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PubMed2003

[Genetic analysis of segregation distortion of molecular markers in maize F2 population].

A genetic linkage map of maize was constructed using 150 SSR and 24 RFLP markers, with F2 population from an elite hybrid (Zong3 x 87-1). Among 174 markers, covering whole maize 10 chromosomes, 49 markers (28.1%) showed the genetic distortion (P < 0.05). Of the total segregation distortion markers, 11 markers (22.5%) deviated toward male parent, Zong3, while 12 markers (24.5%) deviated toward female parent, 87-1, besides 25 markers (51.0%) distorted to heterozygote. Only one marker distorted to both parents. Totally, 14 segregation distortion regions (SDRs) were detected among 9 different chromosomes. Four of them were located in near regions where gametophyte genes were mapped, indicating that segregation distortion may be caused by gametophyte genes partially. Two segregation distortion regions, SDR6-1 and SDR7-1, detected in this study, seemed to be new segregation distortion regions. In this paper, reasons for segregation distortion and effects of segregation distortion on genetic mapping and QTL analysis were discussed. Regarding to QTL analysis with single locus, segregation distortion would not affect QTL mapping, but regarding to analysis of digenic interactions for epistasis, the fewer distortion markers and larger size population would be needed.

Chromosome Mapping↗

PubMed2004

Fine mapping of a malting-quality QTL complex near the chromosome 4H S telomere in barley.

Malting quality has long been an active objective in barley (Hordeum vulgare L.) breeding programs.However, it is difficult for breeders to manipulate malting-quality traits because of inheritance complexity and difficulty in evaluation of these quantitative traits. Quantitative trait locus (QTL) mapping provides breeders a promising basis with which to manipulate quantitative trait genes. A malting-quality QTL complex, QTL2, was mapped previously to a 30-cM interval in the short-arm telomere region of barley chromosome 4H in a "Step-toe"/"Morex" doubled haploid population by the North American Barley Genome Project, using an interval mapping method with a relatively low-resolution genetic map. The QTL2 complex has moderate effects on several malting-quality traits, including malt extract percentage(ME), a-amylase activity (AA), diastatic power (DP), malt 13-glucan content (BG), and seed dormancy, which makes it a promising candidate gene source in malting barley-cultivar development. Fine mapping QTL2 is desirable for precisely studying barley malting-quality trait inheritance and for efficiently manipulating QTL2 in breeding. A reciprocal-substitution mapping method was employed to fine map QTL2. Molecular marker-assisted backcrossing was used to facilitate the generation of isolines. Fourteen different types of "Steptoe" isolines, including regenerated "Steptoe" and 13 different types of "Morex" isolines,including regenerated "Morex", were made within a 41.5-cM interval between MWG634 and BCD265B on chromosome 4H. Duplicates were identified for 12 "Steptoe" and 12 "Morex" isoline types. The isolines together with "Steptoe" and "Morex" were grown variously at three locations in 2 years for a total of five field environments.Four malting-quality traits were measured: ME, DP, AA,and BG. Few significant differences were found between duplicate isolines for these traits. A total of 15 putative QTLs were mapped; three for ME, four for DP, six for AA,and two for BG. Background genotype seemed to make a difference in expression/detection of QTLs. Of the 15 QTLs identified, ten were from the "Morex" and only five from the "Steptoe" background. By combining the results from different years, field environments, and genetic backgrounds and taking into account overlapping QTLsegments, six QTLs can be conservatively estimated: two each for ME and AA and one each for DP and BG with chromosome segments ranging from 0.7 cM to 27.9 cM. A segment of 15.8 cM from the telomere (MWG634-CDO669) includes all or a portion of all QTLs identified. Further study and marker-assisted breeding should focus on this 15.8-cM chromosome region.

Breeding↗

PubMed2006

[Advance in quantitative traits from phenotypic variation to gene discovery].

With the rapid development of molecular biotechnology, many improved approaches have been provided for studying on the genetic bases of quantitative traits. Many studies paid attention to dissect the genetic bases using different emendatory approaches from phenotypic variation to gene discovery, mainly containing QTL mapping, chemical mutagenesis etc. Especially, QTL analysis was executed for a lot of important quantitative traits. This paper summarizes the development of quantitative genetics, the recent progress on QTL mapping populations and methods, the status of QTL locating and QTG identification, positional cloning, and QTL application in breeding.

Animals↗

PubMed2003

Robust indices of Hardy-Weinberg disequilibrium for QTL fine mapping.

