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Results for “quantitative trait locus”

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PubMed2002

Development of isothiocyanate-enriched broccoli, and its enhanced ability to induce phase 2 detoxification enzymes in mammalian cells.

Broccoli florets contain low levels of 3-methylsuphinylpropyl and 4-methylsulphinylbutyl glucosinolates. Following tissue disruption, these glucosinolates are hydrolysed to the corresponding isothiocyanates (ITCs), which have been associated with anticarcinogenic activity through a number of physiological mechanisms including the induction of phase II detoxification enzymes and apoptosis. In this paper, we describe the development of ITC-enriched broccoli through the introgression of three small segments of the genome of Brassica villosa, a wild relative of broccoli, each containing a quantitative trait locus (QTL), into a broccoli genetic background, via marker-assisted selection and analysis of glucosinolates in the florets of backcross populations. Epistatic and heterotic effects of these QTLs are described. The ITC-enriched broccoli had 80-times the ability to induce quinone reductase (a standard assay of phase II induction potential) when compared to standard commercial broccoli, due both to an increase in the precursor glucosinolates and a greater conversion of these into ITCs.

Anticarcinogenic Agents↗
PubMed2003

On different approximations to multilocus identity-by-descent calculations and the resulting power of variance component-based linkage analysis.

An empirical comparison between three different methods for estimation of pair-wise identity-by-descent (IBD) sharing at marker loci was conducted in order to quantify the resulting differences in power and localization precision in variance components-based linkage analysis. On the examined simulated, error-free data set, it was found that an increase in accuracy of allele sharing calculation resulted in an increase in power to detect linkage. Linkage analysis based on approximate multi-marker IBD matrices computed by a Markov chain Monte Carlo approach was much more powerful than linkage analysis based on exact single-marker IBD probabilities. A "multiple two-point" approximation to true "multipoint" IBD computation was found to be roughly intermediate in power. Both multi-marker approaches were similar to each other in accuracy of localization of the quantitative trait locus and far superior to the single-marker approach. The overall conclusions of this study with respect to power are expected to also hold for different data structures and situations, even though the degree of superiority of one approach over another depends on the specific circumstances. It should be kept in mind, however, that an increase in computational accuracy is expected to go hand in hand with a decrease in robustness to various sources of errors.

Body Height↗
PubMed2006

An SNP caused loss of seed shattering during rice domestication.

Loss of seed shattering was a key event in the domestication of major cereals. We revealed that the qSH1 gene, a major quantitative trait locus of seed shattering in rice, encodes a BEL1-type homeobox gene and demonstrated that a single-nucleotide polymorphism (SNP) in the 5' regulatory region of the qSH1 gene caused loss of seed shattering owing to the absence of abscission layer formation. Haplotype analysis and association analysis in various rice collections revealed that the SNP was highly associated with shattering among japonica subspecies of rice, implying that it was a target of artificial selection during rice domestication.

Agriculture↗
PubMed2005

Sex-limited genome-wide linkage scan for body mass index in an unselected sample of 933 Australian twin families.

Genes involved in pathways regulating body weight may operate differently in men and women. To determine whether sex-limited genes influence the obesity-related phenotype body mass index (BMI), we have conducted a general nonscalar sex-limited genome-wide linkage scan using variance components analysis in Mx (Neale, 2002). BMI measurements and genotypic data were available for 2053 Australian female and male adult twins and their siblings from 933 families. Clinical measures of BMI were available for 64.4% of these individuals, while only self-reported measures were available for the remaining participants. The mean age of participants was 39.0 years of age (SD 12.1 years). The use of a sex-limited linkage model identified areas on the genome where quantitative trait loci (QTL) effects differ between the sexes, particularly on chromosome 8 and 20, providing us with evidence that some of the genes responsible for BMI may have different effects in men and women. Our highest linkage peak was observed at 12q24 (-log10p = 3.02), which was near the recommended threshold for suggestive linkage (-log10p = 3.13). Previous studies have found evidence for a quantitative trait locus on 12q24 affecting BMI in a wide range of populations, and candidate genes for noninsulin-dependent diabetes mellitus, a consequence of obesity, have also been mapped to this region. We also identified many peaks near a -log10p of 2 (threshold for replicating an existing finding) in many areas across the genome that are within regions previously identified by other studies, as well as in locations that harbor genes known to influence weight regulation.

Body Mass Index↗
PubMed2003

Interaction between blood pressure quantitative trait loci in rats in which trait variation at chromosome 1 is conditional upon a specific allele at chromosome 10.

