970 resultados para quantitative trait loci (QTLs)


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In this study, we present a comprehensive 5000-rad radiation hybrid map of a 40-cM region on equine chromosome 4 (ECA4) that contains quantitative trait loci for equine osteochondrosis. We mapped 29 gene-associated sequence tagged site markers using primers designed from equine expressed sequence tags or BAC clones in the ECA4q12-q22 region. Three blocks of conserved synteny, showing two chromosomal breakpoints, were identified in the segment of ECA4q12-q22. Markers from other segments of HSA7q mapped to ECA13p and ECA4p, and a region of HSA7p was homologous to ECA13p. Therefore, we have improved the resolution of the human-equine comparative map, which allows the identification of candidate genes underlying traits of interest.

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This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

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Mastitis is the most prevalent infectious disease in dairy herds. Breeding programs considering mastitis susceptibility were adopted as approaches to improve udder health status. In recent decades, conventional selection criteria based on phenotypic characteristics such as somatic cell score in milk have been widely used to select animals. Recently, approaches to incorporate molecular information have become feasible because of the detection of quantitative trait loci (QTL) affecting mastitis resistance. The aims of the study were to explore molecular mechanisms underlying mastitis resistance and the genetic mechanisms underlying a QTL on Bos taurus chromosome 18 found to influence udder health. Primary cell cultures of mammary epithelial cells from heifers that were selected for high or low susceptibility to mastitis were established. Selection based on estimated pedigree breeding value or on the basis of marker-assisted selection using QTL information was implemented. The mRNA expression of 10 key molecules of the innate immune system was measured using quantitative real-time PCR after 1, 6, and 24 h of challenge with heat-inactivated mastitis pathogens (Escherichia coli and Staphylococcus aureus) and expression levels in the high and low susceptibility groups were compared according to selection criteria. In the marker-assisted selection groups, mRNA expression in cells isolated from less-susceptible animals was significantly elevated for toll-like receptor 2, tumor necrosis factor-alpha, IL-1beta, IL-6, IL-8, RANTES (regulated upon activation, normal t-cell expressed and secreted), complement factor C3, and lactoferrin. In the estimated pedigree breeding value groups, mRNA expression was significantly elevated only for V-rel reticuloendotheliosis viral oncogene homolog A, IL-1 beta, and RANTES. These observations provide first insights into genetically determined divergent reactions to pathogens in the bovine mammary gland and indicate that the application of QTL information could be a successful tool for the selection of animals resistant to mastitis.

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A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

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Animal-mediated pollination is essential in the reproductive biology of many flowering plants and tends to be associated with pollination syndromes, sets of floral traits that are adapted to particular groups of pollinators. The complexity and functional convergence of various traits within pollination syndromes are outstanding examples of biological adaptation, raising questions about their mechanisms and origins. In the genus Petunia, complex pollination syndromes are found for nocturnal hawkmoths (P. axillaris) and diurnal bees (P. integrifolia), with characteristic differences in petal color, corolla shape, reproductive organ morphology, nectar quantity, nectar quality, and fragrance. We dissected the Petunia syndromes into their most important phenotypic and genetic components. They appear to include several distinct differences, such as cell-growth and cell-division patterns in the basal third of the petals, elongation of the ventral stamens, nectar secretion and nectar sugar metabolism, and enzymatic differentiation in the phenylpropanoid pathway. In backcross-inbred lines of species-derived chromosome segments in a transposon tagging strain of P. hybrida, one to five quantitative trait loci were identified for each syndrome component. Two loci for stamen elongation and nectar volume were confirmed in introgression lines and showed large allelic differences. The combined data provide a framework for a detailed understanding of floral syndromes from their developmental and molecular basis to their impact on animal behavior. With its molecular genetic tools, this Petunia system provides a novel venue for a pattern of adaptive radiation that is among the most characteristic of flowering plants.

