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PubMed2003

Identification and characterization of aluminum tolerance loci in Arabidopsis (Landsberg erecta x Columbia) by quantitative trait locus mapping. A physiologically simple but genetically complex trait.

Aluminum (Al) toxicity, which is caused by the solubilization of Al3+ in acid soils resulting in inhibition of root growth and nutrient/water acquisition, is a serious limitation to crop production, because up to one-half of the world's potentially arable land is acidic. To date, however, no Al tolerance genes have yet been cloned. The physiological mechanisms of tolerance are somewhat better understood; the major documented mechanism involves the Al-activated release of Al-binding organic acids from the root tip, preventing uptake into the primary site of toxicity. In this study, a quantitative trait loci analysis of Al tolerance in Arabidopsis was conducted, which also correlated Al tolerance quantitative trait locus (QTL) with physiological mechanisms of tolerance. The analysis identified two major loci, which explain approximately 40% of the variance in Al tolerance observed among recombinant inbred lines derived from Landsberg erecta (sensitive) and Columbia (tolerant). We characterized the mechanism by which tolerance is achieved, and we found that the two QTL cosegregate with an Al-activated release of malate from Arabidopsis roots. Although only two of the QTL have been identified, malate release explains nearly all (95%) of the variation in Al tolerance in this population. Al tolerance in Landsberg erecta x Columbia is more complex genetically than physiologically, in that a number of genes underlie a single physiological mechanism involving root malate release. These findings have set the stage for the subsequent cloning of the genes responsible for the Al tolerance QTL, and a genomics-based cloning strategy and initial progress on this are also discussed.

Aluminum↗
PubMed2002

Linkage mapping of quantitative trait loci in humans: an overview.

In this article, we provide an overview of the different statistical procedures that have been developed for linkage mapping of quantitative trait loci. We outline the model assumptions, the data requirements and the underlying tests for linkage for the different methods.

Chromosome Mapping↗
PubMed2006

Relationships between the functional PPARalpha Leu162Val polymorphism and obesity, type 2 diabetes, dyslipidaemia, and related quantitative traits in studies of 5799 middle-aged white people.

Peroxisome proliferator-activated receptor-alpha (PPARalpha) is a nuclear receptor capable of regulating the expression of genes involved in peroxisomal and mitochondrial beta-oxidation pathways. The common Leu162Val polymorphism in the gene encoding PPARalpha has inconsistently shown association with quantitative traits related to obesity, type 2 diabetes, and dyslipidaemia. We genotyped the Leu162Val polymorphism in 1383 patients with type 2 diabetes and 4401 control subjects with normal glucose tolerance (NGT) without showing any association between diabetes and genotype. In addition, the Leu162Val polymorphism was not associated with WHO-defined obesity or dyslipidaemia in case-control settings involving 961 obese and 2563 lean subjects and 1399 dyslipidaemic and 4399 normolipidaemic subjects, respectively. Quantitative trait studies of metabolic variables were carried out in 5799 middle-aged, treatment-naïve subjects showing a difference in fasting serum triglyceride concentrations among homozygous Val-carriers (Leu/Leu+Leu/Val, n=5782, 1.33+/-1.35 mmol/l vs. Val/Val, n=17, 2.22+/-2.4 mmol/l, p=0.007). Similarly, Val/Val was associated with increased fasting serum total cholesterol concentrations (p=0.01). In conclusion, in a relative large-scale study of middle-aged whites we found no evidence of association between the PPARalpha Leu162Val polymorphism and obesity or type 2 diabetes. If replicated, the Val162Val variant may, however, confer an increase in fasting levels of serum lipids.

Aged↗
PubMed2003

Analysis of quantitative trait loci that influence animal behavior.

Behavioral differences between inbred strains of mice and rats have a genetic basis that can now be dissected using quantitative trait locus (QTL) analysis. Over the last 10 years, a large number of genetic loci that influence behavior have been mapped. In this article I review what that information has revealed about the genetic architecture of behavior. I show that most behaviors are influenced by QTL of small effect, each contributing to less than 10% of the variance of a behavioral trait. The small effect of each QTL on behavioral variation suggests that the mutational spectrum is different from that which results in Mendelian disorders. Regions of DNA should be appropriately prioritized to find the molecular variants, for instance by looking at sequences that control the level of gene expression rather than variants in coding regions. While the number of allelic loci that can contribute to a trait is large, this is not necessarily the case: the analysis of selected strains shows that a remarkably small number of QTL can explain the bulk of the genetic variation in behavior. I conclude by arguing that genetic mapping has more to offer than a starting point for positional cloning projects. With advances in multivariate analyses, mapping can also test hypotheses about the psychological processes that give rise to behavioral variation.