We have used inbred and congenic rat strains in F(2) segregation studies to discover epistasis in a polygenic model of hypertension. Previously, we have found evidence that the presence of a blood pressure quantitative trait locus (QTL) on chromosome 1 is conditional upon the allele status of chromosome 10. To prove the existence of an epistatic interaction we have analyzed congenic strains for chromosome 1 and 10 carrying high blood pressure QTL alleles from the spontaneously hypertensive rat on a normotensive background of the Wistar-Kyoto (WKY) rat. Additionally, a double congenic strain was developed with both chromosome 1 and 10 high blood pressure QTL alleles on the WKY background. Analysis of variance for blood pressure phenotypes as determined by radiotelemetry showed a significant effect for chromosome 10 but not chromosome 1 QTL alleles and demonstrated a significant interaction between the two loci (P<0.05). The interaction accounted for 5 mmHg of blood pressure. Thus, the identification of epistasis is critical to the understanding of the quantitative nature of blood pressure genetics.

Alleles↗
PubMed2003

Relationships of testicular iron and ferritin concentrations with testicular weight and sperm production in boars.

The inverse relationship of testicular size and circulating follicle-stimulating hormone (FSH) concentrations has been documented, and accompanying this relationship is the change in color of the parenchymal tissue of the testes. Large testes (300 to 400 g) are pink to light red and small testes (100 g) are dark maroon with color gradations for weights in between. It was hypothesized that this color most likely represented an iron protein. Chromatographic analysis of testicular tissue indicated that the Fe was associated primarily with ferritin, and immunohistochemistry showed that Leydig cells were the primary location of ferritin storage within the testes. Concentrations of Fe and ferritin were higher in small testes and decreased as testes weight increased (P < 0.05). As testicular Fe concentrations increased, daily sperm production (DSP) and total DSP declined (P < 0.05). Genotyping six generations of Meishan x White composite boars (n = 288) for a quantitative trait locus that is indicative of elevated FSH and small testes in boars indicated that the Meishan genotype had elevated testicular iron concentrations and darker color in conjunction with reduced total DSP (P < 0.01). It is not thought the elevated iron concentrations affect testicular weights but are probably a result of elevated FSH and FSH inducement of Fe transport. The storage of Fe in Leydig cells may provide a reservoir of Fe for easy access by Sertoli and germ cells, but still provide a degree of protection to germ cells from ionic iron.

Animals↗
PubMed2005

Human F7 sequence is split into three deep clades that are related to FVII plasma levels.

It is widely accepted that FVII levels are strongly, consistently, and independently related to cardiovascular risk. These levels are influenced by genetic and environmental factors. Among the genetic factors, only a limited number of polymorphisms in the F7 gene have been reported, and they explain only a small proportion of the genetic variability. Recently, we have accomplished the complete dissection of the F7 quantitative trait locus responsible for all of the genetic variability observed in FVII levels. Now, we present the thorough study of the haplotype organization of F7 DNA sequence variation among individuals and the evolutionary processes that produced this variation, by sequencing 15 kb of genomic DNA sequence from the F7 locus in 40 unrelated individual (80 chromosomes) from the genetic analysis of idiopathic thrombophilia (GAIT) project as well as four non-human primate species. Our study revealed 49 polymorphisms, of which 39 SNPs were further considered. Genotyping of these DNA variations in the whole family-based GAIT sample helped resolve linkage phases, and a total of 37 distinct haplotypes were identified.Tajima's D was significantly positive in this sample, suggesting balancing selection. This parameter was a reflection of the phylogenetic structure of F7 haplotype, which was deeply split into three well-supported clades or haplogroups, suggesting that functional differences among F7 variants do not depend on a few single-site variations. Moreover, haplogroup 2 was associated with high FVII levels and haplogroup 3 with low levels. In this study, we have for the first time established a clear relation between genotypic variability structure and phenotypic variability of a particular quantitative trait involved in a complex disease.

Animals↗
PubMed2005

Genotyping DNA pools on microarrays: tackling the QTL problem of large samples and large numbers of SNPs.

BACKGROUND: Quantitative trait locus (QTL) theory predicts that genetic influence on complex traits involves multiple genes of small effect size. To detect QTL associations of small effect size, large samples and systematic screens of thousands of DNA markers are required. An efficient solution is to genotype case and control DNA pools using SNP microarrays. We demonstrate that this is practical using DNA pools of 100 individuals. RESULTS: Using standard microarray protocols for the Affymetrix GeneChip Mapping 10 K Array Xba 131, we show that relative allele signal (RAS) values provide a quantitative index of allele frequencies in pooled DNA that correlate 0.986 with allele frequencies for 104 SNPs that were genotyped individually for 100 individuals. The sensitivity of the assay was demonstrated empirically in a spiking experiment in which 15% and 20% of one individual's DNA was added to a DNA pool. CONCLUSION: We conclude that this approach, which we call SNP-MaP (SNP microarrays and pooling), is rapid, cost effective and promises to be a valuable initial screening method in the hunt for QTLs.

