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PubMed2003

Quantitative trait locus mapping of pyrethroid resistance in Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera: Chrysomelidae).

Quantitative trait locus (QTL) mapping is a valuable new tool for locating genomic regions that underlie variation in important traits such as insecticide resistance. Because QTL mapping complements a candidate gene strategy for understanding the genetic architecture of important traits, it may also facilitate the identification of genes causing important variation. After mapping the QTL locations, markers closely linked to QTL can be used for genetic analysis of population structure and to measure the spread and increase of resistance-causing QTL alleles. In this study, QTL influencing resistance to the pyrethroid insecticide esfenvalerate were mapped in the Colorado potato beetle Leptinotarsa decemlineata (Say) (CPB). Three QTL contributing to esfenvalerate resistance were identified from a mapping population of 79 individuals analyzed at 90 marker loci. One QTL had a large effect and two QTL had smaller effects. The major QTL occurs on the X chromosome, overlapping the position of a candidate gene (Leptinotarsa decemlineata Voltage sensitive sodium channel [LdVssc1]) previously implicated in pyrethroid resistance. Resistance-increasing alleles at the two minor-effect QTL originated with the susceptible parent, suggesting that alleles of small effect may be segregating in susceptible populations. Comparison of the New York population from which the susceptible parent originated with a more-susceptible population from North Carolina suggests that the minor-effect loci identified here may explain some of the variation in tolerance observed among susceptible populations. DNA sequencing of a portion of LdVssc1 shows that the resistance-conferring allele from the resistant parent does not contain the kdr mutation previously found in CPB and typically observed in other insects that are resistant to pyrethroid insecticides because of changes in this gene.

Animals↗

PubMed2005

Mapping of QTL associated with chilling tolerance during reproductive growth in soybean.

Low temperatures in summer bring about drastic reduction in seed yield of soybean [Glycine max (L.) Merr.]. To identify quantitative trait loci (QTL) associated with chilling tolerance during the reproductive growth in soybean, a recombinant inbred line (RIL) population consisting of 104 F(6)-derived lines was created from a cross between two cultivars, chilling-tolerant Hayahikari and chilling-sensitive Toyomusume. The RIL were genotyped with 181 molecular and phenotypic markers and were scored with regard to chilling tolerance, which was evaluated by comparison of seed-yielding abilities in two artificial climatic environments at chilling and usual temperatures. Three QTL were detected for chilling tolerance in seed-yielding ability. Two of them, qCTTSW 1 and qCTTSW 2, were mapped near QTL for flowering time, and the latter had an epistatic interaction with a marker locus located near another QTL for flowering time, where no significant QTL for chilling tolerance was detected. The analysis of an F(2) population derived from the cross between Hayahikari and an RIL of the Hayahikari genotype at all QTL for flowering time confirmed the effect of the third QTL, qCTTSW 3, on chilling tolerance and suggested that qCTTSW 1 was basically independent of the QTL for flowering time. The findings and QTL found in this study may provide useful information for marker-assisted selection (MAS) and further genetic studies on soybean chilling tolerance.

Acclimatization↗

PubMed2003

Construction of a linkage map and QTL analysis of horticultural traits for watermelon [Citrullus lanatus (THUNB.) MATSUM & NAKAI] using RAPD, RFLP and ISSR markers.

