995 resultados para genotype selection
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The objective of this work was to evaluate the carbon isotope fractionation as a phenomic facility for cotton selection in contrasting environments and to assess its relationship with yield components. The experiments were carried out in a randomized block design, with four replicates, in the municipalities of Santa Helena de Goiás (SHGO) and Montividiu (MONT), in the state of Goiás, Brazil. The analysis of carbon isotope discrimination (Δ) was performed in 15 breeding lines and three cultivars. Subsequently, the root growth kinetic and root system architecture from the selected genotypes were determined. In both locations, Δ analyses were suitable to discriminate cotton genotypes. There was a positive correlation between Δ and seed-cotton yield in SHGO, where water deficit was more severe. In this site, the negative correlations found between Δ and fiber percentage indicate an integrative effect of gas exchange on Δ and its association with yield components. As for root robustness and growth kinetic, the GO 05 809 genotype performance contributes to sustain the highest values of Δ found in MONT, where edaphoclimatic conditions were more suitable for cotton. The use of Δ analysis as a phenomic facility can help to select cotton genotypes, in order to obtain plants with higher efficiency for gas exchange and water use.
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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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The objective of this work was to identify key locations for the establishment of soybean (Glycine max) genetic breeding programs, in the Central Region of Brazil. Grain yield data of three maturity groups of soybean genotypes, from regional trials conducted over three years, at 18 locations in Brazilian Cerrado were used. A key location for the early phases of the breeding program was defined as the site that best classifies the winning genotypes in the region. Key locations for the final phases were defined as those sites that best represent each environmental stratum, in relation to the adaptability of the respective winning genotype. This adaptability was estimated by additive main effects and multiplicative interaction (AMMI) model analysis, using the distance between the score of each location in a stratum and the score of the winning genotype, which characterizes such stratum in an AMMI biplot. The locations that best classified the winning genotypes over space and time were Mineiros, Placas and Rio Verde. For the final phases of genotype selection, with data from the three maturity group, the recommended locations were: Buritis, Chapadão do Céu, Iraí, Pamplona, Placas, Planaltina, Rio Verde, Sacramento, Senador Canedo, Uberaba, and Uberlândia.
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P>Curcuma longa L. is a sterile, triploid, vegetatively-propagated crop cultivated mainly in Southeast Asia. When dried rhizomes are ground, the resulting yellow powder is used by the food industry as a natural food dye. Moreover, many pharmacological compounds have broadened the commercial application of the crop. However, conventional breeding is difficult and hence, improvement has been limited to germplasm selection. To better utilize the germplasm collections and facilitate genotype selection, a total of 17 polymorphic microsatellite loci were developed using a CT/GT/CTT enriched genomic library. All microsatellites resulted in amplified PCR products, showing a banding pattern of 2-11 polymorphic bands per locus, enabling genotype discrimination. These results can be used in further studies aimed at characterizing C. longa genetic resource collections and also to improve breeding strategies.
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The objective of this work was to assess, during six years, the temporal stability of natural rubber yield of 25 superior Hevea brasiliensis genotypes, using the Wricke, Eberhart & Russell, Lin & Binns, additive main effect and multiplicative interaction (AMMI) analysis, and harmonic mean of the relative performance of the genetic values (HMRPGV) methods. The IAC 40 and IAC 300 genotypes were identified as stable and high yielding by the Eberhart & Russell, Lin & Binns, HMRPGV, and AMMI Biplot methods. The ranking of the other more stable genotypes identified by these analyses was altered. The observed results in the AMMI Biplot agreed with those observed in the Wricke method for identifying stable, but lower yielding genotypes. The simultaneous use of different methods allows a more accurate indication of stable genotypes. Stability analyses based on different principles show agreement in indicating stable genotypes.
