scholarly journals Inferring Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 457-467 ◽  
Author(s):  
Z W Luo ◽  
S H Tao ◽  
Z-B Zeng
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Random Mating ◽  
Natural Populations ◽  
Polymorphic Marker ◽  
Marker Locus ◽  
Model Parameters ◽  
Phenotypic Variance ◽  
Wide Range ◽  
Trait Locus

Abstract Three approaches are proposed in this study for detecting or estimating linkage disequilibrium between a polymorphic marker locus and a locus affecting quantitative genetic variation using the sample from random mating populations. It is shown that the disequilibrium over a wide range of circumstances may be detected with a power of 80% by using phenotypic records and marker genotypes of a few hundred individuals. Comparison of ANOVA and regression methods in this article to the transmission disequilibrium test (TDT) shows that, given the genetic variance explained by the trait locus, the power of TDT depends on the trait allele frequency, whereas the power of ANOVA and regression analyses is relatively independent from the allelic frequency. The TDT method is more powerful when the trait allele frequency is low, but much less powerful when it is high. The likelihood analysis provides reliable estimation of the model parameters when the QTL variance is at least 10% of the phenotypic variance and the sample size of a few hundred is used. Potential use of these estimates in mapping the trait locus is also discussed.

scholarly journals Modeling Linkage Disequilibrium Between a Polymorphic Marker Locus and a Locus Affecting Complex Dichotomous Traits in Natural Populations

Genetics ◽  
2001 ◽  
Vol 158 (4) ◽  
pp. 1785-1800 ◽  
Author(s):  
Z W Luo ◽  
Chung-I Wu
Keyword(s):  
Linkage Disequilibrium ◽  
Complex Traits ◽  
Natural Populations ◽  
Polymorphic Marker ◽  
Marker Locus ◽  
Likelihood Method ◽  
Model Parameters ◽  
Higher Power ◽  
Trait Locus ◽  
Dichotomous Trait

AbstractLinkage disequilibrium is an important topic in evolutionary and population genetics. An issue yet to be settled is the theory required to extend the linkage disequilibrium analysis to complex traits. In this study, we present theoretical analysis and methods for detecting or estimating linkage disequilibrium (LD) between a polymorphic marker locus and any one of the loci affecting a complex dichotomous trait on the basis of samples randomly or selectively collected from natural populations. Statistical properties of these methods were investigated and their powers were compared analytically or by use of Monte Carlo simulations. The results show that the disequilibrium may be detected with a power of 80% by using phenotypic records and marker genotype when both the trait and marker variants are common (30%) and the LD is relatively high (40–100% of the theoretical maximum). The maximum-likelihood approach provides accurate estimates of the model parameters as well as detection of linkage disequilibrium. The likelihood method is preferred for its higher power and reliability in parameter estimation. The approaches developed in this article are also compared to those for analyzing a continuously distributed quantitative trait. It is shown that a larger sample size is required for the dichotomous trait model to obtain the same level of power in detecting linkage disequilibrium as the continuous trait analysis. Potential use of these estimates in mapping the trait locus is also discussed.

Genetic Analysis of Traits Distinguishing Outcrossing and Self-Pollinating Forms of Currant Tomato, Lycopersicon pimpinellifolium (Jusl.) Mill.

Genetics ◽  
2002 ◽  
Vol 161 (1) ◽  
pp. 333-344 ◽  
Author(s):  
Michael S Georgiady ◽  
Richard W Whitkus ◽  
Elizabeth M Lord
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Natural Populations ◽  
Rflp Markers ◽  
Phenotypic Variance ◽  
Style Length ◽  
Lycopersicon Pimpinellifolium ◽  
Anther Length ◽  
Trait Locus ◽  
Locus Mapping