Hardy-Weinberg disequilibrium (HWD) measures have been proposed using dense markers to fine map a quantitative trait locus (QTL) to regions < approximately 1 cM. Earlier HWD measures may introduce bias in the fine mapping because they are dependent on marker allele frequencies across loci. Hence, HWD indices that do not depend on marker allele frequencies are desired for fine mapping. Based on our earlier work, here we present four new HWD indices that do not depend on marker allele frequencies. Two are for use when marker allele frequencies in a study population are known, and two are for use when marker allele frequencies in a study population are not known and are only known in the extreme samples. The new measures are a function of the genetic distance between the marker locus and a QTL. Through simulations, we investigated and compared the fine mapping performance of the new HWD measures with that of the earlier ones. Our results show that when marker allele frequencies vary across loci, the new measures presented here are more robust and powerful.

Chromosome Mapping↗

PubMed2005

Quantitative trait locus mapping in natural populations: progress, caveats and future directions.

Over the last 15 years quantitative trait locus (QTL) mapping has become a popular method for understanding the genetic basis of continuous variation in a variety of systems. For example, the technique is now an integral tool in medical genetics, livestock production, plant breeding and population genetics of model organisms. Ten years ago, it was suggested that the method could be used to understand continuous variation in natural populations. In this review I: (i) clarify what is meant by natural population in the QTL context, (ii) discuss whether evolutionary biologists have successfully mapped QTL in natural populations, (iii) highlight some of the questions that have been addressed by QTL mapping in natural populations, (iv) describe how QTL mapping can be conducted in unmanipulated natural populations, (v) highlight some of the limitations of QTL mapping and (vi) try to predict some future directions for QTL mapping in natural populations.

Biological Evolution↗

PubMed2003

Fine mapping of quantitative trait loci for improved fruit characteristics from Lycopersicon chmielewskii chromosome 1.

The near-isogenic line (NIL) TA1150 contains a 56-cM introgression from Lycopersicon chmielewskii chromosome 1 and has several interesting phenotypic characteristics including fruit with orange color, high levels of soluble solids, thick pericarp, small stem scars, and good firmness. A set of overlapping recombinant lines (subNILs) was developed and field tested to fine map the quantitative trait loci (QTL) controlling these traits. The results indicated that the solids, pericarp thickness, and firmness QTL are distinct from the color locus. Several of the QTL mapped in this study, including the soluble-solids QTL, probably correspond to QTL mapped in other wild species of tomato. However, analysis of a set of TA523 subNILs containing complementary introgressions from Lycopesicon hirsutum chromosome 1 suggests that this wild species may contain a different locus for improved soluble solids. Thus, it might be possible to combine the L. chmielewskii and L. hirsutum alleles for these loci in a single line with the potential for extremely highly soluble solids. The TA1150 subNIL TA1688 contains the smallest introgression of the solids locus (approximately 19 cM), as well as the pericarp thickness and firmness QTL, with a yield that was equivalent to two of the three control lines. Isolation of recombinant subNILs from TA1688 should break the linkage between orange color and high solids and provide a small introgressed segment for marker-assisted breeding and genetic improvement of processing tomato.

Alleles↗

PubMed2002

The nature of quantitative genetic variation for Drosophila longevity.

Longevity is a typical quantitative trait: the continuous variation in life span observed in natural populations is attributable to genetic variation at multiple quantitative trait loci (QTL), environmental sensitivity of QTL alleles, and truly continuous environmental variation. To begin to understand the genetic architecture of longevity at the level of individual QTL, we have mapped QTL for Drosophila life span that segregate between two inbred strains that were not selected for longevity. A mapping population of 98 recombinant inbred lines (RIL) was derived from these strains, and life span of virgin male and female flies measured under control culture conditions, chronic heat and cold stress, heat shock and starvation stress, and high and low density larval environments. The genotypes of the RIL were determined for polymorphic roo transposable element insertion sites, and life span QTL were mapped using composite interval mapping methods. A minimum of 19 life span QTL were detected by recombination mapping. The life span QTL exhibited strong genotype by sex, genotype by environment, and genotype by genotype (epistatic) interactions. These interactions complicate mapping efforts, but evolutionary theory predicts such properties of segregating QTL alleles. Quantitative deficiency mapping of four longevity QTL detected in the control environment by recombination mapping revealed a minimum of 11 QTL in these regions. Clearly, longevity is a complex quantitative trait. In the future, linkage disequilibrium mapping can be used to determine which candidate genes in a QTL region correspond to the genetic loci affecting variation in life span, and define the QTL alleles at the molecular level.

