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PubMed2006

Shrinkage estimation method for mapping multiple quantitative trait loci.

In this article, shrinkage estimation method for multiple-marker analysis and for mapping multiple quantitative trait loci (QTL) was reviewed. For multiple-marker analysis, Xu (Genetics, 2003, 163:789-801) developed a Bayesian shrinkage estimation (BSE) method. The key to the success of this method is to allow each marker effect have its own variance parameter, which in turn has its own prior distribution so that the variance can be estimated from the data. Under this hierarchical model, a large number of markers can be handled although most of them may have negligible effects. Under epistatic genetic model, however, the running time is very long. To overcome this problem, a novel method of incorporating the idea described above into maximum likelihood, known as penalized likelihood method, was proposed. A simulated study showed that this method can handle a model with multiple effects, which are ten times larger than the sample size. For multiple QTL analysis, two modified versions for the BSE method were introduced: one is the fixed-interval method and another is the variable-interval method. The former deals with markers with intermediate density, and the latter can handle markers with extremely high density as well as model with epistatic effects. For the detection of epistatic effects, penalized likelihood method and the variable-interval approach of the BSE method are available.

Bayes Theorem↗
PubMedDate not supplied

Linkage disequilibrium fine mapping of quantitative trait loci: a simulation study.

Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance.

Animals↗
PubMed1996

A genome-wide search for quantitative trait loci underlying asthma.

Asthma now affects one child in seven in the United Kingdom. Most cases (95%) of childhood asthma are associated with atopy, the immunoglobulin E (IgE)-mediated familial syndrome of allergic asthma, eczema and rhinitis. Segregation analysis has consistently suggested the presence of major genes influencing atopy and IgE levels, with the expectation that these genes may be identified by positional cloning or the examination of candidate genes. Here we report the results of a genome-wide search for linkage to one qualitative and four quantitative traits associated with allergic (atopic) asthma. We have identified six potential linkages (P<0.001), five of which are to quantitative traits. Monte Carlo simulations show that 1.6 false-positive linkages at this level of significance would be expected from the data. One linkage, to chromosome 11q13, has been established previously. Three of the new loci show evidence of linkage to a second panel of families, in which maternal effects and pleiotropy of linked phenotypes are seen. The results demonstrate the extent and the complexity of the genetic predisposition to asthma.

Adolescent↗
PubMed2003

Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle.

A whole genome scan of Finnish Ayrshire was conducted to map quantitative trait loci (QTL) affecting milk production. The analysis included 12 half-sib families containing a total of 494 bulls in a granddaughter design. The families were genotyped with 150 markers to construct a 2764 cM (Haldane) male linkage map. In this study interval mapping with multiple-marker regression approach was extended to analyse multiple chromosomes simultaneously. The method uses identified QTL on other chromosomes as cofactors to increase mapping power. The existence of multiple QTL on the same linkage group was also analyzed by fitting a two-QTL model to the analysis. Empirical values for chromosome-wise significance thresholds were determined using a permutation test. Two genome-wise significant QTL were identified when chromosomes were analyzed individually, one affecting fat percentage on chromosome (BTA) 14 and another affecting fat yield on BTA12. The cofactor analysis revealed in total 31 genome-wise significant QTL. The result of two-QTL analysis suggests the existence of two QTL for fat percentage on BTA3. In general, most of the identified QTL confirm results from previous studies of Holstein-Friesian cattle. A new QTL for all yield components was identified on BTA12 in Finnish Ayrshire.

Animals↗
PubMed2004

Evidence of a novel quantitative-trait locus for obesity on chromosome 4p in Mexican Americans.