Abstract The evolution of inbreeding is common throughout the angiosperms, although little is known about the developmental and genetic processes involved. Lycopersicon pimpinellifolium (currant tomato) is a self-compatible species with variation in outcrossing rate correlated with floral morphology. Mature flowers from inbreeding and outcrossing populations differ greatly in characters affecting mating behavior (petal, anther, and style lengths); other flower parts (sepals, ovaries) show minimal differences. Analysis of genetic behavior, including quantitative trait locus (QTL) mapping, was performed on representative selfing and outcrossing plants derived from two contrasting natural populations. Six morphological traits were analyzed: flowers per inflorescence; petal, anther, and style lengths; and lengths of the fertile and sterile portions of anthers. All traits were smaller in the selfing parent and had continuous patterns of segregation in the F2. Phenotypic correlations among traits were all positive, but varied in strength. Quantitative trait locus mapping was done using 48 RFLP markers. Five QTL total were found involving four of the six traits: total anther length, anther sterile length, style length, and flowers per inflorescence. Each of these four traits had a QTL of major (>25%) effect on phenotypic variance.

scholarly journals EFFECTS OF PLEIOTROPY ON PREDICTIONS CONCERNING MUTATION-SELECTION BALANCE FOR POLYGENIC TRAITS

Genetics ◽  
1985 ◽  
Vol 111 (1) ◽  
pp. 165-195
Author(s):  
Michael Turelli
Keyword(s):  
Genetic Model ◽  
Gaussian Approximation ◽  
Natural Populations ◽  
Pleiotropic Effects ◽  
Mutation Rates ◽  
Phenotypic Variance ◽  
Wide Range ◽  
Polygenic Traits ◽  
Selection Parameters ◽  
Mutation And Selection

ABSTRACT Previous mathematical analyses of mutation-selection balance for metric traits assume that selection acts on the relevant loci only through the character(s) under study. Thus, they implicitly assume that all of the relevant mutation and selection parameters are estimable. A more realistic analysis must recognize that many of the pleiotropic effects of loci contributing variation to a given character are not known. To explore the consequences of these hidden effects, I analyze models of two pleiotropically connected polygenic traits, denoted P  1 and P  2. The actual equilibrium genetic variance for P  1, based on complete knowledge of all mutation and selection parameters for both P  1 and P  2, can be compared to a prediction based solely on observations of P  1. This extrapolation mimics empirically obtainable predictions because of the inevitability of unknown pleiotropic effects. The mutation parameters relevant to P  1 are assumed to be known, but selection intensity is estimated from the within-generation reduction of phenotypic variance for P  1. The extrapolated prediction is obtained by substituting these parameters into formulas based on single-character analyses. Approximate analytical and numerical results show that the level of agreement between these univariate extrapolations and the actual equilibrium variance depends critically on both the genetic model assumed and the relative magnitudes of the mutation and selection parameters. Unless per locus mutation rates are extremely high, i.e., generally greater than 10-4, the widely used gaussian approximation for genetic effects at individual loci is not applicable. Nevertheless, the gaussian approximations predict that the true and extrapolated equilibria are in reasonable agreement, i.e., within a factor of two, over a wide range of parameter values. In contrast, an alternative approximation that applies for moderate and low per locus mutation rates predicts that the extrapolation will generally overestimate the true equilibrium variance unless there is little selection associated with hidden effects. The tendency to overestimate is understandable because selection acts on all of the pleiotropic manifestations of a new mutation, but equilibrium covariances among the characters affected may not reveal all of this selection. This casts doubt on the proposal that much of the additive polygenic variance observed in natural populations can be explained by mutation-selection balance. It also indicates the difficulty of critically evaluating this hypothesis.

scholarly journals STATISTICAL STUDIES ON PROTEIN POLYMORPHISM IN NATURAL POPULATIONS. III. DISTRIBUTION OF ALLELE FREQUENCIES AND THE NUMBER OF ALLELES PER LOCUS

Genetics ◽  
1980 ◽  
Vol 94 (4) ◽  
pp. 1039-1063
Author(s):  
Ranajit Chakraborty ◽  
Paul A Fuerst ◽  
Masatoshi Nei
Keyword(s):  
Molecular Weight ◽  
Allele Frequency ◽  
Frequency Distribution ◽  
Gene Frequency ◽  
Natural Populations ◽  
Allele Frequencies ◽  
Protein Polymorphism ◽  
Allele Frequency Distribution ◽  
Wide Range ◽  
Rare Alleles