Animals↗
PubMed2005

Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure.

A population-based study of a quantitative trait may be seriously compromised when the trait is subject to the effects of a treatment. For example, in a typical study of quantitative blood pressure (BP) 15 per cent or more of middle-aged subjects may take antihypertensive treatment. Without appropriate correction, this can lead to substantial shrinkage in the estimated effect of aetiological determinants of scientific interest and a marked reduction in statistical power. Correction relies upon imputation, in treated subjects, of the underlying BP from the observed BP having invoked one or more assumptions about the bioclinical setting. There is a range of different assumptions that may be made, and a number of different analytical models that may be used. In this paper, we motivate an approach based on a censored normal regression model and compare it with a range of other methods that are currently used or advocated. We compare these methods in simulated data sets and assess the estimation bias and the loss of power that ensue when treatment effects are not appropriately addressed. We also apply the same methods to real data and demonstrate a pattern of behaviour that is consistent with that in the simulation studies. Although all approaches to analysis are necessarily approximations, we conclude that two of the adjustment methods appear to perform well across a range of realistic settings. These are: (1) the addition of a sensible constant to the observed BP in treated subjects; and (2) the censored normal regression model. A third, non-parametric, method based on averaging ordered residuals may also be advocated in some settings. On the other hand, three approaches that are used relatively commonly are fundamentally flawed and should not be used at all. These are: (i) ignoring the problem altogether and analysing observed BP in treated subjects as if it was underlying BP; (ii) fitting a conventional regression model with treatment as a binary covariate; and (iii) excluding treated subjects from the analysis. Given that the more effective methods are straightforward to implement, there is no argument for undertaking a flawed analysis that wastes power and results in excessive bias.

Aged↗
PubMed2005

Theoretical models of selection and mutation on quantitative traits.

Empirical studies of quantitative genetic variation have revealed robust patterns that are observed both across traits and across species. However, these patterns have no compelling explanation, and some of the observations even appear to be mutually incompatible. We review and extend a major class of theoretical models, 'mutation-selection models', that have been proposed to explain quantitative genetic variation. We also briefly review an alternative class of 'balancing selection models'. We consider to what extent the models are compatible with the general observations, and argue that a key issue is understanding and modelling pleiotropy. We discuss some of the thorny issues that arise when formulating models that describe many traits simultaneously.

Evolution, Molecular↗
PubMed2002

[Molecular mapping of quantitative trait loci (QTL) for characters of vascular bundles in peduncle related to indica-japonica differentiation in rice (Oryza sativa L.)].

A doubled-haploid population, consisting of 81 DH lines derived from the F1 hybrid of a cross between an indica cultivar and a japonica cultivar, was used to map quantitative trait loci (QTL) controlling numbers of vascular bundles in peduncle, primary rachis branches and the ratio of vascular bundles to primary rachis branches (V/R ratio). For vascular bundles, three QTL were detected. Among them, the QTL qVB-8 with the largest effect individually accounted for 31.1% of the total variation. Two QTL controlling primary rachis branches were identified and they were co-located with 2 of the 3 QTL for vascular bundles respectively. Three QTL for the V/R ratio were mapped on chromosome 1, 2 and 8, respectively. Of the three QTL, the QTL qV/R-1 with the largest additive effect, explained 25.3% of the total variation, was located on chromosome 1 and found to be closely linked to the gene sh-2, a major gene underlying grain-shattering ability. In addition, four and two pairs of significant epistatic QTL were detected for vascular bundles and the V/R ratio, respectively, but none for rachis branches. Our results suggested that the numbers of vascular bundles and primary rachis branches were independently controlled by different polygenic systems, but the two polygenic systems shared a fraction of quantitative trait loci. It was also shown that the chromosome region carrying the QTL qV/R-1 on chromosome 1 might play an important role in the processes of indica-japonica differentiation in rice.

Chromosome Mapping↗
PubMed2004

Quantitative trait loci for male reproductive traits in beef cattle.