Although several genomewide scans have identified quantitative-trait loci influencing several obesity-related traits in humans, genes influencing normal variation in obesity phenotypes have not yet been identified. We therefore performed a genome scan of body mass index (BMI) on Mexican Americans, a population prone to obesity and diabetes, using a variance-components linkage analysis to identify loci that influence BMI. We used phenotypic data from 430 individuals (26% diabetics, 59% females, mean age +/- SD = 43 +/- 17 years, mean BMI +/- SD = 30.0 +/- 6.7, mean leptin (ng/ml) +/- SD = 22.1 +/- 17.1) distributed across 27 low-income Mexican American pedigrees who participated in the San Antonio Family Diabetes Study (SAFDS) for whom a 10-15-cM map is available. In this genomewide search, after accounting for the covariate effects of age, sex, diabetes, and leptin, we identified a genetic region exhibiting the most highly significant evidence for linkage (LOD 4.5) with BMI on chromosome 4p (4p15.1) at 42 cM, near marker D4S2912. This linkage result has been confirmed in an independent linkage study of severe obesity in Utah pedigrees. Two strong positional candidates, the human peroxisome proliferator-activated receptor gamma coactivator 1 (PPARGC1) and cholecystokinin A receptor (CCKAR) with major roles in the development of obesity, are located in this region. In conclusion, we identified a major genetic locus influencing BMI on chromosome 4p in Mexican Americans.

Body Mass Index↗
PubMed2006

Transmission disequilibrium test for quantitative trait loci detection in livestock populations.

The performance of several transmission disequilibrium tests (TDT) for detection of quantitative trait loci (QTL) in data structures typical of outbred livestock populations were investigated. Factorial mating designs were simulated with 10 sires mated to either 50 or 200 dams, each family having five or eight full sibs. A single marker and QTL, both bi-allelic, were simulated using a disequilibrium coefficient based on complete initial disequilibrium and 50 generations of recombination [i.e. D = D(0)(1 - theta)50], where theta is the recombination fraction between marker and QTL. The QTL explained either 10% (small QTL) or 30% (large QTL) of the genetic variance for a trait with heritability of 0.3. Methods were: TDT for QTL (Q-TDT; both parents known), 1-TDT (only one parent known) and sibling-based TDT (S-TDT; neither parent known, but sibs available). All were found to be effective tests for association and linkage between the QTL and a tightly linked marker (theta < 0.02) in these designs. For a large QTL, theta = 0.01, and five full sibs per family, the empirical power for Q-TDT, 1-TDT and S-TDT was 0.966, 0.602 and 0.974, respectively, in a large population, versus 0.700, 0.414 and 0.654, respectively, in a small population. For a small QTL effect, theta = 0.01, large population the empirical power of these tests were 0.709, 0.287 and 0.634. The power of Q-TDT, 1-TDT and S-TDT was satisfactory for large populations, for QTL with large effects and for five full sibs per family. The 1-TDT based on a linear model was more powerful than the normal 1-TDT. The empirical power for Q-TDT and 1-TDT with a linear model was 0.978 and 0.995 respectively. TDT based on analogous linear models, incorporating the polygenic covariance structure, provided only small increases in power compared with the usual TDT for QTL.

Algorithms↗
PubMed2002

Mapping quantitative trait loci for plant height in wheat (Triticum aestivum L.) using a F2:3 population.

To detect quantitative trait loci (QTLs) controlling plant height, the plant height of 240 F2:3 lines derived from the cross of a dwarf wheat line ND3338 with a tall line F390, was assessed in field trials at two locations with three replications in 2000 and 2001. Microsatellite markers were used to construct a framework linkage map containing 215 loci with 21 linkage groups, and covering the whole genome about 3600cM. With the method of interval mapping, seven putative QTLs affecting plant height were detected on chromosomes 1B, 4B (two regions), 6A (two regions), 6D and 7A, respectively. Phenotypic variations explained by each QTL ranged from 5.2% to 50.1%, and in each environment the total putative QTLs explained about 64.8%-75% of the total phenotypic variation respectively. A major QTL located on chromosome arm 4BS near the locus Xgwm113, around the Rht-Blb locus, explained a large part of the phenotypic variation (27.8%-36.2% depending on the years or the locations). Except the QTL on chromosome 7A, all the other QTLs from ND3338 decreased the plant height, variously from 0.94 cm to 9.33 cm. Most of the identified QTLs were consistent in all the environments, and should be useful in future marker-assisted-selection programs for breeding dwarf and semi-dwarf wheat cultivars.

