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PubMed2006

Linkage disequilibrium interval mapping of quantitative trait loci.

BACKGROUND: For many years gene mapping studies have been performed through linkage analyses based on pedigree data. Recently, linkage disequilibrium methods based on unrelated individuals have been advocated as powerful tools to refine estimates of gene location. Many strategies have been proposed to deal with simply inherited disease traits. However, locating quantitative trait loci is statistically more challenging and considerable research is needed to provide robust and computationally efficient methods. RESULTS: Under a three-locus Wright-Fisher model, we derived approximate expressions for the expected haplotype frequencies in a population. We considered haplotypes comprising one trait locus and two flanking markers. Using these theoretical expressions, we built a likelihood-maximization method, called HAPim, for estimating the location of a quantitative trait locus. For each postulated position, the method only requires information from the two flanking markers. Over a wide range of simulation scenarios it was found to be more accurate than a two-marker composite likelihood method. It also performed as well as identity by descent methods, whilst being valuable in a wider range of populations. CONCLUSION: Our method makes efficient use of marker information, and can be valuable for fine mapping purposes. Its performance is increased if multiallelic markers are available. Several improvements can be developed to account for more complex evolution scenarios or provide robust confidence intervals for the location estimates.

Animals↗
PubMed2000

Bayesian mapping of quantitative trait loci under the identity-by-descent-based variance component model.

Variance component analysis of quantitative trait loci (QTL) is an important strategy of genetic mapping for complex traits in humans. The method is robust because it can handle an arbitrary number of alleles with arbitrary modes of gene actions. The variance component method is usually implemented using the proportion of alleles with identity-by-descent (IBD) shared by relatives. As a result, information about marker linkage phases in the parents is not required. The method has been studied extensively under either the maximum-likelihood framework or the sib-pair regression paradigm. However, virtually all investigations are limited to normally distributed traits under a single QTL model. In this study, we develop a Bayes method to map multiple QTL. We also extend the Bayesian mapping procedure to identify QTL responsible for the variation of complex binary diseases in humans under a threshold model. The method can also treat the number of QTL as a parameter and infer its posterior distribution. We use the reversible jump Markov chain Monte Carlo method to infer the posterior distributions of parameters of interest. The Bayesian mapping procedure ends with an estimation of the joint posterior distribution of the number of QTL and the locations and variances of the identified QTL. Utilities of the method are demonstrated using a simulated population consisting of multiple full-sib families.

Alleles↗
PubMed1990

Fine mapping of quantitative trait loci using selected overlapping recombinant chromosomes, in an interspecies cross of tomato.

Quantitative trait loci (QTLs) have been mapped to small intervals along the chromosomes of tomato (Lycopersicon esculentum), by a method we call substitution mapping. The size of the interval to which a QTL can be mapped is determined primarily by the number and spacing of previously mapped genetic markers in the region surrounding the QTL. We demonstrate the method using tomato genotypes carrying chromosomal segments from Lycopersicon chmielewskii, a wild relative of tomato with high soluble solids concentration but small fruit and low yield. Different L. chmielewskii chromosomal segments carrying a common restriction fragment length polymorphism were identified, and their regions of overlap determined using all available genetic markers. The effect of these chromosomal segments on soluble solids concentration, fruit mass, yield, and pH, was determined in the field. Many overlapping chromosomal segments had very different phenotypic effects, indicating QTLs affecting the phenotype(s) to lie in intervals of as little as 3 cM by which the segments differed. Some associations between different traits were attributed to close linkage between two or more QTLs, rather than pleiotropic effects of a single QTL: in such cases, recombination should separate desirable QTLs from genes with undesirable effects. The prominence of such trait associations in wide crosses appears partly due to infrequent reciprocal recombination between heterozygous chromosomal segments flanked by homozygous regions. Substitution mapping is particularly applicable to gene introgression from wild to domestic species, and generally useful in narrowing the gap between linkage mapping and physical mapping of QTLs.

Alleles↗
PubMed1987

Homozygosity mapping: a way to map human recessive traits with the DNA of inbred children.

An efficient strategy for mapping human genes that cause recessive traits has been devised that uses mapped restriction fragment length polymorphisms (RFLPs) and the DNA of affected children from consanguineous marriages. The method involves detection of the disease locus by virtue of the fact that the adjacent region will preferentially be homozygous by descent in such inbred children. A single affected child of a first-cousin marriage is shown to contain the same total information about linkage as a nuclear family with three affected children. Calculations show that it should be practical to map a recessive disease gene by studying DNA from fewer than a dozen unrelated, affected inbred children, given a complete RFLP linkage map. The method should make it possible to map many recessive diseases for which it is impractical or impossible to collect adequate numbers of families with multiple affected offspring.

