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Results for “QTL mapping”

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PubMed2005

Methodology of mapping quantitative trait loci for ordinal traits of disease resistance in livestock.

Methodology of QTL mapping for ordinal traits of disease resistance based on the framework of a generalized linear model (GLM) was presented. The location and effect parameters of putative QTL were estimated using maximum likelihood method. The efficiency and power were compared with the linear model (LM). The factors influencing QTL detection efficiency (e.g. QTL effect and heritability) were simulated in our study too. Daughter design with multiple families was applied,and the number of segregating population was 500. Results showed that the threshold model has a certain advantage in location estimation and power of QTL mapping, and has efficiency and accuracy for ordinal traits. In addition,the accuracy of QTL mapping depends on the effect of putative quantitative trait loci and the value of heritability. With the increase of QTL effect and heritability, the accuracy of QTL mapping improves slightly.

Animals↗

PubMed2001

Screening for highly heterozygous chickens in outbred commercial broiler lines to increase detection power for mapping quantitative trait loci.

Two commercial broiler lines were used in an experiment to map quantitative trait loci (QTL) affecting disease resistance. Chickens from these lines were genotyped with 27 microsatellite markers to estimate heterozygosity and polymorphism information content (PIC), the probability that one parent is heterozygous at a marker locus and the other has a different genotype. Heterozygosity estimated from allelic frequencies was 0.52 for the two lines; however, heterozygosity calculated from actual counts of heterozygous loci was much lower (0.36) than the estimated heterozygosity. The PIC was 0.45 in these lines, and average allele number per marker locus was about 3.5. Twenty-five males produced from a cross between these two lines were screened with the DNA markers to select birds with high heterozygosity at marker loci. Mating simulation showed that uninformative matings could be reduced by about 5% if 12 pairs of males and females with the highest heterozygosity at marker loci were selected, which was about a 25% reduction in total uninformative matings. This experiment demonstrated that the heterozygosity and PIC in commercial broiler lines were low and selection for the birds with high heterozygosity at marker loci could increase informative content in chickens used in the experiments of QTL mapping, thus increasing detection power for QTL mapping.

Animal Husbandry↗

PubMed2003

Identification of quantitative trait loci influencing wood property traits in loblolly pine (Pinus taeda L.). III. QTL Verification and candidate gene mapping.

A long-term series of experiments to map QTL influencing wood property traits in loblolly pine has been completed. These experiments were designed to identify and subsequently verify QTL in multiple genetic backgrounds, environments, and growing seasons. Verification of QTL is necessary to substantiate a biological basis for observed marker-trait associations, to provide precise estimates of the magnitude of QTL effects, and to predict QTL expression at a given age or in a particular environment. Verification was based on the repeated detection of QTL among populations, as well as among multiple growing seasons for each population. Temporal stability of QTL was moderate, with approximately half being detected in multiple seasons. Fewer QTL were common to different populations, but the results are nonetheless encouraging for restricted applications of marker-assisted selection. QTL from larger populations accounted for less phenotypic variation than QTL detected in smaller populations, emphasizing the need for experiments employing much larger families. Additionally, 18 candidate genes related to lignin biosynthesis and cell wall structure were mapped genetically. Several candidate genes colocated with wood property QTL; however, these relationships must be verified in future experiments.

Chromosome Mapping↗

PubMed1997

Interval-specific congenic strains (ISCS): an experimental design for mapping a QTL into a 1-centimorgan interval.

A general experimental design that allows mapping of a quantitative trait locus (QTL) into a 1-cM interval is presented. The design consists of a series of strains, termed "interval-specific congenic strains (ISCS)". Each ISCS is recombinant at a specific 1-cM sub-interval out of an ordered set of sub-intervals, which together comprise a wider interval, to which a QTL was previously mapped. It is shown that a specific and previously detected QTL of moderate or even small effect can be accurately mapped into a 1-cM interval in a program involving a total of no more than 1000 individuals. Consequently, ISCS can serve as the ultimate genetic mapping procedure before the application of physical mapping tools for positional cloning of a QTL.

Chromosome Mapping↗

PubMed2006

Mapping quantitative trait loci using the experimental designs of recombinant inbred populations.