Alleles↗
PubMed2005

A genomewide scan for intelligence identifies quantitative trait loci on 2q and 6p.

Between 40% and 80% of the variation in human intelligence (IQ) is attributable to genetic factors. Except for many rare mutations resulting in severe cognitive dysfunction, attempts to identify these factors have not been successful. We report a genomewide linkage scan involving 634 sibling pairs designed to identify chromosomal regions that explain variation in IQ. Model-free multipoint linkage analysis revealed evidence of a significant quantitative-trait locus for performance IQ at 2q24.1-31.1 (LOD score 4.42), which overlaps the 2q21-33 region that has repeatedly shown linkage to autism. A second region revealed suggestive linkage for both full-scale and verbal IQs on 6p25.3-22.3 (LOD score 3.20 for full-scale IQ and 2.33 for verbal IQ), overlapping marginally with the 6p22.3-21.31 region implicated in reading disability and dyslexia.

Adolescent↗
PubMed2005

A QTL analysis of female variation contributing to refractoriness and sperm competition in Drosophila melanogaster.

Sperm competition is an important fitness component in many animal groups. Drosophila melanogaster males exhibit substantial genetic variation for sperm competitive ability and females show considerable genetic variation for first versus second male sperm use. Currently, the forces responsible for maintaining genetic variation in sperm competition related phenotypes are receiving much attention. While several candidate genes contributing to the variation seen in male competitive ability are known, genes involved in female sperm use remain largely undiscovered. Without knowledge of the underlying genes, it will be difficult to distinguish between different models of sexual selection such as cryptic female choice and sexual conflict. We used quantitative trait locus (QTL) mapping to identify regions of the genome contributing to female propensity to use first or second male sperm, female refractoriness to re-mating, and early-life fertility. The most well supported markers influencing the phenotypes include 33F/34A (P2), 57B (refractoriness) and 23F/24A (fertility). Between 10% and 15% of the phenotypic variance observed in these recombinant inbred lines was explained by these individual QTLs. More detailed investigation of the regions detected in this experiment may lead to the identification of genes responsible for the QTLs identified here.

Animals↗
PubMed2000

Mapping quantitative trait loci for circadian behavioral rhythms in SMXA recombinant inbred strains.

SM/J and A/J inbred strain of mice have different characteristics in circadian behaviors such as free-running period (tau), phase relationship (psi) between light-dark cycles and activity rhythms, and amount of wheel-running activity. To determine the genes which affect these behaviors, a quantitative trait locus (QTL) analysis using SMXA recombinant inbred strains derived from SM/J and A/J mice was performed. Concerning tau, two regions on chromosomes (Chrs) 7 and 18 surpassed the genome-wide suggestive level. As for psi, one suggestive QTL was detected on Chr 7. The QTLs which affect daily activity counts under light-dark cycles and constant darkness were mapped to the same chromosomal regions on Chrs 1 and 17, respectively. The provisional QTLs detected in the present study might be useful for understanding the complex mechanism regulating circadian behaviors.

Animals↗
PubMed1997

Mapping of rat chromosome 2 markers generated from chromosome-sorted DNA.

A quantitative trait locus (QTL) for blood pressure has recently been mapped to a region of roughly 30 cM on rat Chromosome (Chr) 2 by linkage and by the use of congenic strains. For further fine mapping of the QTL, however, closely linked chromosome markers residing in this 30-cM region are required. In the current work, 36 new markers were generated by screening rat Chr 2-sorted DNA libraries and subsequently mapped using five F2 populations. Combining new and existing markers, the marker density for the 30-cM region approaches, on average, one marker per 1.1 cM.

Animals↗
PubMed2002

Comparison of methods used for recovering the line origin of alleles in a cross between outbred lines.

Here, we introduce the idea of probabilities of line origins for alleles in general pedigrees as found in crosses between outbred lines. We also present software for calculating these probabilities. The proposed algorithm is based on the linear regression method of Haley, Knott and Elsen (1994) combined with the Markov chain Monte Carlo (MCMC) method for estimating quantitative trait locus coefficients used as regressors. We compared the relative precision of our method and the original method as proposed by Haley et al. (1994). The scenarios studied varied in the allelic distribution of marker alleles in parental lines and in the frequency of missing marker genotypes. We found that the MCMC method achieves a higher accuracy in all scenarios considered. The benefits of using MCMC approximation are substantial if the frequency of missing marker data is high or the number of marker alleles is low and the allelic frequency distribution is similar in both parental lines.

Animals↗
PubMed2005

Genome-wide scan of resistin mRNA expression in omental adipose tissue of baboons.