Chromosome Mapping↗
PubMed2002

On the mapping of quantitative trait loci at marker and non-marker locations.

Previous studies have noted that the estimated positions of a large proportion of mapped quantitative trait loci (QTLs) coincide with marker locations and have suggested that this indicates a bias in the mapping methodology. In this study we predict the expected proportion of QTLs with positions estimated to be at the location of a marker and further examine the problem using simulated data. The results show that the higher proportion of putative QTLs estimated to be at marker positions compared with non-marker positions is an expected consequence of the estimation methods. The study initially focused on a single interval with no QTLs and was extended to include multiple intervals and QTLs of large effect. Further, the study demonstrated that the larger proportion of estimated QTL positions at the location of markers was not unique to linear regression mapping. Maximum likelihood produced similar results, although the accumulation of positional estimates at outermost markers was reduced when regions outside the linkage group were also considered. The bias towards marker positions is greatest under the null hypothesis of no QTLs or when QTL effects are small. This study discusses the impact the findings could have on the calculation of thresholds and confidence intervals produced by bootstrap methods.

Animals↗
PubMed2001

The application of capillary electrophoresis for DNA polymorphism analysis.

CE fractions may also be collected and then subjected to additional analysis. Nanoliter fractions containing size or shape fractionated DNA fragments can be collected on moving affinity membranes (125) or into sample chambers (126). The exact timing of the collection steps is achieved by determining the velocity of each individual zone measured between two detection points near the end of the capillary. The DNA samples may subsequently be identified by probe hybridization, or by PCR-linked sequencing. Capillary fractions containing metabolites and derivatives of DNA and small DNA adducts can also be sampled, and then characterized directly by highly sensitive MALDI-TOF atomic analysis (112-118) and ESI-MS (118,119). The automation and integration of PCR and CE analysis (PCR-CE) on a microchip (3-12,96) will also contribute greatly to its adoption as the analysis tool of choice. Significantly, these tools will be applied for DNA sequencing (75,108), for genome mapping (65) and genotyping (42-46), for improved certainty in disease detection (3-6,107,120) and for DNA mutation analysis (2-12,27,58). Recent improvements in the design CAE arrays and associated equipment such as the radial CAE microplate and rotary confocal signal detection system (127) overcome some of the detection limitations of linear CAE and microchip devices and allow the parallel genotyping of 96 samples in about 120 s. The integration of microreactive capillary surface assays (128) and "in-capillary" analysis will also lead to further increases in the speed and sensitivity of CE-based analysis. The recent announcement of the completion of the first draft sequence of the 90% of the entire human genome within 6 mo by Celera Genomics by sequencing random DNA fragments using several hundred ABI 3700 machines (129) illustrates the enormous efficiency realized through the automation of DNA sequencing by CAE. Sequencing was performed at an average rate of approximately 6 x 10(9) bases/yr. The CAE machines will now be employed for a concerted resequencing of genome elements to create an extremely high-density polymorphism map of the entire genome (130). This map will be based principally on single nucleotide polymorphisms, and will catapult human medicine into a new era of closely detailed genetic trait mapping to identify the genetic basis of multi-gene diseases.

Animals↗
PubMed2002

Functional mapping of quantitative trait loci underlying the character process: a theoretical framework.

Unlike a character measured at a finite set of landmark points, function-valued traits are those that change as a function of some independent and continuous variable. These traits, also called infinite-dimensional characters, can be described as the character process and include a number of biologically, economically, or biomedically important features, such as growth trajectories, allometric scalings, and norms of reaction. Here we present a new statistical infrastructure for mapping quantitative trait loci (QTL) underlying the character process. This strategy, termed functional mapping, integrates mathematical relationships of different traits or variables within the genetic mapping framework. Logistic mapping proposed in this article can be viewed as an example of functional mapping. Logistic mapping is based on a universal biological law that for each and every living organism growth over time follows an exponential growth curve (e.g., logistic or S-shaped). A maximum-likelihood approach based on a logistic-mixture model, implemented with the EM algorithm, is developed to provide the estimates of QTL positions, QTL effects, and other model parameters responsible for growth trajectories. Logistic mapping displays a tremendous potential to increase the power of QTL detection, the precision of parameter estimation, and the resolution of QTL localization due to the small number of parameters to be estimated, the pleiotropic effect of a QTL on growth, and/or residual correlations of growth at different ages. More importantly, logistic mapping allows for testing numerous biologically important hypotheses concerning the genetic basis of quantitative variation, thus gaining an insight into the critical role of development in shaping plant and animal evolution and domestication. The power of logistic mapping is demonstrated by an example of a forest tree, in which one QTL affecting stem growth processes is detected on a linkage group using our method, whereas it cannot be detected using current methods. The advantages of functional mapping are also discussed.