In the data collection of the QTL experiments using recombinant inbred (RI) populations, when individuals are genotyped for markers in a population, the trait values (phenotypes) can be obtained from the genotyped individuals (from the same population) or from some progeny of the genotyped individuals (from the different populations). Let Fu be the genotyped population and Fv (v>or=u) be the phenotyped population. The experimental designs that both marker genotypes and phenotypes are recorded on the same populations can be denoted as (Fu/Fv, u=v) designs and that genotypes and phenotypes are obtained from the different populations can be denoted as (Fu/Fv, v>u) designs. Although most of the QTL mapping experiments have been conducted on the backcross and F2(F2/F2) designs, the other (Fu/Fv, v>or=u) designs are also very popular. The great benefits of using the other (Fu/Fv, v>or=u) designs in QTL mapping include reducing cost and environmental variance by phenotyping several progeny for the genotyped individuals and taking advantages of the changes in population structures of other RI populations. Current QTL mapping methods including those for the (Fu/Fv, u=v) designs, mostly for the backcross or F2/F2 design, and for the F2/F3 design based on a one-QTL model are inadequate for the investigation of the mapping properties in the (Fu/Fv, u or=u) designs. In addition, the QTL mapping properties of the proposed and approximate methods in different designs are discussed. Simulations were performed to evaluate the performance of the proposed and approximate methods. The proposed method is proven to be able to correct the problems of the approximate and current methods for improving the resolution of genetic architecture of quantitative traits and can serve as an effective tool to explore the QTL mapping study in the system of RI populations.

Algorithms↗

PubMed2000

Bayesian mapping of quantitative trait loci for complex binary traits.

A complex binary trait is a character that has a dichotomous expression but with a polygenic genetic background. Mapping quantitative trait loci (QTL) for such traits is difficult because of the discrete nature and the reduced variation in the phenotypic distribution. Bayesian statistics are proved to be a powerful tool for solving complicated genetic problems, such as multiple QTL with nonadditive effects, and have been successfully applied to QTL mapping for continuous traits. In this study, we show that Bayesian statistics are particularly useful for mapping QTL for complex binary traits. We model the binary trait under the classical threshold model of quantitative genetics. The Bayesian mapping statistics are developed on the basis of the idea of data augmentation. This treatment allows an easy way to generate the value of a hypothetical underlying variable (called the liability) and a threshold, which in turn allow the use of existing Bayesian statistics. The reversible jump Markov chain Monte Carlo algorithm is used to simulate the posterior samples of all unknowns, including the number of QTL, the locations and effects of identified QTL, genotypes of each individual at both the QTL and markers, and eventually the liability of each individual. The Bayesian mapping ends with an estimation of the joint posterior distribution of the number of QTL and the locations and effects of the identified QTL. Utilities of the method are demonstrated using a simulated outbred full-sib family. A computer program written in FORTRAN language is freely available on request.

Algorithms↗

PubMed2006

Modeling segregation distortion for viability selection. I. Reconstruction of linkage maps with distorted markers.

Molecular markers have been widely used to map quantitative trait loci (QTL). The QTL mapping partly relies on accurate linkage maps. The non-Mendelian segregation of markers, which affects not only the estimation of genetic distance between two markers but also the order of markers on a same linkage group, is usually observed in QTL analysis. However, these distorted markers are often ignored in the real data analysis of QTL mapping so that some important information may be lost. In this paper, we developed a multipoint approach via Hidden Markov chain model to reconstruct the linkage maps given a specified gene order while simultaneously making use of distorted, dominant and missing markers in an F(2) population. The new method was compared with the methods in the MapManager and Mapmaker programs, respectively, and verified by a series of Monte Carlo simulation experiments along with a working example. Results showed that the adjusted linkage maps can be used for further QTL or segregation distortion locus (SDL) analysis unless there are strong evidences to prove that all markers show normal Mendelian segregation.

Chromosome Mapping↗

PubMed2006

Statistical methods for expression quantitative trait loci (eQTL) mapping.

