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PubMed2000

Familial aggregation and heritability of asthma-associated quantitative traits in a population-based sample of nuclear families.

Asthma is a common, genetically complex human disease. Elevated serum immunoglobulin E (IgE) levels, elevated blood eosinophil counts, variably reduced spirometric measures and increased airway responsiveness (AR) are physiological traits which are characteristic of asthma. We investigated the genetic and environmental components of variance of serum total and specific IgE levels, blood eosinophil counts, the forced expiratory volume in one second (FEV1) and forced vital capacity (FVC), and AR in an Australian population-based sample of 232 Caucasian nuclear families. With the exception of FVC levels, all traits were closely associated with clinical asthma in this population. Loge total serum IgE levels had a narrow-sense heritability (h2N) of 47.3% (SE = 10. 0%). Specific serum IgE levels against house dust mite and Timothy grass, measured as a RAST Index, had a h2N of 33.8% (SE = 7.3%). FEV1 levels had a h2N of 6.1% (SE = 11.6%), whilst FVC levels had a h2N of 30.6% (SE = 26.8%). AR, quantified by the loge dose-response slope to methacholine (DRS), had a h2N of 30.3% (SE = 12.3%). These data are consistent with the existence of important genetic determinants of the pathophysiological traits associated with asthma. Our study suggests that total and specific serum IgE levels, blood eosinophil counts and airways responsiveness to inhaled agonist are appropriate phenotypes for molecular investigations of the genetic susceptibility to asthma.

Adolescent↗
PubMed2004

Genome-wide scans reveal quantitative trait Loci on 8p and 13q related to insulin action and glucose metabolism: the San Antonio Family Heart Study.

Type 2 diabetes is a complex disease that arises from physiological disruptions of the body's sensitivity to insulin and ability to metabolize glucose. Multipoint linkage analyses for insulin sensitivity phenotypes were conducted in 1,280 Mexican Americans from 41 families who participated in the San Antonio Family Heart Study. A significant linkage signal (logarithm of odds [LOD] = 2.98) affecting corrected insulin response to glucose was detected on chromosome 13q between D13787 and D13S252, in the region where the MODY-4 gene has previously been mapped. Another signal on chromosome 13 was observed at D13S285 (LOD = 1.86), where the insulin receptor substrate 2 gene resides. Significant linkage (LOD = 3.09) for insulin response to glucose was found on chromosome 8 between D8S1130 and D8S1106, near the lipoprotein lipase and macrophage scavenger receptor genes. Multipoint analysis of abdominal skinfold with an LOD of 2.68 showed signals in the same region. There was also suggestive evidence for linkage of quantitative insulin sensitivity check index and fasting glucose to a previously reported location at D9S301 (LOD = 2.19). These results indicate that chromosomal locations on 8p and 13q might harbor genes that affect a variety of insulin- and glucose-related phenotypes that contribute to the observed variations in these important risk factors for diabetes in Mexican Americans.

Adult↗
PubMed2007

Effects of genome-wide heterozygosity on a range of biomedically relevant human quantitative traits.

The dramatic changes in human population structure over the last 200 years have resulted in significant levels of outbreeding, which, in turn, is predicted to lead to increased levels of individual genetic diversity (genome-wide heterozygosity, h). To investigate possible effects of these large demographic changes on global health, we studied the effect of h, measured as relative heterozygosity, h(R), on 15 disease-related traits in four groups of individuals with widely differing ancestral histories (ranging from outbred to inbred) from the Dalmatian islands in Croatia. Higher levels of h(R), estimated using 1184 STR/indel markers, were found in the outbred group (P < 0.0001) and were associated with lower blood pressure (BP) and total/LDL cholesterol (P = 0.01 and 0.01, respectively) after controlling for other factors, with BP showing a strong sex effect (males P > 0.5 and females P = 0.002). These findings, if replicated, suggest that h(R) be considered as a genetic risk factor in genetic epidemiological studies on common disease traits. They are consistent with the well-known effects of heterosis (hybrid vigour) described when outcrossing animals and plants. Outbreeding resulting from urbanization and migration from traditional population subgroups may be leading to increasing h(R) and may have beneficial effects on a range of traits associated with human health and disease. Other traits, such as age at menarche, IQ and lifespan, which have been changing during the decades of urbanization, may also have been influenced by demographic factors.

