989 resultados para Association mapping


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Association mapping seeks to identify marker alleles present at significantly different frequencies in cases carrying a particular disease or trait compared with controls. Genome-wide association studies are increasingly replacing candidate gene-based association studies for complex diseases, where a number of loci are likely to contribute to disease risk and the effect size of each particular risk allele is typically modest or low. Good study design is essential to the success of an association study, and factors such as the heritability of the disease under investigation, the choice of controls, statistical power, multiple testing and whether the association can be replicated need to be considered before beginning. Likewise, thorough quality control of the genotype data needs to be undertaken prior to running any association analyses. Finally, it should be kept in mind that a significant genetic association is not proof positive that a particular genetic locus causes a disease, but rather an important first step in discovering the genetic variants underlying a complex disease.

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Key message “To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants.” Abstract Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.

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Sk?t, L., Humphreys, M. O., Armstead, I. P., Heywood, S., Sk?t, K. P., Sanderson, R., Thomas, I. D., Chorlton, K. H., & Sackville Hamilton, N. R. (2005). An association mapping approach to identify flowering time genes in natural populations of Lolium perenne (L.). Molecular Breeding, 15(3), 233-245. Sponsorship: BBSRC RAE2008

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The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of,300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.

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Although commonplace in human disease genetics, genome-wide association (GWA) studies have only relatively recently been applied to plants. Using 32 phenotypes in the inbreeding crop barley, we report GWA mapping of 15 morphological traits across ∼500 cultivars genotyped with 1,536 SNPs. In contrast to the majority of human GWA studies, we observe high levels of linkage disequilibrium within and between chromosomes. Despite this, GWA analysis readily detected common alleles of high penetrance. To investigate the potential of combining GWA mapping with comparative analysis to resolve traits to candidate polymorphism level in unsequenced genomes, we fine-mapped a selected phenotype (anthocyanin pigmentation) within a 140-kb interval containing three genes. Of these, resequencing the putative anthocyanin pathway gene HvbHLH1 identified a deletion resulting in a premature stop codon upstream of the basic helix-loop-helix domain, which was diagnostic for lack of anthocyanin in our association and biparental mapping populations. The methodology described here is transferable to species with limited genomic resources, providing a paradigm for reducing the threshold of map-based cloning in unsequenced crops.

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Background: Association mapping, initially developed in human disease genetics, is now being applied to plant species. The model species Arabidopsis provided some of the first examples of association mapping in plants, identifying previously cloned flowering time genes, despite high population sub-structure. More recently, association genetics has been applied to barley, where breeding activity has resulted in a high degree of population sub-structure. A major genotypic division within barley is that between winter- and spring-sown varieties, which differ in their requirement for vernalization to promote subsequent flowering. To date, all attempts to validate association genetics in barley by identifying major flowering time loci that control vernalization requirement (VRN-H1 and VRN-H2) have failed. Here, we validate the use of association genetics in barley by identifying VRN-H1 and VRN-H2, despite their prominent role in determining population sub-structure. Results: By taking barley as a typical inbreeding crop, and seasonal growth habit as a major partitioning phenotype, we develop an association mapping approach which successfully identifies VRN-H1 and VRN-H2, the underlying loci largely responsible for this agronomic division. We find a combination of Structured Association followed by Genomic Control to correct for population structure and inflation of the test statistic, resolved significant associations only with VRN-H1 and the VRN-H2 candidate genes, as well as two genes closely linked to VRN-H1 (HvCSFs1 and HvPHYC). Conclusion: We show that, after employing appropriate statistical methods to correct for population sub-structure, the genome-wide partitioning effect of allelic status at VRN-H1 and VRN-H2 does not result in the high levels of spurious association expected to occur in highly structured samples. Furthermore, we demonstrate that both VRN-H1 and the candidate VRN-H2 genes can be identified using association mapping. Discrimination between intragenic VRN-H1 markers was achieved, indicating that candidate causative polymorphisms may be discerned and prioritised within a larger set of positive associations. This proof of concept study demonstrates the feasibility of association mapping in barley, even within highly structured populations. A major advantage of this method is that it does not require large numbers of genome-wide markers, and is therefore suitable for fine mapping and candidate gene evaluation, especially in species for which large numbers of genetic markers are either unavailable or too costly.

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Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables.