Animals↗

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↗

PubMed1997

Quick method for confirmation of quantitative trait loci.

Numerous algorithms for the identification and genetic mapping of quantitative trait loci (QTL) have been developed. Methods for confirming QTL maps involve either examination of independent segregating populations or the construction of congenic lines differing only in the QTL of interest. Because these projects require a minimum of several years or thousands of marker assessments in laboratory mice, an alternative, faster congenic method has been proposed. In a preliminary study, we tested this method for confirming QTLs identified in crosses between the ILS and ISS selected lines of mice for differential sensitivity to the hypnotic effects of ethanol. Herein, we report the construction of "segregating congenic" strains in which each QTL is made homozygous in a single generation, whereas the remainder of the genetic background is allowed to segregate. Sensitivity to ethanol among the progeny of such mice is consistent with predictions. Phenotypic variation is high, as expected, due to the background segregation, and statistical significance was attained in only 2 of 7 comparisons. Such segregating congenic populations may be a valuable research tool for confirming QTL map positions and for subsequent assessment of individual pathways and mechanisms of action of individual QTLs.

Alcoholism↗

PubMed2005

[Methodology of mapping quantitative trait loci for discrete traits using maximum likelihood].

The maximum likelihood method was used to compare the efficiency of interval mapping with either the threshold model or the linear model. The irfluencing factors of quantitative trait loci (QTL) detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the number of segregating population was 500. The results showed that the threshold model was superior in terms of parameter estimation. It was a more efficient and accurate model of QTL mapping for discrete traits. In addition, the accuracy of QTL mapping depended on the effect of the putative QTL, the value of heritability and incidence directly. With an increase of QTL effect, heritability and incidence of categories, the accuracy of QTL mapping improved correspondingly.

Algorithms↗

PubMed2006

Quantitative trait loci x maternal cytoplasmic environment interaction for development rate in Oncorhynchus mykiss.

Effects of maternal cytoplasmic environment (MCE) on development rate in rainbow trout were evaluated within a quantitative trait loci (QTL) analysis framework. Previous research had identified QTL for development rate in doubled haploid (DH) progeny produced from a cross between the Oregon State University (OSU) and the Swanson (SW) River rainbow trout clonal lines. In this study, progeny for QTL mapping were produced from a cross between the OSU and Clearwater (CW) River clonal lines. Doubled haploids were produced from the OSU x CW F1 by androgenesis using eggs from different females (or MCEs); with androgenesis, the maternal nuclear genome was destroyed by irradiation and diploidy was restored by blocking the first embryonic cleavage by heat shock. All embryos were incubated at the same temperature and development rate quantified as time to hatch. Using a linkage map constructed primarily with AFLP markers, QTL mapping was performed, including MCE covariates and QTL x MCE effects in models for testing. The major QTL for development rate in the OSU x SW cross overlaps with the major QTL found in this OSU x CW cross; effects at this locus were the same across MCEs. Both MCE and QTL x MCE effects contribute to variability in development rate, but QTL x MCE were minor and detected only at small-effect QTL.

Animals↗

PubMed1993

Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci.

It is now possible to use complete genetic linkage maps to locate major quantitative trait loci (QTLs) on chromosome regions. The current methods of QTL mapping (e.g., interval mapping, which uses a pair or two pairs of flanking markers at a time for mapping) can be subject to the effects of other linked QTLs on a chromosome because the genetic background is not controlled. As a result, mapping of QTLs can be biased, and the resolution of mapping is not very high. Ideally when we test a marker interval for a QTL, we would like our test statistic to be independent of the effects of possible QTLs at other regions of the chromosome so that the effects of QTLs can be separated. This test statistic can be constructed by using a pair of markers to locate the testing position and at the same time using other markers to control the genetic background through a multiple regression analysis. Theory is developed in this paper to explore the idea of a conditional test via multiple regression analysis. Various properties of multiple regression analysis in relation to QTL mapping are examined. Theoretical analysis indicates that it is advantageous to construct such a testing procedure for mapping QTLs and that such a test can potentially increase the precision of QTL mapping substantially.

Chromosome Mapping↗

PubMed2005

An expectation-maximization-likelihood-ratio test for handling missing data: application in experimental crosses.

