986 resultados para Quantitative genetic


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Among the huge radiations of haplochromine cichlid fish in Lakes Malawi and Victoria, closely related species are often reproductively isolated via female mate choice although viable fertile hybrids can be produced when females are confined only with heterospecific males. We generated F(2) hybrid males from a cross between a pair of closely related sympatric cichlid fish from Lake Malawi. Laboratory mate choice experiments using microsatellite paternity analysis demonstrated that F(2) hybrid males differed significantly in their attractiveness to females of the two parental species, indicating heritable variation in traits involved in mate choice that may contribute to reproductive isolation between these species. We found no significant correlation between male mating success and any measurement of male colour pattern. A simple quantitative genetic model of reproductive isolation suggests that there may be as few as two chromosomal regions controlling species-specific attractiveness. We propose that adaptive radiation of Lake Malawi cichlids could be facilitated by the presence of genes with major effects on mate choice and reproductive isolation.

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Adaptive and non-adaptive evolutionary processes are likely to play important roles in biological invasions but their relative importance has hardly ever been quantified. Moreover, although genetic differences between populations in their native versus invasive ranges may simply reflect different positions along a genetic latitudinal cline, this has rarely been controlled for. To study non-adaptive evolutionary processes in invasion of Mimulus guttatus, we used allozyme analyses on offspring of seven native populations from western North America, and three and four invasive populations from Scotland and New Zealand, respectively. To study quantitative genetic differentiation, we grew 2474 plants representing 17 native populations and the seven invasive populations in a common greenhouse environment under temporarily and permanently wet soil conditions. The absence of allozyme differentiation between the invasive and native range indicates that multiple genotypes had been introduced to Scotland and New Zealand, and suggests that founder effects and genetic drift played small, if any, roles in shaping genetic structure of invasive M. guttatus populations. Plants from the invasive and native range did not differ in phenology, floral traits and sexual and vegetative reproduction, and also not in plastic responses to the watering treatments. However, plants from the invasive range produced twice as many flower-bearing upright side branches than the ones from the native populations. Further, with increasing latitude of collection, vegetative reproduction of our experimental plants increased while sexual reproduction decreased. Plants from the invasive and native range shared these latitudinal clines. Because allozymes showed that the relatedness between native and invasive populations did not depend on latitude, this suggests that plants in the invasive regions have adapted to the local latitude. Overall, our study indicates that quantitative genetic variation of M. guttatus in its two invasive regions is shaped by adaptive evolutionary processes rather than by non-adaptive ones. (C) 2007 Gesellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.

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• Premise of the study: Because not all plant species will be able to move in response to global warming, adaptive evolution matters largely for plant persistence. As prerequisites for adaptive evolution, genetic variation in and selection on phenotypic traits are needed, but these aspects have not been studied in tropical species. We studied how plants respond to transplantation to different elevations on Mt. Kilimanjaro, Tanzania, and whether there is quantitative genetic (among-seed family) variation in and selection on life-history traits and their phenotypic plasticity to the different environments. • Methods: We reciprocally transplanted seed families of 15 common tropical, herbaceous species of the montane and savanna vegetation zone at Mt. Kilimanjaro to a watered experimental garden in the montane (1450 m) and in the savanna (880 m) zone at the mountain’s slope and measured performance, reproductive, and phenological traits. • Results: Plants generally performed worse in the savanna garden, indicating that the savanna climate was more stressful and thus that plants may suffer from future climate warming. We found significant quantitative genetic variation in all measured performance and reproductive traits in both gardens and for several measures of phenotypic plasticity in response to elevational transplantation. Moreover, we found positive selection on traits at low and intermediate trait values levelling to neutral or negative selection at high values. • Conclusions: We conclude that common plants at Mt. Kilimanjaro express quantitative genetic variation in fitness-relevant traits and in their plasticities, suggesting potential to adapt evolutionarily to future climate warming and increased temperature variability.

