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PubMed1997

Transmission-disequilibrium tests for quantitative traits.

The transmission-disequilibrium test (TDT) of Spielman et al. is a family-based linkage-disequilibrium test that offers a powerful way to test for linkage between alleles and phenotypes that is either causal (i.e., the marker locus is the disease/trait allele) or due to linkage disequilibrium. The TDT is equivalent to a randomized experiment and, therefore, is resistant to confounding. When the marker is extremely close to the disease locus or is the disease locus itself, tests such as the TDT can be far more powerful than conventional linkage tests. To date, the TDT and most other family-based association tests have been applied only to dichotomous traits. This paper develops five TDT-type tests for use with quantitative traits. These tests accommodate either unselected sampling or sampling based on selection of phenotypically extreme offspring. Power calculations are provided and show that, when a candidate gene is available (1) these TDT-type tests are at least an order of magnitude more efficient than two common sib-pair tests of linkage; (2) extreme sampling results in substantial increases in power; and (3) if the most extreme 20% of the phenotypic distribution is selectively sampled, across a wide variety of plausible genetic models, quantitative-trait loci explaining as little as 5% of the phenotypic variation can be detected at the .0001 alpha level with <300 observations.

Genetic Markers↗
PubMed2006

Interval mapping of quantitative trait loci for time-to-event data with the proportional hazards mixture cure model.

Interval mapping using normal mixture models has been an important tool for analyzing quantitative traits in experimental organisms. When the primary phenotype is time-to-event, it is natural to use survival models such as Cox's proportional hazards model instead of normal mixtures to model the phenotype distribution. An extra challenge for modeling time-to-event data is that the underlying population may consist of susceptible and nonsusceptible subjects. In this article, we propose a semiparametric proportional hazards mixture cure model which allows missing covariates. We discuss applications to quantitative trait loci (QTL) mapping when the primary trait is time-to-event from a population of mixed susceptibility. This model can be used to characterize QTL effects on both susceptibility and time-to-event distribution, and to estimate QTL location. The model can naturally incorporate covariate effects of other risk factors. Maximum likelihood estimates for the parameters in the model as well as their corresponding variance estimates can be obtained numerically using an EM-type algorithm. The proposed methods are assessed by simulations under practical settings and illustrated using a real data set containing survival times of mice after infection with Listeria monocytogenes. An extension to multiple intervals is also discussed.

Algorithms↗
PubMed2001

Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the alpha subunit of protein kinase CK2.

Hd6 is a quantitative trait locus involved in rice photoperiod sensitivity. It was detected in backcross progeny derived from a cross between the japonica variety Nipponbare and the indica variety Kasalath. To isolate a gene at Hd6, we used a large segregating population for the high-resolution and fine-scale mapping of Hd6 and constructed genomic clone contigs around the Hd6 region. Linkage analysis with P1-derived artificial chromosome clone-derived DNA markers delimited Hd6 to a 26.4-kb genomic region. We identified a gene encoding the alpha subunit of protein kinase CK2 (CK2 alpha) in this region. The Nipponbare allele of CK2 alpha contains a premature stop codon, and the resulting truncated product is undoubtedly nonfunctional. Genetic complementation analysis revealed that the Kasalath allele of CK2 alpha increases days-to-heading. Map-based cloning with advanced backcross progeny enabled us to identify a gene underlying a quantitative trait locus even though it exhibited a relatively small effect on the phenotype.

Amino Acid Sequence↗
PubMed2001

Quantitative-trait-locus analysis of body-mass index and of stature, by combined analysis of genome scans of five Finnish study groups.