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Understanding the genetic basis of traits involved in adaptation is a major challenge in evolutionary biology but remains poorly understood. Here, we use genome-wide association mapping using a custom 50 k single nucleotide polymorphism (SNP) array in a natural population of collared flycatchers to examine the genetic basis of clutch size, an important life-history trait in many animal species. We found evidence for an association on chromosome 18 where one SNP significant at the genome-wide level explained 3.9% of the phenotypic variance. We also detected two suggestive quantitative trait loci (QTLs) on chromosomes 9 and 26. Fitness differences among genotypes were generally weak and not significant, although there was some indication of a sex-by-genotype interaction for lifetime reproductive success at the suggestive QTL on chromosome 26. This implies that sexual antagonism may play a role in maintaining genetic variation at this QTL. Our findings provide candidate regions for a classic avian life-history trait that will be useful for future studies examining the molecular and cellular function of, as well as evolutionary mechanisms operating at, these loci.

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The aim of this study was to identify candidate genes and genomic regions associated with ultrasound-derived measurements of the rib-eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.

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In wheat, stem rust is known to rapidly evolve new virulence to resistance genes. While more than 50 stem rust resistance (Sr) loci have been identified in wheat, only a few remain effective, particularly against the highly virulent race Ug99 (TTKSK race) and a mixture of durum-specific races. An association mapping (AM) study based on 183 durum wheat accessions was utilized to identify resistance loci for stem rust response in Ethiopia over four seasons and artificial inoculation with Ug99 (TTKSK race) and a mixture of durum-specific races under field conditions as well as in greenhouse test at seedling stage under controlled conditions for resistance to four highly virulent stem rust races: TRTTF, TTTTF, (TTKSK (Ug99) and JRCQC. The panel was profiled with 1,253 SSR and DArT markers. Twelve QTL-tagging markers were significant (P < 0.05) across three to four seasons. The role of Sr13, Sr9, Sr14, Sr17, and Sr28 was confirmed. Thirteen significant markers were in regions with no Sr genes/QTLs. The results under controlled conditions showed that 15, 20, 19 and 19 chromosome regions harbored markers that showed significant effects for races TRTTF, TTTTF, TTKSK and JRCQC, respectively. These genomic regions showed marker R2 values ranging from 1.13 to 8.34, 1.92 to 17.64, 1.75 to 23.12 and 1.51 to 15.33% for races TRTTF, TTTTF, TTKSK and JRCQC, respectively. The study demonstrates that stem rust resistance in durum wheat is governed in part by shared loci and in part by race-specific ones. The QTLs identified in this study through AM will be useful in the marker-assisted development of durum wheat cultivars with durable stem rust resistance.

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Cauliflower (Brassica oleracea var. botrytis) is a vernalization-responsive crop. High ambient temperatures delay harvest time. The elucidation of the genetic regulation of floral transition is highly interesting for a precise harvest scheduling and to ensure stable market supply. This study aims at genetic dissection of temperature-dependent curd induction in cauliflower by genome-wide association studies and gene expression analysis. To assess temperature dependent curd induction, two greenhouse trials under distinct temperature regimes were conducted on a diversity panel consisting of 111 cauliflower commercial parent lines, genotyped with 14,385 SNPs. Broad phenotypic variation and high heritability (0.93) were observed for temperature-related curd induction within the cauliflower population. GWA mapping identified a total of 18 QTL localized on chromosomes O1, O2, O3, O4, O6, O8, and O9 for curding time under two distinct temperature regimes. Among those, several QTL are localized within regions of promising candidate flowering genes. Inferring population structure and genetic relatedness among the diversity set assigned three main genetic clusters. Linkage disequilibrium (LD) patterns estimated global LD extent of r(2) = 0.06 and a maximum physical distance of 400 kb for genetic linkage. Transcriptional profiling of flowering genes FLOWERING LOCUS C (BoFLC) and VERNALIZATION 2 (BoVRN2) was performed, showing increased expression levels of BoVRN2 in genotypes with faster curding. However, functional relevance of BoVRN2 and BoFLC2 could not consistently be supported, which probably suggests to act facultative and/or might evidence for BoVRN2/BoFLC-independent mechanisms in temperature regulated floral transition in cauliflower. Genetic insights in temperature-regulated curd induction can underpin genetically informed phenology models and benefit molecular breeding strategies toward the development of thermo-tolerant cultivars.

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Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.