Traditional genetic mapping has largely focused on the identification of loci affecting one, or at most a few, complex traits. Microarrays allow for measurement of thousands of gene expression abundances, themselves complex traits, and a number of recent investigations have considered these measurements as phenotypes in mapping studies. Combining traditional quantitative trait loci (QTL) mapping methods with microarray data is a powerful approach with demonstrated utility in a number of recent biological investigations. These expression quantitative trait loci (eQTL) studies are similar to traditional QTL studies, as a main goal is to identify the genomic locations to which the expression traits are linked. However, eQTL studies probe thousands of expression transcripts; and as a result, standard multi-trait QTL mapping methods, designed to handle at most tens of traits, do not directly apply. One possible approach is to use single-trait QTL mapping methods to analyze each transcript separately. This leads to an increased number of false discoveries, as corrections for multiple tests across transcripts are not made. Similarly, the repeated application, at each marker, of methods for identifying differentially expressed transcripts suffers from multiple tests across markers. Here, we demonstrate the deficiencies of these approaches and propose a mixture over markers (MOM) model that shares information across both markers and transcripts. The utility of all methods is evaluated using simulated data as well as data from an F(2) mouse cross in a study of diabetes. Results from simulation studies indicate that the MOM model is best at controlling false discoveries, without sacrificing power. The MOM model is also the only one capable of finding two genome regions previously shown to be involved in diabetes.

Animals↗

PubMedDate not supplied

Parallel computing in interval mapping of quantitative trait loci.

Linear regression analysis is considered the least computationally demanding method for mapping quantitative trait loci (QTL). However, simultaneous search for multiple QTL, the use of permutations to obtain empirical significance thresholds, and larger experimental studies significantly increase the computational demand. This report describes an easily implemented parallel algorithm, which significantly reduces the computing time in both QTL mapping and permutation testing. In the example provided, the analysis time was decreased to less than 15% of a single processor system by the use of 18 processors. We indicate how the efficiency of the analysis could be improved by distributing the computations more evenly to the processors and how other ways of distributing the data facilitate the use of more processors. The use of parallel computing in QTL mapping makes it possible to routinely use permutations to obtain empirical significance thresholds for multiple traits and multiple QTL models. It could also be of use to improve the computational efficiency of the more computationally demanding QTL analysis methods.

Algorithms↗

PubMedDate not supplied

Efficiency of population structures for mapping of Mendelian and imprinted quantitative trait loci in outbred pigs using variance component methods.

In a simulation study different designs for a pure line pig population were compared for efficiency of mapping QTL using the variance component method. Phenotypes affected by a Mendelian QTL, a paternally expressed QTL, a maternally expressed QTL or by a QTL without an effect were simulated. In all alternative designs 960 progeny were phenotyped. Given the limited number of animals there is an optimum between the number of families and the family size. Estimation of Mendelian and parentally expressed QTL is more efficient in a design with large family sizes. Too small a number of sires should be avoided to minimize chances of sires to be non-segregating. When a large number of families is used, the number of haplotypes increases which reduces the accuracy of estimating the QTL effect and thereby reduces the power to show a significant QTL and to correctly position the QTL. Dense maps allow for smaller family size due to exploitation of LD-information. Given the different possible modes of inheritance of the QTL using 8 to 16 boars, two litters per dam was optimal with respect to determining significance and correct location of the QTL for a data set consisting of 960 progeny. The variance component method combining linkage disequilibrium and linkage analysis seems to be an appropriate choice to analyze data sets which vary in marker density and which contain complex family structures.

Analysis of Variance↗

PubMed2005

A model selection-based interval-mapping method for autopolyploids.

While extensive progress has been made in quantitative trait locus (QTL) mapping for diploid species, similar progress in QTL mapping for polyploids has been limited due to the complex genetic architecture of polyploids. To date, QTL mapping in polyploids has focused mainly on tetraploids with dominant and/or codominant markers. Here, we extend this view to include any even ploidy level under a dominant marker system. Our approach first selects the most likely chromosomal marker configurations using a Bayesian selection criterion and then fits an interval-mapping model to each candidate. Profiles of the likelihood-ratio test statistic and the maximum-likelihood estimates (MLEs) of parameters including QTL effects are obtained via the EM algorithm. Putative QTL are then detected using a resampling-based significance threshold, and the corresponding parental configuration is identified to be the underlying parental configuration from which the data are observed. Although presented via pseudo-doubled backcross experiments, this approach can be readily extended to other breeding systems. Our method is applied to single-dose restriction fragment autotetraploid alfalfa data, and the performance is investigated through simulation studies.

Algorithms↗

PubMed2002

Modeling epistasis of quantitative trait loci using Cockerham's model.