Age Factors↗
PubMed2000

Multitrait least squares for quantitative trait loci detection.

A multiple-trait QTL mapping method using least squares is described. It is presented as an extension of a single-trait method for use with three-generation, outbred pedigrees. The multiple-trait framework allows formal testing of whether the same QTL affects more than one trait (i.e., a pleiotropic QTL) or whether more than one linked QTL are segregating. Several approaches to the testing procedure are presented and their suitability discussed. The performance of the method is investigated by simulation. As previously found, multitrait analyses increase the power to detect a pleiotropic QTL and the precision of its location estimate. With enough information, discrimination between alternative genetic models is possible.

Animals↗
PubMed2002

Scaling to account for heterogeneous variances in a Bayesian analysis of broiler quantitative trait loci.

A Bayesian method for QTL analysis that is capable of accounting for heterogeneity of variance between sexes, is introduced. The Bayesian method uses a parsimonious model that includes scaling parameters for polygenic and QTL allelic effects per sex. Furthermore, the method employs a reduced animal model to increase computational efficiency. Markov Chain Monte Carlo techniques were applied to obtain estimates of genetic parameters. In comparison with previous regression analyses, the Bayesian method 1) estimates dispersion parameters and polygenic effects, 2) uses individual observations instead of offspring averages, and 3) estimates fixed effect levels and covariates and heterogeneity of variance between sexes simultaneously with other parameters, taking uncertainties fully into account. Broiler data collected in a feed efficiency and a carcass experiment were used to illustrate QTL analysis based on the Bayesian method. The experiments were conducted in a population consisting of 10 full-sib families of a cross between two broiler lines. Microsatellite genotypes were determined on generation 1 and 2 animals and phenotypes were collected on third-generation offspring from mating members from different families. Chromosomal regions that seemed to contain a QTL in previous regression analyses and showed heterogeneity of variance were chosen. Traits analyzed in the feed efficiency experiment were BW at 48 d and growth, feed intake, and feed intake corrected for BW between 23 and 48 d. In the carcass experiment, carcass percentage was analyzed. The Bayesian method was successful in finding QTL in all regions previously detected.

Animals↗
PubMed2006

Mapping quantitative trait loci for yield components and morphological traits in an advanced backcross population between Oryza grandiglumis and the O. sativa japonica cultivar Hwaseongbyeo.

Introgression has been achieved from wild species Oryza grandiglumis (2n = 48, CCDD, Acc. No. 101154) into O. sativa subsp. japonica cv. Hwaseongbyeo as a recurrent parent. An advanced introgression (backcross) line, HG101, produced from a single plant from BC5F3 families resembled Hwaseongbyeo, but it showed differences from Hwaseongbyeo in several traits, including days to heading and culm length. To detect the introgressions, 450 microsatellite markers of known chromosomal position were used for the parental survey. Of the 450 markers, 51 (11.3%) detected O. grandiglumis segments in HG101. To characterize the effects of alien genes introgressed into HG101, an F(2:3) population (150 families) from the cross Hwaseongbyeo/HG101 was developed and evaluated for 13 agronomic traits. Several lines outperformed Hwaseongbyeo in several traits, including days to heading. Genotypes were determined for 150 F2 plants using simple sequence repeat markers. Qualitative trait locus (QTL) analysis was carried out to determine the relationship between marker genotype and the traits evaluated. A total of 39 QTL and 1 gene conferring resistance to blast isolate were identified using single-point analysis. Phenotypic variation associated with each QTL ranged from 4.2 to 30.5%. For 18 (46.2%) of the QTL identified in this study, the O. grandiglumis-derived alleles contributed a desirable agronomic effect despite the overall undesirable characteristics of the wild phenotype. Favorable wild alleles were detected for days to heading, spikelets per panicle, and grain shape traits. Grain shape QTL for grain weight, thickness, and width identified in the F(2:3) lines were further confirmed based on the F4 progeny test. The confirmed locus, tgw2 for grain weight is of particular interest because of its independence from undesirable height and maturity. Several QTL controlling amylose content and grain traits have not been detected in the previous QTL studies between Oryza cultivars, indicating potentially novel alleles from O. grandiglumis. The QTL detected in this study could be a rich source of natural genetic variation underlying the evolution and breeding of rice.