Chromosome Mapping↗
PubMed2006

A genome scan for quantitative trait loci associated with body weight at different developmental stages in chickens.

A genome scan to detect quantitative trait loci (QTL) affecting body weight in chickens was conducted on 238 F(2) chickens from a reciprocal cross of Silky Fowl and White Plymouth Rock using 125 microsatellite markers covering 23 autosomes and the Z chromosome. Two types of QTL were considered: static QTL (SQ) and developmental QTL (DQ). Static QTL affected the body weight from hatch to time t, and DQ affected the body weight from time t-1 to time t. Six SQ and nine DQ were detected. Of these QTL, four reached a genome-wide significance of 5% or better, with SQ1 and DQ1 being the most significant QTL. Static QTL1 was on chromosome 1 between GCT0006 and MCW0106 and explained 4.05-9.80% of the phenotypic variation in body weights from 3 to 12 weeks of age. At 9, 10 and 11 weeks, the genome-wide significance thresholds of SQ1 were <1%. Developmental QTL1 was located on chromosome 1 between MCW0168 and GCT0006, and explained 2.75% of the phenotypic variation for body weight from week 7 to 8 with a genome-wide significance level <1%. The results suggest that body weight from hatch to time t and developmental growth from time t-1 to time t may involve two different sets of genes or gene actions.

Animals↗
PubMed1999

Identification of an acute ethanol response quantitative trait locus on mouse chromosome 2.

A two-stage strategy was used to identify and confirm quantitative trait loci (QTLs) associated with the changes in locomotor activity induced by a 1.5 gm/kg ethanol challenge. For stage 1, putative QTLs were identified by analysis of the strain means for 25 strains of the BXD recombinant inbred (RI) series (males only). QTLs were identified on chromosomes 1, 2, 4, and 6. The activity response to chlordiazepoxide generated similar QTLs on chromosomes 2 and 6. None of the QTLs were similar to those generated from analysis of the saline response data. For stage 2, 900 male C57BL/6J (B6) x DBA/2J (D2) F2 intercross animals were phenotyped for ethanol response, and the phenotypic extremes (those animals > and <1 SD from the mean) were identified. These extremes differed by >10,000 cm/15 min in their response to ethanol. The extreme progeny were used for a genome-wide scan both to confirm the putative RI-generated QTLs and to detect new QTLs. The F2 analysis generated no new QTLs with logarithm of the likelihood for linkage (LOD) scores >3. For RI-generated QTLs, only the QTL on chromosome 2 was confirmed (LOD = 5.3). The position of the peak LOD was estimated to be 47 cM with a 20 cM 1 LOD support interval; this QTL accounted for 6% of the phenotypic variance. The 1 LOD support interval overlaps with QTLs previously identified for alcohol preference and acute ethanol withdrawal (;; ).

Animals↗
PubMed1999

Time-related mapping of quantitative trait loci underlying tiller number in rice.

Using time-related phenotypic data, methods of composite interval mapping and multiple-trait composite interval mapping based on least squares were applied to map quantitative trait loci (QTL) underlying the development of tiller number in rice. A recombinant inbred population and a corresponding saturated molecular marker linkage map were constructed for the study. Tiller number was recorded every 4 or 5 days for a total of seven times starting at 20 days after sowing. Five QTL were detected on chromosomes 1, 3, and 5. These QTL explained more than half of the genetic variance at the final observation. All the QTL displayed an S-shaped expression curve. Three QTL reached their highest expression rates during active tillering stage, while the other two QTL achieved this either before or after the active tillering stage.

Chromosome Mapping↗
PubMed2006

Quantitative trait loci determining weight reduction of testes and pituitary by diethylstilbesterol in LEXF and FXLE recombinant inbred strain rats.