We use the orthogonal contrast scales proposed by Cockerham to construct a genetic model, called Cockerham's model, for studying epistasis between genes. The properties of Cockerham's model in modeling and mapping epistatic genes under linkage equilibrium and disequilibrium are investigated and discussed. Because of its orthogonal property, Cockerham's model has several advantages in partitioning genetic variance into components, interpreting and estimating gene effects, and application to quantitative trait loci (QTL) mapping when compared to other models, and thus it can facilitate the study of epistasis between genes and be readily used in QTL mapping. The issues of QTL mapping with epistasis are also addressed. Real and simulated examples are used to illustrate Cockerham's model, compare different models, and map for epistatic QTL. Finally, we extend Cockerham's model to multiple loci and discuss its applications to QTL mapping.

Analysis of Variance↗

PubMed2000

Mapping quantitative trait loci in tetraploid populations.

Knowledge of quantitative trait locus (QTL) mapping in polyploids is almost void, albeit many exquisite strategies of QTL mapping have been proposed and extensive investigations have been carried out in diploid animals and plants. In this paper we develop a simple algorithm which uses an iteratively reweighted least square method to map QTLs in tetraploid populations. The method uses information from all markers in a linkage group to infer the probability distribution of QTL genotype under the assumption of random chromosome segregation. Unlike QTL mapping in diploid species, here we estimate and test the compound 'gametic effect', which consists of the composite 'genic effect' of alleles and higher-order gene interactions. The validity and efficiency of the proposed method are investigated through simulation studies. Results show that the method can successfully locate QTLs and separates different sources (e.g. additive and dominance) of variance components contributed by the QTLs.

Algorithms↗

PubMed2001

Consequences of recombination rate variation on quantitative trait locus mapping studies. Simulations based on the Drosophila melanogaster genome.

We examine the effect of variation in gene density per centimorgan on quantitative trait locus (QTL) mapping studies using data from the Drosophila melanogaster genome project and documented regional rates of recombination. There is tremendous variation in gene density per centimorgan across this genome, and we observe that this variation can cause systematic biases in QTL mapping studies. Specifically, in our simulated mapping experiments of 50 equal-effect QTL distributed randomly across the physical genome, very strong QTL are consistently detected near the centromeres of the two major autosomes, and few or no QTL are often detected on the X chromosome. This pattern persisted with varying heritability, marker density, QTL effect sizes, and transgressive segregation. Our results are consistent with empirical data collected from QTL mapping studies of this species and its close relatives, and they explain the "small X-effect" that has been documented in genetic studies of sexual isolation in the D. melanogaster group. Because of the biases resulting from recombination rate variation, results of QTL mapping studies should be taken as hypotheses to be tested by additional genetic methods, particularly in species for which detailed genetic and physical genome maps are not available.

Animals↗

PubMed2005

Quantitative trait loci affecting the difference in pigmentation between Drosophila yakuba and D. santomea.

Using quantitative trait locus (QTL) mapping, we studied the genetic basis of the difference in pigmentation between two sister species of Drosophila: Drosophila yakuba, which, like other members of the D. melanogaster subgroup, shows heavy black pigmentation on the abdomen of males and females, and D. santomea, an endemic to the African island of São Tomé, which has virtually no pigmentation. Here we mapped four QTL with large effects on this interspecific difference in pigmentation: two on the X chromosome and one each on the second and third chromosomes. The same four QTL were detected in male hybrids in the backcrosses to both D. santomea and D. yakuba and in the female D. yakuba backcross hybrids. All four QTL exhibited strong epistatic interactions in male backcross hybrids, but only one pair of QTL interacted in females from the backcross to D. yabuka. All QTL from each species affected pigmentation in the same direction, consistent with adaptive evolution driven by directional natural selection. The regions delimited by the QTL included many positional candidate loci in the pigmentation pathway, including genes affecting catecholamine biosynthesis, melanization of the cuticle, and many additional pleiotropic effects.

Animals↗

PubMed2004

Detection and mapping of QTL for earliness components in a bread wheat recombinant inbred lines population.