The mapping of quantitative trait loci (QTL) is an important research question in animal and human studies. Missing data are common in such study settings, and ignoring such missing data may result in biased estimates of the genotypic effect and thus may eventually lead to errant results and incorrect inferences. In this article, we developed an expectation-maximization (EM)-likelihood-ratio test (LRT) in QTL mapping. Simulation studies based on two different types of phylogenetic models revealed that the EM-LRT, a statistical technique that uses EM-based parameter estimates in the presence of missing data, offers a greater statistical power compared with the ordinary analysis-of-variance (ANOVA)-based test, which discards incomplete data. We applied both the EM-LRT and the ANOVA-based test in a real data set collected from F2 intercross studies of inbred mouse strains. It was found that the EM-LRT makes an optimal use of the observed data and its advantages over the ANOVA F-test are more pronounced when more missing data are present. The EM-LRT method may have important implications in QTL mapping in experimental crosses.

Algorithms↗

PubMed2002

Similar genetic susceptibility to form-deprivation myopia in three strains of chicken.

Myopia development in humans depends on a complex interplay between genetic and environmental factors. Many of those who become myopic when exposed to a myopigenic environment are likely to do so because of a genetic susceptibility, whereas others somehow remain immune. In the most intensively studied model of environmentally induced myopia, form-deprivation myopia in the chick, there is convincing evidence of differential genetic susceptibility to myopia development, both within-strains and between-strains. To date, however, these have involved relatively small differential responses. The aim of this investigation was to examine genetic susceptibility to a highly uniform regimen of form-deprivation in three strains of chick (white leghorn, brown leghorn and broiler) expected to differ greatly in genetic background and in normal eye size, and to gauge the potential for mapping the quantitative trait loci (QTL) underlying this differential susceptibility. Despite striking differences in normal eye size, all three strains studied developed a similar degree of induced myopia. Whilst the degree of induced vitreous chamber elongation differed significantly between-strains, it was concluded that the high within-strain variation in the response to form-deprivation would prevent the effective application of QTL mapping approaches to identify genes conferring this susceptibility. In contrast, the strains used here would be ideal for use in mapping QTL controlling normal ocular component dimensions.

Analysis of Variance↗

PubMed1996

Genetic mapping of quantitative trait loci controlling growth and wood quality traits in Eucalyptus grandis using a maternal half-sib family and RAPD markers.

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping, BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding.

Chromosome Mapping↗

PubMed2004

BioMercator: integrating genetic maps and QTL towards discovery of candidate genes.

SUMMARY: Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. AVAILABILITY: Available upon request (http://moulon/~bioinfo/BioMercator/). Free of charge for academic use.

Algorithms↗

PubMed1998

Combining different line crosses for mapping quantitative trait loci using the identical by descent-based variance component method.

Mapping quantitative trait loci (QTLs) is usually conducted with a single line cross. The power of such QTL mapping depends highly on the two parental lines. If the two lines are fixed for the same allele at a putative QTL, the QTL is undetectable. On the other hand, if a QTL is segregating in the line cross and is detected, the estimated variance of the QTL cannot be extrapolated beyond the statistical inference space of the two parental lines. To reduce the likelihood of missing a QTL and to increase the statistical inference space of the estimated QTL variance, we present a consensus QTL mapping strategy. We adopt the identical by descent (IBD)-based variance component method originally applied to human linkage analysis by combining multiple line crosses as independent families. We explore the properties of consensus QTL mapping and demonstrate the method with F2, backcross (BC), and full-sib (FS) families. In addition, we examine the effects of the QTL heritability, marker informativeness, QTL position, the number of families, and family size. We show that F2 families notably outperform BC and FS families in detecting a QTL. There is a substantial reduction in the standard deviation of the estimated QTL position and the separation of the QTL and polygenic variance. Finally, we show that the power to detect a QTL is greater when using a small number of large families than a large number of small families.

Chromosome Mapping↗

PubMed2003

Mapping quantitative trait loci in the case of a spike in the phenotype distribution.

A common departure from the usual normality assumption in QTL mapping concerns a spike in the phenotype distribution. For example, in measurements of tumor mass, some individuals may exhibit no tumors; in measurements of time to death after a bacterial infection, some individuals may recover from the infection and fail to die. If an appreciable portion of individuals share a common phenotype value (generally either the minimum or the maximum observed phenotype), the standard approach to QTL mapping can behave poorly. We describe several alternative approaches for QTL mapping in the case of such a spike in the phenotype distribution, including the use of a two-part parametric model and a nonparametric approach based on the Kruskal-Wallis test. The performance of the proposed procedures is assessed via computer simulation. The procedures are further illustrated with data from an intercross experiment to identify QTL contributing to variation in survival of mice following infection with Listeria monocytogenes.

Computer Simulation↗