955 resultados para QUANTITATIVE TRAIT LOCI


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Interest in chromosome 18 in essential hypertension comes from comparative mapping of rat blood pressure quantitative trait loci (QTL), familial orthostatic hypotensive syndrome studies, and essential hypertension pedigree linkage analyses indicating that a locus or loci on human chromosome 18 may play a role in hypertension development. To further investigate involvement of chromosome 18 in human essential hypertension, the present study utilized a linkage scan approach to genotype twelve microsatellite markers spanning human chromosome 18 in 177 Australian Caucasian hypertensive (HT) sibling pairs. Linkage analysis showed significant excess allele sharing of the D18S61 marker when analyzed with SPLINK (P=0.00012), ANALYZE (Sibpair) (P=0.0081), and also with MAPMAKER SIBS (P=0.0001). Similarly, the D18S59 marker also showed evidence for excess allele sharing when analyzed with SPLINK (P=0.016), ANALYZE (Sibpair) (P=0.0095), and with MAPMAKER SIBS (P = 0.014). The adenylate cyclase activating polypeptide 1 gene (ADCYAP1) is involved in vasodilation and has been co-localized to the D18S59 marker. Results testing a microsatellite marker in the 3′ untranslated region of ADCYAP1 in age and gender matched HT and normotensive (NT) individuals showed possible association with hypertension (P = 0.038; Monte Carlo P = 0.02), but not with obesity. The present study shows a chromosome 18 role in essential hypertension and indicates that the genomic region near the ADCYAP1 gene or perhaps the gene itself may be implicated. Further investigation is required to conclusively determine the extent to which ADCYAP1 polymorphisms are involved in essential hypertension. © 2003 Wiley-Liss, Inc.

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Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

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Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

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To discover quantitative trait loci for intraocular pressure, amajor risk factor for glaucoma and the only modifiable one,weperformed agenome-wide association studyonadiscoverycohort of2175individualsfromSydney, Australia. We found a novel association between intraocular pressure and a common variant at 7p21 near to GLCCI1 and ICA1. The findings in this region were confirmed through two UK replication cohorts totalling 4866 individuals (rs59072263, Pcombined = 1.10 × 10-8). A copy of the G allele at this SNP is associated with an increase in mean IOP of 0.45 mmHg (95%CI = 0.30-0.61 mmHg). These results lend support to the implication of vesicle trafficking and glucocorticoid inducibility pathways in the determination of intraocular pressure and in the pathogenesis of primary open-angle glaucoma.

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Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap. © 2013 Macmillan Publishers Limited. All rights reserved.

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As part of a comparative mapping study between sugarcane and sorghum, a sugarcane cDNA clone with homology to the maize Rp1-D rust resistance gene was mapped in sorghum. The cDNA probe hybridised to multiple loci, including one on sorghum linkage group (LG) E in a region where a major rust resistance QTL had been previously mapped. Partial sorghum Rp1-D homologues were isolated from genomic DNA of rust-resistant and -susceptible progeny selected from a sorghum mapping population. Sequencing of the Rp1-D homologues revealed five discrete sequence classes: three from resistant progeny and two from susceptible progeny. PCR primers specific to each sequence class were used to amplify products from the progeny and confirmed that the five sequence classes mapped to the same locus on LG E. Cluster analysis of these sorghum sequences and available sugarcane, maize and sorghum Rp1-D homologue sequences showed that the maize Rp1-D sequence and the partial sugarcane Rp1-D homologue were clustered with one of the sorghum resistant progeny sequence classes, while previously published sorghum Rp1-D homologue sequences clustered with the susceptible progeny sequence classes. Full-length sequence information was obtained for one member of a resistant progeny sequence class ( Rp1-SO) and compared with the maize Rp1-D sequence and a previously identified sorghum Rp1 homologue ( Rph1-2). There was considerable similarity between the two sorghum sequences and less similarity between the sorghum and maize sequences. These results suggest a conservation of function and gene sequence homology at the Rp1 loci of maize and sorghum and provide a basis for convenient PCR-based screening tools for putative rust resistance alleles in sorghum.

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A molecular marker-based map of perennial ryegrass (Lolium perenne L.) has been constructed through the use of polymorphisms associated with expressed sequence tags (ESTs). A pair-cross between genotypes from a North African ecotype and the cultivar Aurora was used to generate a two-way pseudo-testcross population. A selection of 157 cDNAs assigned to eight different functional categories associated with agronomically important biological processes was used to detect polymorphic EST–RFLP loci in the F1(NA6 × AU6) population. A comprehensive set of EST–SSR markers was developed from the analysis of 14,767 unigenes, with 310 primer pairs showing efficient amplification and detecting 113 polymorphic loci. Two parental genetic maps were produced: the NA6 genetic map contains 88 EST–RFLP and 71 EST–SSR loci with a total map length of 963 cM, while the AU6 genetic map contains 67 EST–RFLP and 58 EST–SSR loci with a total map length of 757 cM. Bridging loci permitted the alignment of homologous chromosomes between the parental maps, and a sub-set of genomic DNA-derived SSRs was used to relate linkage groups to the perennial ryegrass reference map. Regions of segregation distortion were identified, in some instances in common with other perennial ryegrass maps. The EST-derived marker-based map provides the basis for in silico comparative genetic mapping, as well as the evaluation of co-location between QTLs and functionally associated genetic loci.