Chromosome Mapping↗
PubMed2001

Mapping of quantitative trait locus related to submergence tolerance in rice with aid of chromosome walking.

The major QTL for submergence tolerance was locate in the 5.9 cM interval between flanking RFLP markers. To narrow down this region, a physical map was constructed using YAC and BAC clones. A 400-kb YAC was identified in this region and later its end fragments were used to screen a rice BAC library. Through chromosome walking, 24 positive BAC clones formed two contigs around linked-RFLP markers, R1164 and RZ698. Using one YAC end, six BAC ends and three RFLP markers, a fine-scale map was constructed of the 6.8-cM interval of S10709-RZ698 on rice chromosome 9. The submergence tolerance and related trait were located in a small, well-defined region around BAC-end marker 180D1R and RFLP marker R1164. The physical-to-map distance ratio in this region is as small as 172.5 kb/cM, showing that this region is a hot spot for recombination in the rice genome.

Chromosome Walking↗
PubMed2000

A unified Haseman-Elston method for testing linkage with quantitative traits.

The Haseman and Elston (H-E) method uses a simple linear regression to model the squared trait difference of sib pairs with the shared allele identical by descent (IBD) at marker locus for linkage testing. Under this setting, the squared mean-corrected trait sum is also linearly related to the IBD sharing. However, the resulting slope estimate for either model is not efficient. In this report, we propose a simple linkage test that optimally uses information from the estimates of both models. We also demonstrate that the new test is more powerful than both the traditional one and the recently revisited H-E methods.

Alleles↗
PubMed2001

Interval mapping of quantitative trait loci in autotetraploid species.

This article presents a method for QTL interval mapping in autotetraploid species for a full-sib family derived by crossing two parents. For each offspring, the marker information on each chromosome is used to identify possible configurations of chromosomes inherited from the two parents and the locations of crossovers on these chromosomes. A branch and bound algorithm is used to identify configurations with the minimum number of crossovers. From these configurations, the conditional probability of each possible QTL genotype for a series of positions along the chromosome can be estimated. An iterative weighted regression is then used to relate the trait values to the QTL genotype probabilities. A simulation study is performed to assess this approach and to investigate the effects of the proportion of codominant to dominant markers, the heritability, and the population size. We conclude that the method successfully locates QTL and estimates their parameters accurately, and we discuss different modes of action of the QTL that may be modeled.

Algorithms↗
PubMed2004

On the Metropolis-Hastings acceptance probability to add or drop a quantitative trait locus in Markov chain Monte Carlo-based Bayesian analyses.

The Metropolis-Hastings algorithm used in analyses that estimate the number of QTL segregating in a mapping population requires the calculation of an acceptance probability to add or drop a QTL from the model. Expressions for this acceptance probability need to recognize that sets of QTL are unordered such that the number of equivalent sets increases with the factorial of the QTL number. Here, we show how accounting for this fact affects the acceptance probability and review expressions found in the literature.

Algorithms↗
PubMed1998

Quantitative trait loci implicated in corpus callosum midsagittal area in mice.

The midsagittal area of the corpus callosum expressed as the percentage of the hemispheric surface is smaller in the NZB/BlNJ than in the C57BL/6By inbred strain of mice. We performed a QTL mapping analysis using 284 F2s. Two loci linked to this measure were found: the CCrSQTL1 and CCrSQTL2 at 87 and 67 centiMorgans from the centromere on chromosomes 1 and 4 respectively. The two loci interacted significantly. The total source of genetic variation contributed to 25% of the observed variance.

