943 resultados para Quantitative trait locus (QTL)


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Submergence stress regularly affects 15 million hectares or more of rainfed lowland rice areas in South and Southeast Asia. A major QTL on chromosome 9, Sub1, has provided the opportunity to apply marker assisted backcrossing (MAB) to develop submergence tolerant versions of rice cultivars that are widely grown in the region. In the present study, molecular markers that were tightly linked with Sub1, flanking Sub1, and unlinked to Sub1 were used to apply foreground, recombinant, and background selection, respectively, in backcrosses between a submergence-tolerant donor and the widely grown recurrent parent Swarna. By the BC2F2 generation a submergence tolerant plant was identified that possessed Swarna type simple sequence repeat (SSR) alleles on all fragments analyzed except the tip segment of rice chromosome 9 that possessed the Sub1 locus. A BC3F2 double recombinant plant was identified that was homozygous for all Swarna type alleles except for an approximately 2.3-3.4 Mb region surrounding the Sub1 locus. The results showed that the mega variety Swarna could be efficiently converted to a submergence tolerant variety in three backcross generations, involving a time of two to three years. Polymorphic markers for foreground and recombinant selection were identified for four other mega varieties to develop a wider range of submergence tolerant varieties to meet the needs of farmers in the flood-prone regions. This approach demonstrates the effective use of marker assisted selection for a major QTL in a molecular breeding program.

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While the genetic control of wheat processing characteristics such as dough rheology is well understood, limited information is available concerning the genetic control of baking parameters, particularly sponge and dough (S&D) baking. In this study, a quantitative trait loci (QTL) analysis was performed using a population of doubled haploid lines derived from a cross between Australian cultivars Kukri x Janz grown at sites across different Australian wheat production zones (Queensland in 2001 and 2002 and Southern and Northern New South Wales in 2003) in order to examine the genetic control of protein content, protein expression, dough rheology and sponge and dough baking performance. The study highlighted the inconsistent genetic control of protein content across the test sites, with only two loci (3A and 7A) showing QTL at three of the five sites. Dough rheology QTL were highly consistent across the 5 sites, with major effects associated with the Glu-B1 and Glu-D1 loci. The Glu-D1 5 + 10 allele had consistent effects on S&D properties across sites; however, there was no evidence for a positive effect of the high dough strength Glu-B1-al allele at Glu-B1. A second locus on 5D had positive effects on S&D baking at three of five sites. This study demonstrated that dough rheology measurements were poor predictors of S&D quality. In the absence of robust predictive tests, high heritability values for S&D demonstrate that direct selection is the current best option for achieving genetic gain in this product category.

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QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.