ABSTRACT With the aim of understanding the mechanism of maintenance of protein polymorphism, we have studied the properties of allele frequency distribution and the number of alleles per locus, using gene-frequency data from a wide range of organisms (mammals, birds, reptiles, amphibians, Drosophila and non-Drosophila invertebrates) in which 20 or more loci with at least 100 genes were sampled. The observed distribution of allele frequencies was U-shaped in all of the 138 populations (mostly species or subspecies) examined and generally agreed with the theoretical distribution expected under the mutation-drift hypothesis, though there was a significant excess of rare alleles (gene frequency, 0 ~ 0.05) in about a quarter of the populations. The agreement between the mutation-drift theory and observed data was quite satisfactory for the numbers of polymorphic (gene frequency, 0.05 ~ 0.95) and monomorphic (0.95 ~ 1.O) alleles.—The observed pattern of allele-frequency distribution was incompatible with the prediction from the overdominance hypothesis. The observed correlations of the numbers of rare alleles, polymorphic alleles and monomorphic alleles with heterozygosity were of the order of magnitude that was expected under the mutation-drift hypothesis. Our results did not support the view that intracistronic recombination is an important source of genetic variation. The total number of alleles per locus was positively correlated with molecular weight in most of the species examined, and the magnitude of the correlation was consistent with the theoretical prediction from mutation-drift hypothesis. The correlation between molecular weight and the number of alleles was generally higher than the correlation between molecular weight and heterozygosity, as expected.

scholarly journals Linkage Disequilibrium Between Allozymes in Natural Populations of Lodgepole Pine

Genetics ◽  
1987 ◽  
Vol 115 (2) ◽  
pp. 341-352
Author(s):  
B K Epperson ◽  
R W Allard
Keyword(s):  
Linkage Disequilibrium ◽  
Pinus Contorta ◽  
Lodgepole Pine ◽  
Random Mating ◽  
Natural Populations ◽  
Population Substructure ◽  
Population Subdivision ◽  
Chi Square ◽  
Pairwise Linkage Disequilibrium ◽  
Allozyme Loci

ABSTRACT Pairwise linkage disequilibrium values (D) were estimated for 14 allozyme loci in two natural populations of lodgepole pine (Pinus contorta ssp. latifolia). Maternal multilocus genotypes were inferred from samples of (haploid) megagametophytic seed-endosperms. Coupling/repulsion double heterozygotes were distinguished for closely linked pairs of loci. Assays of seven of the loci in seed embryos allowed estimates of D for these loci in the outcross pollen pool (estimates of outcrossing rates indicate no significant departures from random mating in either population). No disequilibrium was observed between unlinked loci in either maternal genotypes or outcross pollen. However, significant disequilibrium was observed within and between gametes for some allelic combinations of four tightly linked loci; the assumption of random association of gamete types within individuals is thus invalid for some loci in lodgepole pine. Possible causes of the observed D were examined using the noncentrality parameter of the general noncentral chi square distribution. We concluded, from estimates of population size, linkage and measurements of population substructure, that neither drift nor population subdivision was responsible for the significant values of D which were observed and that epistatic selection was the most likely cause of the disequilibrium observed.

scholarly journals Allele frequency changes in artificial selection experiments: statistical power and precision of QTL mapping

1999 ◽  
Vol 73 (2) ◽  
pp. 177-184 ◽  
Author(s):  
YUSEOB KIM ◽  
WOLFGANG STEPHAN
Keyword(s):  
Allele Frequency ◽  
Artificial Selection ◽  
Statistical Power ◽  
Statistical Tests ◽  
Marker Locus ◽  
Marker Allele ◽  
Selection Experiments ◽  
Correct Location ◽  
Trait Locus ◽  
Frequency Changes

A simple mathematical model of genic directional selection is developed to study frequency changes of genetic marker alleles that are partially linked to a quantitative trait locus (QTL) under artificial selection. The effects of population size, number of generations of artificial selection, recombination between marker locus and QTL, and the strength of selection on the change in allele frequency are analysed by the diffusion equation approach and by stimulation. Using these results, we investigate the power of statistical tests for the detection of QTLs based on the observation of significant marker allele frequency changes in selection experiments. The probability of inferring the correct location of a QTL is also obtained.

scholarly journals Polygenicity and epistasis underlie fitness-proximal traits in the Caenorhabditis elegans multiparental experimental evolution (CeMEE) panel