Earliness, an adaptative trait and factor of variation for agronomic characters, is a major trait in plant breeding. Its constituent traits, photoperiod sensitivity (PS), vernalization requirement (VR) and intrinsic earliness (IE), are largely under independent genetic controls. Mapping of major genes and quantitative trait loci (QTL) controlling these components is in progress. Most of the studies focusing on earliness considered it as a whole or through one (or two) of its components. The purpose of this study was to detect and map QTL for the three traits together through an experimental design combining field trials and controlled growth conditions. QTL were mapped in a population of F(7) recombinant inbred lines derived by single-seed descent from a cross between two French varieties, 'Renan' and 'Recital'. A map was previously constructed, based on 194 lines and 254 markers, covering about 77% of the genome. Globally, 13 QTL with a LOD>2.5 were detected, of which four control PS, five control VR and four control IE. Two major photoperiod sensitive QTL, together explaining more than 31% of the phenotypic variation, were mapped on chromosomes 2B and 2D, at the same position as the two major genes Ppd-B1 and Ppd-D1. One major VR QTL explaining (depending on the year) 21.8-39.6% of the phenotypic variation was mapped on 5A. Among the other QTL, two QTL of PS and VR not referenced so far were detected on 5A and 6D, respectively. A VR QTL already detected on 2B in a connected population was confirmed.

Bread↗

PubMed2004

Saturation mapping of QTL regions and identification of putative candidate genes for drought tolerance in rice.

We have developed 85 new markers (50 RFLPs, 5 SSRs, 12 DD cDNAs, 9 ESTs, 8 HSP-encoding cDNAs and one BSA-derived AFLP marker) for saturation mapping of QTL regions for drought tolerance in rice, in our efforts to identify putative candidate genes. Thirteen of the markers were localized in the close vicinity of the targeted QTL regions. Fifteen of the additional markers mapped, respectively, inside one QTL region controlling osmotic adjustment on chromosome 3 ( oa3.1) and 14 regions that affect root traits on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 10 and 12. Differential display was used to identify more putative candidate genes and to saturate the QTL regions of the genetic map. Eleven of the isolated cDNA clones were found to be derived from drought-inducible genes. Two of them were unique and did not match any genes in the GenBank, while nine were highly similar to cDNAs encoding known proteins, including a DnaJ-related protein, a zinc-finger protein, a protease inhibitor, a glutathione-S-transferase, a DNA recombinase, and a protease. Twelve new cDNA fragments were mapped onto the genetic linkage map; seven of these mapped inside, or in close proximity to, the targeted QTL regions determining root thickness and osmotic adjustment capacity. The gene I12A1, which codes for a UDP-glucose 4-epimerase homolog, was identified as a putative target gene within the prt7.1/brt7.1 QTL region, as it is involved in the cell wall biogenesis pathway and hence may be implicated in modulating the ability of rice roots to penetrate further into the substratum when exposed to drought conditions. RNAs encoding elongation factor 1beta, a DnaJ-related protein, and a homolog of wheat zinc-finger protein were more prominently induced in the leaves of IR62266 (the lowland rice parent of the mapping materials used) than in those of CT9993 (the upland rice parent) under drought conditions. Homologs of 18S ribosomal RNA, and mRNAs for a multiple-stress induced zinc-finger protein, a protease inhibitor, and a glutathione-S-transferase were expressed at significantly higher levels in CT9993 than in IR62266. Thus several genes involved in the regulation of DNA structure and mRNA translation were found to be drought-regulated, and may be implicated in drought resistance.

Blotting, Northern↗

PubMed2000

A general mixture model approach for mapping quantitative trait loci from diverse cross designs involving multiple inbred lines.

Most current statistical methods developed for mapping quantitative trait loci (QTL) based on inbred line designs apply to crosses from two inbred lines. Analysis of QTL in these crosses is restricted by the parental genetic differences between lines. Crosses from multiple inbred lines or multiple families are common in plant and animal breeding programmes, and can be used to increase the efficiency of a QTL mapping study. A general statistical method using mixture model procedures and the EM algorithm is developed for mapping QTL from various cross designs of multiple inbred lines. The general procedure features three cross design matrices, W, that define the contribution of parental lines to a particular cross and a genetic design matrix, D, that specifies the genetic model used in multiple line crosses. By appropriately specifying W matrices, the statistical method can be applied to various cross designs, such as diallel, factorial, cyclic, parallel or arbitrary-pattern cross designs with two or multiple parental lines. Also, with appropriate specification for the D matrix, the method can be used to analyse different kinds of cross populations, such as F2 backcross, four-way cross and mixed crosses (e.g. combining backcross and F2). Simulation studies were conducted to explore the properties of the method, and confirmed its applicability to diverse experimental designs.

Animals↗