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PubMed2001

Multiple flowering time QTLs within several Brassica species could be the result of duplicated copies of one ancestral gene.

Quantitative trait locus (QTL) analysis was used to study the evolution of genes controlling the timing of flowering in four Brassica genomes that are all extensively replicated. Comparative mapping showed that a chromosomal region from the top of Arabidopsis thaliana chromosome 5 corresponded to three homoeologous copies in each of the diploid species Brassica nigra, B. oleracea, and B. rapa and six copies in the amphidiploid B. juncea. QTLs were detected in two of the three replicated segments in each diploid genome and in three of the six replicated segments in B. juncea. These results indicate that, for the studied trait, multiple QTLs resulting from genome duplication is the rule rather than the exception. Brassica homologues to two candidate genes (CO and FLC) identified from the corresponding A. thaliana region were mapped. CO homologues mapped close to the QTL peaks in eight of nine QTLs, while FLC homologues mapped farther away in those cases where the mapping resolution allowed a comparison. Thus, our data are consistent with the hypothesis that all the major QTLs we detected in the different species of Brassica could be the result of duplicated copies of the same ancestral gene, possibly the ancestor of CO.

Arabidopsis Proteins↗
PubMed2006

A modified algorithm for the improvement of composite interval mapping.

Composite interval mapping (CIM) is the most commonly used method for mapping quantitative trait loci (QTL) with populations derived from biparental crosses. However, the algorithm implemented in the popular QTL Cartographer software may not completely ensure all its advantageous properties. In addition, different background marker selection methods may give very different mapping results, and the nature of the preferred method is not clear. A modified algorithm called inclusive composite interval mapping (ICIM) is proposed in this article. In ICIM, marker selection is conducted only once through stepwise regression by considering all marker information simultaneously, and the phenotypic values are then adjusted by all markers retained in the regression equation except the two markers flanking the current mapping interval. The adjusted phenotypic values are finally used in interval mapping (IM). The modified algorithm has a simpler form than that used in CIM, but a faster convergence speed. ICIM retains all advantages of CIM over IM and avoids the possible increase of sampling variance and the complicated background marker selection process in CIM. Extensive simulations using two genomes and various genetic models indicated that ICIM has increased detection power, a reduced false detection rate, and less biased estimates of QTL effects.

Algorithms↗
PubMed2002

Mapping of qualitative and quantitative phenotypic traits in Rosa using AFLP markers.

A segregating population of 91 hybrids issued from a cross between a dihaploid rose, derived from the haploidisation of a modern cultivar, and a diploid species was used to construct linkage maps of the parental genomes. As in other recent genetic studies in Rosa, AFLPs were used as molecular markers. Two segregating qualitative traits, recurrent blooming and double corolla, already known to be inherited as single recessive and dominant genes, respectively, were recorded in the mapping population. A quantitative trait, thorn density of the shoots, was also evaluated in this population. Sixty eight and 108 AFLP markers located on 8 and 6 linkage groups could be analysed in the female and male parent, respectively. The two recorded qualitative phenotypic markers were mapped as well as the quantitative one, after having performed QTL analyses on the parental maps in the latter case. It appears that thorn quantity is controlled by a major and a minor QTL which are located on the same linkage group at 36.5 and 3.2 cM from the single seasonal-blooming gene, respectively.

Journal Article↗
PubMed2004

Comparative genetic analysis of quantitative traits in sunflower (Helianthus annuus L.) 3. Characterisation of QTL involved in resistance to Sclerotinia sclerotiorum and Phoma macdonaldi.

One hundred and fifty F(2)-F(3) families from a cross between two inbred sunflower lines FU and PAZ2 were used to map quantitative trait loci (QTL) for resistance to white rot (Sclerotinia sclerotiorum) attacks of terminal buds and capitula, and black stem ( Phoma macdonaldii). A genetic linkage map of 18 linkage groups with 216 molecular markers spanning 1,937 cM was constructed. Disease resistances were measured in field experiments for S. sclerotiorum and under controlled conditions for P. macdonaldii. For resistance to S. sclerotiorum terminal bud attack, seven QTL were identified, each explaining less than 10% of phenotypic variance. For capitulum attack by this parasite, there were four QTL (each explaining up to 20% of variation) and for P. macdonaldii resistance, four QTL were identified, each having effects of up to 16%. The S. sclerotiorum capitulum resistance QTL were compared with those reported previously and it was concluded that resistance to this disease is governed by a considerable number of QTL, located on almost all the sunflower linkage groups.