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The present work aimed to characterize and identify QTLs for wood quality and growth traits in E. grandis x E. urophylla hybrids. For this purpose a RAPD linkage map was developed for the hybrids (LOD=3 and r=0.40) containing 52 markers and 12 linkage groups. Traits related to wood quality and growth were evaluated in the QTL analyses. QTL analyses were performed using chi-square tests, single-marker, interval mapping and composite interval mapping analyses. All approaches led to the identification of similar QTLs associated with wood density, cellulose pulp yield and percentage of extractives, which were detected and confirmed by both the interval mapping and composite interval mapping methodologies. Some QTLs regions were confirmed only by the composite interval mapping methodology: percentage of soluble lignin, percentage of insoluble lignin, CBH and total height. Overlapping QTLs regions were detected, and these, can be the result of major genes involved in the regulation and control of the growth traits by epistatic interactions. In order to evaluate the effect of early selection using RAPD molecular data, molecular markers adjacent to QTLs were used genotype selection. The analysis of selection differential values suggests that for all the traits the phenotypic selection at seven years should generate larger genetic gains than early selection assisted by molecular markers and the combination of the strategies should elevate the selection efficiency.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Climate models predict more frequent and more severe extreme events (e.g., heat waves, extended drought periods, flooding) in many regions for the next decades. The impact of adverse environmental conditions on crop plants is ecologically and economically relevant. This review is focused on drought and heat effects on physiological status and productivity of agronomically important plants. Stomatal opening represents an important regulatory mechanism during drought and heat stress since it influences simultaneously water loss via transpiration and CO2 diffusion into the leaf apoplast which further is utilized in photosynthesis. Along with the reversible short-term control of stomatal opening, stomata and leaf epidermis may produce waxy deposits and irreversibly down-regulate the stomatal conductance and non-stomatal transpiration. As a consequence photosynthesis will be negatively affected. Rubisco activase—a key enzyme in keeping the Calvin cycle functional—is heat-sensitive and may become a limiting factor at elevated temperature. The accumulated reactive oxygen species (ROS) during stress represent an additional challenge under unfavorable conditions. Drought and heat cause accumulation of free amino acids which are partially converted into compatible solutes such as proline. This is accompanied by lower rates of both nitrate reduction and de novo amino acid biosynthesis. Protective proteins (e.g., dehydrins, chaperones, antioxidant enzymes or the key enzyme for proline biosynthesis) play an important role in leaves and may be present at higher levels under water deprivation or high temperatures. On the whole plant level, effects on long-distance translocation of solutes via xylem and phloem and on leaf senescence (e.g., anticipated, accelerated or delayed senescence) are important. The factors mentioned above are relevant for the overall performance of crops under drought and heat and must be considered for genotype selection and breeding programs.
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The objective of this study was to compare the BLUP selection method with different selection strategies in F-2:4 and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F-2:4 progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.
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With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^
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Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.
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We investigated the role of chemoreception in the host selection and oviposition behaviour of Helicoverpa armigera in the laboratory using five cotton genotypes and synthetic volatile terpenes. Female moths oviposited on substrates treated with methanol, ethanol, acetone and pentane extracts of leaves, squares and flowers of the cotton genotypes. Phytochemicals soluble in pentane were the most efficient in eliciting oviposition behaviour. In a two-way bioassay, pentane extracts of leaves or squares of a Multiple Host-plant Resistance genotype (MHR11), Deltapine commercial (DP90), and Smith Red Leaf (SRL) received significantly more eggs than solvent-treated controls. Extracts of squares of the native genotype Gossypium nelsonii did not receive more eggs. Females preferred DP90 and MHR11 to SRL and G. nelsonii. Female moths also laid more eggs on pentane extracts of MHR11 flowers than MHR11 leaves from preflowering, early flowering and peak-flowering plants. In a flight chamber, female moths used olfactory cues at short range to mediate oviposition and discrimination between host plants. Egg-laying, mated females were attracted at a distance (1.5 m) to volatile compounds released by whole plants and odours emanating from filter papers treated with synthetic volatile terpenes. Individually, the terpenes did not stimulate any significant oviposition response. However, there was a significant oviposition response to a mixture of equal volumes of the terpenes (trans-beta-caryophyllene, alpha-pinene, beta-pinene, myrcene, beta-bisabolol, and alpha-humulene). Conversely, antennectomised (moths with transected antennae), egg-laying, mated females did not stimulate any significant oviposition response. The significance of these findings in relation to H. armigera hostplant selection are discussed.
