991 resultados para JOINT COMPOSITE INTERVAL MAPPING


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

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Background: Common bean (Phaseolus vulgaris L.) is the most important grain legume for human diet worldwide and the angular leaf spot (ALS) is one of the most devastating diseases of this crop, leading to yield losses as high as 80%. In an attempt to breed resistant cultivars, it is important to first understand the inheritance mode of resistance and to develop tools that could be used in assisted breeding. Therefore, the aim of this study was to identify quantitative trait loci (QTL) controlling resistance to ALS under natural infection conditions in the field and under inoculated conditions in the greenhouse. Results: QTL analyses were made using phenotypic data from 346 recombinant inbreed lines from the IAC-UNA x CAL 143 cross, gathered in three experiments, two of which were conducted in the field in different seasons and one in the greenhouse. Joint composite interval mapping analysis of QTL x environment interaction was performed. In all, seven QTLs were mapped on five linkage groups. Most of them, with the exception of two, were significant in all experiments. Among these, ALS10.1(DG,UC) presented major effects (R-2 between 16% - 22%). This QTL was found linked to the GATS11b marker of linkage group B10, which was consistently amplified across a set of common bean lines and was associated with the resistance. Four new QTLs were identified. Between them the ALS5.2 showed an important effect (9.4%) under inoculated conditions in the greenhouse. ALS4.2 was another major QTL, under natural infection in the field, explaining 10.8% of the variability for resistance reaction. The other QTLs showed minor effects on resistance. Conclusions: The results indicated a quantitative inheritance pattern of ALS resistance in the common bean line CAL 143. QTL x environment interactions were observed. Moreover, the major QTL identified on linkage group B10 could be important for bean breeding, as it was stable in all the environments. Thereby, the GATS11b marker is a potential tool for marker assisted selection for ALS resistance.

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Four of the 12 major Glycine max ancestors of all modern elite U.S.A. soybean cultivars were the grandparents of Harosoy and Clark, so a Harosoy x Clark population would include some of that genetic diversity. A mating of eight Harosoy and eight Clark plants generated eight F1 plants. The eight F1:2 families were advanced via a plant-to-row selfing method to produce 300 F6-derived RILs that were genotyped with 266 SSR, 481 SNP, and 4 classical markers. SNPs were genotyped with the Illumina 1536-SNP assay. Three linkage maps, SSR, SNP, and SSR-SNP, were constructed with a genotyping error of < 1 %. Each map was compared with the published soybean consensus map. The best subset of 94 RILs for a high-resolution framework (joint) map was selected based on the expected bin length statistic computed with MapPop. The QTLs of seven traits measured in a 2-year replicated performance trial of the 300 RILs were identified using composite interval mapping (CIM) and multiple-interval mapping (MIM). QTL x Year effects in multiple trait analysis were compared with results of multiple-interval mapping. QTL x QTL effects were identified in MIM.

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QTL mapping provides usefull information for breeding programs since it allows the estimation of genomic locations and genetic effects of chromossomal regions related to the expression of quantitative traits. The objective of this study was to map QTL related to several agronomic important traits associated with grain yield: ear weight (EW), prolificacy (PROL), ear number (NE), ear length (EL) and diameter (ED), number of rows on the ear (NRE) and number of kernels per row on the ear (NKPR). Four hundred F-2:3 tropical maize progenies were evaluated in five environments in Piracicaba, Sao Paulo, Brazil. The genetic map was previously estimated and had 117 microssatelite loci with average distance of 14 cM. Data was analysed using Composite Interval Mapping for each trait. Thirty six QTL were mapped and related to the expression of EW (2), PROL (3), NE (2), EL (5), ED (5), NRE (10), NKPR (5). Few QTL were mapped since there was high GxE interaction. Traits EW, PROL and EN showed high genetic correlation with grain yield and several QTL mapped to similar genomic regions, which could cause the observed correlation. However, further analysis using apropriate statistical models are required to separate linked versus pleiotropic QTL. Five QTL (named Ew1, Ne1, Ed3, Nre3 and Nre10) had high genetic effects, explaining from 10.8% (Nre3) to 16.9% (Nre10) of the phenotypic variance, and could be considered in further studies.

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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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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.