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The identification of quantitative trait loci (QTL) such as height and their underlying causative variants is still challenging and often requires large sample sizes. In humans hundreds of loci with small effects control the heritable portion of height variability. In domestic animals, typically only a few loci with comparatively large effects explain a major fraction of the heritability. We investigated height at withers in Shetland ponies and mapped a QTL to ECA 6 by genome-wide association (GWAS) using a small cohort of only 48 animals and the Illumina equine SNP70 BeadChip. Fine-mapping revealed a shared haplotype block of 793 kb in small Shetland ponies. The HMGA2 gene, known to be associated with height in horses and many other species, was located in the associated haplotype. After closing a gap in the equine reference genome we identified a non-synonymous variant in the first exon of HMGA2 in small Shetland ponies. The variant was predicted to affect the functionally important first AT-hook DNA binding domain of the HMGA2 protein (c.83G>A; p.G28E). We assessed the functional impact and found impaired DNA binding of a peptide with the mutant sequence in an electrophoretic mobility shift assay. This suggests that the HMGA2 variant also affects DNA binding in vivo and thus leads to reduced growth and a smaller stature in Shetland ponies. The identified HMGA2 variant also segregates in several other pony breeds but was not found in regular-sized horse breeds. We therefore conclude that we identified a quantitative trait nucleotide for height in horses.

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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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Ecological speciation is the process by which reproductively isolated populations emerge as a consequence of divergent natural or ecologically-mediated sexual selection. Most genomic studies of ecological speciation have investigated allopatric populations, making it difficult to infer reproductive isolation. The few studies on sympatric ecotypes have focused on advanced stages of the speciation process after thousands of generations of divergence. As a consequence, we still do not know what genomic signatures of the early onset of ecological speciation look like. Here, we examined genomic differentiation among migratory lake and resident stream ecotypes of threespine stickleback reproducing in sympatry in one stream, and in parapatry in another stream. Importantly, these ecotypes started diverging less than 150 years ago. We obtained 34,756 SNPs with restriction-site associated DNA sequencing and identified genomic islands of differentiation using a Hidden Markov Model approach. Consistent with incipient ecological speciation, we found significant genomic differentiation between ecotypes both in sympatry and parapatry. Of 19 islands of differentiation resisting gene flow in sympatry, all were also differentiated in parapatry and were thus likely driven by divergent selection among habitats. These islands clustered in quantitative trait loci controlling divergent traits among the ecotypes, many of them concentrated in one region with low to intermediate recombination. Our findings suggest that adaptive genomic differentiation at many genetic loci can arise and persist in sympatry at the very early stage of ecotype divergence, and that the genomic architecture of adaptation may facilitate this.

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Pulmonary fibrosis (PF) is the result of a variety of environmental and cancer treatment related insults and is characterized by excessive deposition of collagen. Gas exchange in the alveoli is impaired as the normal lung becomes dense and collapsed leading to a loss of lung volume. It is now accepted that lung injury and fibrosis are in part genetically regulated. ^ Bleomycin is a chemotherapeutic agent used for testicular cancer and lymphomas that induces significant pulmonary toxicity. We delivered bleomycin to mice subcutaneously via a miniosmotic pump in order to elicit lung injury (LI) and quantified the %LI morphometrically using video imaging software. We previously identified a quantitative trait loci, Blmpf-1(LOD=17.4), in the Major Histocompatibility Complex (MHC), but the exact genetic components involved have remained unknown. ^ In the current studies, Blmpf-1 was narrowed to an interval spanning 31.9-32.9Mb on Chromosome 17 using MHC Congenic mice. This region includes the MHC Class II and III genes, and is flanked by the TNF-alpha super locus and MHC Class I genes. Knockout mice of MHC Class I genes (B2mko), MHC Class II genes (Cl2ko), and TNF-alpha (TNF-/-) and its receptors (p55-/-, p75-/-, and p55/p75-/-) were treated with bleomycin in order to ascertain the role of these genes in the pathogenesis of lung injury. ^ Cl2ko mice had significantly better survival and %LI when compared to treated background BL/6 (B6, P<.05). In contrast, B2mko showed no differences in survival or %LI compared to B6. This suggests that the MHC Class II locus contains susceptibility genes for bleomycin-induced lung injury. ^ TNF-alpha, a Class III gene, was examined and it was found that TNF-/- and p55-/- mice had higher %LI and lower survival when compared to B6 (P<.05). In contrast, p75-/- mice had significantly reduced %LI when compared to TNF-/-, p55-/-, and B6 mice as well as higher survival (P<.01). These data contradict the current paradigm that TNF-alpha is a profibrotic mediator of lung injury and suggest a novel and distinct role for the p55 and p75 receptors in mediating lung injury. ^