In recent years, many genomewide screens have been performed, to identify novel loci predisposing to various complex diseases. Often, only a portion of the collected clinical data from the study subjects is used in the actual analysis of the trait, and much of the phenotypic data is ignored. With proper consent, these data could subsequently be used in studies of common quantitative traits influencing human biology, and such a reanalysis method would be further justified by the nonbiased ascertainment of study individuals. To make our point, we report here a quantitative-trait-locus (QTL) analysis of body-mass index (BMI) and stature (i.e., height), with genotypic data from genome scans of five Finnish study groups. The combined study group was composed of 614 individuals from 247 families. Five study groups were originally ascertained in genetic studies on hypertension, obesity, osteoarthritis, migraine, and familial combined hyperlipidemia. Most of the families are from the Finnish Twin Cohort, which represents a population-wide sample. In each of the five genome scans, approximately 350 evenly spaced markers were genotyped on 22 autosomes. In analyzing the genotype data by a variance-component method, we found, on chromosome 7pter (maximum multipoint LOD score of 2.91), evidence for QTLs affecting stature, and a second locus, with suggestive evidence for linkage to stature, was detected on chromosome 9q (maximum multipoint LOD score of 2.61). Encouragingly, the locus on chromosome 7 is supported by the data reported by Hirschhorn et al. (in this issue), who used a similar method. We found no evidence for QTLs affecting BMI.

Body Height↗
PubMed2005

Complement factor 5 is a quantitative trait gene that modifies liver fibrogenesis in mice and humans.

Fibrogenesis or scarring of the liver is a common consequence of all chronic liver diseases. Here we refine a quantitative trait locus that confers susceptibility to hepatic fibrosis by in silico mapping and show, using congenic mice and transgenesis with recombined artificial chromosomes, that the gene Hc (encoding complement factor C5) underlies this locus. Small molecule inhibitors of the C5a receptor had antifibrotic effects in vivo, and common haplotype-tagging polymorphisms of the human gene C5 were associated with advanced fibrosis in chronic hepatitis C virus infection. Thus, the mouse quantitative trait gene led to the identification of an unknown gene underlying human susceptibility to liver fibrosis, supporting the idea that C5 has a causal role in fibrogenesis across species.

Animals↗
PubMed2002

Microsatellite markers associated with quantitative trait loci controlling antibody response to Escherichia coli and Salmonella enteritidis in young broilers.

A unique resource population was produced to facilitate detection of microsatellite markers associated with quantitative trait loci controlling antibody (Ab) response in broiler chickens. Three F1 males were produced by mating two lines divergently selected on Ab response to Escherichia coli vaccination. Each F1 male was mated with females from four genetic backgrounds: F1, high-Ab line (HH), low-Ab line and commercial line, producing three resource families, each with four progeny types. About 1700 chicks were immunized with E. coli and Salmonella enteritidis vaccines. Selective genotyping was conducted on the individuals with highest or lowest average Ab to E. coli and S. enteritidis within each progeny type in each sire family. Twelve markers were significantly associated with Ab to E. coli and six of them were also associated with Ab to S. enteritidis, mostly exhibiting a similar low effect (approximately 0.35 phenotypic SD) in all progeny types. Four markers exhibited a highly significant and much larger effect (approximately 1.7 SD), but only in progeny of females from the HH, suggesting that a backcross to the high parental line should be preferred over the commonly used F2 population. Results from two markers suggested a quantitative trait locus on chromosome 2 around 400 cM. The marker MCW0083, significant in two sire families, is closely linked to the bone morphogenetic protein 2 (BMP2) gene, known to be associated with the control of T-cell transformation in humans.

Animals↗
PubMed2003

Diagnostic tools in linkage analysis for quantitative traits.

Diagnostic methods are key components in any good statistical analysis. Because of the similarities between the variance components approach and regression analysis with respect to the normality assumption, when performing quantitative genetic linkage analysis using variance component methods, one must check the normality assumption of the quantitative trait and outliers. Thus, the main purposes of this paper are to describe methods for testing the normality assumption, to describe various diagnostic methods for identifying outliers, and to discuss the issues that may arise when outliers are present when using variance components models in quantitative trait linkage analysis. Data from the Rochester Family Heart Study are used to illustrate the various diagnostic methods and related issues.

Coronary Artery Disease↗
PubMed2003

Quantitative trait loci variation for growth and obesity between and within lines of pigs (Sus scrofa).

