Topic
Quantitative trait locus
About: Quantitative trait locus is a research topic. Over the lifetime, 24006 publications have been published within this topic receiving 998782 citations. The topic is also known as: QTL & Quantitative Trait Locus.
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Book•
01 Jan 1996
TL;DR: This book discusses the genetic Basis of Quantitative Variation, Properties of Distributions, Covariance, Regression, and Correlation, and Properties of Single Loci, and Sources of Genetic Variation for Multilocus Traits.
Abstract: I. The Genetic Basis of Quantitative Variation - An Overview of Quantitative Genetics - Properties of Distributions - Covariance, Regression, and Correlation - Properties of Single Loci - Sources of Genetic Variation for Multilocus Traits - Sources of Environmental Variation - Resemblance Between Relatives - Introduction to Matrix Algebra and Linear Models - Analysis of Line Crosses - Inbreeding Depression - Matters of Scale - II. Quantitative-Trait Loci - Polygenes and Polygenic Mutation - Detecting Major Genes - Basic Concepts of Marker-Based Analysis - Mapping and Characterizing QTLs: Inbred-Line Crosses - Mapping and Characterizing QTLs: Outbred Populations - III. Estimation Procedures - Parent-Offspring Regression - Sib AnalysisTwins and Clones - Cross-Classified Designs - Correlations Between Characters - Genotype x Environment Interaction - Maternal Effects Sex Linkage and Sexual Dimorphism - Threshold Characters - Estimation of Breeding Values - Variance-Component Estimation with Complex Pedigrees - Appendices - Expectations, Variances and Covariances of Compound Variables - Path Analysis - Matrix Algebra and Linear Models - Maximum Likelihood Estimation and Likelihood-Ratio Tests - Estimation of Power of Statistical Tests -
6,530 citations
TL;DR: The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets and focuses on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation.
Abstract: For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the “missing heritability” problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.
5,867 citations
TL;DR: An empirical method is described, based on the concept of a permutation test, for estimating threshold values that are tailored to the experimental data at hand, and is demonstrated using two real data sets derived from F(2) and recombinant inbred plant populations.
Abstract: The detection of genes that control quantitative characters is a problem of great interest to the genetic mapping community. Methods for locating these quantitative trait loci (QTL) relative to maps of genetic markers are now widely used. This paper addresses an issue common to all QTL mapping methods, that of determining an appropriate threshold value for declaring significant QTL effects. An empirical method is described, based on the concept of a permutation test, for estimating threshold values that are tailored to the experimental data at hand. The method is demonstrated using two real data sets derived from F(2) and recombinant inbred plant populations. An example using simulated data from a backcross design illustrates the effect of marker density on threshold values.
4,964 citations
TL;DR: In this paper, a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs) are described, and explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.
Abstract: The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.
4,856 citations
TL;DR: It is proposed that the diminishing additivity of QTL effects is amplified when more loci are involved; this mode of epistasis may be an important factor in phenotype canalization and in breeding.
Abstract: Epistasis plays a role in determining the phenotype, yet quantitative trait loci (QTL) mapping has uncovered little evidence for it. To address this apparent contradiction, we analyzed interactions between individual Lycopersicon pennellii chromosome segments introgressed into an otherwise homogeneous genetic background of L. esculentum (cv. M82). Ten different homozygous introgression lines, each containing from 4 to 58 cM of introgressed DNA, were crossed in a half diallele scheme. The 45 derived double heterozygotes were evaluated in the field for four yield-associated traits, along with the 10 single heterozygotes and M82. Of 180 (45 X 4) tested interactions, 28% were epistatic (P < 0.05) on both linear and geometric scales. The detected epistasis was predominately less-than-additive, i.e., the effect of the double heterozygotes was smaller than the sum of the effects of the corresponding single heterozygotes. Epistasis was also found for homozygous linked QTL affecting fruit mass and total soluble solids. Although the frequency of epistasis was high, additivity was the major component in the interaction of pairs of QTL. We propose that the diminishing additivity of QTL effects is amplified when more loci are involved; this mode of epistasis may be an important factor in phenotype canalization and in breeding.
4,694 citations