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The Juvenile Wood Initiative (JWI) project has been running successfully since July 2003 under a Research Agreement with FWPA and Letters of Association with the consortium partners STBA (Southern Tree Breeding Association), ArborGen and FPQ (Forestry Plantations Queensland). Over the last five and half years, JWI scientists in CSIRO, FPQ, and STBA have completed all 12 major milestones and 28 component milestones according to the project schedule. We have made benchmark progress in understanding the genetic control of wood formation and interrelationships among wood traits. The project has made 15 primary scientific findings and several results have been adopted by industry as summarized below. This progress was detailed in 10 technical reports to funding organizations and industry clients. Team scientists produced 16 scientific manuscripts (8 published, 1 in press, 2 submitted, and several others in the process of submission) and 15 conference papers or presentations. Primary Scientific Findings. The 15 major scientific findings related to wood science, inheritance and the genetic basis of juvenile wood traits are: 1. An optimal method to predict stiffness of standing trees in slash/Caribbean pine is to combine gravimetric basic density from 12 mm increment cores with a standing tree prediction of MoE using a time of flight acoustic tool. This was the most accurate and cheapest way to rank trees for breeding selection for slash/Caribbean hybrid pine. This method was also recommended for radiata pine. 2. Wood density breeding values were predicted for the first time in the STBA breeding population using a large sample of 7,078 trees (increment cores) and it was estimated that selection of the best 250 trees for deployment will produce wood density gains of 12.4%. 3. Large genetic variation for a suite of wood quality traits including density, MFA, spiral grain, shrinkage, acoustic and non-acoustic stiffness (MoE) for clear wood and standing trees were observed. Genetic gains of between 8 and 49% were predicted for these wood quality traits with selection intensity between 1 to 10% for radiata pine. 4. Site had a major effect on juvenile-mature wood transition age and the effect of selective breeding for a shorter juvenile wood formation phase was only moderate (about 10% genetic gain with 10% selection intensity, equivalent to about 2 years reduction of juvenile wood). 5. The study found no usable site by genotype interactions for the wood quality traits of density, MFA and MoE for both radiata and slash/Caribbean pines, suggesting that assessment of wood properties on one or two sites will provide reliable estimates of the genetic worth of individuals for use in future breeding. 6. There were significant and sizable genotype by environment interactions between the mainland and Tasmanian regions and within Tasmania for DBH and branch size. 7. Strong genetic correlations between rings for density, MFA and MoE for both radiata and slash/Caribbean pines were observed. This suggests that selection for improved wood properties in the innermost rings would also result in improvement of wood properties in the subsequent rings, as well as improved average performance of the entire core. 8. Strong genetic correlations between pure species and hybrid performance for each of the wood quality traits were observed in the hybrid pines. Parental performance can be used to identify the hybrid families which are most likely to have superior juvenile wood properties of the slash/Caribbean F1 hybrid in southeast Queensland. 9. Large unfavourable genetic correlations between growth and wood quality traits were a prominent feature in radiata pine, indicating that overcoming this unfavourable genetic correlation will be a major technical issue in progressing radiata pine breeding. 10. The project created the first radiata pine 18 k cDNA microarray and generated 5,952 radiata pine xylogenesis expressed sequence tags (ESTs) which assembled into 3,304 unigenes. 11. A total of 348 genes were identified as preferentially expressed genes in earlywood or latewood while a total of 168 genes were identified as preferentially expressed genes in either juvenile or mature wood. 12. Juvenile earlywood has a distinct transcriptome relative to other stages of wood development. 13. Discovered rapid decay of linkage disequilibrium (LD) in radiata pine with LD decaying to approximately 50% within 1,700 base pairs (within a typical gene). A total of 913 SNPS from sequencing 177,380 base pairs were identified for association genetic studies. 14. 149 SNPs from 44 genes and 255 SNPs from a further 51 genes (total 95 genes) were selected for association analysis with 62 wood traits, and 30 SNPs were shortlisted for their significant association with variation of wood quality traits (density, MFA and MoE) with individual significant SNPs accounting for between 1.9 and 9.7% of the total genetic variation in traits. 15. Index selection using breeding objectives was the most profitable selection method for radiata pine, but in the long term it may not be the most effective in dealing with negative genetic correlations between wood volume and quality traits. A combination of economic and biological approaches may be needed to deal with the strong adverse correlation.

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BACKGROUND Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. METHODS Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. RESULTS No findings reached genome-wide significance (p = 8.4 x 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 x 10(-7). Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. CONCLUSIONS We conclude that: - 1) meta-analyses of consumption data may contribute usefully to gene discovery; - 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging, and; - 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).

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Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

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Root architecture traits in wheat are important in deep soil moisture acquisition and may be used to improve adaptation to water-limited environments. The genetic architecture of two root traits, seminal root angle and seminal root number, were investigated using a doubled haploid population derived from SeriM82 and Hartog. Multiple novel quantitative trait loci (QTL) were identified, each one having a modest effect. For seminal root angle, four QTL (-log10(P) >3) were identified on 2A, 3D, 6A and 6B, and two suggestive QTL (-log10(P) >2) on 5D and 6B. For root number, two QTL were identified on 4A and 6A with four suggestive QTL on 1B, 3A, 3B and 4A. QTL for root angle and root number did not co-locate. Transgressive segregation was found for both traits. Known major height and phenology loci appear to have little effect on root angle and number. Presence or absence of the T1BL.1RS translocation did not significantly influence root angle. Broad sense heritability (h 2) was estimated as 50 % for root angle and 31 % for root number. Root angle QTL were found to be segregating between wheat cultivars adapted to the target production region indicating potential to select for root angle in breeding programs. © 2013 Springer-Verlag Berlin Heidelberg.