We have been constructing linkage maps for watermelon ( Citrullus lanatus) on the basis of random amplified polymorphic DNA (RAPD), restriction fragment length polymorphism (RFLP), inter-simple sequence repeats (ISSRs) and isozymes using an F(2) population derived from a crossing between a cultivated inbred line (H-7; C. lanatus) and an African wild form (SA-1; C. lanatus). A total of 120 F(2) plants was used for construction of a linkage map using 477 RAPDs, 53 RFLPs, 23 ISSRs and one isozyme markers. Linkage analysis revealed that 554 loci could be mapped to 11 linkage groups that extended for 2,384 centimorgans (cM). While a BC(1) population [(H-7 x SA-1) x H-7] consisting of 60 individuals was grown and scored for quantitative traits. Another linkage map with a total length of 1,729 cM was constructed in the BC(1) using genetic markers found to segregate in the F(2) population. A QTL analysis was applied by means of interval mapping for locating such agronomic traits as hardness of rind, Brix of flesh juice, flesh color (red and yellow) and rind color. The relative order of markers in the BC(1) map was essentially the same as that on the linkage map in the F(2). A total of five QTLs for four agronomic traits was detected. The QTL for hardness of rind was mapped on group 4. The linkage group 8 contained the QTL for sugar content of the flesh as expressed in Brix of the juice. The QTL for red flesh color was detected on groups 2 and 8. The QTL for rind color mapped on the group 3. The present map and QTL analysis may provide a useful tool for breeders by introducing valuable wild watermelon genes to cultivars.

Chromosome Mapping↗

PubMed1997

Mapping of mouse obesity genes: A generic approach to a complex trait.

Identification of genes underlying any complex trait such as obesity is an important and difficult problem in genetics. Traditional candidate gene approaches cannot be relied on to identify all of the genes influencing a complex trait, and positional cloning is very laborious. With the advent of new tools and methods, however, comprehensive approaches to the identification of any genes underlying complex traits are now available. Quantitative trait locus (QTL) mapping is a general technique to map Mendelian factors influencing complex traits. The QTL approach involves the crossing of two strains that differ in the trait of interest to produce F2 or back-cross progeny, individually phenotyping and genotyping each progeny, and statistically associating the typed markers and the phenotype. QTL mapping has been used in the last 4 years to map genes for a wide variety of traits, including body weight and growth, obesity, atherosclerosis and susceptibility to cancer in the mouse, and hypertension, hyperactivity and arthritis in the rat. QTL mapping has also been used to map genes in pigs, poultry, cows, fish and plants. Once a trait has been located in a chromosomal subregion, identifying the underlying gene remains a significant problem. A monogenic model must be developed, isolating one gene influencing a trait from other genes affecting the same phenotype. Then the positional candidate strategy, which relies on a combination of mapping to a chromosomal subregion followed by a survey of the interval to see if attractive candidates reside there, becomes practical.

Animals↗

PubMed2002

[Mapping QTLs for horizontal resistance to sheath blight in an elite rice restorer line, Minghui 63].

This study was conducted with a recombinant inbred line (RILs) population consisting of 240 recombination lines, derived from an elite combination, Zhenshan 97B x Minghui 63. The RILs and their parents were grown in a randomized complete design with two replications in the years of 1999 and 2000. Sheath blight response ratings for the population and their parents were identified by an improved method of inoculation, which was carried out with short woody toothpicks incubated with a Rhizoctonia solani strain, RH-9, and inserted the third sheath in the late tillering/green ring stage of growth. A linkage map was constructed from the RILs. The QTL mapping of sheath blight resistance was carried out by the method of interval QTL mapping. Two QTLs for sheath blight resistance were detected in each year, and were located on chromosome 5 and chromosome 9, respectively. The QTL for sheath blight resistance on chromosome 5 was flanked by markers C624 and C246 on the basis of 1999 data, and by markers C246 and RM26 using 2000 data. The 1-LOD-confidence intervals of QTLs for sheath blight resistance on chromosome 5 detected in two years greatly overlapped with each other, and the peak of the 1-LOD-confidence intervals were approximately the same site. This suggested that the QTL for resistance on chromosome 5 detected in 1999 was probably the same as the QTL detected in 2000. The QTL for sheath blight resistance on chromosome 9 was located on the marker interval of C472-R2638 in term of 1999 data, and on the interval of RM257-RM242 based on 2000 data, and the two intervals were 9.7 cM away from each other. Based on the effect analysis of QTLs for resistance, the genotype of MH63 had negative additive effects or reduced sheath blight rating.