Increasing exposure to environmental endocrine disruptor, xeno-estrogen, is a serious hazard to male reproductive activity. To explore possible genetic control in susceptibility to xeno-estrogen, the weight reduction of testes induced by the continuous administration of a synthetic estrogen, diethylstilbesterol, were investigated by quantitative trait analysis in LEXF and FXLE recombinant inbred strain rats, consisting of 21 independent strains, 9 of their substrains, parental F344/Stm and LE/Stm strains, and (F344 x LE)F1. For the weight of testes, one highly significant quantitative trait locus (QTL) and one significant QTL were mapped on chromosomes 7 and 1, respectively. The QTL on chromosome 7 is closely associated with c-myc. Pituitary weight and serum prolactin were also variable among recombinant inbred strains, but no QTL was detected for them in this study.

Animals↗
PubMed1997

Familial aggregation of obesity, candidate genes and quantitative trait loci.

This brief review covers the findings reported in 1996 and in the first 2 months of 1997 on the genetic epidemiology and the molecular markers of human obesity. Although relatively little new evidence has been published on the heritability and other genetic epidemiology characteristics of obesity and fat topography, more has been reported on candidate genes, positional candidate genes and quantitative trait loci. Two recent genome-wide scans have revealed that several molecular markers on different chromosomes were linked to obesity-related phenotypes. Little support for a role for specific candidate genes can be found at this time. A large number of rodent quantitative trait loci have been uncovered so far but they have not yet been systematically tested in human populations.

Adaptor Proteins, Signal Transducing↗
PubMed2003

A haplotype-based algorithm for multilocus linkage disequilibrium mapping of quantitative trait loci with epistasis.

For tightly linked loci, cosegregation may lead to nonrandom associations between alleles in a population. Because of its evolutionary relationship with linkage, this phenomenon is called linkage disequilibrium. Today, linkage disequilibrium-based mapping has become a major focus of recent genome research into mapping complex traits. In this article, we present a new statistical method for mapping quantitative trait loci (QTL) of additive, dominant, and epistatic effects in equilibrium natural populations. Our method is based on haplotype analysis of multilocus linkage disequilibrium and exhibits two significant advantages over current disequilibrium mapping methods. First, we have derived closed-form solutions for estimating the marker-QTL haplotype frequencies within the maximum-likelihood framework implemented by the EM algorithm. The allele frequencies of putative QTL and their linkage disequilibria with the markers are estimated by solving a system of regular equations. This procedure has significantly improved the computational efficiency and the precision of parameter estimation. Second, our method can detect marker-QTL disequilibria of different orders and QTL epistatic interactions of various kinds on the basis of a multilocus analysis. This can not only enhance the precision of parameter estimation, but also make it possible to perform whole-genome association studies. We carried out extensive simulation studies to examine the robustness and statistical performance of our method. The application of the new method was validated using a case study from humans, in which we successfully detected significant QTL affecting human body heights. Finally, we discuss the implications of our method for genome projects and its extension to a broader circumstance. The computer program for the method proposed in this article is available at the webpage http://www.ifasstat.ufl.edu/genome/~LD.

Algorithms↗
PubMed2005

Cross-species replication of a serum osteocalcin quantitative trait locus on human chromosome 16q in pedigreed baboons.

Osteocalcin (OC), a serum marker of bone formation, in its intact form reflects osteoblast activity. It is of interest to clinicians and bone biologists due to easy measurability and potential utility as an identifier of those at risk for fracture and other complications associated with bone metabolism disorders. The only published linkage study in humans shows significant evidence for a quantitative trait locus (QTL) affecting OC levels on 16q. We used the baboon, a primate model for skeletal maintenance and turnover, to detect and quantify the effects of genes on serum OC levels and to localize chromosomal regions harboring the responsible loci. We assayed OC levels in 591 pedigreed animals, assessed OC heritability, and conducted a genomewide linkage scan for evidence of QTLs affecting this phenotype. Heritability in these baboons is 0.24. Suggestive linkage is evident with markers in a region homologous to human chromosome 16q. This first genomewide linkage scan in a nonhuman primate for QTLs affecting bone formation as reflected by OC levels provides cross-species replication of the QTL on chromosome 16q previously localized in humans. Given the concordance of results of the only two genome scans for this trait in two primate species, further studies of this region are warranted.