Chromosome Mapping↗
PubMed1995

[Computer technology of gene geographic analysis of a gene pool: III. Derivation of trend surfaces].

A computer technology for obtaining a set of trend (background) maps on the basis of an original geographic map is reported. These trend maps reveal the patterns of distribution of the mapped trait. The technology allows one to shape the reliefs of the genetic surfaces that reflect patterns having different origin and appearing at different times, via changing the parameters of algorithms for averaging and approximation. The set of maps, which is obtained with the use of approximation methods, simulates the hypotheses of the through trend and of the mono-, di-, or polycentric distribution of the trait. New methods for deriving the trend surfaces on the basis of averaging throughout the area of either the "moving window" or the window of variable size ("changing window") are proposed. The informative significance of maps that are obtained with the use of Chebyshev polynomials of high (up to several tens of) degrees is demonstrated.

Algorithms↗
PubMed2000

Quantitative trait loci and candidate gene mapping of bud set and bud flush in populus.

The genetic control of bud phenology in hybrid poplar was studied by mapping quantitative trait loci (QTL) affecting the timing of autumn bud set and spring bud flush. The founders of the mapping pedigree were collected from widely separated latitudes to maximize segregating variation for dormancy-related traits in the F(2) generation-the female Populus trichocarpa parent is from Washington State (48 degrees N) and the male P. deltoides parent is from Texas (31 degrees N). Bud set and bud flush timing were measured on the F(2) generation in a replicated clonal field trial. Using a linkage map constructed of AFLP and microsatellite markers, three QTL controlling bud set and six QTL controlling bud flush were detected. Additionally, five candidate genes believed to be involved in perception of photoperiod (PHYB1, PHYB2) or transduction of abscisic acid response signals (ABI1B, ABI1D, and ABI3) were placed on the QTL map. PHYB2 and ABI1B were found to be coincident with QTL affecting bud set and bud flush.

Base Sequence↗
PubMed2001

Mapping of quantitative trait loci with knockout/congenic strains.

Recently we have explored the use of knockout/congenic mouse strains for isolating and mapping quantitative trait loci (QTLs). Because most knockout strains have been bred to be B6.129 congenic strains, they can be used to test for QTLs in the targeted chromosomal area as long as there is a genetic difference between B6 and 129. Thus, we have tested a number of knockout/congenic strains in a series of behavioral tests in which mouse performance has a significant genetic component. We have also developed a breeding scheme for distinguishing the effects of background flanking genes from the targeted ablation. In screening several knockout/congenics, we have found at least one that harbors a behavioral QTL in the 129 chromosomal segment. The position of this QTL was confirmed subsequently by several F1 crosses.

Animals↗
PubMed2000

Fine-mapping of quantitative trait loci in half-sib families using current recombinations.

Two groups of methods are being developed to fine-map quantitative trait loci (QTLs): identity-by-descent methods or methods using historical recombinations, and genetic chromosome dissection methods or methods utilizing current recombinations. Here we propose two methods that fall into the second group: contrast mapping and substitution mapping. A QTL has previously been detected via linkage mapping in a half-sib design (granddaughter or daughter design), and sires (grandsires) likely to be heterozygous at the QTL have been identified. A sire (grandsire) and its recombinant offspring are then genotyped for a series of ordered markers spanning the initial marker interval. Offspring are grouped by paternal multi-marker haplotype with haplotypes differing in the location of the recombination event. In the contrast method, contrasts between the phenotypic averages of haplotypes or offspring groups are calculated which correspond to marker intervals within the original interval. The expected value of the contrast for the true QTL interval is always maximum, hence the interval with maximum observed contrast is assumed to contain the QTL. Alternative statistics for determining the interval most likely to contain a QTL are presented for contrast mapping, as well as a bootstrap estimation of the probability of having identified the correct interval. For an initial marker bracket of 20 cM and 10 additional equidistant markers, the probability of assigning the QTL to the correct 2 cM marker interval or to a combined 4 cM interval was calculated. For substitution effects of 0.093, 0.232, 0.464, 0.696 and 0.928 (in additive genetic SD), power values near 0.14, 0.26, 0.48, 0.67 and 0.80 (0.25, 0.53, 0.86, 0.97 and 0.99) are achieved for a family of 200 (1000) sons, respectively. In substitution mapping, QTL segregation status of recombinant sons must be determined using daughter genotyping. Combinations of two haplotypes with their segregation status are required to assign the QTL to an interval. Probabilities of correct QTL assignment were calculated assuming absence of the mutant QTL allele in dams of sons. For a 2 cM interval and a QTL at the midpoint of an interval, power near 0.95 (0.90) is reached when the number of recombinant sons is 70 (60), or total number of sons is 424 (363). For QTL positions away from the midpoint, power decreases but can be improved by combining marker intervals. For a QTL located halfway to the midpoint, and 182 sons in a family resulting in 30 recombinant sons, probability is 0.94 for assignment to either a 2 cM or a combined 4 cM interval. Effect of type I and type II errors in segregation status determination on power of QTL assignment was found to be small. Errors in segregation status due to QTL segregation in dams have an impact if the frequency of the mutant QTL allele is intermediate to high.