The objective of the present study was to detect quantitative trait loci (QTL) for male reproductive traits in a half-sib family from a Bos indicus (Brahman) x Bos taurus (Hereford) sire. The sire was mated with MARC III (1/4 Hereford, 1/4 Angus, 1/4 Red Poll and 1/4 Pinzgauer) cows. Testicular traits were measured from 126 male offspring born in 1996 and castrated at 8.5 months. Traits analysed were concentration of follicle stimulating hormone in peripheral blood at castration (FSH), paired testicular weight (PTW) and paired testicular volume (PTV) adjusted for age of dam, calculated age at puberty (AGE), and body weight at castration (BYW). A putative QTL was observed for FSH on chromosome 5. The maximum F-statistic was detected at 70 cM from the beginning of the linkage group. Animals inheriting the Hereford allele had a 2.47-ng/ml higher concentration of FSH than those inheriting the Brahman allele. Evidence also suggests the existence of a putative QTL on chromosome 29 for PTW, PTV, AGE and BYW. The maximum F-statistic was detected at cM 44 from the beginning of the linkage group for PTW, PTV and AGE, and at cM 52 for BYW. Animals that inherited the Brahman allele at this chromosomal region had a 45-g heavier PTW, a 42-cm(3) greater PTV, a 39-day younger AGE and a 22.8-kg heavier BYW, compared with those inheriting the Hereford allele. This is the first report of QTL for male reproductive traits in cattle.

Age Factors↗
PubMed2005

Further evidence of a quantitative trait locus on chromosome 18 influencing postural change in systolic blood pressure: the Hypertension Genetic Epidemiology Network (HyperGEN) Study.

BACKGROUND: Postural change in systolic blood pressure (SBP) is prospectively associated with several disease outcomes including hypertension, stroke, and coronary heart disease. The objective of this study was to characterize further a possible quantitative trait locus on chromosome 18q21 influencing SBP response to a postural challenge. METHODS: A prior genome scan of postural SBP response in 636 subjects of white ethnicity from 285 hypertensive sibships in the Hypertension Genetic Epidemiology Network (HyperGEN) indicated suggestive evidence for linkage on chromosome 18q21. This study included a de novo set of 452 African American pedigrees from the HyperGEN study and an expanded set of 372 white pedigrees. Variance components linkage analysis of postural SBP change was conducted using microsatellite markers on chromosome 18, and association studies were performed with a common single nucleotide polymorphism (variant 13) in the gene encoding NEDD4L, a key regulator of fine sodium reabsorption in the distal nephron. RESULTS: Combined analysis of all white and African American pedigrees yielded a LOD score of 4.25 at 80 cM on chromosome 18q21, with at least nominal evidence of linkage at this position in both white (LOD: 3.43) and African American (LOD: 1.14) subjects. Postural SBP response was associated with variant 13 of the NEDD4L in a subset of white subjects taking medications effective in treating sodium volume-dependent hypertension (alpha1-blockers, calcium channel blockers, and/or diuretics). CONCLUSION: These data provide further evidence for a quantitative trait locus on chromosome 18q21 influencing postural change in SBP.

Adult↗
PubMed2004

Quantitative trait loci affecting health traits in Swedish dairy cattle.

The purpose of this study was to map quantitative trait loci (QTL) affecting health traits in Swedish dairy cattle. A genome scan covering 17 chromosomes was performed. Ten grandsire families were used in a granddaughter design. Nine of the families belonged to the Swedish Red and White breed, which is related to other Nordic Ayrshire breeds, and one family was of the Swedish Holstein breed. A total of 417 bulls were genotyped for 116 microsatellite markers distributed over 17 chromosomes. Daughter yield deviations for clinical mastitis, somatic cell count (SCC), and other diseases (OD) were included in the analysis. Least squares interval mapping using putative QTL as cofactors was applied both within and across grandsire families. Significance thresholds were set by permutation tests. In the across-family analysis, we detected 8 suggestive QTL and 3 QTL significant at the genome level. The QTL affecting clinical mastitis were found on 3 chromosomes (9, 11, and 25), 4 QTL for SCC were found (on chromosomes 5, 9, 11, and 23), and we detected 4 QTL for OD (on chromosomes 9, 11, 15, and 25). In addition, we found several QTL that segregated within single families but where the QTL effect was not significant in the across-family analysis. In conclusion, we were able to locate QTL for all 3 analyzed traits, and overlapping QTL for several traits were observed.

Animals↗
PubMed2001

The power to detect linkage disequilibrium with quantitative traits in selected samples.

Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL-marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis.

Alleles↗
PubMed2005

Chromosomes 18 and X are quantitative trait loci for nephrotic-range proteinuria in rats.

