11 resultados para polygenes


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A common breeding strategy is to carry out basic studies to investigate the hypothesis of a single gene controlling the trait (major gene) with or without polygenes of minor effect. In this study we used Bayesian inference to fit genetic additive-dominance models of inheritance to plant breeding experiments with multiple generations. Normal densities with different means, according to the major gene genotype, were considered in a linear model in which the design matrix of the genetic effects had unknown coefficients (which were estimated in individual basis). An actual data set from an inheritance study of partenocarpy in zucchini (Cucurbita pepo L.) was used for illustration. Model fitting included posterior probabilities for all individual genotypes. Analysis agrees with results in the literature but this approach was far more efficient than previous alternatives assuming that design matrix was known for the generations. Partenocarpy in zucchini is controlled by a major gene with important additive effect and partial dominance.

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Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

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BACKGROUND: Highly recurrent major depressive disorder (MDD) has reportedly increased risk of shifting to bipolar disorder; high recurrence frequency has, therefore, featured as evidence of 'soft bipolarity'. We aimed to investigate the genetic underpinnings of total depressive episode count in recurrent MDD. METHODS: Our primary sample included 1966 MDD cases with negative family history of bipolar disorder from the RADIANT studies. Total episode count was adjusted for gender, age, MDD duration, study and center before being tested for association with genotype in two separate genome-wide analyses (GWAS), in the full set and in a subset of 1364 cases with positive family history of MDD (FH+). We also calculated polygenic scores from the Psychiatric Genomics Consortium MDD and bipolar disorder studies. RESULTS: Episodicity (especially intermediate episode counts) was an independent index of MDD familial aggregation, replicating previous reports. The GWAS produced no genome-wide significant findings. The strongest signals were detected in the full set at MAGI1 (p=5.1×10(-7)), previously associated with bipolar disorder, and in the FH+ subset at STIM1 (p=3.9×10(-6) after imputation), a calcium channel signaling gene. However, these findings failed to replicate in an independent Munich cohort. In the full set polygenic profile analyses, MDD polygenes predicted episodicity better than bipolar polygenes; however, in the FH+ subset, both polygenic scores performed similarly. LIMITATIONS: Episode count was self-reported and, therefore, subject to recall bias. CONCLUSIONS: Our findings lend preliminary support to the hypothesis that highly recurrent MDD with FH+ is part of a 'soft bipolar spectrum' but await replication in larger cohorts.

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The yearly genetic progress obtained by breeding for increased soybean yield has been considered acceptable worldwide. It is common sense, however, that this progress can be improved further if refined breeding techniques, developed from the knowledge of the genetic mechanisms controlling soybean yield, are used. In this paper, data from four cultivars and/or lines and their derived sets of F2, F3, F7, F8, F9 and F10 generations assayed in 17 environments were analyzed to allow an insight of the genetic control of soybean yield under different environmental conditions. The general picture was of a complex polygene system controlling yield in soybeans. Additive genetic effects predominated although dominance was often found to be significant. Complications such as epistasis, linkage and macro and micro genotype x environment (G x E) interactions were also commonly detected. The overall heritability was 0.29. The relative magnitude of the additive effects and the complicating factors allowed the inference that the latter are not a serious problem to the breeder. The low heritability values and the considerable magnitude of G x E interactions for yield, however, indicated that careful evaluation through experiments designed to allow for the presence of these effects is necessary for successful selection.

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The objective of this work was to distinguish the parental source of alleles in heterozygous progeny using semiquantitative polymerase chain reaction (PCR) in maize endosperm. Endosperms derived from direct and reciprocal single-cross hybrids between maize inbred lines L3 and L1113-01 were genotyped by semiquantitative PCR methodology (SQ-PCR) using fluorescent microsatellite primers. The amplification products were evaluated by the ratios of fluorescence intensity (RFI), calculated between the peaks corresponding to the alleles derived from each parental line. Based on the statistically significant contrast between RFI mean values of direct and reciprocal single-cross hybrids, it was possible to distinguish the number of alleles received from each parental line and, ultimately, to determine the origin of the alleles of each cross. Thus, endosperm genotyping using SQ-PCR is a promising strategy to map QTL in maize outbred populations.

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The objective of this work was to determine the inheritance of resistance by antixenosis in tomato plants (Lycopersicon esculentum) to tomato leafminer [Tuta absoluta (Lepidoptera: Gelechiidae)]. Evaluations were performed for tomato plants of the generations P1, P2, F1, F2, RC1 and RC2. The measured characteristic in the parents, BGH-1497 (P2 male) and 'Santa Clara' (P1 female), and in the F1, F2, RC1 and RC2 generations was the number of eggs per plant. This number was converted to the oviposition nonpreference index. The inheritance of antixenosis resistance of genotype BGH-1497 is ruled by a gene of greater effect and polygenes in epistatic interactions, with a phenotypic proportion of 13:3 between susceptible and resistant genotypes, respectively.

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Three egg-type stocks segregating dwarf (dw) and bantam (dwB) genes in female progeny were produced from the same 18 heterozygous (dwB/dw) sires used to inseminate dams of three different genotypes: normal (dw+), dwarf (dw) and bantam (dwB) dams. The heritability of 8-week body weight estimated from full-sibs of the same phenotype of progeny was 0.40, and that estimated from paternal half-sibs of the same phenotype (dwarf or bantam), and from the same genotype of dam was 0.38. Therefore, maternal and non-additive effects within genotypic classes of dam made little contribution to the genetic variance for 8-week body weight among their progeny. The interaction of sires (S) with genotypes (dw+, dw and dwB) of dam (G) was significant at the 5% level. This indicates that the rankings of the sires within each one of the three genotypes of dam were not the same, probably due to non-additive genetic variation among genotypes of dams. The evidence indicated that in general the genes from individual sires combined differently with each type of dam (G). Those genes which combined well with the genes from normal (dw+) dams combined poorly with both the genes from the dwarf (dw) and the genes from the bantam (dwB) dams. The interaction of sires (S) with phenotypes (dwarf and bantam) of progeny (P) was significant at the 10% level. The results indicated a probable gene x genotype interaction for 8-week weight between genes at the dwarf locus (dw and dwB) and the background genotype (single and/or polygenes). The correlation among paternal half-sibs was influenced more by the S x G than by the S x P interaction, but the effects tended to be cumulative

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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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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Lod scores provide a method to unify linkage tests based on identity by descent and identity in marker state while permitting selection of the most informative individuals through their disease-related phenotypes and markers in relatives. After parametric lods are reviewed, a nonparametric approach that depends on a single logistic parameter beta is introduced. Lods for parents tested or unknown are derived, multiple pairwise mapping is presented, and power is shown to be good even for moderately small values of beta. Comparison of parametric and nonparametric approaches (yet to be made) will provide for polygenes the efficiency and reliability that lod scores gave to mapping of major loci 40 years ago.