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Analysis of the three most ancient Zea mays inflorescence fragments from Guilá Naquitz, Oaxaca, Mexico shows they did not disarticulate naturally, indicating that agricultural selection of domesticated teosinte was underway by 5,400 14C years before the present (about 4,200 dendrocalibrated years B.C.). The cooccurrence of two-ranked specimens with two rows and four rows of grain and numerous additional morphological characteristics of these specimens support hypotheses based on molecular and quantitative genetic analyses that maize evolved from teosinte. Domestication of the wild ancestor of maize occurred before the end of the 5th millennium B.C.

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The biological bases of learning and memory are being revealed today with a wide array of molecular approaches, most of which entail the analysis of dysfunction produced by gene disruptions. This perspective derives both from early “genetic dissections” of learning in mutant Drosophila by Seymour Benzer and colleagues and from earlier behavior-genetic analyses of learning and in Diptera by Jerry Hirsch and coworkers. Three quantitative-genetic insights derived from these latter studies serve as guiding principles for the former. First, interacting polygenes underlie complex traits. Consequently, learning/memory defects associated with single-gene mutants can be quantified accurately only in equilibrated, heterogeneous genetic backgrounds. Second, complex behavioral responses will be composed of genetically distinct functional components. Thus, genetic dissection of complex traits into specific biobehavioral properties is likely. Finally, disruptions of genes involved with learning/memory are likely to have pleiotropic effects. As a result, task-relevant sensorimotor responses required for normal learning must be assessed carefully to interpret performance in learning/memory experiments. In addition, more specific conclusions will be obtained from reverse-genetic experiments, in which gene disruptions are restricted in time and/or space.

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Stabilizing selection is a fundamental concept in evolutionary biology. In the presence of a single intermediate optimum phenotype (fitness peak) on the fitness surface, stabilizing selection should cause the population to evolve toward such a peak. This prediction has seldom been tested, particularly for suites of correlated traits. The lack of tests for an evolutionary match between population means and adaptive peaks may be due, at least in part, to problems associated with empirically detecting multivariate stabilizing selection and with testing whether population means are at the peak of multivariate fitness surfaces. Here we show how canonical analysis of the fitness surface, combined with the estimation of confidence regions for stationary points on quadratic response surfaces, may be used to define multivariate stabilizing selection on a suite of traits and to establish whether natural populations reside on the multivariate peak. We manufactured artificial advertisement calls of the male cricket Teleogryllus commodus and played them back to females in laboratory phonotaxis trials to estimate the linear and nonlinear sexual selection that female phonotactic choice imposes on male call structure. Significant nonlinear selection on the major axes of the fitness surface was convex in nature and displayed an intermediate optimum, indicating multivariate stabilizing selection. The mean phenotypes of four independent samples of males, from the same population as the females used in phonotaxis trials, were within the 95% confidence region for the fitness peak. These experiments indicate that stabilizing sexual selection may play an important role in the evolution of male call properties in natural populations of T. commodus.

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Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.

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The constancy of phenotypic variation and covariation is an assumption that underlies most recent investigations of past selective regimes and attempts to predict future responses to selection. Few studies have tested this assumption of constancy despite good reasons to expect that the pattern of phenotypic variation and covariation may vary in space and time. We compared phenotypic variance-covariance matrices (P) estimated for Populations of six species of distantly related coral reef fishes sampled at two locations on Australia's Great Barrier Reef separated by more than 1000 km. The intraspecific similarity between these matrices was estimated using two methods: matrix correlation and common principal component analysis. Although there was no evidence of equality between pairs of P, both statistical approaches indicated a high degree of similarity in morphology between the two populations for each species. In general, the hierarchical decomposition of the variance-covariance structure of these populations indicated that all principal components of phenotypic variance-covariance were shared but that they differed in the degree of variation associated with each of these components. The consistency of this pattern is remarkable given the diversity of morphologies and life histories encompassed by these species. Although some phenotypic instability was indicated, these results were consistent with a generally conserved pattern of multivariate selection between populations.