Animals↗
PubMed2005

An independent confirmation of a quantitative trait locus for milk yield and composition traits on bovine chromosome 26.

Several reports have demonstrated that bovine chromosome 26 (BTA26) harbours significant or suggestive quantitative trait loci (QTL) for milk production and composition traits in dairy cattle. Our previous study showed that a C/T substitution in the bovine TCF7L2 gene on BTA26 was significantly linked to QTL for protein yield (PY) in a Canadian dairy cattle population. Actually, this polymorphism was one of the markers derived from a genome-wide screening of QTL for milk PY using an amplified fragment length polymorphism technique combined with a DNA pooling strategy. In the present study, 990 Holstein bulls with complete genotype and phenotype data from 14 sire families were analysed to confirm, if the QTL effects exist in other populations. Statistical analysis revealed that this marker was significantly associated with PY, protein percentage, milk yield and fat yield (FY) (p < 0.001) in the US Holstein population. These results indicate that this QTL region has a pleiotrophic effecton different milk traits and is portable in different populations.

Analysis of Variance↗
PubMed2004

Quantitative trait loci controlling phenotypes related to the perennial versus annual habit in wild relatives of maize.

We used quantitative trait locus/loci (QTL) mapping to study the inheritance of traits associated with perennialism in a cross between an annual (Zea mays ssp. parviglumis) and a perennial (Z. diploperennis) species of teosinte. The most striking difference between these species is that Z. diploperennis forms rhizomes, whereas Z. mays ssp. parviglumis lacks these over-wintering underground stems. An F2 population of 425 individuals was genotyped at 95 restriction fragment length polymorphism marker loci and the association between phenotype and genotype was analyzed by composite interval mapping. We detected a total of 38 QTL for eight traits. The number of QTL found for each trait ranged from two for rhizome formation to nine for tillering. QTL for six of the traits mapped near each other on chromosome 2, and QTL for four traits mapped near each other on chromosome 6, suggesting that these regions play an important role in the evolution of the perennial habit in teosinte. Most of the 38 QTL had small effects, and no single QTL showed a strikingly large effect. The map positions that we determined for rhizome formation and other traits in teosinte may help to locate corresponding QTL in pasture and turf grasses used as forage for cattle and for erosion control in agro-ecosystems.

Chromosome Mapping↗
PubMed2003

Quantitative trait loci analysis of nitrogen use efficiency in Arabidopsis.

Improving plant nitrogen (N) use efficiency or controlling soil N requires a better knowledge of the regulation of plant N metabolism. This could be achieved using Arabidopsis as a model genetic system, taking advantage of the natural variation available among ecotypes. Here, we describe an extensive study of N metabolism variation in the Bay-0 x Shahdara recombinant inbred line population, using quantitative trait locus (QTL) mapping. We mapped QTL for traits such as shoot growth, total N, nitrate, and free-amino acid contents, measured in two contrasting N environments (contrasting nitrate availability in the soil), in controlled conditions. Genetic variation and transgression were observed for all traits, and most of the genetic variation was identified through QTL and QTL x QTL epistatic interactions. The 48 significant QTL represent at least 18 loci that are polymorphic between parents; some may correspond to known genes from the N metabolic pathway, but others represent new genes controlling or interacting with N physiology. The correlations between traits are dissected through QTL colocalizations: The identification of the individual factors contributing to the regulation of different traits sheds new light on the relations among these characters. We also point out that the regulation of our traits is mostly specific to the N environment (N availability). Finally, we describe four interesting loci at which positional cloning is feasible.

Amino Acids↗
PubMed1997

The power of iterated generalized least squares (GLS) method to detect direct relationships in the analysis of correlated quantitative traits.

We examined the power of the stepwise iterated generalized least squares (GLS) method by modeling the relationship between quantitative traits and other variables using the simulated data for Problem 2A. The comparison between the generating model provided by the workshop and the results of the stepwise iterated GLS model showed that this method could be used as a first step in identifying the underlying model for genetic data. The estimated covariance matrices also provide useful information about the genetic properties of the traits.

Computer Simulation↗