Ascomycota↗
PubMed2003

Molecular marker analysis and genetic basis for sterility of typical indica/japonica hybrids.

To explore the genes differentiated between typical indica and japonica varieties, two typical indica/japonica varieties, Balilla (japonica) and Nantehao (NTH, indica), were selected to construct genetic populations based on the widely surveying for spikelet and pollen fertility of 90 indica/japonica F1 hybrids, which also were used as the wide compatability testers. In order to analyze the genes (QTLs) related to spikelet and pollen fertility, two reciprocal backcross populations Balilla/NTH//Balilla and Balilla/NTH//NTH were constructed and the spikelet and pollen fertility of each individuals were assessed. In both populations, two traits all appeared distorted normal distribution, but in the first population, they forwarded to low-level fertility type, the later population, forwarded to high-level fertility type relatively. The results indicated that both of male and female gametophytes of Balilla/NTH hybrids were partial sterile. Then we analyzed the SSR marker genotype of each individuals of Balilla/NTH//Balilla population containing 142 individuals, and constructed a SSR linkage map, in which, there were 108 information markers distributing on all 12 chromosomes equably, average marker distance was about 11.9 cM. Therefore the linkage map was qualified for QTL analysis. Two methods were employed to conduct QTLs analysis, i.e., single marker analysis and interval mapping. According to single marker analysis, 17 and 12 markers were found significantly responsible for spikelet and pollen fertility, respectively. And further study by means of MAPMAKER/QTL software, for spikelet fertility trait, two QTLs were detected, qSPTF1 on chromosome 1 and qSPTF6 on chromosome 6, and their additive effect were 13.501 and -16.414, respectively. According to previous studies, qSPTF6 was deduced to be the same locus as S-5. For pollen fertility, qPLLN7 on chromosome 7 and qPLLN9 on chromosome 9 were detected, and their additive effects were -12.003 and -11.012, respectively. Because the QTLs detected cannot explain completely the total variance of mapping population, other genetic factors must be existed to be responsible for spikelet and pollen partial sterility. Hence we let two random markers as putative covariates, and divide the 142 individuals into four groups according to the two marker genotypes, then the average values of spikelet and pollen fertility of each groups were calculated for two-way ANOVA (analysis of variance). The results indicated that there existed strong interaction for both spikelet fertility and pollen fertility. At a significance level of 0.005, there over 61 and 51 pairs loci interactions detected playing an important role in spikelet and pollen sterility expression, respectively. These results indicated that epistasis also was one of major genetic components controlling indica/japonica hybrid sterility.

Analysis of Variance↗
PubMed2002

Novel linkage mapping approach using DNA pooling in human and animal genetics. II. Detection of quantitative traits loci in dairy cattle.

Selective DNA pooling is an advanced methodology for linkage mapping of quantitative trait loci (QTL) in farm animals. The principle is based on densitometric estimates of marker allele frequency in pooled DNA samples of phenotypically extreme individuals from half-sib, backcross and F(2) experimental designs in farm animals. This methodology provides a rapid and efficient analysis of a large number of individuals with short tandem repeat markers that are essential to detect QTL through the genome - wide searching approach. Several strategies involving whole genome scanning with a high statistical power have been developed for systematic search to detect the quantitative traits loci and linked loci of complex traits. In recent studies, greater success has been achieved in mapping several QTLs in Israel-Holstein cattle using selective DNA pooling. This paper outlines the currently emerged novel strategies of linkage mapping to identify QTL based on selective DNA pooling with more emphasis on its theoretical pre-requisite to detect linked QTLs, applications, a general theory for experimental half-sib designs, the power of statistics and its feasibility to identify genetic markers linked QTL in dairy cattle. The study reveals that the application of selective DNA pooling in dairy cattle can be best exploited in the genome-wide detection of linked loci with small and large QTL effects and applied to a moderately sized half-sib family of about 500 animals.

Animals↗
PubMed2001

Mapping epistatic quantitative trait loci with one-dimensional genome searches.