Animals↗
PubMed2002

Low-level microsatellite instability occurs in most colorectal cancers and is a nonrandomly distributed quantitative trait.

About 10-15% of colorectal cancers show high-level microsatellite instability. The characteristics and very existence of low-level instability (MSI-L) are unclear, although some studies have found associations between MSI-L and molecular characteristics, notably more frequent K-ras mutations and a low level of allele loss near APC. We have attempted to define a MSI-L group of tumors by analyzing 107 sporadic colorectal carcinomas at 44 microsatellites. Ten (9.7%) MSI-H cancers were identified, but there was no evidence for a discrete MSI-L group. However, the 97 non-MSI-H cancers showed greater variation in the frequency of MSI than was expected by chance. Most cancers (68%) in the non-MSI-H group showed some MSI and could therefore be classed as nominally MSI-L. No association was found between MSI-L (or the level of MSI) and any clinicopathological or molecular variable, including K-ras mutation and loss of heterozygosity at APC. The causes of variation in level of the MSI in non-MSI-H colorectal cancers are unknown, but the differences are quantitative and probably reflect the evolutionary histories of the cancers rather than qualitatively different genetic pathways of tumorigenesis.

Colorectal Neoplasms↗
PubMed1999

Mapping of a blood pressure quantitative trait locus to chromosome 15q in a Chinese population.

Blood pressure is a complex trait of pivotal biological importance, in which 20-50% of interindividual variation is genetically determined. Whereas genes have been identified in several rare Mendelian forms of hypertension, little progress has been made in understanding the genetics of blood pressure variation in the general population. Recently, we screened the human genome using rural Chinese sibling pairs with extreme blood pressure and identified suggestive linkage for two chromosomal regions. By refining the trait definition and genotyping additional markers, we detected significant linkage (maximum lod score = 3.77) near D15S203 in lower extreme diastolic blood pressure sibling pairs. Using a second independent data set from the same geographical area, we marginally replicated ( P = 0.05) this result, suggesting that this locus is very likely to be involved in the regulation of diastolic blood pressure.

Adult↗
PubMed2003

Quantitative trait loci for femoral size and shape in a genetically heterogeneous mouse population.

UNLABELLED: The aim of this study was to examine the genetic effects on cortical bone geometry. Genotypes from 487 mice were compared with geometric traits obtained from microCT. We found 14 genetic markers that associate with geometric traits, showing the complexity of genetic control over bone geometry. INTRODUCTION: Previous studies have shown that genetic background affects bone characteristics, particularly bone mineral density, in both mouse and human populations. Much less is known, however, about the effects of polymorphic genes on bone size, shape, and mechanical integrity. In this study, we investigated the genetic determinants of geometric properties of cortical bone in mice. MATERIALS AND METHODS: This study used a genetically heterogeneous mouse population, which is denoted UM-HET3 stock and is derived as the progeny of (BALB/cJ X C57BL/6J) F1 females and (C3H/HeJ X DBA/2J) F1 males. The experimental group consisted of 487 female UM-HET3 mice. Genotypic data from 99 polymorphic genetic loci was obtained from the mice at 4 weeks of age. At 18 months of age, the mice were humanely killed, and the right femurs were scanned with microcomputed tomography to assess geometric properties of cortical bone. A permutation-based test was used to detect significant associations between genetic markers and geometric traits. This test generates experiment-wise p values, which account for the effect of testing multiple hypotheses. An experiment-wise p < or = 0.05 was considered statistically significant. RESULTS: Fourteen genetic markers were found to significantly associate with one or more geometric traits. Two markers (D3Mit62 and D4Mit155) were associated with traits describing bone size; 2 (D12Mit167 and D14Mit170) were linked with traits describing bone shape; and 10 (D1Nds2, D5Mit95, D6Mit216, D7Mit91, D8Mit51, D9Mit110, D11Mit83, D15Mit100, D15Mit171, and D17Mit46) were associated with both size and shape. CONCLUSIONS: Our results indicate that the genetic control of cortical bone geometry is complex and that femoral size and shape may be influenced by different, although overlapping, groups of polymorphic loci.