The hypothesis that quantitative trait loci (QTL) that explain variation between divergent populations also account for genetic variation within populations was tested using pig populations. Two regions of the porcine genome that had previously been reported to harbor QTL with allelic effects that differed between the modern pig and its wild-type ancestor and between the modern pig and a more distantly related population of Asian pigs were studied. QTL for growth and obesity traits were mapped using selectively genotyped half-sib families from five domesticated modern populations. Strong support was found for at least one QTL segregating in each population. For all five populations there was evidence of a segregating QTL affecting fatness in a region on chromosome 7. These findings confirm that QTL can be detected in highly selected commercial populations and are consistent with the hypothesis that the same chromosome locations that account for variation between populations also explain genetic variation within populations.

Alleles↗
PubMed2006

The sex-specific genetic architecture of quantitative traits in humans.

Mapping genetically complex traits remains one of the greatest challenges in human genetics today. In particular, gene-environment and gene-gene interactions, genetic heterogeneity and incomplete penetrance make thorough genetic dissection of complex traits difficult, if not impossible. Sex could be considered an environmental factor that can modify both penetrance and expressivity of a wide variety of traits. Sex is easily determined and has measurable effects on recognizable morphology; neurobiological circuits; susceptibility to autoimmune disease, diabetes, asthma, cardiovascular and psychiatric disease; and quantitative traits like blood pressure, obesity and lipid levels, among others. In this study, we evaluated sex-specific heritability and genome-wide linkages for 17 quantitative traits in the Hutterites. The results of this study could have important implications for mapping complex trait genes.

Genetic Linkage↗
PubMed1994

Maximum likelihood estimation of quantitative trait loci parameters with the aid of genetic markers using a standard statistical package.

Consistent parameter estimates of quantitative trait loci linked to genetic markers can be derived by maximum likelihood methodology. For many experimental designs of interest, parameter estimates and their standard errors can be obtained by program LE of BMDP, which uses the Newton-Raphson method of iteration. Program LE was tested on data simulated for a backcross between two inbred lines. A single quantitative trait locus linked to either one or two genetic markers was simulated. Convergence was rapid, and computing and programming time were insignificant. All parameter estimates were within the expected bounds. Many different designs can be readily analyzed.

Algorithms↗
PubMed1999

A genome search identifies major quantitative trait loci on human chromosomes 3 and 4 that influence cholesterol concentrations in small LDL particles.

Small, dense LDL particles are associated with increased risk of cardiovascular disease. To identify the genes that influence LDL size variation, we performed a genome-wide screen for cholesterol concentrations in 4 LDL size fractions. Samples from 470 members of randomly ascertained families were typed for 331 microsatellite markers spaced at approximately 15 cM intervals. Plasma LDLs were resolved by using nondenaturing gradient gel electrophoresis into 4 fraction sizes (LDL-1, 26.4 to 29.0 nm; LDL-2, 25.5 to 26.4 nm; LDL-3, 24.2 to 25.5 nm; and LDL-4, 21.0 to 24.2 nm) and cholesterol concentrations were estimated by staining with Sudan Black B. Linkage analyses used variance component methods that exploited all of the genotypic and phenotypic information in the large extended pedigrees. In multipoint linkage analyses with quantitative trait loci for the 4 fraction sizes, only LDL-3, a fraction containing small LDL particles, gave peak multipoint log10 odds in favor of linkage (LOD) scores that exceeded 3.0, a nominal criterion for evidence of significant linkage. The highest LOD scores for LDL-3 were found on chromosomes 3 (LOD=4.1), 4 (LOD=4.1), and 6 (LOD=2.9). In oligogenic analyses, the 2-locus LOD score (for chromosomes 3 and 4) increased significantly (P=0.0012) to 6.1, but including the third locus on chromosome 6 did not significantly improve the LOD score (P=0.064). Thus, we have localized 2 major quantitative trait loci that influence variation in cholesterol concentrations of small LDL particles. The 2 quantitative trait loci on chromosomes 3 and 4 are located in regions that contain the genes for apoD and the large subunit of the microsomal triglyceride transfer protein, respectively.

Adolescent↗
PubMed1999

Comparison of linkage-disequilibrium methods for localization of genes influencing quantitative traits in humans.