Numerous cellular and molecular perturbations have been studied to elucidate the pathogenic mechanisms underlying nephrotic-range proteinuria, which may in turn shed light on disease-specific mechanisms. We have analyzed the publicly available data from the PhysGen partial panel of consomic rats to determine whether there are quantitative trait loci that associate with nephrotic-range proteinuria. As of this writing, consomic rat strains subjected to the renal protocol have been bred by the Program for Genomic Applications for 15 of the 22 rat chromosomes for both genders, predominantly with the Brown-Norway (BN) and Dahl salt-sensitive (SS) strains as parents. We defined chromosomes of interest as consomic SS-xBN strains whose phenotype measurements differed significantly from SS but not BN strains, stratified by gender. We filtered and clustered differentially expressed genes by function in renal tissue from relevant strains. Proteinuria was significantly higher in male SS vs. male SS-18BN, and it was significantly higher in male SS vs. female SS. Functional clustering of differentially expressed genes yielded two specific functional clusters: apoptosis (p=0.022) and angiogenesis (p=0.046). Gene expression profiles demonstrated differential expression of apoptotic and angiogenic genes. However, TUNEL stains of renal tissue showed no significant difference in the number of apoptotic nuclei. We conclude that chromosomes 18 and X are quantitative trait loci for nephrotic-range proteinuria in rats.

Animals↗
PubMed2003

Removing phenotypic distribution assumptions from tests of linkage disequilibrium for quantitative traits.

The transmission disequilibrium test (TDT) has become a family-based method of reference to search for linkage disequilibrium (LD). Although it was first developed for dichotomous traits, numerous approaches have extended the TDT to quantitative phenotypes that either rely on regression or variance component techniques. Both of these approaches are based on some phenotypic distribution assumptions, the violation of which can lead to inflation of type I error rates, and derive information from phenotypic variability, so that their power is very low under some selection schemes (e.g., one-tailed selection). We propose a new family-based test of association for quantitative traits, denoted maximum-likelihood-binomial (MLB)-QTDT, which addresses the two previous issues by incorporating a latent binary variable that captures the LD information between the marker allele and the quantitative phenotype. The method can be understood as a classical TDT for binary traits that would include pure affected and pure unaffected children, and the probability for a child to be affected or unaffected depends on his/her quantitative phenotypic value. Simulation studies under the null hypothesis show that the MLB-QTDT provides very consistent type I errors even in small and/or selected samples. Under the alternative hypothesis, the MLB-QTDT has good power to analyze one-tailed selected samples, and performs as well as a classical approach in other designs. The MLB-QTDT is a flexible distribution-free method to test for LD with quantitative phenotypes in nuclear families, and can easily incorporate previous extensions developed in the context of family-based association studies with binary traits.

Alleles↗
PubMed1995

Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti.

Susceptibility of the mosquito Aedes aegypti to the malarial parasite Plasmodium gallinaceum was investigated as a quantitative trait using restriction fragment length polymorphisms (RFLP). Two F2 populations of mosquitoes were independently prepared from pairwise matings between a highly susceptible and a refractory strain of A. aegypti. RFLP were tested for association with oocyst development on the mosquito midgut. Two putative quantitative trait loci (QTL) were identified that significantly affect susceptibility. One QTL, pgs[2,LF98], is located on chromosome 2 and accounted for 65 and 49% of the observed phenotypic variance in the two populations, respectively. A second QTL, pgs[3,MalI], is located on chromosome 3 and accounted for 14 and 10% of the observed phenotypic variance in the two populations, respectively. Both QTL exhibit a partial dominance effect on susceptibility, wherein the dominance effect is derived from the refractory parent. No indication of epistasis between these QTL was detected. Evidence suggests that either a tightly linked cluster of independent genes or a single locus affecting susceptibility to various mosquito-borne parasites and pathogens has evolved near the LF98 locus; in addition to P. gallinaceum susceptibility, this general genome region has previously been implicated in susceptibility to the filarial nematode Brugia malayi and the yellow fever virus.

Aedes↗
PubMed2005

Quantitative trait loci for novelty/stress-induced locomotor activation in recombinant inbred (RI) and recombinant congenic (RC) strains of mice.