2017 ◽  
Author(s):  
Luke M. Noble ◽  
Ivo Chelo ◽  
Thiago Guzella ◽  
Bruno Afonso ◽  
David D. Riccardi ◽  
...  
Keyword(s):  
Caenorhabditis Elegans ◽  
Experimental Evolution ◽  
Complex Traits ◽  
Genetic Basis ◽  
Natural Populations ◽  
Phenotypic Variance ◽  
Nucleotide Polymorphisms ◽  
C Elegans ◽  
Mapping Panel ◽  
Trait Locus

ABSTRACTUnderstanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty is problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here we report a recombinant inbred line (RIL) quantitative trait locus (QTL) mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs, was created by hybridization of 16 wild isolates, experimental evolution at moderate population sizes and predominant outcrossing for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single nucleotide polymorphisms known to segregate in natural populations, and complements existing mapping resources for C. elegans by providing high nucleotide diversity across >95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad sense heritability in the CeMEE. While simulations show we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits does not feature such alleles. We instead find that a significant fraction of trait variance, particularly for fertility, can be explained by sign epistasis with weak main effects. In congruence, phenotype prediction, while generally poor (r2 < 10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the highly recombinant, rapidly evolving chromosome arms.

scholarly journals Re-evaluation of SNP heritability in complex human traits

2016 ◽  
Author(s):  
Doug Speed ◽  
Na Cai ◽  
Michael R. Johnson ◽  
Sergey Nejentsev ◽  
David J Balding ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Minor Allele Frequency ◽  
Minor Allele ◽  
Phenotypic Variance ◽  
Improved Model ◽  
Complex Human Traits ◽  
Variance Explained

SNP heritability, the proportion of phenotypic variance explained by SNPs, has been reported for many hundreds of traits. Its estimation requires strong prior assumptions about the distribution of heritability across the genome, but the assumptions in current use have not been thoroughly tested. By analyzing imputed data for a large number of human traits, we empirically derive a model that more accurately describes how heritability varies with minor allele frequency, linkage disequilibrium and genotype certainty. Across 19 traits, our improved model leads to estimates of common SNP heritability on average 43% (SD 3) higher than those obtained from the widely-used software GCTA, and 25% (SD 2) higher than those from the recently-proposed extension GCTA-LDMS. Previously, DNaseI hypersensitivity sites were reported to explain 79% of SNP heritability; using our improved heritability model their estimated contribution is only 24%.

scholarly journals Estimating Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽  
1999 ◽  
Vol 151 (1) ◽  
pp. 359-371 ◽  
Author(s):  
Z W Luo ◽  
S Suhai
Keyword(s):  
Linkage Disequilibrium ◽  
Maximum Likelihood ◽  
Genetic Marker ◽  
Positional Cloning ◽  
Genetic Parameters ◽  
Marker Locus ◽  
Maximum Likelihood Estimates ◽  
Accurate Estimation ◽  
Asymptotic Covariance Matrix ◽  
Trait Locus

Abstract Positional cloning of gene(s) underlying a complex trait requires a high-resolution linkage map between the trait locus and genetic marker loci. Recent research has shown that this may be achieved through appropriately modeling and screening linkage disequilibrium between the candidate marker locus and the major trait locus. A quantitative genetics model was developed in the present study to estimate the coefficient of linkage disequilibrium between a polymorphic genetic marker locus and a locus underlying a quantitative trait as well as the relevant genetic parameters using the sample from randomly mating populations. Asymptotic covariances of the maximum-likelihood estimates of the parameters were formulated. Convergence of the EM-based statistical algorithm for calculating the maximum-likelihood estimates was confirmed and its utility to analyze practical data was exploited by use of extensive Monte-Carlo simulations. Appropriateness of calculating the asymptotic covariance matrix in the present model was investigated for three different approaches. Numerical analyses based on simulation data indicated that accurate estimation of the genetic parameters may be achieved if a sample size of 500 is used and if segregation at the trait locus explains not less than a quarter of phenotypic variation of the trait, but the study reveals difficulties in predicting the asymptotic variances of these maximum-likelihood estimates. A comparison was made between the statistical powers of the maximum-likelihood analysis and the previously proposed regression analysis for detecting the disequilibrium.

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