INTRODUCTION: The hormone resistin was recently discovered in adipose tissue of mice. Functional tests suggest a role for resistin in the regulation of insulin sensitivity. However, human studies have reported controversial results on the metabolic function of this hormone. METHODS: A 1 g omental adipose tissue biopsy was obtained from 404 adult baboons. Resistin mRNA expression was assayed by real-time, quantitative RT-PCR, and univariate and bivariate quantitative genetic analyses were performed, via the variance decomposition approach. A genome scan analysis was conducted using resistin mRNA abundance in omental adipose tissue as a quantitative phenotype. RESULTS: A significant heritability of h2 = 0.23 (P = 0.003) was found for resistin mRNA abundance in omental adipose tissue. A genome scan detected a quantitative trait locus for resistin expression with an LOD score of 3.8, in the region between markers D19S431 and D19S714, corresponding to human chromosome 19 p13. This chromosomal region contains genes related to insulin resistance phenotypes, such as resistin, insulin receptor, angiopoietin-like 4 protein and LDL receptor. CONCLUSIONS: Individual variation in resistin mRNA expression has a significant genetic component, and a gene or genes on chromosome 19 p13 may regulate resistin mRNA levels in baboon omental adipose tissue.

Adipose Tissue↗
PubMed2003

Mouse models for genetic dissection of polygenic gastrointestinal diseases.

Many diseases with a major public health impact are the result of complex interactions between environmental factors and multiple genes. In the past decade, methods for genome analysis, in particular quantitative trait locus (QTL) analysis in animal models, were developed to identify and localize the genes responsible for multifactorial (polygenic) diseases; QTL analysis is based on experimental crosses between inbred strains with high and low genetic susceptibility. Recently the genes underlying several QTLs could be cloned successfully. Here we describe the impact of these genomic approaches in mice on our understanding of the multifactorial genetics of three gastrointestinal diseases related to metabolism (cholesterol cholelithiasis), development (gastroschisis), and colorectal cancer. The examples demonstrate how mouse models continue to be an invaluable tool in unravelling complex pathomechanisms and unlocking our understanding of human diseases.

Animals↗
PubMed2005

pain1: a neuropathic pain QTL on mouse chromosome 15 in a C3HxC58 backcross.

We have produced a backcross (BC) population of 267 mice from the parental strains C3H/HeN and C58/J. The mice were phenotyped for neuropathic pain using the neuroma model. Subsequently all BC mice were genotyped in a region of chromosome 15 that has been previously suggested to contain a quantitative trait locus (QTL) for this trait. We have confirmed the linkage of the QTL, named pain1, to the central region of chromosome 15. Our finding provides the necessary robustness to justify efforts towards identification of the underlying gene.

Animals↗
PubMed2007

Type I error rates in association versus joint linkage/association tests in related individuals.

Positional gene discovery on pedigree data typically involves initial gross localization by linkage analysis with subsequent finer localization by association analysis in areas that show evidence of linkage. We examine the effect of including linkage information when testing for association in the context of variance-components-based pedigree analysis. We present simulation experiments showing that, at least in the extreme case of a rare private allele, failing to include the linkage variance component in the association model results in excessive Type I error that increases with allele copy number and/or quantitative trait locus (QTL) effect size. Joint estimation of the linkage variance component in the association model reduces Type I error to nominal expectations. This holds whether allele-sharing probabilities are estimated from a polymorphic marker or from the very single-nucleotide polymorphism (SNP) being tested for association, although the latter provides much less power. These results support the idea that an appropriate association analysis must test both the random effect of shared marker alleles (linkage) and the mean effects of the marker genotypes (association).

Alleles↗
PubMed2001

Comparative mapping of BTA15 and HSA11 including a region containing a QTL for meat tenderness.

The starting point of the present study was the reported identification of a chromosomal region on bovine Chromosome (Chr) 15 (BTA15) carrying loci affecting meat tenderness. A comparative linkage map of BTA15 and human Chr 11 (HSA11) was constructed to identify potential positional candidate genes and to provide a resource of genetic markers to support marker-assisted selection (MAS). Relative rearrangements between the bovine and human genomes for these chromosomes are the most complex observed in comparative mapping between the two species, with nine alternating blocks of conserved synteny between HSA11 and bovine Chrs 15 and 29. The results of this study were the addition of nine genes to the HSA11/BTA15 comparative linkage map, and development of five microsatellite markers within the quantitative trait locus (QTL) interval. One gene with known effects on muscle development (MYOD1) was mapped to the interval. A second gene (CALCA) involved in regulation of calcium levels, a key factor in postmortem tenderization, also mapped within the interval. Refinement of the comparative map and QTL position will reduce the interval on the human transcription map to be scanned in search of candidates, reducing the effort and resources required to identify the allelic variation responsible for the genetic effect.

Animals↗