Chromosome Mapping↗

PubMed2000

Quantitative trait loci for floral morphology in Arabidopsis thaliana.

A central question in biology is how genes control the expression of quantitative variation. We used statistical methods to estimate genetic variation in eight Arabidopsis thaliana floral characters (fresh flower mass, petal length, petal width, sepal length, sepal width, long stamen length, short stamen length, and pistil length) in a cosmopolitan sample of 15 ecotypes. In addition, we used genome-wide quantitative trait locus (QTL) mapping to evaluate the genetic basis of variation in these same traits in the Landsberg erecta x Columbia recombinant inbred line population. There was significant genetic variation for all traits in both the sample of naturally occurring ecotypes and in the Ler x Col recombinant inbred line population. In addition, broad-sense genetic correlations among the traits were positive and high. A composite interval mapping (CIM) analysis detected 18 significant QTL affecting at least one floral character. Eleven QTL were associated with several floral traits, supporting either pleiotropy or tight linkage as major determinants of flower morphological integration. We propose several candidate genes that may underlie these QTL on the basis of positional information and functional arguments. Genome-wide QTL mapping is a promising tool for the discovery of candidate genes controlling morphological development, the detection of novel phenotypic effects for known genes, and in generating a more complete understanding of the genetic basis of floral development.

Arabidopsis↗

PubMed2005

Improving quantitative trait loci mapping resolution in experimental crosses by the use of genotypically selected samples.

One of the key factors contributing to the success of a quantitative trait locus (QTL) mapping experiment is the precision with which QTL positions can be estimated. We show, using simulations, that QTL mapping precision for an experimental cross can be increased by the use of a genotypically selected sample of individuals rather than an unselected sample of the same size. Selection is performed using a previously described method that optimizes the complementarity of the crossover sites within the sample. Although the increase in precision is accompanied by a decrease in QTL detection power at markers distant from QTL, only a modest increase in marker density is needed to obtain equivalent power over the whole map. Selected samples also show a slight reduction in the number of false-positive QTL. We find that two features of selected samples independently contribute to these effects: an increase in the number of crossover sites and increased evenness in crossover spacing. We provide an empirical formula for crossover enrichment in selected samples that is useful in experimental design and data analysis. For QTL studies in which the phenotyping is more of a limiting factor than the generation of individuals and the scoring of genotypes, selective sampling is an attractive strategy for increasing genome-wide QTL map resolution.

Chromosome Mapping↗

PubMed2005

An entropy-based measure of founder informativeness.

Optimizing quantitative trait locus (QTL) mapping experiments requires a generalized measure of marker informativeness because variable information is obtained from different marker systems, marker distribution and pedigree types. Such a measure can be derived from the concept of Shannon entropy, a central concept in information theory. Here we introduce entropy-based founder informativeness (EFI), a new measure of information content generalized across pedigrees, maps, marker systems and mating configurations. We derived equations for inbred- and outbred-derived mapping populations. Mathematical properties of EFI include enhanced sensitivity to mapping population type and extension to any number of founders. To illustrate the use of EFI, we compared experimental designs for QTL mapping for three examples: (i) different marker systems for an F2 pedigree, (ii) different marker densities and sampling sizes for a BC1 pedigree and (iii) a comparison of haplotypic versus zygotic analyses of an outbred pedigree. As an a priori generalized measure of information content, EFI does not require phenotypic data for optimizing experimental designs for QTL mapping.

Alleles↗

PubMed2005

A comparison of regression interval mapping and multiple interval mapping for linked QTL.