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Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloë festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource. They permit the interrogation of 3806 Neotyphodium genes (NchipTM microarray), and 4195 Neotyphodium and 920 Epichloë genes (EndoChipTM microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass–symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloë was performed

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Barley hull plays an important role in malt and feed quality and processing. In this study we measured the variation in hull con-tent along with other grain quality traits namely, kernel discolouration and degree of pre-harvest sprouting, in a single map-ping population. There were significant (p < 0.05) genetic as well as environment effects. In addition, heritability was calculated for hull content to be 29% and 47% for two years’ data. From the analysis, major QTL markers were identified in con-trolling the expression of hull content on chromosomes 2 (2H), and 6 (6H) with significant (P < 0.05) LOD scores of 5.4 and 3.46 respectively. Minor QTLs were identified on 1 (7H), 4 (4H), 5 (1H) and 7 (5H). The region at marker Bmac310 on 4(4H) could be associated with dormancy gene SD4. A number of the QTLs also coincided with regions for either kernel discolouration or preharvest sprouting resistance (dormancy). The results indicate that variation exists for hull content, which is influenced by both growing environment as well as genetically, although the genetic variance explained less than half of the total variance. Further, hull content also impacts on other grain quality attributes including dormancy, sprouting resistance and kernel appearance.

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In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.

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The aim of the pedigree-based genome mapping project is to investigate and develop systems for implementing marker assisted selection to improve the efficiency of selection and increase the rate of genetic gain in breeding programs. Pedigree-based whole genome marker application provides a vehicle for incorporating marker technologies into applied breeding programs by bridging the gap between marker-trait association and marker implementation. We report on the development of protocols for implementation of pedigree-based whole genome marker analysis in breeding programs within the Australian northern winter cereals region. Examples of applications from the Queensland DPI&F wheat and barley breeding programs are provided, commenting on the use of microsatellites and other types of molecular markers for routine genomic analysis, the integration of genotypic, phenotypic and pedigree information for targeted wheat and barley lines, the genomic impacts of strong selection pressure in case study pedigrees, and directions for future pedigree-based marker development and analysis.

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Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

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Sorghum ergot, caused predominantly by Claviceps africana Frederickson, Mantle, de Milliano, is a significant threat to the sorghum industry worldwide. The objectives of this study were firstly, to identify molecular markers linked to ergot resistance and to two pollen traits, pollen quantity (PQ) and pollen viability (PV), and secondly, to assess the relationship between the two pollen traits and ergot resistance in sorghum. A genetic linkage map of sorghum RIL population R931945-2-2 x IS 8525 (resistance source) was constructed using 303 markers including 36 SSR, 117 AFLP™, 148 DArT™ and two morphological trait loci. Composite interval mapping identified nine, five, and four QTL linked to molecular markers for percentage ergot infection (PCERGOT), PQ and PV, respectively, at a LOD >2.0. Co-location/linkage of QTL were identified on four chromosomes while other QTL for the three traits mapped independently, indicating that both pollen and non pollen-based mechanisms of ergot resistance were operating in this sorghum population. Of the nine QTL identified for PCERGOT, five were identified using the overall data set while four were specific to the group data sets defined by temperature and humidity. QTL identified on SBI-02 and SBI-06 were further validated in additional populations. This is the first report of QTL associated with ergot resistance in sorghum. The markers reported herein could be used for marker-assisted selection for this important disease of sorghum.

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QTL for stem sugar-related and other agronomic traits were identified in a converted sweet (R9188) × grain (R9403463-2-1) sorghum population. QTL analyses were conducted using phenotypic data for 11 traits measured in two field experiments and a genetic map comprising 228 SSR and AFLP markers grouped into 16 linkage groups, of which 11 could be assigned to the 10 sorghum chromosomes (SBI-01 to SBI-10). QTL were identified for all traits and were generally co-located to five locations (SBI-01, SBI-03, SBI-05, SBI-06 and SBI-10). QTL alleles from R9188 were detected for increased sucrose content and sugar content on SBI-01, SBI-05 and SBI-06. R9188 also contributed QTL alleles for increased Brix on SBI-05 and SBI-06, and increased sugar content on SBI-03. QTL alleles from R9403463-2-1 were found for increased sucrose content and sucrose yield on SBI-10, and increased glucose content on SBI-07. QTL alleles for increased height, later flowering and greater total dry matter yield were located on SBI-01 of R9403463-2-1, and SBI-06 of R9188. QTL alleles for increased grain yield from both R9403463-2-1 and R9188 were found on SBI-03. As an increase in stem sugars is an important objective in sweet sorghum breeding, the QTL identified in this study could be further investigated for use in marker-assisted selection of sweet sorghum.

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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 F1 (n=287) and an inbred-like F2 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 F2 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 F1 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.