The discovery of epistatically interacting QTL is hampered by the intractability and low power to detect QTL in multidimensional genome searches. We describe a new method that maps epistatic QTL by identifying loci of high QTL by genetic background interaction. This approach allows detection of QTL involved not only in pairwise but also higher-order interaction, and does so with one-dimensional genome searches. The approach requires large populations derived from multiple related inbred-line crosses as is more typically available for plants. Using maximum likelihood, the method contrasts models in which QTL allelic values are either nested within, or fixed over, populations. We apply the method to simulated doubled-haploid populations derived from a diallel among three inbred parents and illustrate the power of the method to detect QTL of different effect size and different levels of QTL by genetic background interaction. Further, we show how the method can be used in conjunction with standard two-locus QTL detection models that use two-dimensional genome searches and find that the method may double the power to detect first-order epistasis.

Alleles↗
PubMed2004

Mapping of a milk production quantitative trait locus to a 420-kb region on bovine chromosome 6.

A QTL affecting milk production traits was previously mapped to an interval of 7.5 cM on chromosome 6 in Norwegian dairy cattle. This article aimed to refine this position by increasing the map density in the region by a set of single-nucleotide polymorphisms and analyzing the data with a combined linkage and linkage disequilibrium approach. Through a series of single- and multitrait and single- and multipoint analyses, the QTL was positioned to an interval surrounded by the genes ABCG2 and LAP3. As no recombinations were detected in this interval, physical mapping was required for further refining. By using radiation hybrid mapping as well as BAC clones, the bovine and human comparative maps in the region are resolved, and the QTL is mapped within a distance of 420 kb.

Animals↗
PubMed2003

Dimension reduction for mapping mRNA abundance as quantitative traits.

The advent of sophisticated genomic techniques for gene mapping and microarray analysis has provided opportunities to map mRNA abundance to quantitative trait loci (QTL) throughout the genome. Unfortunately, simple mapping of each individual mRNA trait on the scale of a typical microarray experiment is computationally intensive, subject to high sample variance, and therefore underpowered. However, this problem can be addressed by capitalizing on correlation among the large number of mRNA traits. We present a method to reduce the dimensionality for mapping gene expression data as quantitative traits. We used a blind method, principal components, and a sighted method, hierarchical clustering seeded by disease relevant traits, to define new traits composed of a small collection of promising mRNAs. We validated the principle of our approach by mapping the expression levels of metabolism genes in a population of F(2)-ob/ob mice derived from the BTBR and C57BL/6J strains. We found that lipogenic and gluconeogenic mRNAs, which are known targets of insulin action, were closely associated with the insulin trait. Multiple interval mapping and Bayesian interval mapping of this new trait revealed significant linkages to chromosome regions that were contained in loci associated with type 2 diabetes in this same mouse sample. As a further statistical refinement, we show that principal component analysis also effectively reduced dimensions for mapping phenotypes composed of mRNA abundances.

Animals↗
PubMed2004

Joint mapping of quantitative trait Loci for multiple binary characters.

Joint mapping for multiple quantitative traits has shed new light on genetic mapping by pinpointing pleiotropic effects and close linkage. Joint mapping also can improve statistical power of QTL detection. However, such a joint mapping procedure has not been available for discrete traits. Most disease resistance traits are measured as one or more discrete characters. These discrete characters are often correlated. Joint mapping for multiple binary disease traits may provide an opportunity to explore pleiotropic effects and increase the statistical power of detecting disease loci. We develop a maximum-likelihood method for mapping multiple binary traits. We postulate a set of multivariate normal disease liabilities, each contributing to the phenotypic variance of one disease trait. The underlying liabilities are linked to the binary phenotypes through some underlying thresholds. The new method actually maps loci for the variation of multivariate normal liabilities. As a result, we are able to take advantage of existing methods of joint mapping for quantitative traits. We treat the multivariate liabilities as missing values so that an expectation-maximization (EM) algorithm can be applied here. We also extend the method to joint mapping for both discrete and continuous traits. Efficiency of the method is demonstrated using simulated data. We also apply the new method to a set of real data and detect several loci responsible for blast resistance in rice.

Algorithms↗
PubMed2002

Cold sweetening in diploid potato: mapping quantitative trait loci and candidate genes.

A candidate gene approach has been used as a first step to identify the molecular basis of quantitative trait variation in potato. Sugar content of tubers upon cold storage was the model trait chosen because the metabolic pathways involved in starch and sugar metabolism are well known and many of the genes have been cloned. Tubers of two F(1) populations of diploid potato grown in six environments were evaluated for sugar content after cold storage. The populations were genotyped with RFLP, AFLP, and candidate gene markers. QTL analysis revealed that QTL for glucose, fructose, and sucrose content were located on all potato chromosomes. Most QTL for glucose content mapped to the same positions as QTL for fructose content. QTL explaining >10% of the variability for reducing sugars were located on linkage groups I, III, VII, VIII, IX, and XI. QTL consistent across populations and/or environments were identified. QTL were linked to genes encoding invertase, sucrose synthase 3, sucrose phosphate synthase, ADP-glucose pyrophosphorylase, sucrose transporter 1, and a putative sucrose sensor. The results suggest that allelic variants of enzymes operating in carbohydrate metabolic pathways contribute to the genetic variation in cold sweetening.