Alleles↗
PubMed2004

Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model.

The incorporation of developmental control mechanisms of growth has proven to be a powerful tool in mapping quantitative trait loci (QTL) underlying growth trajectories. A theoretical framework for implementing a QTL mapping strategy with growth laws has been established. This framework can be generalized to an arbitrary number of time points, where growth is measured, and becomes computationally more tractable, when the assumption of variance stationarity is made. In practice, however, this assumption is likely to be violated for age-specific growth traits due to a scale effect. In this article, we present a new statistical model for mapping growth QTL, which also addresses the problem of variance stationarity, by using a transform-both-sides (TBS) model advocated by Carroll and Ruppert (1984, Journal of the American Statistical Association 79, 321-328). The TBS-based model for mapping growth QTL cannot only maintain the original biological properties of a growth model, but also can increase the accuracy and precision of parameter estimation and the power to detect a QTL responsible for growth differentiation. Using the TBS-based model, we successfully map a QTL governing growth trajectories to a linkage group in an example of forest trees. The statistical and biological properties of the estimates of this growth QTL position and effect are investigated using Monte Carlo simulation studies. The implications of our model for understanding the genetic architecture of growth are discussed.

Biometry↗
PubMed1995

High-resolution genetic mapping of complex traits.

Positional cloning requires high-resolution genetic mapping. To plan a positional cloning project, one needs to know how many informative meioses will be required to narrow the search for a disease gene to an acceptably small region. For a simple Mendelian trait studied with linkage analysis, the answer is straightforward. In this paper, we address the situation of a complex trait studied with affected-relative-pair methods. We derive mathematical formulas for the size of an appropriate confidence region, as a function of the relative risk attributable to the gene. Using these results, we provide graphs showing the number of relative pairs required to narrow the gene hunt to an interval of a given size. For example, we show that localizing a gene to 1 cM requires a median of 200 sib pairs for a locus causing a fivefold increased risk to an offspring and 700 sib pairs for a locus causing a twofold increased risk. We discuss the implications of these results for the positional cloning of genes underlying complex traits.

Alleles↗
PubMed2006

The genetics and genomics of the drought response in Populus.

The genetic nature of tree adaptation to drought stress was examined by utilizing variation in the drought response of a full-sib second generation (F(2)) mapping population from a cross between Populus trichocarpa (93-968) and P. deltoides Bart (ILL-129) and known to be highly divergent for a vast range of phenotypic traits. We combined phenotyping, quantitative trait loci (QTL) analysis and microarray experiments to demonstrate that 'genetical genomics' can be used to provide information on adaptation at the species level. The grandparents and F(2) population were subjected to soil drying, and contrasting responses to drought across genotypes, including leaf coloration, expansion and abscission, were observed, and QTL for these traits mapped. A subset of extreme genotypes exhibiting extreme sensitivity and insensitivity to drought on the basis of leaf abscission were defined, and microarray experiments conducted on these genotypes and the grandparent species. The extreme genotype groups induced a different set of genes: 215 and 125 genes differed in their expression response between groups in control and drought, respectively, suggesting species adaptation at the gene expression level. Co-location of differentially expressed genes with drought-specific and drought-responsive QTLs was examined, and these may represent candidate genes contributing to the variation in drought response.

Disasters↗
PubMed2006

A population-based latent variable approach for association mapping of quantitative trait loci.