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The polymorphisms of the important xenobiotic metabolizing enzymes CYP2D6, CYP2C19 and CYP2E1 have been studied extensively in a large number of populations and show significant heterogeneity in the frequency of different alleles/genotypes and in the prevalence of the extensive and poor metabolizer phenotypes, Understanding of inter-ethnic differences in genotypes is important in prediction of either beneficial or adverse effects from therapeutic agents and other xenobiotics. Since no data were available for Australian Aborigines, we investigated the frequencies of alleles and genotypes for CYP2D6, CYP2C19 and CYP2E1 in a population living in the far north of Western Australia. Because of its geographical isolation, this population can serve as a model to study the impact of evolutionary forces on the distribution of different alleles for xenobiotic metabolizing enzymes. Twelve CYP2D6 alleles were analysed, The wild-type allele *1 was the most frequent (85.8%) and the non-functional alleles (*4, *5, *16) had an overall frequency of less than 10%. Only one subject (0.4%) was a poor metabolizer for CYP2D6 because of the genotype *5/*5, For CYP2C19, the frequencies of the *1 (wild-type) and the non-functional (*2 and *3) alleles were 50.2%, 35.5% and 14.3%, respectively. The combined CYP2C19 genotypes (*2/*2, *2/*3 or *3/*3) correspond to a predicted frequency of 25.6% for the CYP2C19 poor metabolizer phenotype, For CYP2E1, only one subject had the rare c2 allele giving an overall allele frequency of 0.2%. For CYP2D6 and CYP2C19, allele frequencies and predicted phenotypes differed significantly from those for Caucasians but were similar to those for Orientals indicating a close relationship to East Asian populations. Differences between Aborigines and Orientals in allele frequencies for CYP2D6*10 and CYP2E1 c2 may have arisen through natural selection, or genetic drift, respectively, Pharmacogenetics 11:69-76 (C) 2001 Lippincott Williams & Wilkins.
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We compared diurnal patterns of vaginal temperature in lactating cows under grazing conditions to evaluate genotype effects on body temperature regulation. Genotypes evaluated were Holstein, Jersey, Jersey x Holstein and Swedish Red x Holstein. The comparison of Holstein and Jersey versus Jersey x Holstein provided a test of whether heterosis effects body temperature regulation. Cows were fitted with intravaginal temperature recording devices that measured vaginal temperature every 15 min for 7 days. Vaginal temperature was affected by time of day (P < 0.0001) and genotype x time (P < 0.0001) regardless of whether days in milk and milk yield were used as covariates. Additional analyses indicated that the Swedish Red x Holstein had a different pattern of vaginal temperatures than the other three genotypes (Swedish Red x Holstein vs others x time; P < 0.0001) and that Holstein and Jersey had a different pattern than Jersey x Holstein [(Holstein + Jersey vs Jersey x Holstein) x time, P < 0.0001]. However, Holstein had a similar pattern to Jersey [(Holstein vs Jersey) x time, P > 0.10]. These genotype x time interactions reflect two effects. First, Swedish Red x Holstein had higher vaginal temperatures than the other genotypes in the late morning and afternoon but not after the evening milking. Secondly, Jersey x Holstein had lower vaginal temperatures than other genotypes in the late morning and afternoon and again in the late night and early morning. Results point out that there are effects of specific genotypes and evidence for heterosis on regulation of body temperature of lactating cows maintained under grazing conditions and suggest that genetic improvement for thermotolerance through breed choice or genetic selection is possible.