1000 resultados para Experimental crosses


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The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

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Farmed fish are typically genetically different from wild conspecifics. Escapees from fish farms may contribute one-way gene flow from farm to wild gene pools, which can depress population productivity, dilute local adaptations and disrupt coadapted gene complexes. Here, we reanalyse data from two experiments (McGinnity et al., 1997, 2003) where performance of Atlantic salmon (Salmo salar) progeny originating from experimental crosses between farm and wild parents (in three different cohorts) were measured in a natural stream under common garden conditions. Previous published analyses focussed on group-level differences but did not account for pedigree structure, as we do here using modern mixed-effect models. Offspring with one or two farm parents exhibited poorer survival in their first and second year of life compared with those with two wild parents and these group-level inferences were robust to excluding outlier families. Variation in performance among farm, hybrid and wild families was generally similar in magnitude. Farm offspring were generally larger at all life stages examined than wild offspring, but the differences were moderate (5–20%) and similar in magnitude in the wild versus hatchery environments. Quantitative genetic analyses conducted using a Bayesian framework revealed moderate heritability in juvenile fork length and mass and positive genetic correlations (>0.85) between these morphological traits. Our study confirms (using more rigorous statistical techniques) previous studies showing that offspring of wild fish invariably have higher fitness and contributes fresh insights into family-level variation in performance of farm, wild and hybrid Atlantic salmon families in the wild. It also adds to a small, but growing, number of studies that estimate key evolutionary parameters in wild salmonid populations. Such information is vital in modelling the impacts of introgression by escaped farm salmon.

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Background: Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F2 populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F2 animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature. Methods: We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F2 population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight. Results: Five of the nine QTL detected with the original F2 population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL. Conclusions: Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.

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

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

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

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

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Allopatric speciation results from geographic isolation between populations. In the absence of gene flow, reproductive isolation arises gradually and incidentally as a result of mutation, genetic drift and the indirect effects of natural selection driving local adaptation(1-3). In contrast, speciation by reinforcement is driven directly by natural selection against maladaptive hybridization(1,4). This gives individuals that choose the traits of their own lineage greater fitness, potentially leading to rapid speciation between the lineages(1,4). Reinforcing natural selection on a population of one of the lineages in a mosaic contact zone could also result in divergence of the population from the allopatric range of its own lineage outside the zone(4-6). Here we test this with molecular data, experimental crosses, field measurements and mate choice experiments in a mosaic contact zone between two lineages of a rainforest frog. We show that reinforcing natural selection has resulted in significant premating isolation of a population in the contact zone not only from the other lineage but also, incidentally, from the closely related main range of its own lineage. Thus we show the potential for reinforcement to drive rapid allopatric speciation.

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Erythropoietin (EPO), recognized for its central role in erythropoiesis, also mediates neuroprotection when the recombinant form (r-Hu-EPO) is directly injected into ischemic rodent brain. We observed abundant expression of the EPO receptor at brain capillaries, which could provide a route for circulating EPO to enter the brain. In confirmation of this hypothesis, systemic administration of r-Hu-EPO before or up to 6 h after focal brain ischemia reduced injury by ≈50–75%. R-Hu-EPO also ameliorates the extent of concussive brain injury, the immune damage in experimental autoimmune encephalomyelitis, and the toxicity of kainate. Given r-Hu-EPO's excellent safety profile, clinical trials evaluating systemically administered r-Hu-EPO as a general neuroprotective treatment are warranted.

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This paper investigates the feasibility of using an instrumented vehicle to detect bridge dynamic parameters, such as natural frequency and structural damping, in a scaled laboratory experiment. In the experiment, a scaled vehicle model crosses a steel girder which has been adopted as the bridge model. The bridge model also includes a scaled road surface profile. The effects of varying vehicle model mass and speed are investigated. The damping of the girder is also varied. The bridge frequency and changes in damping are detected in the vehicle acceleration response in the presence of a rough road surface profile.

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

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

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reduce costs and labor associated with predicting the genotypic mean (GM) of a synthetic variety (SV) of maize (Zea mays L.), breeders can develop SVs from L lines and s single crosses (SynL,SC) instead of L+2s lines (SynL). The objective of this work was to derive and study formulae for the inbreeding coefficient (IC) and GM of SynL,SC, SynL, and the SV derived from (L+2s)/2 single crosses (SynSC). All SVs were derived from the same L+2s unrelated lines whose IC is FL, and each parent of a SV was represented by m plants. An a priori probability equation for the IC was used. Important results were: 1) the largest and smallest GMs correspond to SynL and SynL,SC, respectively; 2) the GM predictors with the largest and intermediate precision are those for SynL and SynL,SC, respectively; 3) only when FL=1, or m is large, SynL and SynSC are the same population, but only with SynSC prediction costs and labor undergo the maximum decrease, although its prediction precision is the lowest. To determine the SV to be developed, breeders should also consider the availability of lines, single crosses, manpower and land area; besides budget, target farmers, target environments, etc.