A population-based latent variable approach is proposed for association mapping of quantitative trait loci (QTL), using multiple closely linked genetic markers within a small candidate region in the genome. By incorporating QTL as latent variables into a penetrance model, the QTL are flexible to characterize either alleles at putative trait loci or potential risk haplotypes/sub-haplotypes of the markers. Under a general likelihood framework, we develop an EM-based algorithm to estimate genetic effects of the QTL and haplotype frequencies of the QTL and markers jointly. Closed form solutions derived in the maximization step of the EM procedure for updating the joint haplotype frequencies of QTL and markers can effectively reduce the computational intensity. Various association measures between QTL and markers can then be derived from the haplotype frequencies of markers and used to infer QTL positions. The likelihood ratio statistic also provides a joint test for association between a quantitative trait and marker genotypes without requiring adjustment for the multiple testing. Extensive simulation studies are performed to evaluate the approach.

Algorithms↗
PubMed2004

In silico mapping of quantitative trait loci in maize.

Quantitative trait loci (QTL) are most often detected through designed mapping experiments. An alternative approach is in silico mapping, whereby genes are detected using existing phenotypic and genomic databases. We explored the usefulness of in silico mapping via a mixed-model approach in maize (Zea mays L.). Specifically, our objective was to determine if the procedure gave results that were repeatable across populations. Multilocation data were obtained from the 1995-2002 hybrid testing program of Limagrain Genetics in Europe. Nine heterotic patterns comprised 22,774 single crosses. These single crosses were made from 1,266 inbreds that had data for 96 simple sequence repeat (SSR) markers. By a mixed-model approach, we estimated the general combining ability effects associated with marker alleles in each heterotic pattern. The numbers of marker loci with significant effects--37 for plant height, 24 for smut [Ustilago maydis (DC.) Cda.] resistance, and 44 for grain moisture--were consistent with previous results from designed mapping experiments. Each trait had many loci with small effects and few loci with large effects. For smut resistance, a marker in bin 8.05 on chromosome 8 had a significant effect in seven (out of a maximum of 18) instances. For this major QTL, the maximum effect of an allele substitution ranged from 5.4% to 41.9%, with an average of 22.0%. We conclude that in silico mapping via a mixed-model approach can detect associations that are repeatable across different populations. We speculate that in silico mapping will be more useful for gene discovery than for selection in plant breeding programs.

Analysis of Variance↗
PubMed2004

QTL mapping of ten agronomic traits on the soybean ( Glycine max L. Merr.) genetic map and their association with EST markers.

A set of 184 recombinant inbred lines (RILs) derived from soybean vars. Kefeng No.1 x Nannong 1138-2 was used to construct a genetic linkage map. The two parents exhibit contrasting characteristics for most of the traits that were mapped. Using restricted fragment length polymorphisms (RFLPs), simple sequence repeats (SSRs) and expressed sequence tags (ESTs), we mapped 452 markers onto 21 linkage groups and covered 3595.9 cM of the soybean genome. All of the linkage groups except linkage group F were consistent with those of the consensus map of Cregan et al. (1999). Linkage group F was divided into two linkage groups, F1 and F2. The map consisted of 189 RFLPs, 219 SSRs, 40 ESTs, three R gene loci and one phenotype marker. Ten agronomic traits-days to flowering, days to maturity, plant height, number of nodes on main stem, lodging, number of pods per node, protein content, oil content, 100-seed weight, and plot yield-were studied. Using winqtlcart, we detected 63 quantitative trait loci (QTLs) that had LOD>3 for nine of the agronomic traits (only exception being seed oil content) and mapped these on 12 linkage groups. Most of the QTLs were clustered, especially on groups B1 and C2. Some QTLs were mapped to the same loci. This pleiotropism was common for most of the QTLs, and one QTL could influence at most five traits. Seven EST markers were found to be linked closely with or located at the same loci as the QTLs. EST marker GmKF059a, encoding a repressor protein and mapped on group C2, accounted for about 20% of the total variation of days to flowering, plant height, lodging and nodes on the main stem, respectively.

Agriculture↗
PubMed1997

Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages.

Power to detect linkage and localization of a major gene were compared in univariate and bivariate variance components linkage analysis of three related quantitative traits in general pedigrees. Although both methods demonstrated adequate power to detect loci of moderate effect, bivariate analysis improved both power and localization for correlated quantitative traits mapping to the same chromosomal region, regardless of whether co-localization was the result of pleiotropy. Additionally, a test of pleiotropy versus co-incident linkage was shown to have adequate power and a low error rate.

Chromosome Mapping↗