Regression interval mapping and multiple interval mapping are compared with regard to mapping linked quantitative trait loci (QTL) in inbred-line cross experiments. For that purpose, a simulation study was performed using genetic models with two linked QTL. Data were simulated for F(2) populations of different sizes and with all QTL and marker alleles fixed for alternative alleles in the parental lines. The criteria for comparison are power of QTL identification and the accuracy of the QTL position and effect estimates. Further, the estimates of the relative QTL variance are assessed. There are distinct differences in the QTL position estimates between the two methods. Multiple interval mapping tends to be more powerful as compared to regression interval mapping. Multiple interval mapping further leads to more accurate QTL position and QTL effect estimates. The superiority increased with wider marker intervals and larger population sizes. If QTL are in repulsion, the differences between the two methods are very pronounced. For both methods, the reduction of the marker interval size from 10 to 5 cM increases power and greatly improves QTL parameter estimates. This contrasts with findings in the literature for single QTL scenarios, where a marker density of 10 cM is generally considered as sufficient. The use of standard (asymptotic) statistical theory for the computation of the standard errors of the QTL position and effect estimates proves to give much too optimistic standard errors for regression interval mapping as well as for multiple interval mapping.

Chromosome Mapping↗

PubMed2005

Quantitative trait Loci analysis using the false discovery rate.

False discovery rate control has become an essential tool in any study that has a very large multiplicity problem. False discovery rate-controlling procedures have also been found to be very effective in QTL analysis, ensuring reproducible results with few falsely discovered linkages and offering increased power to discover QTL, although their acceptance has been slower than in microarray analysis, for example. The reason is partly because the methodological aspects of applying the false discovery rate to QTL mapping are not well developed. Our aim in this work is to lay a solid foundation for the use of the false discovery rate in QTL mapping. We review the false discovery rate criterion, the appropriate interpretation of the FDR, and alternative formulations of the FDR that appeared in the statistical and genetics literature. We discuss important features of the FDR approach, some stemming from new developments in FDR theory and methodology, which deem it especially useful in linkage analysis. We review false discovery rate-controlling procedures--the BH, the resampling procedure, and the adaptive two-stage procedure-and discuss the validity of these procedures in single- and multiple-trait QTL mapping. Finally we argue that the control of the false discovery rate has an important role in suggesting, indicating the significance of, and confirming QTL and present guidelines for its use.

Chromosome Mapping↗

PubMed2003

Genetic architecture of a selection response in Arabidopsis thaliana.

Quantitative trait locus (QTL) mapping has become an established and effective method for studying the genetic architecture of complex traits. In this report, we use a QTL mapping approach in combination with data from a large selection experiment in Arabidopsis thaliana to explore a response to selection of experimental populations with differentiated genetic backgrounds. Experimental populations with genetic backgrounds derived from ecotypes Landsberg and Niederzenz were exposed to multiple generations of fertility and viability selection. This selection resulted in phenotypic shifts in a number of life-history and fitness-related characters including early development time, flowering time, dry biomass, longevity, and fruit production. Quantitative trait loci were mapped for these traits and their positions were compared to previously characterized allele frequency changes in the experimental populations (Ungerer et al. 2003). Quantitative trait locus positions largely colocalized with genomic regions under strong and consistent selection in populations with differentiated genetic backgrounds, suggesting that alleles for these traits were selected similarly in differentiated genetic backgrounds. However, one QTL region exhibited a more variable response; being positively selected on one genetic background but apparently neutral in another. This study demonstrates how QTL mapping approaches can be combined with map-based population genetic data to study how selection acts on standing genetic variation in populations.

Analysis of Variance↗

PubMed1995

Alcohol acceptance, preference, and sensitivity in mice. II. Quantitative trait loci mapping analysis using BXD recombinant inbred strains.

