistatiques (EMs) où les QTLs appartenant à un même EM sont épistatiques entre eux et participent à une même voie régulatrice. Les EMs/cascades agissent alors en parallèle pour réguler la PA. Grâce à l’existence de QTLs ayant des effets opposés sur la PA, nous avons pu établir l’ordre hiérarchique entre trois paires de QTLs. Cependant, lorsque cette suite régulatrice ne peut être déterminée, d’autres approches sont nécessaires. Nos travaux nous ont mené à l’identification d’un QTL situé sur le chromosome 16 du rat (C16QTL), appartenant au EM1 et qui révélerait une nouvelle voie de l’homéostasie de la PA. Le gène retinoblastoma-associated protein 140 (Rap140)/family with sequence similarity 208 member A (Fam208a), présentant une mutation non synonyme entre SS/Jr et LEW est le gène candidat le plus plausible pour représenter C16QTL. Celui-ci code pour un facteur de transcription et semblerait influencer l’expression de Solute carrier family 7 (cationic amino acid transporter, y+ system) member 12 (Slc7a12), spécifiquement et significativement sous exprimé dans les reins de la souche congénique portant C16QTL par rapport à la souche SS/Jr. Rap140/Fam208a agirait comme un inhibiteur de la transcription de Slc7a12 menant à une diminution de la pression chez Lewis. Conclusions: L’architecture complexe de la régulation de la PA se dévoile mettant en scène de nouveaux acteurs, pour la plupart inconnus pour leur implication dans la PA. L’étude de la nouvelle voie de signalisation Rap140/Fam208a - Slc7a12 nous permettra d’approfondir nos connaissances quant à l’homéostasie de la pression artérielle et de l’hypertension chez SS/Jr. À long terme, de nouveaux traitements anti-hypertenseurs, ciblant plus d’une voie de régulation à la fois, pourraient voir le jour.

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.

Genome-wide association mapping in a wild avian population identifies a link between genetic and phenotypic variation in a life-history trait

Understanding the genetic basis of traits involved in adaptation is a major challenge in evolutionary biology but remains poorly understood. Here, we use genome-wide association mapping using a custom 50 k single nucleotide polymorphism (SNP) array in a natural population of collared flycatchers to examine the genetic basis of clutch size, an important life-history trait in many animal species. We found evidence for an association on chromosome 18 where one SNP significant at the genome-wide level explained 3.9% of the phenotypic variance. We also detected two suggestive quantitative trait loci (QTLs) on chromosomes 9 and 26. Fitness differences among genotypes were generally weak and not significant, although there was some indication of a sex-by-genotype interaction for lifetime reproductive success at the suggestive QTL on chromosome 26. This implies that sexual antagonism may play a role in maintaining genetic variation at this QTL. Our findings provide candidate regions for a classic avian life-history trait that will be useful for future studies examining the molecular and cellular function of, as well as evolutionary mechanisms operating at, these loci.

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.

Factors that cause genotype by environment interaction and use of a multiple-trait herd-cluster model for milk yield of Holstein cattle from Brazil and Colombia

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.

Marker-trait association and epistasis for brown rust resistance in sugarcane

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

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction

Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes ire fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories. Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of air asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction. Important findings For entirely vegetative or sexual reproduction, predictions. of the gametic SEIB model were close to the ones of spatially explicit CSMs gametic phenotypic models, hut for mixed modes of reproduction they appoximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of trails governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually, miss the optimum and that selection may lead to loci with smaller effects, in derived compared with ancestral lines.

Genetic Distance between Species Predicts Novel Trait Expression in Their Hybrids

Interspecific hybridization can generate transgressive hybrid phenotypes with extreme trait values exceeding the combined range of the parental species. Such variation can enlarge the working surface for natural selection, and may facilitate the evolution of novel adaptations where ecological opportunity exists. The number of quantitative trait loci fixed for different alleles in different species should increase with time since speciation. If transgression is caused by complementary gene action or epistasis, hybrids between more distant species should be more likely to display transgressive phenotypes. To test this prediction we collected data on transgression frequency from the literature, estimated genetic distances between the hybridizing species from gene sequences, and calculated the relationship between the two using phylogenetically controlled methods. We also tested if parental phenotypic divergence affected the occurrence of transgression. We found a highly significant positive correlation between transgression frequency and genetic distance in eudicot plants explaining 43% of the variance in transgression frequency. In total, 36% of the measured traits were transgressive. The predicted effect of time since speciation on transgressive segregation was unconfounded by the potentially conflicting effects of phenotypic differentiation between species. Our analysis demonstrates that the potential impact hybridization may have on phenotypic evolution is predictable from the genetic distance between species.

