944 resultados para quantitative trait loci (QTL)


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Key message We have identified QTLs for stomatal characteristics on chromosome II of faba bean by applying SNPs derived from M. truncatula , and have identified candidate genes within these QTLs using synteny between the two species. Abstract Faba bean (Vicia faba L.) is a valuable food and feed crop worldwide, but drought often limits its production, and its genome is large and poorly mapped. No information is available on the effects of genomic regions and genes on drought adaptation characters such as stomatal characteristics in this species, but the synteny between the sequenced model legume, Medicago truncatula, and faba bean can be used to identify candidate genes. A mapping population of 211 F5 recombinant inbred lines (Mélodie/2 × ILB 938/2) were phenotyped to identify quantitative trait loci (QTL) affecting stomatal morphology and function, along with seed weight, under well-watered conditions in a climate-controlled glasshouse in 2013 and 2014. Canopy temperature (CT) was evaluated in 2013 under water-deficit (CTd). In total, 188 polymorphic single nucleotide polymorphisms (SNPs), developed from M. truncatula genome data, were assigned to nine linkage groups that covered ~928 cM of the faba bean genome with an average inter-marker distance of 5.8 cM. 15 putative QTLs were detected, of which eight (affecting stomatal density, length and conductance and CT) co-located on chromosome II, in the vicinity of a possible candidate gene—a receptor-like protein kinase found in the syntenic interval of M. truncatula chromosome IV. A ribose-phosphate pyrophosphokinase from M. truncatula chromosome V, postulated as a possible candidate gene for the QTL for CTd, was found some distance away in the same chromosome. These results demonstrate that genomic information from M. truncatula can successfully be translated to the faba bean genome.

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Background qtl.outbred is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/qtl. Findings Using qtl.outbred, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL. Conclusion qtl.outbred will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.

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This study aimed to detect quantitative trait loci (QTL) by fALP (Fluorescent Amplified Fragment Length Polymorphism) markers associated to the trait tomato fruit set at high temperatures. A biparental cross between line Jab-95 (heat-tolerant) and cultivar Caribe (heat-susceptible) was made. A total of 192 plants of the F2 generation were evaluated, generating 172 polymorphic markers through six primer combinations previously identified by the Bulked Segregant Analysis technique. To construct the genetic map, 106 of the 172 markers that segregated in the expected Mendelian segregation proportion (3:1) were used. The map covered 1191.46 cM of the genome. Six trait-linked QTL were identified in the analysis of simple markers and three others by the interval-mapping methodology. These results could be highly useful in improvement programs, since heat-tolerant plants can be selected rapidly, which improves tomato fruit set.

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

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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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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The identification of quantitative trait loci (QTL) and marker-assisted selection with a view to breeding programs have aroused great interest, including for cashew improvement. This study identified QTL for yield-related traits: nut weight, male and hermaphrodite flowers. The traits were evaluated in 71 F-1 genotypes of the cross CCP 1001 x CP 96. The methods of interval mapping and multiple QTL mapping were applied to identify QTL. Eleven QTL were detected: three for nut weight, four for male flowers and four for hermaphrodite flowers. The QTL accounted for 3.79 to 12.98 % of the total phenotypic variance and had phenotypic effects of -31.81 to 34.25 %. The potential for marker-assisted selection of the QTL hf-2f and hf-3m is great and the phenotypic effects and percentage of phenotypic variation higher than of the others.

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Multiparental cross designs for mapping quantitative trait loci (QTL) in crops are efficient alternatives to conventional biparental experimental populations because they exploit a broader genetic basis and higher mapping resolution. We describe the development and deployment of a multiparental recombinant inbred line (RIL) population in durum wheat (Triticum durum Desf.) obtained by crossing four elite cultivars characterized by different traits of agronomic value. A linkage map spanning 2,663 cM and including 7,594 single nucleotide polymorphisms (SNPs) was produced by genotyping 338 RILs with a wheat-dedicated 90k SNP chip. A cluster file was developed for correct allele calling in the framework of the tetraploid durum wheat genome. Based on phenotypic data collected over four field experiments, a multi-trait quantitative trait loci (QTL) analysis was carried out for 18 traits of agronomic relevance (including yield, yield-components, morpho-physiological and seed quality traits). Across environments, a total of 63 QTL were identified and characterized in terms of the four founder haplotypes. We mapped two QTL for grain yield across environments and 23 QTL for grain yield components. A novel major QTL for number of grain per spikelet/ear was mapped on chr 2A and shown to control up to 39% of phenotypic variance in this cross. Functionally different QTL alleles, in terms of direction and size of genetic effect, were distributed among the four parents. Based on the occurrence of QTL-clusters, we characterized the breeding values (in terms of effects on yield) of most of QTL for heading and maturity as well as yield component and quality QTL. This multiparental RIL population provides the wheat community with a highly informative QTL mapping resource enabling the dissection of the genetic architecture of multiple agronomic relevant traits in durum wheat.

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Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings.