Linkage disequilibrium has been used to help in the identification of genes predisposing to certain qualitative diseases. Although several linkage-disequilibrium tests have been developed for localization of genes influencing quantitative traits, these tests have not been thoroughly compared with one another. In this report we compare, under a variety of conditions, several different linkage-disequilibrium tests for identification of loci affecting quantitative traits. These tests use either single individuals or parent-child trios. When we compared tests with equal samples, we found that the truncated measured allele (TMA) test was the most powerful. The trait allele frequencies, the stringency of sample ascertainment, the number of marker alleles, and the linked genetic variance affected the power, but the presence of polygenes did not. When there were more than two trait alleles at a locus in the population, power to detect disequilibrium was greatly diminished. The presence of unlinked disequilibrium (D'*) increased the false-positive error rates of disequilibrium tests involving single individuals but did not affect the error rates of tests using family trios. The increase in error rates was affected by the stringency of selection, the trait allele frequency, and the linked genetic variance but not by polygenic factors. In an equilibrium population, the TMA test is most powerful, but, when adjusted for the presence of admixture, Allison test 3 becomes the most powerful whenever D'*>.15.

Alleles↗
PubMed1991

Linkage analysis of quantitative traits: increased power by using selected samples.

Although a number of methods have been developed for linkage analysis of quantitative traits, power is relatively poor unless there is a single major locus of very large effect. Here it is demonstrated that the use of selected samples (i.e., ascertainment of a proband with an extreme score on the quantitative measure) can dramatically increase power, especially when proband selection is performed on the tail of a distribution with an infrequent recessive gene. Depending on gene action and allele frequency, selected samples permit detection of a major locus that accounts for as little as 10%-20% of the phenotypic variation. The judicious use of selected samples can make an appreciable difference in the feasibility of linkage studies for quantitative traits.

Gene Frequency↗
PubMed2002

[Detection of quantitative trait loci for growth in large white x Meishan intercross].

The development of molecular biology techniques and the application of these techniques to farm animals have progressed rapidly and have opened new vistas for investigators wishing to identify genes that control quantitative traits. Now that a comprehensive map has been developed for the porcine genome, genomic scans to detect quantitative trait loci (QTL) can begin. In order to locate the genetic regions in the swine genome that are responsible for economically important traits, a resource population was developed by intercross with three Large White and seven Meishan pigs. In subsequent generations, 66 F2 offsprings in 2000 were recorded for four growth traits including birth weight (BWT), body weight at 60 day (WT60), average daily gain from birth to 60 day (ADG1) and average daily gain from 60 day to the end of test (ADG2), and genotyped for 48 microsatellite markers spanning six chromosomes. Association analyses were performed using interval mapping by regression under an outbred line-cross model on chromosomes 1, 2, 3, 4, 6 and 7. The F threshold values were determined by permutation. A total of 12 QTL were detected at suggestive level for the four traits evaluated in this study. Of the 12 suggestive QTL, 3 and 1 QTL were significant at the chromosome-wise and genome-wise levels. There was a QTL for ADG2 at genome-wide level on chromosome 4 explained additive variance 2.19%. A chromosome-wide QTL affecting ADG1 and WT60 were detected on chromosomes 2 and 1 explained additive variance 0.01% and 26.01%, respectively.

Animals↗
PubMed2006

Association of hypertension with single nucleotide polymorphisms in the quantitative trait locus for abdominal obesity-metabolic syndrome on chromosome 17.

Genome scan in Chinese revealed an association of blood pressure with the microsatellite marker D17S1303, which lies in a quantitative trait locus for the abdominal obesity-metabolic syndrome (AOMS2) at 17p12 on chromosome 17. We previously reported that D17S1303 was associated with hypertension and obesity. Therefore, we studied 10 single nucleotide polymorphisms (SNP) within 3 kb of D17S1303. One hundred and eighty hypertensive subjects (91 men, 89 women, age 53+/-12 years) and 180 normotensive matched controls (91 men, 89 women, age 52+/-11) were genotyped using the Sequenom genotyping platform. Allelic frequencies in these Chinese subjects differed from those reported for Caucasians. Three SNPs (rs11656507, rs1357926, rs852319) were homozygous in our subjects. The genotype frequencies of rs852320, rs852321 and rs852322 did not differ between hypertensive and normotensive subjects. However, there were significant differences for rs1525402 (P=0.048), rs2692343 (P=0.022), rs2692344 (P=0.017) and rs2321313 (P=0.028). A four-locus haplotype comprising G at rs1525402, C at rs2692343, C at rs2692344 and G at rs2321313 was associated with lower systolic blood pressure (P=0.023) and normotension (P=0.048). Our results provide further evidence that there is a gene, as yet unidentified, influencing blood pressure in the vicinity of D17S1303 in a quantitative trait locus for abdominal obesity-metabolic syndrome at 17p12.