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Systemic sclerosis (SSc) or Scleroderma is a complex disease and its etiopathogenesis remains unelucidated. Fibrosis in multiple organs is a key feature of SSc and studies have shown that transforming growth factor-β (TGF-β) pathway has a crucial role in fibrotic responses. For a complex disease such as SSc, expression quantitative trait loci (eQTL) analysis is a powerful tool for identifying genetic variations that affect expression of genes involved in this disease. In this study, a multilevel model is described to perform a multivariate eQTL for identifying genetic variation (SNPs) specifically associated with the expression of three members of TGF-β pathway, CTGF, SPARC and COL3A1. The uniqueness of this model is that all three genes were included in one model, rather than one gene being examined at a time. A protein might contribute to multiple pathways and this approach allows the identification of important genetic variations linked to multiple genes belonging to the same pathway. In this study, 29 SNPs were identified and 16 of them located in known genes. Exploring the roles of these genes in TGF-β regulation will help elucidate the etiology of SSc, which will in turn help to better manage this complex disease. ^

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A mapping F2 population from the cross ‘Piel de Sapo’ × PI124112 was selectively genotyped to study the genetic control of morphological fruit traits by QTL (Quantitative Trait Loci) analysis. Ten QTL were identified, five for FL (Fruit Length), two for FD (Fruit Diameter) and three for FS (Fruit Shape). At least one robust QTL per character was found, flqs8.1 (LOD = 16.85, R2 = 34%), fdqs12.1 (LOD = 3.47, R2 = 11%) and fsqs8.1 (LOD = 14.85, R2 = 41%). flqs2.1 and fsqs2.1 cosegregate with gene a (andromonoecious), responsible for flower sex determination and with pleiotropic effects on FS. They display a positive additive effect (a) value, so the PI124112 allele causes an increase in FL and FS, producing more elongated fruits. Conversely, the negative a value for flqs8.1 and fsqs8.1 indicates a decrease in FL and FS, what results in rounder fruits, even if PI124112 produces very elongated melons. This is explained by a significant epistatic interaction between fsqs2.1 and fsqs8.1, where the effects of the alleles at locus a are attenuated by the additive PI124112 allele at fsqs8.1. Roundest fruits are produced by homozygous for PI124112 at fsqs8.1 that do not carry any dominant A allele at locus a (PiPiaa). A significant interaction between fsqs8.1 and fsqs12.1 was also detected, with the alleles at fsqs12.1 producing more elongated fruits. fsqs8.1 seems to be allelic to QTL discovered in other populations where the exotic alleles produce elongated fruits. This model has been validated in assays with backcross lines along 3 years and ultimately obtaining a fsqs8.1-NIL (Near Isogenic Line) in ‘Piel de Sapo’ background which yields round melons.