Animals↗
PubMed2003

A quantitative trait locus influencing free plasma protein S levels on human chromosome 1q: results from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) project.

OBJECTIVE: Protein S (PS) is a component of the protein C anticoagulant system. PS deficiency is associated with myocardial infarction and venous thromboembolism, two highly prevalent causes of death in industrialized nations. As part of the Genetic Analysis of Idiopathic Thrombophilia (GAIT) project, we conducted a genome-wide linkage screen to localize genes influencing variation in free PS (fPS) plasma levels. METHODS AND RESULTS: fPS levels were measured in 397 individuals in 21 Spanish families. A total of 363 highly informative microsatellite markers were genotyped to provide a 10-cM genetic map, and variance component linkage methods were used. A region on chromosome 1q32, flanked by markers D1S425 and D1S213, showed strong evidence of linkage with fPS levels (LOD score, 4.07; nominal P=7.5x10(-6); genome-wide P=0.0024). This region contains two positional candidate genes, the complement component 4-binding protein alpha and beta chains, which encode the principal binding protein for PS. Suggestive evidence for linkage was also observed on chromosomes 11p and 19p. CONCLUSIONS: These results represent one of the first genomic screens for quantitative variation in a component of the hemostatic pathway and provide strong evidence for a locus on chromosome 1q influencing fPS levels.

Adolescent↗
PubMed1998

Testing causal hypotheses in multivariate linkage analysis of quantitative traits: general formulation and application to sibpair data.

We provide a general framework for the development of model-free methods for the linkage analysis of multivariate phenotypic data. It is possible within this framework to test both for linkage of a set of phenotypes to one or more markers and for the presence of structural relations among the phenotypes themselves. This report presents the general model, paying special attention to the assumptions that enter its formulation, and outlines the estimation procedures that may be used.

Chromosome Mapping↗
PubMed2005

Single-nucleotide polymorphism versus microsatellite markers in a combined linkage and segregation analysis of a quantitative trait.

Increasingly, single-nucleotide polymorphism (SNP) markers are being used in preference to microsatellite markers. However, methods developed for microsatellites may be problematic when applied to SNP markers. We evaluated the results of using SNPs vs. microsatellites in Monte Carlo Markov chain (MCMC) oligogenic combined segregation and linkage analysis methods. These methods were developed with microsatellite markers in mind. We selected chromosome 7 from the Collaborative Study on the Genetics of Alcoholism dataset for analysis because linkage to an electrophysiological trait had been reported there. We found linkage in the same region of chromosome 7 with the Affymetrix SNP data, the Illumina SNP data, and the microsatellite marker data. The MCMC sampler appears to mix with both types of data. The sampler implemented in this MCMC oligogenic combined segregation and linkage analysis appears to handle SNP data as well as microsatellite data and it is possible that the localizations with the SNP data are better.

Chromosome Mapping↗
PubMed2002

Mapping of quantitative trait loci affecting quality and production traits in egg layers.

A mapping population segregating for egg quality traits was created by a line cross between two egg layer lines and screened by a genome scan. The F2 generation consisted of 307 hens, which were scored for egg quality and production traits. The mapping population was genotyped for 99 microsatellite loci, spanning nine macrochromosomes and five small linkage groups. The linkage maps were used in mapping QTL affecting 14 traits, by using multiple markers and a least-squares approach. We detected 14 genomewide significant and six suggestive QTL that were located on chromosomes 2, 3, 4, 5, and, 8 and sex chromosome Z. A significant QTL affecting egg white thinning was found on chromosome 2. For eggshell strength, a significant QTL was found on chromosome Z. For production traits, the most interesting area was on chromosome 4, where highly significant QTL effects were detected for BW, egg weight, and feed intake in the same area. The most significant QTL explains 25.8% of the phenotypic variance in F2 of body weight. An area affecting the age at first egg, egg weight, and the number of eggs was located on chromosome Z.

Animals↗