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Grain dormancy provides protection against pre-harvest sprouting (PHS) in cereals. Composite interval mapping and association analyses were performed to identify quantitative trait loci (QTL) contributing grain dormancy in a doubled haploid (DH) barley population (ND24260 x Flagship) consisting of 321 lines genotyped with DArT markers. Harvest-ripe grain collected from three field experiments was germinated over a 7-day period to determine a weighted germination index for each line. DH lines displaying moderate to high levels of grain dormancy were identified; however, both parental lines were non-dormant and displayed rapid germination within the first two days of testing. Genetic analysis identified two QTL on chromosome 5H that were expressed consistently in each of the three environments. One QTL (donated by Flagship) was located close to the centromeric region of chromosome 5H (qSDFlag), accounting for up to 15% of the phenotypic variation. A second QTL with a larger effect (from ND24260) was detected on chromosome 5HL (qSDND), accounting for up to 35% of the phenotypic variation. qSDFlag and qSDND displayed an epistatic interaction and DH lines that had the highest levels of grain dormancy carried both genes. We demonstrate that qSDND in the ND24260 9 Flagship DH population is positioned proximal and independent to the well-characterised SD2 region that is associated with both high levels of dormancy and inferior malt quality. This indicates that it should be possible to develop cultivars that combine acceptable malting quality and adequate levels of grain dormancy for protection against PHS by utilizing these alternate QTL.

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Barley (Hordeum vulgare) is a major feed source for the intensive livestock industry. Competitiveness against other cereal grains depends largely on the price per unit of expressed feed quality. The traits which contribute to feed quality in barley are largely quantitative in nature but little is known about their genetic control. A study to identify the quantitative trait loci (QTLs) associated with feed quality was performed using a F6-derived recombinant inbred barley population. Samples from each line were incubated in the rumen of fistulated cattle, recovered, washed and dried for determination of in situ dry matter digestibility. Additionally, both pre- and post-digestion samples were analysed to quantify the content of key quality components relating to acid detergent fibre, total starch and protein. The data was used to identify trait-associated QTLs. Genetic analysis identified significant QTLs on chromosomes 2H, 5H and 7H. Genetic markers linked to these QTL should provide an effective tool for the selection and improvement of feed barley in the future.

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The goal of this research is to understand the function of allelic variation of genes underpinning the stay-green drought adaptation trait in sorghum in order to enhance yield in water-limited environments. Stay-green, a delayed leaf senescence phenotype in sorghum, is primarily an emergent consequence of the improved balance between the supply and demand of water. Positional and functional fine-mapping of candidate genes associated with stay-green in sorghum is the focus of an international research partnership between Australian (UQ/DAFFQ) and US (Texas A&M University) scientists. Stay-green was initially mapped to four chromosomal regions (Stg1, Stg2, Stg3, and Stg4) by a number of research groups in the US and Australia. Physiological dissection of near-isolines containing single introgressions of Stg QTL (Stg1-4) indicate that these QTL reduce water demand before flowering by constricting the size of the canopy, thereby increasing water availability during grain filling and, ultimately, grain yield. Stg and root angle QTL are also co-located and, together with crop water use data, suggest the role of roots in the stay-green phenomenon. Candidate genes have been identified in Stg1-4, including genes from the PIN family of auxin efflux carriers in Stg1 and Stg2, with 10 of 11 PIN genes in sorghum co-locating with Stg QTL. Modified gene expression in some of these PIN candidates in the stay-green compared with the senescent types has been found in preliminary RNA expression profiling studies. Further proof-of-function studies are underway, including comparative genomics, SNP analysis to assess diversity at candidate genes, reverse genetics and transformation.

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Although it has recently been shown that A/J mice are highly susceptible to Staphylococcus aureus sepsis as compared to C57BL/6J, the specific genes responsible for this differential phenotype are unknown. Using chromosome substitution strains (CSS), we found that loci on chromosomes 8, 11, and 18 influence susceptibility to S. aureus sepsis in A/J mice. We then used two candidate gene selection strategies to identify genes on these three chromosomes associated with S. aureus susceptibility, and targeted genes identified by both gene selection strategies. First, we used whole genome transcription profiling to identify 191 (56 on chr. 8, 100 on chr. 11, and 35 on chr. 18) genes on our three chromosomes of interest that are differentially expressed between S. aureus-infected A/J and C57BL/6J. Second, we identified two significant quantitative trait loci (QTL) for survival post-infection on chr. 18 using N(2) backcross mice (F(1) [C18A]xC57BL/6J). Ten genes on chr. 18 (March3, Cep120, Chmp1b, Dcp2, Dtwd2, Isoc1, Lman1, Spire1, Tnfaip8, and Seh1l) mapped to the two significant QTL regions and were also identified by the expression array selection strategy. Using real-time PCR, 6 of these 10 genes (Chmp1b, Dtwd2, Isoc1, Lman1, Tnfaip8, and Seh1l) showed significantly different expression levels between S. aureus-infected A/J and C57BL/6J. For two (Tnfaip8 and Seh1l) of these 6 genes, siRNA-mediated knockdown of gene expression in S. aureus-challenged RAW264.7 macrophages induced significant changes in the cytokine response (IL-1 beta and GM-CSF) compared to negative controls. These cytokine response changes were consistent with those seen in S. aureus-challenged peritoneal macrophages from CSS 18 mice (which contain A/J chromosome 18 but are otherwise C57BL/6J), but not C57BL/6J mice. These findings suggest that two genes, Tnfaip8 and Seh1l, may contribute to susceptibility to S. aureus in A/J mice, and represent promising candidates for human genetic susceptibility studies.