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The genomic era revolutionized evolutionary biology. The enigma of genotypic-phenotypic diversity and biodiversity evolution of genes, genomes, phenomes, and biomes, reviewed here, was central in the research program of the Institute of Evolution, University of Haifa, since 1975. We explored the following questions. (i) How much of the genomic and phenomic diversity in nature is adaptive and processed by natural selection? (ii) What is the origin and evolution of adaptation and speciation processes under spatiotemporal variables and stressful macrogeographic and microgeographic environments? We advanced ecological genetics into ecological genomics and analyzed globally ecological, demographic, and life history variables in 1,200 diverse species across life, thousands of populations, and tens of thousands of individuals tested mostly for allozyme and partly for DNA diversity. Likewise, we tested thermal, chemical, climatic, and biotic stresses in several model organisms. Recently, we introduced genetic maps and quantitative trait loci to elucidate the genetic basis of adaptation and speciation. The genome–phenome holistic model was deciphered by the global regressive, progressive, and convergent evolution of subterranean mammals. Our results indicate abundant genotypic and phenotypic diversity in nature. The organization and evolution of molecular and organismal diversity in nature at global, regional, and local scales are nonrandom and structured; display regularities across life; and are positively correlated with, and partly predictable by, abiotic and biotic environmental heterogeneity and stress. Biodiversity evolution, even in small isolated populations, is primarily driven by natural selection, including diversifying, balancing, cyclical, and purifying selective regimes, interacting with, but ultimately overriding, the effects of mutation, migration, and stochasticity.

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Representational difference analysis (RDA) was applied to isolate chromosomal markers in the rat. Four series of RDA [restriction enzymes, BamHI and HindIII; subtraction of ACI/N (ACI) amplicon from BUF/Nac (BUF) amplicon and vice versa] yielded 131 polymorphic markers; 125 of these markers were mapped to all chromosomes except for chromosome X. This was done by using a mapping panel of 105 ACI x BUF F2 rats. To complement the relative paucity of chromosomal markers in the rat, genetically directed RDA, which allows isolation of polymorphic markers in the specific chromosomal region, was performed. By changing the F2 driver-DNA allele frequency around the region, four markers were isolated from the D1Ncc1 locus. Twenty-five of 27 RDA markers were informative regarding the dot blot analysis of amplicons, hybridizing only with tester amplicons. Dot blot analysis at a high density per unit of area made it possible to process a large number of samples. Quantitative trait loci can now be mapped in the rat genome by processing a large number of samples with RDA markers and then by isolating markers close to the loci of interest by genetically directed RDA.

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1. The natriuretic peptide precursor A (Nppa) and B (Nppb) genes are candidate genes for hypertension and cardiac hypertrophy in the spontaneously hypertensive rat (SHR). The purpose of the present study was to determine the role of the Nppa and Nppb genes in the development of hypertension in the SHR. 2. A cohort (n = 162) of F2 segregating intercross animals was established between strains of hypertensive SHR and normotensive Wistar-Kyoto rats. Blood pressure and heart weight were measured in each rat at 12-16 weeks of age. Rats were genotyped using 11 informative microsatellite markers, distributed in the vicinity of the Nppa marker on rat chromosome 5 including an Nppb marker. The phenotype values were compared with genotype using the computer package MAP-MAKER 3.0 (Whitehead Institute, Boston, MA, USA) to determine whether there was a link between the genetic variants of the natriuretic peptide family and blood pressure or cardiac hypertrophy. 3. A strong correlation was observed between the Nppa marker and blood pressure. A quantitative trait locus (QTL) for blood pressure on chromosome 5 was identified between the Nppa locus and the D5Mgh15 marker, less than 2 cM from the Nppa locus. The linkage score for the blood pressure QTL on chromosome 5 was 3.8 and the QTL accounted for 43% of the total variance of systolic blood pressure, 54% of diastolic blood pressure and 59% of mean blood pressure. No association was found between the Nppb gene and blood pressure. This is the first report of linkage between the Nppa marker and blood pressure in the rat. There was no correlation between the Nppa or Nppb genes or other markers in this region and either heart weight or left ventricular weight in F2 rats. 4. These findings suggest the existence of a blood pressure-dependent Nppa marker variant or a gene close to Nppa predisposing to spontaneous hypertension in the rat. It provides a strong foundation for further detailed genetic studies in congenic strains, which may help to narrow down the location of this gene and lead to positional cloning.

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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.