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Nitrogen (N) is an essential plant nutrient in maize production, and if considering only natural sources, is often the limiting factor world-wide in terms of a plant’s grain yield. For this reason, many farmers around the world supplement available soil N with synthetic man-made forms. Years of over-application of N fertilizer have led to increased N in groundwater and streams due to leaching and run-off from agricultural sites. In the Midwest Corn Belt much of this excess N eventually makes its way to the Gulf of Mexico leading to eutrophication (increase of phytoplankton) and a hypoxic (reduced oxygen) dead zone. Growing concerns about these types of problems and desire for greater input use efficiency have led to demand for crops with improved N use efficiency (NUE) to allow reduced N fertilizer application rates and subsequently lower N pollution. It is well known that roots are responsible for N uptake by plants, but it is relatively unknown how root architecture affects this ability. This research was conducted to better understand the influence of root complexity (RC) in maize on a plant’s response to N stress as well as the influence of RC on other above-ground plant traits. Thirty-one above-ground plant traits were measured for 64 recombinant inbred lines (RILs) from the intermated B73 & Mo17 (IBM) population and their backcrosses (BCs) to either parent, B73 and Mo17, under normal (182 kg N ha-1) and N deficient (0 kg N ha-1) conditions. The RILs were selected based on results from an earlier experiment by Novais et al. (2011) which screened 232 RILs from the IBM to obtain their root complexity measurements. The 64 selected RILs were comprised of 31 of the lowest complexity RILs (RC1) and 33 of the highest complexity RILs (RC2) in terms of root architecture (characterized as fractal dimensions). The use of the parental BCs classifies the experiment as Design III, an experimental design developed by Comstock and Robinson (1952) which allows for estimation of dominance significance and level. Of the 31 traits measured, 12 were whole plant traits chosen due to their documented response to N stress. The other 19 traits were ear traits commonly measured for their influence on yield. Results showed that genotypes from RC1 and RC2 significantly differ for several above-ground phenotypes. We also observed a difference in the number and magnitude of N treatment responses between the two RC classes. Differences in phenotypic trait correlations and their change in response to N were also observed between the RC classes. RC did not seem to have a strong correlation with calculated NUE (ΔYield/ΔN). Quantitative genetic analysis utilizing the Design III experimental design revealed significant dominance effects acting on several traits as well as changes in significance and dominance level between N treatments. Several QTL were mapped for 26 of the 31 traits and significant N effects were observed across the majority of the genome for some N stress indicative traits (e.g. stay-green). This research and related projects are essential to a better understanding of plant N uptake and metabolism. Understanding these processes is a necessary step in the progress towards the goal of breeding for better NUE crops.

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Despite its importance to agriculture, the genetic basis of heterosis is still not well understood. The main competing hypotheses include dominance, overdominance, and epistasis. NC design III is an experimental design that. has been used for estimating the average degree of dominance of quantitative trait 106 (QTL) and also for studying heterosis. In this study, we first develop a multiple-interval mapping (MIM) model for design III that provides a platform to estimate the number, genomic positions, augmented additive and dominance effects, and epistatic interactions of QTL. The model can be used for parents with any generation of selling. We apply the method to two data sets, one for maize and one for rice. Our results show that heterosis in maize is mainly due to dominant gene action, although overdominance of individual QTL could not completely be ruled out due to the mapping resolution and limitations of NC design III. For rice, the estimated QTL dominant effects could not explain the observed heterosis. There is evidence that additive X additive epistatic effects of QTL could be the main cause for the heterosis in rice. The difference in the genetic basis of heterosis seems to be related to open or self pollination of the two species. The MIM model for NC design III is implemented in Windows QTL Cartographer, a freely distributed software.

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Abstract: Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 +/- 0.18 (between tibia length and BW42) to 0.89 +/- 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

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Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time.

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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.