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BACKGROUND:

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

RESULTS:

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

CONCLUSION:

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.

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Les traits quantitatifs complexes sont des caractéristiques mesurables d’organismes vivants qui résultent de l’interaction entre plusieurs gènes et facteurs environnementaux. Les locus génétiques liés à un caractère complexe sont appelés «locus de traits quantitatifs » (QTL). Récemment, en considérant les niveaux d’expression tissulaire de milliers de gènes comme des traits quantitatifs, il est devenu possible de détecter des «QTLs d’expression» (eQTL). Alors que ces derniers ont été considérés comme des phénotypes intermédiaires permettant de mieux comprendre l’architecture biologique des traits complexes, la majorité des études visent encore à identifier une mutation causale dans un seul gène. Cette approche ne peut remporter du succès que dans les situations où le gène incriminé a un effet majeur sur le trait complexe, et ne permet donc pas d’élucider les situations où les traits complexes résultent d’interactions entre divers gènes. Cette thèse propose une approche plus globale pour : 1) tenir compte des multiples interactions possibles entre gènes pour la détection de eQTLs et 2) considérer comment des polymorphismes affectant l’expression de plusieurs gènes au sein de groupes de co-expression pourraient contribuer à des caractères quantitatifs complexes. Nos contributions sont les suivantes : Nous avons développé un outil informatique utilisant des méthodes d’analyse multivariées pour détecter des eQTLs et avons montré que cet outil augmente la sensibilité de détection d’une classe particulière de eQTLs. Sur la base d’analyses de données d’expression de gènes dans des tissus de souris recombinantes consanguines, nous avons montré que certains polymorphismes peuvent affecter l’expression de plusieurs gènes au sein de domaines géniques de co-expression. En combinant des études de détection de eQTLs avec des techniques d’analyse de réseaux de co-expression de gènes dans des souches de souris recombinantes consanguines, nous avons montré qu’un locus génétique pouvait être lié à la fois à l’expression de plusieurs gènes au niveau d’un domaine génique de co-expression et à un trait complexe particulier (c.-à-d. la masse du ventricule cardiaque gauche). Au total, nos études nous ont permis de détecter plusieurs mécanismes par lesquels des polymorphismes génétiques peuvent être liés à l’expression de plusieurs gènes, ces derniers pouvant eux-mêmes être liés à des traits quantitatifs complexes.

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Platelet response to activation varies widely between individuals but shows interindividual consistency and strong heritability. The genetic basis of this variation has not been properly explored. We therefore systematically measured the effect on function of sequence variation in 97 candidate genes in the collagen and adenosine-diphosphate (ADP) signaling pathways. Resequencing of the genes in 48 European DNA samples nearly doubled the number of known single nucleotide polymorphisms (SNPs) and informed the selection of 1327 SNPs for genotyping in 500 healthy Northern European subjects with known platelet responses to collagen-related peptide (CRP-XL) and ADP. This identified 17 novel associations with platelet function (P < .005) accounting for approximately 46% of the variation in response. Further investigations with platelets of known genotype explored the mechanisms behind some of the associations. SNPs in PEAR1 associated with increased platelet response to CRP-XL and increased PEAR1 protein expression after platelet degranulation. The minor allele of a 3' untranslated region (UTR) SNP (rs2769668) in VAV3 was associated with higher protein expression (P = .03) and increased P-selectin exposure after ADP activation (P = .004). Furthermore the minor allele of the intronic SNP rs17786144 in ITPR1 modified Ca2+ levels after activation with ADP (P < .004). These data provide novel insights into key hubs within platelet signaling networks.

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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.