Carbohydrate Metabolism↗
PubMed2004

A statistical model for functional mapping of quantitative trait loci regulating drug response.

Differential drug response, that is, pharmacodynamics, is most often likely to be a complex trait, controlled by the combined influences of multiple genes and environmental influences. Genetic mapping has proven to be a powerful tool for detecting and identifying specific genes affecting complex traits, that is, quantitative trait loci (QTL), based on polymorphic markers. In this article, we present a novel statistical model for genetic mapping of QTL governing pharmacodynamic processes. In principle, this model is a combination of functional mapping proposed to map function-valued traits and linkage disequilibrium mapping designed to provide high-resolution mapping of QTL by making use of recombination events created at a historic time. We implement a closed-form solution for the Expectation-Maximization algorithm to estimate the population genetic parameters of QTL and the simplex algorithm to estimate the curve parameters describing the pharmacodynamic changes of different QTL genotypes in response to drug dose or concentrations. Extensive simulations are performed to investigate the statistical properties of our model. The implications of our model in pharmacogenetic and pharmacogenomic research are discussed.

Algorithms↗
PubMed2006

Quantitative trait loci modifying cardiac atrial septal morphology and risk of patent foramen ovale in the mouse.

Atrial septal defect (ASD) is a common congenital heart disease (CHD) occurring in 5 to 7 per 10,000 live births. Mutations in 5 human genes (NKX2.5, TBX5, GATA4, MYHC, ACTC) are known to cause dominant ASD, but these account for a minority of cases. Human and mouse data suggest that ASD exists in an anatomical continuum with milder septal variants patent foramen ovale (PFO) and atrial septal aneurysm, strongly associated with ischemic stroke and migraine. We have previously shown in inbred mice that the incidence of PFO strongly correlates with length of the interatrial septum primum, defining a quantitative trait underlying PFO risk. To better understand genetic causation of atrial septal abnormalities, we mapped quantitative trait loci (QTL) influencing septal morphology using mouse strains (QSi5 and 129T2/SvEms) maximally informative for PFO incidence and 3 quantitative septal anatomical traits including septum primum length. [QSi5x129T2/SvEms]F2 intercross animals (n=1437) were phenotyped and a whole genome scan performed at an average 17-cM interval. Statistical methodology scoring PFO as a binary phenotype was developed as a confirmatory mapping technique. We mapped 7 significant and 6 suggestive QTL modifying quantitative phenotypes, with 4 supported by binary analysis. Quantitative traits, although strongly associated with PFO (P<0.001), correlated poorly with each other and in all but 1 case QTL for different traits were nonoverlapping. Thus, multiple anatomical processes under separate genetic control contribute to risk of PFO. Our findings demonstrate the feasibility of modeling the genetic basis of common CHD using animal genetic and genomic technologies.

Animals↗
PubMed2002

Effectiveness of selective genotyping for detection of quantitative trait loci: an analysis of grain and malt quality traits in three barley populations.

Marker genotype data and grain and malt quality phenotype data from three barley (Hordeum vulgare L.) mapping populations were used to investigate the feasibility of selective genotyping for detection of quantitative trait loci (QTLs). With selective genotyping, only individuals with high and low phenotypic values for the trait of interest are genotyped. Here, genotyping of 10 to 70% of each population (i.e., 5 to 35% in each tail of the phenotypic distribution) was considered. Genomic positions detected by selective genotyping were compared to QTL position estimates from interval mapping analysis using marker genotype data from the entire population. Selective genotyping reliably detected almost all of the mapped QTLs, often with only 10% of the population genotyped. Selective genotyping also detected spurious QTLs in regions of the genome where no significant QTL had been mapped. Even with additional genotyping to verify putative QTLs, the total genotyping effort for detection of QTLs for a single trait by selective genotyping was usually less than 30% of that required for conventional interval mapping. Simultaneous investigation of two or more traits by selective genotyping would require additional genotyping effort, but could still be worthwhile.