Quantitative trait loci (QTL) mapping of complex phenotypes has emerged as an important feature of the recombinant inbred (RI) strain methodology. In this second study of our series on alcohol-related behaviors in mice, we examine alcohol acceptance, preference, and hypnotic dose sensitivity (HDS) to a standard dose of alcohol measured in BXD RI strains to identify candidate QTL regions responsible for their heritability. We detected highly significant marker associations for acceptance on chromosome 12 (Eif4e), for preference on chromosome 1 (D1Rti2) and chromosome 7 (D7Mit7), and for HDS on chromosome 7 (Mpmv1). These are the strongest QTL associations that we detected, but several other candidate QTL regions are reported. Given the limited number of BXD RI strains available, the large number of markers used herein, and the consequent chance of identifying false marker associations, these RI QTL mapping results must be seen as tentative, but an important first step toward identifying QTL for alcohol-related behaviors.

Alcohol Drinking↗

PubMed2006

Quantitative trait loci define genes and pathways underlying genetic variation in longevity.

Quantitative trait locus (QTL) mapping provides a means to discover and roughly position regions of the genome that harbor genes responsible for natural variation in a complex trait. QTL mapping has been utilized extensively in the pursuit of genes contributing to longevity, chiefly in two animal models, the nematode Caenorhabditis elegans and the dipteran insect Drosophila melanogaster. Research on both species has demonstrated that a relatively small set of loci accounts for most of their genetic variance in lifespan. QTL mapping complements the discovery of longevity genes by mutagenesis screens, because the two procedures are predicted to unveil overlapping but distinct types of genes. We argue that information gained from animal models, even invertebrates, can greatly facilitate the process of gene identification and testing of homologous genes in humans.

Aging↗

PubMed2002

A method for computing identity by descent probabilities and quantitative trait loci mapping with dominant (AFLP) markers.

Amplified fragment length polymorphisms (AFLPs) are a widely used marker system: the technique is very cost-effective, easy and rapid, and reproducibly generates hundreds of markers. Unfortunately, AFLP alleles are typically scored as the presence or absence of a band and, thus, heterozygous and dominant homozygous genotypes cannot be distinguished. This results in a significant loss of information, especially as regards mapping of quantitative trait loci (QTLs). We present a Monte Carlo Markov Chain method that allows us to compute the identity by descent probabilities (IBD) in a general pedigree whose individuals have been typed for dominant markers. The method allows us to include the information provided by the fluorescent band intensities of the markers, the rationale being that homozygous individuals have on average higher band intensities than heterozygous individuals, as well as information from linked markers in each individual and its relatives. Once IBD probabilities are obtained, they can be combined into the QTL mapping strategy of choice. We illustrate the method with two simulated populations: an outbred population consisting of full sib families, and an F2 cross between inbred lines. Two marker spacings were considered, 5 or 20 cM, in the outbred population. There was almost no difference, for the practical purpose of QTL estimation, between AFLPs and biallelic codominant markers when the band density is taken into account, especially at the 5 cM spacing. The performance of AFLPs every 5 cM was also comparable to that of highly polymorphic markers (microsatellites) spaced every 20 cM. In economic terms, QTL mapping with a dense map of AFLPs is clearly better than microsatellite QTL mapping and little is lost in terms of accuracy of position. Nevertheless, at low marker densities, AFLPs or other biallelic markers result in very inaccurate estimates of QTL position.

Algorithms↗

PubMed1998

Mapping quantitative trait loci for binary traits using a heterogeneous residual variance model: an application to Marek's disease susceptibility in chickens.

A typical problem in mapping quantitative trait loci (QTLs) comes from missing QTL genotype. A routine method for parameter estimation involving missing data is the mixture model maximum likelihood method. We developed an alternative QTL mapping method that describes a mixture of several distributions by a single model with a heterogeneous residual variance. The two methods produce similar results, but the heterogeneous residual variance method is computationally much faster than the mixture model approach. In addition, the new method can automatically generate sampling variances of the estimated parameters. We derive the new method in the context of QTL mapping for binary traits in a F2 population. Using the heterogeneous residual variance model, we identified a QTL on chromosome IV that controls Marek's disease susceptibility in chickens. The QTL alone explains 7.2% of the total disease variation.