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Leaf rust caused by Puccinia triticina is a serious disease of durum wheat (Triticum durum) worldwide. However, genetic and molecular mapping studies aimed at characterizing leaf rust resistance genes in durum wheat have been only recently undertaken. The Italian durum wheat cv. Creso shows a high level of resistance to P. triticina that has been considered durable and that appears to be due to a combination of a single dominant gene and one or more additional factors conferring partial resistance. In this study, the genetic basis of leaf rust resistance carried by Creso was investigated using 176 recombinant inbred lines (RILs) from the cross between the cv. Colosseo (C, leaf rust resistance donor) and Lloyd (L, susceptible parent). Colosseo is a cv. directly related to Creso with the leaf rust resistance phenotype inherited from Creso, and was considered as resistance donor because of its better adaptation to local (Emilia Romagna, Italy) cultivation environment. RILs have been artificially inoculated with a mixture of 16 Italian P. triticina isolates that were characterized for virulence to seedlings of 22 common wheat cv. Thatcher isolines each carrying a different leaf rust resistance gene, and for molecular genotypes at 15 simple sequence repeat (SSR) loci, in order to determine their specialization with regard to the host species. The characterization of the leaf rust isolates was conducted at the Cereal Disease Laboratory of the University of Minnesota (St. Paul, USA) (Chapter 2). A genetic linkage map was constructed using segregation data from the population of 176 RILs from the cross CL. A total of 662 loci, including 162 simple sequence repeats (SSRs) and 500 Diversity Arrays Technology markers (DArTs), were analyzed by means of the package EasyMap 0.1. The integrated SSR-DArT linkage map consisted of 554 loci (162 SSR and 392 DArT markers) grouped into 19 linkage blocks with an average marker density of 5.7 cM/marker. The final map spanned a total of 2022 cM, which correspond to a tetraploid genome (AABB) coverage of ca. 77% (Chapter 3). The RIL population was phenotyped for their resistance to leaf rust under artificial inoculation in 2006; the percentage of infected leaf area (LRS, leaf rust susceptibility) was evaluated at three stages through the disease developmental cycle and the area under disease progress curve (AUDPC) was then calculated. The response at the seedling stage (infection type, IT) was also investigated. QTL analysis was carried out by means of the Composite Interval Mapping method based on a selection of markers from the CL map. A major QTL (QLr.ubo-7B.2) for leaf rust resistance controlling both the seedling and the adult plant response, was mapped on the distal region of chromosome arm 7BL (deletion bin 7BL10-0.78-1.00), in a gene-dense region known to carry several genes/QTLs for resistance to rusts and other major cereal fungal diseases in wheat and barley. QLr.ubo-7B.2 was identified within a supporting interval of ca. 5 cM tightly associated with three SSR markers (Xbarc340.2, Xgwm146 e Xgwm344.2), and showed an R2 and an LOD peak value for the AUDPC equal to 72.9% an 44.5, respectively. Three additional minor QTLs were also detected (QLr.ubo-7B.1 on chr. 7BS; QLr.ubo-2A on chr. 2AL and QLr.ubo-3A on chr. 3AS) (Chapter 4). The presence of the major QTL (QLr.ubo-7B.2) was validated by a linkage disequilibrium (LD)-based test using field data from two different plant materials: i) a set of 62 advanced lines from multiple crosses involving Creso and his directly related resistance derivates Colosseo and Plinio, and ii) a panel of 164 elite durum wheat accessions representative of the major durum breeding program of the Mediterranean basin. Lines and accessions were phenotyped for leaf rust resistance under artificial inoculation in two different field trials carried out at Argelato (BO, Italy) in 2006 and 2007; the durum elite accessions were also evaluated in two additional field experiments in Obregon (Messico; 2007 and 2008) and in a green-house experiment (seedling resistance) at the Cereal Disease Laboratory (St. Paul, USA, 2008). The molecular characterization involved 14 SSR markers mapping on the 7BL chromosome region found to harbour the major QTL. Association analysis was then performed with a mixed-linear-model approach. Results confirmed the presence of a major QTL for leaf rust resistance, both at adult plant and at seedling stage, located between markers Xbarc340.2, Xgwm146 and Xgwm344.2, in an interval that coincides with the supporting interval (LOD-2) of QLr.ubo-7B.2 as resulted from the RIL QTL analysis. (Chapter 5). The identification and mapping of the major QTL associated to the durable leaf rust resistance carried by Creso, together with the identification of the associated SSR markers, will enhance the selection efficiency in durum wheat breeding programs (MAS, Marker Assisted Selection) and will accelerate the release of cvs. with durable resistance through marker-assisted pyramiding of the tagged resistance genes/QTLs most effective against wheat fungal pathogens.

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Heterosis is widely used in breeding, but the genetic basis of this biological phenomenon has not been elucidated. We postulate that additive and dominance genetic effects as well as two-locus interactions estimated in classical QTL analyses are not sufficient for quantifying the contributions of QTL to heterosis. A general theoretical framework for determining the contributions of different types of genetic effects to heterosis was developed. Additive x additive epistatic interactions of individual loci with the entire genetic background were identified as a major component of midparent heterosis. On the basis of these findings we defined a new type of heterotic effect denoted as augmented dominance effect di* that comprises the dominance effect at each QTL minus half the sum of additive x additive interactions with all other QTL. We demonstrate that genotypic expectations of QTL effects obtained from analyses with the design III using testcrosses of recombinant inbred lines and composite-interval mapping precisely equal genotypic expectations of midparent heterosis, thus identifying genomic regions relevant for expression of heterosis. The theory for QTL mapping of multiple traits is extended to the simultaneous mapping of newly defined genetic effects to improve the power of QTL detection and distinguish between dominance and overdominance.