Chi-Square Distribution↗
PubMed2005

Quantitative trait loci for internal nematode resistance in sheep: a review.

Internal nematode resistance in sheep has a large impact on the economy of sheep industries. Selection for nematode resistance in sheep breeding schemes would help to reduce the direct and indirect cost of parasitism to these industries. However, this is not widely practiced because of the difficulty of measuring parasite resistance or correlated indirect selection criteria. The identification of genes or linked markers that have a significant association with the variance of indicator traits of internal nematode resistance in sheep would facilitate the inclusion of nematode resistance in sheep breeding operations. This review summarises findings reported in the literature of quantitative trait loci for internal nematode resistance in sheep. Issues relating to the analytical and phenotypic complexity of nematode resistance are discussed in the context of the findings of quantitative trait loci for nematode resistance published to date.

Animals↗
PubMed2001

DNA microsatellites linked to quantitative trait loci affecting antibody response and survival rate in meat-type chickens.

Selection for immune response parameters may lead to improved general disease resistance. Because disease resistance and immune response are hard-to-measure quantitative traits with low to moderate heritability, they may respond more efficiently to marker-assisted selection (MAS) than to phenotypic selection. To detect DNA markers linked to quantitative trait loci (QTL) associated with immune response, a resource half-sib family of 160 backcross (BC1) and intercross (F2) birds was derived from a cross between two meat-type lines divergently selected for high or low antibody (Ab) response to Escherichia coli. By using 25 microsatellite DNA markers covering approximately 25% of the chicken genome, initial genotyping of 40% of the resource family was followed by complete genotyping of the entire family with four suggestive markers. Three of these markers exhibited significant association with immune response: (1) ADL0146 on Chromosome 2 associated with Ab to SRBC and Newcastle disease virus (NDV), (2) ADL0290 on linkage group 31 affecting Ab to NDV, and (3) ADL0298 on linkage group 34 associated with Ab to E. coli and survival. The family was also genotyped with five linked markers from two of the suggested regions, and interval mapping was applied. The results confirmed the significant effects, suggested the location of the QTL, and confirmed the genetic association between immune responses and disease resistance. These findings support the idea of improving poultry immunocompetence by MAS.

Animals↗
PubMed2003

Novel quantitative trait loci controlling development of experimental autoimmune encephalomyelitis and proportion of lymphocyte subpopulations.

The B10.RIII mouse strain (H-2(r)) develops chronic experimental autoimmune encephalomyelitis (EAE) upon immunization with the myelin basic protein 89-101 peptide. EAE was induced and studied in a backcross between B10.RIII and the EAE-resistant RIIIS/J strain (H-2(r)), and a complete genome scan with microsatellite markers was performed. Five loci were significantly linked to different traits and clinical subtypes of EAE on chromosomes 1, 5, 11, 15, and 16, three of the loci having sex specificity. The quantitative trait locus on chromosome 15 partly overlapped with the Eae2 locus, previously identified in crosses between the B10.RIII and RIIIS/J mouse strains. The loci on chromosomes 11 and 16 overlapped with Eae loci identified in other mouse crosses. By analyzing the backcross animals for lymphocyte phenotypes, the proportion of B and T cells in addition to the levels of CD4(+)CD8(-) and CD4(-)CD8(+) T cells and the CD4(+)/CD8(+) ratio in spleen were linked to different loci on chromosomes 1, 2, 3, 5, 6, 11, and 15. On chromosome 16, we found significant linkage to spleen cell proliferation. Several linkages overlapped with the quantitative trait loci for disease phenotypes. The identification of subphenotypes that are linked to the same loci as disease traits could be most useful in the search for candidate genes and biological pathways involved in the pathological process.

Animals↗