Algorithms↗

PubMed1995

Molecular dissection of quantitative traits: progress and prospects.

QTL mapping is an increasingly useful approach to the study and manipulation of complex traits important in agriculture, evolution, and medicine. The molecular dissection of quantitative phenotypes, supplementing the principles of classical quantitative genetics, is accelerating progress in the manipulation of plant and animal genomes. A growing appreciation of the similarities among different organisms and the usefulness of comparative genetic information is making genome analysis more efficient, and providing new opportunities for using model systems to overcome the limitations of less-favorable systems. The expanding repertoire of techniques and information available for studying heredity is removing obstacles to the cloning of QTLs. Although QTL mapping alone is limited to a resolution of 0.1%-1.0% of a genome, use of QTL mapping in conjunction with a search for mapped candidate genes, with emerging technologies for isolation of genes expressed under conditions likely to account for the quantitative phenotype, and with ever more efficient megabase DNA manipulation and characterization bodes well for the prospect of isolating the genetic determinants of QTLs in the foreseeable future. In the words of Thoday (1961), "An extensive attack on quantitative genetics made from this point of view as well as the biometric approach should be a great help in answering questions concerning the nature of polygenes...."

Animals↗

PubMed1998

Genes on mouse chromosomes 2 and 9 determine variation in ethanol consumption.

Quantitative trait locus (QTL) mapping efforts in alcohol (ethanol) research are beginning to generate promising data that may ultimately lead to the identification of genes influencing alcohol addiction. Rodents have been extensively utilized to study ethanol's rewarding and aversive effects, and to demonstrate the existence of genetic influences on traits such as free-choice ethanol-consumption, ethanol-conditioned place preference and ethanol-conditioned taste aversion. The purpose of the current investigation was to verify or eliminate from further consideration putative QTLs for free-choice ethanol consumption originally identified in BXD Recombinant Inbred (RI) strains and other informative genetic crosses. B6D2F2 mice were utilized in a verification testing strategy to evaluate the viability of putative ethanol consumption QTLs. When data were combined from BXD RI, B6D2F2 and short-term selected line (STSL) mapping studies, verification was obtained for two QTLs, one on Chromosome (Chr) 9 (proximal-mid) and another on Chr 2 (distal), and suggestive verification was obtained for QTLs on Chrs 2 (proximal), 3, 4, 7, and 15. In addition, the possible genetic association of ethanol consumption with conditioned place preference was evaluated. Genetic correlations were estimated from BXD RI strain means, and QTL maps for these traits were compared to evaluate the possibility of a genetic association. The correlational analysis yielded a trend (r = 0.34, p = 0.09), but no statistically significant results. However, comparisons of QTL mapping results between phenotypes suggested some possible genetic overlap for these traits, both putative measures of ethanol reward. These data suggest that the determinants of these two measures are genetically diverse, but may share some common genetic elements.

Alcohol Drinking↗

PubMed2003

Development of a linkage map and QTL scan for growth traits in North American bison.

PCR protocols incorporating fluorescently labeled multiplexed primer combinations were developed to produce a linkage map for bison. Three hundred fifty eight microsatellite loci spanning all 29 autosomes were genotyped via 83 PCR multiplexes and nine individual amplifications. A total of 292 markers were integrated into an autosomal linkage map for bison. The sex averaged bison map (2,647 cM) was approximately 9% longer than the corresponding USDA MARC map, which covered 2,415 cM. Utilizing weaning, yearling and 17-month weights from two private bison herds, a QTL scan was conducted using the developed linkage map. LOD peaks suggestive of QTL were identified on chromosomes 2, 7, 15, and 24 for weaning weight, chromosomes 4, 14, and 15 for yearling weight and chromosomes 8, 14, and 25 for 17-month weight. Four of the identified chromosomes have conserved synteny with regions harboring growth QTL in cattle.

Animals↗