Genotype↗
PubMed2004

A bivalent polyploid model for mapping quantitative trait loci in outcrossing tetraploids.

Two major aspects have made the genetic and genomic study of polyploids extremely difficult. First, increased allelic or nonallelic combinations due to multiple alleles result in complex gene actions and interactions for quantitative trait loci (QTL) in polyploids. Second, meiotic configurations in polyploids undergo a complex biological process including either bivalent or multivalent formation, or both. For bivalent polyploids, different degrees of preferential chromosome pairings may occur during meiosis. In this article, we develop a maximum-likelihood-based model for mapping QTL in tetraploids by considering the quantitative inheritance and meiotic mechanism of bivalent polyploids. This bivalent polyploid model is implemented with the EM algorithm to simultaneously estimate QTL position, QTL effects, and QTL-marker linkage phases by incorporating the impact of a cytological parameter determining bivalent chromosome pairings (the preferential pairing factor). Simulation studies are performed to investigate the performance and robustness of our statistical method for parameter estimation. The implication and extension of the bivalent polyploid model are discussed.

Algorithms↗
PubMed2003

Chromosome substitution strains: some quantitative considerations for genome scans and fine mapping.

A chromosome substitution strain (CSS) is an inbred strain in which one chromosome has been substituted from a different inbred strain by repeated backcrossing. A complete CSS set has one strain representing each chromosome against a uniform background, thus allowing genome-wide scans to be carried out for quantitative trait loci (QTLs) influencing any trait of interest. A one-way ANOVA by strain is first carried out, followed by planned comparisons using Dunnett's method. A QTL is detected and mapped to a chromosome when a significant difference is observed in a background strain vs CSS comparison. The most efficient ratio of background to CSS mice in any one comparison is 4.5:1, and the threshold for p <.05 genome-wide significance is estimated to be p =.003 to.004, a much less stringent criterion than any other mammalian mapping population. The use of false discovery rates tends to further reduce threshold stringency. Comparisons are made to the widely used conventional F(2) intercross, and both advantages and disadvantages are noted. The proportion of the trait variance due to a QTL is often much larger than the same QTL in an F(2), and the number of generations to attain fine mapping is greatly reduced. To serve as guidelines for planning experiments, methods to estimate sample sizes for QTL detection are presented for the initial genome scan and for subsequent fine mapping.

Analysis of Variance↗
PubMed2003

Exponential mapping of quantitative trait loci governing allometric relationships in organisms.

Allometric scaling relationships or quarter-power rules, as a universal biological law, can be viewed as having some genetic component, and the particular genes (or quantitative trait loci, QTL) underlying these allometric relationships can be mapped using molecular markers. We develop a mathematical and statistical model for mapping allometric QTL on the basis of nonlinear power functions using Taylor's approximation theory. Simulation studies indicate that the QTL position and effect can be estimated using our model, but the estimation precision can be improved from the higher- over lower-order approximation when the sample size used and gene effects are small. The application of our approach in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship between 3rd-year stem height and 3rd-year stem biomass. It is expected that our model will have broad implications for genetic, evolutionary, biomedical and breeding research.

Algorithms↗
PubMed2004

An algorithm for molecular dissection of tumor progression.

The volumetric growth of tumor cells as a function of time is most often likely to be a complex trait, controlled by the combined influences of multiple genes and environmental influences. Genetic mapping has proven to be a powerful tool for detecting and identifying specific genes affecting complex traits, i.e., quantitative trait loci (QTL), based on polymorphic markers. In this article, we present a novel statistical model for genetic mapping of QTL governing tumor growth trajectories in humans. In principle, this model is a combination of functional mapping proposed to map function-valued traits and linkage disequilibrium mapping designed to provide high resolution mapping of QTL by making use of recombination events created at a historic time. We implement an EM-simplex hybrid algorithm for parameter estimation, in which a closed-form solution for the EM algorithm is derived to estimate the population genetic parameters of QTL including the allele frequencies and the coefficient of linkage disequilibrium, and the simplex algorithm incorporated to estimate the curve parameters describing the dynamic changes of cancer cells for different QTL genotypes. Extensive simulations are performed to investigate the statistical properties of our model. Through a number of hypothesis tests, our model allows for cutting-edge studies aimed to decipher the genetic mechanisms underlying cancer growth, development and differentiation. The implications of our model in gene therapy for cancer research are discussed.

Algorithms↗