Cost and power analysis of linkage disequilibrium methods for locating genes influencing quantitative traits in humans

Linkage disequilibrium methods can be used to find genes influencing quantitative trait variation in humans. Linkage disequilibrium methods can require smaller sample sizes than linkage equilibrium methods, such as the variance component approach to find loci with a specific effect size. The increase in power is at the expense of requiring more markers to be typed to scan the entire genome. This thesis compares different linkage disequilibrium methods to determine which factors influence the power to detect disequilibrium. The costs of disequilibrium and equilibrium tests were compared to determine whether the savings in phenotyping costs when using disequilibrium methods outweigh the additional genotyping costs.^ Nine linkage disequilibrium tests were examined by simulation. Five tests involve selecting isolated unrelated individuals while four involved the selection of parent child trios (TDT). All nine tests were found to be able to identify disequilibrium with the correct significance level in Hardy-Weinberg populations. Increasing linked genetic variance and trait allele frequency were found to increase the power to detect disequilibrium, while increasing the number of generations and distance between marker and trait loci decreased the power to detect disequilibrium. Discordant sampling was used for several of the tests. It was found that the more stringent the sampling, the greater the power to detect disequilibrium in a sample of given size. The power to detect disequilibrium was not affected by the presence of polygenic effects.^ When the trait locus had more than two trait alleles, the power of the tests maximized to less than one. For the simulation methods used here, when there were more than two-trait alleles there was a probability equal to 1-heterozygosity of the marker locus that both trait alleles were in disequilibrium with the same marker allele, resulting in the marker being uninformative for disequilibrium.^ The five tests using isolated unrelated individuals were found to have excess error rates when there was disequilibrium due to population admixture. Increased error rates also resulted from increased unlinked major gene effects, discordant trait allele frequency, and increased disequilibrium. Polygenic effects did not affect the error rates. The TDT, Transmission Disequilibrium Test, based tests were not liable to any increase in error rates.^ For all sample ascertainment costs, for recent mutations ($<$100 generations) linkage disequilibrium tests were less expensive than the variance component test to carry out. Candidate gene scans saved even more money. The use of recently admixed populations also decreased the cost of performing a linkage disequilibrium test. ^

Modularisation épistatique des loci à trait quantitatif associés à la pression artérielle et identification de gènes candidats pour l’hypertension

Problématique: L’hypertension artérielle essentielle, facteur de risque majeur dans le développement des maladies cardiovasculaires, est un trait multigénique complexe dont les connaissances sur le déterminisme génétique nécessitent d’être approfondies. De nombreux loci à trait quantitatif (QTLs); soit des gènes responsables de faire varier la pression artérielle (PA), ont été identifiés chez l’humain et le modèle animal. Cependant, le mystère plane encore sur la façon dont ces gènes fonctionnent ensemble pour réguler la PA. Hypothèse et objectif: Plutôt qu’une addition de QTLs ayant chacun une action infinitésimale sur la PA, une interaction épistatique entre les gènes serait responsable du phénotype hypertendu. Ainsi, l’étude de cette épistasie entre les gènes impliqués, directement ou indirectement, dans l’homéostasie de la PA nous permettrait d’explorer de nouvelles voies de régulation moléculaire en cause dans cette maladie. Méthodes: Via la réalisation de souches congéniques de rats, où un segment chromosomique provenant d’une souche receveuse hypertendue (Dahl Salt Sensitive, SS/Jr) est remplacé par son homologue provenant d’une souche donneuse normotendue (Lewis, LEW), des QTLs peuvent être mis en évidence. Dans ce contexte, la combinaison de QTLs via la création de doubles ou multiples congéniques constitue la première démonstration fonctionnelle des interactions intergéniques. Résultats: Vingt-sept combinaisons au total nous ont menés à l’appréciation d’une modularisation des QTLs. Ces derniers ont été catégorisés selon deux principaux modules épistatiques (EMs) où les QTLs appartenant à un même EM sont épistatiques entre eux et participent à une même voie régulatrice. Les EMs/cascades agissent alors en parallèle pour réguler la PA. Grâce à l’existence de QTLs ayant des effets opposés sur la PA, nous avons pu établir l’ordre hiérarchique entre trois paires de QTLs. Cependant, lorsque cette suite régulatrice ne peut être déterminée, d’autres approches sont nécessaires. Nos travaux nous ont mené à l’identification d’un QTL situé sur le chromosome 16 du rat (C16QTL), appartenant au EM1 et qui révélerait une nouvelle voie de l’homéostasie de la PA. Le gène retinoblastoma-associated protein 140 (Rap140)/family with sequence similarity 208 member A (Fam208a), présentant une mutation non synonyme entre SS/Jr et LEW est le gène candidat le plus plausible pour représenter C16QTL. Celui-ci code pour un facteur de transcription et semblerait influencer l’expression de Solute carrier family 7 (cationic amino acid transporter, y+ system) member 12 (Slc7a12), spécifiquement et significativement sous exprimé dans les reins de la souche congénique portant C16QTL par rapport à la souche SS/Jr. Rap140/Fam208a agirait comme un inhibiteur de la transcription de Slc7a12 menant à une diminution de la pression chez Lewis. Conclusions: L’architecture complexe de la régulation de la PA se dévoile mettant en scène de nouveaux acteurs, pour la plupart inconnus pour leur implication dans la PA. L’étude de la nouvelle voie de signalisation Rap140/Fam208a - Slc7a12 nous permettra d’approfondir nos connaissances quant à l’homéostasie de la pression artérielle et de l’hypertension chez SS/Jr. À long terme, de nouveaux traitements anti-hypertenseurs, ciblant plus d’une voie de régulation à la fois, pourraient voir le jour.

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.