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Senescence, the decline in survivorship and fertility with increasing age, is a near-universal property of organisms. Senescence and limited lifespan are thought to arise because weak natural selection late in life allows the accumulation of mutations with deleterious late-age effects that are either neutral (the mutation accumulation hypothesis) or beneficial (the antagonistic pleiotropy hypothesis) early in life. Analyses of Drosophila spontaneous mutations, patterns of segregating variation and covariation, and lines selected for late-age fertility have implicated both classes of mutation in the evolution of aging, but neither their relative contributions nor the properties of individual loci that cause aging in nature are known. To begin to dissect the multiple genetic causes of quantitative variation in lifespan, we have conducted a genome-wide screen for quantitative trait loci (QTLs) affecting lifespan that segregate among a panel of recombinant inbred lines using a dense molecular marker map. Five autosomal QTLs were mapped by composite interval mapping and by sequential multiple marker analysis. The QTLs had large sex-specific effects on lifespan and age-specific effects on survivorship and mortality and mapped to the same regions as candidate genes with fertility, cellular aging, stress resistance and male-specific effects. Late age-of-onset QTL effects are consistent with the mutation accumulation hypothesis for the evolution of senescence, and sex-specific QTL effects suggest a novel mechanism for maintaining genetic variation for lifespan.

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Polymorphisms in the prion protein gene are known to affect prion disease incubation times and susceptibility in humans and mice. However, studies with inbred lines of mice show that large differences in incubation times occur even with the same amino acid sequence of the prion protein, suggesting that other genes may contribute to the observed variation. To identify these loci we analyzed 1,009 animals from an F2 intercross between two strains of mice, CAST/Ei and NZW/OlaHSd, with significantly different incubation periods when challenged with RML scrapie prions. Interval mapping identified three highly significantly linked regions on chromosomes 2, 11, and 12; composite interval mapping suggests that each of these regions includes multiple linked quantitative trait loci. Suggestive evidence for linkage was obtained on chromosomes 6 and 7. The sequence conservation between the mouse and human genome suggests that identification of mouse prion susceptibility alleles may have direct relevance to understanding human susceptibility to bovine spongiform encephalopathy (BSE) infection, as well as identifying key factors in the molecular pathways of prion pathogenesis. However, the demonstration of other major genetic effects on incubation period suggests the need for extreme caution in interpreting estimates of variant Creutzfeldt–Jakob disease epidemic size utilizing existing epidemiological models.

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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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Root-yield-1.06 is a major QTL affecting root system architecture (RSA) and other agronomic traits in maize. The effect of this QTL has been evaluated with the development of near isogenic lines (NILs) differing at the QTL position. The objective of this study was to fine map qroot-yield-1.06 by marker-assisted searching for chromosome recombinants in the QTL interval and concurrent root phenotyping in both controlled and field conditions, through successive generations. Complementary approaches such as QTL meta-analysis and RNA-seq were deployed in order to help prioritizing candidate genes within the QTL target region. Using a selected group of genotypes, field based root analysis by ‘shovelomics’ enabled to accurately collect RSA information of adult maize plants. Shovelomics combined with software-assisted root imaging analysis proved to be an informative and relatively highly automated phenotyping protocol. A QTL interval mapping was conducted using a segregating population at the seedling stage grown in controlled environment. Results enabled to narrow down the QTL interval and to identify new polymorphic markers for MAS in field experiments. A collection of homozygous recombinant NILs was developed by screening segregating populations with markers flanking qroot-yield-1.06. A first set of lines from this collection was phenotyped based on the adapted shovelomics protocol. QTL analysis based on these data highlighted an interval of 1.3 Mb as completely linked with the target QTL but, a larger safer interval of 4.1 Mb was selected for further investigations. QTL meta-analysis allows to synthetize information on root QTLs and two mQTLs were identified in the qroot-yield-1.06 interval. Trascriptomics analysis based on RNA-seq data of the two contrasting QTL-NILs, confirmed alternative haplotypes at chromosome bin 1.06. qroot-yield-1.06 has now been delimited to a 4.1-Mb interval, and thanks to the availability of additional untested homozygous recombinant NILs, the potentially achievable mapping resolution at qroot-yield-1.06 is c. 50 kb.

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In this work the problem of performing a numerical simulation of quasi-static crack propagation within an adhesive layer of a bonded joint under Mode I loading affected by stress field changes due to thermal-chemical shrinkage induced by cure process is addressed. Secondly, a parametric study on fracture critical energy, cohesive strength and Young's modulus is performed. Finally, a particular case of adhesive layer stiffening is simulated in order to verify qualitatively the major effect.

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The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.