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To identify novel quantitative trait loci (QTL) within horses, we performed genome-wide association studies (GWAS) based on sequence-level genotypes for conformation and performance traits in the Franches-Montagnes (FM) horse breed. Sequence-level genotypes of FM horses were derived by re-sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de-regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence-derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data.

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A high-resolution physical and genetic map of a major fruit weight quantitative trait locus (QTL), fw2.2, has been constructed for a region of tomato chromosome 2. Using an F2 nearly isogenic line mapping population (3472 individuals) derived from Lycopersicon esculentum (domesticated tomato) × Lycopersicon pennellii (wild tomato), fw2.2 has been placed near TG91 and TG167, which have an interval distance of 0.13 ± 0.03 centimorgan. The physical distance between TG91 and TG167 was estimated to be ≤ 150 kb by pulsed-field gel electrophoresis of tomato DNA. A physical contig composed of six yeast artificial chromosomes (YACs) and encompassing fw2.2 was isolated. No rearrangements or chimerisms were detected within the YAC contig based on restriction fragment length polymorphism analysis using YAC-end sequences and anchored molecular markers from the high-resolution map. Based on genetic recombination events, fw2.2 could be narrowed down to a region less than 150 kb between molecular markers TG91 and HSF24 and included within two YACs: YAC264 (210 kb) and YAC355 (300 kb). This marks the first time, to our knowledge, that a QTL has been mapped with such precision and delimited to a segment of cloned DNA. The fact that the phenotypic effect of the fw2.2 QTL can be mapped to a small interval suggests that the action of this QTL is likely due to a single gene. The development of the high-resolution genetic map, in combination with the physical YAC contig, suggests that the gene responsible for this QTL and other QTLs in plants can be isolated using a positional cloning strategy. The cloning of fw2.2 will likely lead to a better understanding of the molecular biology of fruit development and to the genetic engineering of fruit size characteristics.

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Weather damage reduces the value of commercial mungbean, but hard-seededness can reduce the level of damage. However, attempts to breed large- and hard-seeded mungbean varieties have been unsuccessful. To understand the relationship between seed weight and hard-seededness, these traits were investigated using a quantitative trait loci (QTL) mapping approach with a recombinant inbred population derived from a cross between a completely soft-seeded variety and a completely hard-seeded genotype. The two parental genotypes also had a sixfold difference in seed weight. QTL analyses revealed four loci for hard-seededness and I I loci for seed weight. Two of the hardseededness loci co-localized with seed weight QTL. When seed weight was used as a covariate in the analysis of hard-seededness from the field data, two of the four hard-seeded QTL remained significant with the effect at one of these remaining unchanged. These results explain why retaining hard-seededness in large seeded mungbean lines has been unsuccessful. The existence of a persistent locus, however, indicated that breeding large and persistently hard-seeded varieties of mungbean may be possible.

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Targeting between-species effects for improvement in synthetic hybrid populations derived from outcrossing parental tree species may be one way to increase the efficacy and predictability of hybrid breeding. We present a comparative analysis of the quantitative trait loci (QTL) which resolved between from within-species effects for adventitious rooting in two populations of hybrids between Pinus elliottii and P. caribaea, an outbred F-1 (n=287) and an inbred-like F-2 family (n=357). Most small to moderate effect QTL (each explaining 2-5% of phenotypic variation, PV) were congruent (3 out of 4 QTL in each family) and therefore considered within-species effects as they segregated in both families. A single large effect QTL (40% PV) was detected uniquely in the F-2 family and assumed to be due to a between-species effect, resulting from a genetic locus with contrasting alleles in each parental species. Oligogenic as opposed to polygenic architecture was supported in both families (60% and 20% PV explained by 4 QTL in the F-2 and F-1 respectively). The importance of adventitious rooting for adaptation to survive water-logged environments was thought in part to explain oligogenic architecture of what is believed to be a complex trait controlled by many hundreds of genes.

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Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.

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The rust Puccinia psidii infects many species in the family Myrtaceae. Native to South America, the pathogen has recently entered Australia which has a rich Myrtaceous flora, including trees of the ecologically and economically important genus Eucalyptus. We studied the genetic basis of variation in rust resistance in Eucalyptus globulus, the main plantation eucalypt in Australia. Quantitative trait loci (QTL) analysis was undertaken using 218 genotypes of an outcross F2 mapping family, phenotyped by controlled inoculation of their open pollinated progeny with the strain of P. psidii found in Australia. QTL analyses were conducted using a binary classification of individuals with no symptoms (immune) versus those with disease symptoms, and in a separate analysis dividing plants with disease symptoms into those exhibiting the hypersensitive response versus those with more severe symptoms. Four QTL were identified, two influencing whether a plant exhibited symptoms (Ppr2 and Ppr3), and two influencing the presence or absence of a hypersensitive reaction (Ppr4 and Ppr5). These QTL mapped to four different linkage groups, none of which overlap with Ppr1, the major QTL previously identified for rust resistance in Eucalyptus grandis. Candidate genes within the QTL regions are presented and possible mechanisms discussed. Together with past findings, our results suggest that P. psidii resistance in eucalypts is quantitative in nature and influenced by the complex interaction of multiple loci of variable effect.