The objective of the present study was to map and compare quantitative trait loci (QTLs) for an anxiety-related trait (novelty/stress-induced activation) in the AXB/BXA recombinant inbred (RI) and AcB/BcA recombinant congenic (RC) strains of mice derived from the A/J and C57BL/6J inbred progenitor strains. Activational responses to a novel open field (OF) were measured under identical stressful conditions (no prior handling or exposure to testing procedures) in both the RI and RC strains. Naive male and female mice were weighed, injected with IP saline and locomotor activity was monitored in a computerized OF apparatus for 15 min. Measures obtained from this experimental design included: (1) total activity scores, (2) time course of response (5 min time blocks over the 15 min session). Data for the RI strains were subjected to a QTL analysis using composite interval mapping. Significant loci were identified on chr 5 (D5Mit356, 41 cM), chr 8 (D8Mit305, 37 cM) and chr 14 (D14Mit36, 6 3cM). Single locus association analysis of the AcB/BcA RC strains identified 15 putative regions, 7 of which overlapped regions independently mapped in the RI strains on chr 1 (58.5-63.1cM), chr 4 (21.9-28.6 cM), chr 5 (19-45 & 74-86 cM), chr 6 (0.5-20.4cM), chr 9 (15-38 cM), chr 13 (47cM) and chr 19 (47cM). The loci identified on chr 5 near D5Mit356 (41cM) in both the AXB/BXA RIS and AcB/BcA RCS maps to a region containing the genes for several GABA(A) receptor subunits. Additionally, the present study provides further confirmation of a frequently identified QTL on chromosome 1. The results are discussed in the context of previous QTL studies of anxiety-related traits that have used genetic crosses that include the A or B6 progenitors.

Analysis of Variance↗
PubMed2005

Smoothing of the bivariate LOD score for non-normal quantitative traits.

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Alcoholism↗
PubMed2005

Quantitative trait loci analysis of heat stress resistance of spermatocytes in the MRL/MpJ mouse.

The MRL/MpJ mouse has previously been reported to possess an interesting phenotype in which spermatocytes are resistant to the abdominal temperature heat shock. In this study genetic analysis for it was performed. The phenotypes of F2 progenies produced by mating MRL/MpJ and control strain C57BL/6 mice were not segregated into two types as parental phenotypes, suggesting that the phenotype is controlled by multiple genetic loci. Thus, quantitative trait loci (QTL) analysis was performed using 98 microsatellite markers. The weight ratio of the cryptorchid testis to the intact testis (testis weight ratio) and the Sertoli cell index were used for quantitative traits. QTL analysis revealed two significant QTLs located on Chrs 1 and 11 for testis weight ratio and one significant QTL located in the same region of Chr 1 for the Sertoli cell index. A microsatellite marker locus located in the peak of the QTL on Chr 1 did not recombine with the exonuclease 1 (Exo1) gene locus in 140 F2 progenies. Mutation of the Exo1 gene was previously reported to be responsible for metaphase-specific apoptosis (MSA) of spermatocytes in the MRL/MpJ mouse. These results raise the possibility that mutation of the Exo1 gene is responsible for both MSA and heat stress resistance of spermatocytes in the MRL/MpJ mouse.

Animals↗
PubMed2006

Identification of quantitative trait loci affecting body composition in a mouse intercross.

Gravimetric analysis and dual energy x-ray absorptiometry densitometry were used to determine lean, fat, and bone tissue traits in a F(2) mouse population from a C57BL/6J and CASA/Rk intercross (B6CASAF2). These traits were used in a linkage analysis to identify quantitative trait loci that affect body composition. Linkage mapping showed that body weight (BW) loci on proximal chromosome 2 occurred in the same region as body length, lean tissue mass, and bone mineral content and on chromosome 13 in the same region as lean tissue mass, bone mineral density, and bone mineral content. Fat-related loci occurring on mid-chromosome 2 near 60 cM, proximal chromosome 6, and mid-chromosome 10 were distinct from BW, lean tissue, and bone tissue loci. In B6CASAF2 females, heterozygotes and CASA/Rk homozygotes at the chromosome 6 locus marker had higher body fat percentages, and this locus was responsible for 11% of the variance for body fat percentage. Female heterozygotes and C57BL/6J homozygotes at the chromosome 15 locus marker had higher bone mineral densities, and this locus could explain 8% of that trait's variance. A survey of the literature did not reveal any previous reports of fat-specific loci in the chromosomal 10 region near 42 cM reported in this study. The results of this study indicate that BW and BMI have limited usefulness as phenotypes in linkage or association studies when used as obesity phenotypes.

Adipocytes↗