Joint Multipoint Linkage Analysis of Multivariate Qualitative and Quantitative Traits. II. Alcoholism and Event-Related Potentials

The availability of robust quantitative biological markers that are correlated with qualitative psychiatric phenotypes can potentially improve the power of linkage methods to detect quantitative-trait loci influencing psychiatric disorders. We apply a variance-component method for joint multipoint linkage analysis of multivariate discrete and continuous traits to the extended pedigree data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate analysis of qualitative alcoholism phenotypes and quantitative event-related potentials. Joint consideration of the DSM-IV diagnosis of alcoholism and the amplitude of the P300 component of the Cz event-related potential significantly increases the evidence for linkage of these traits to a chromosome 4 region near the class I alcohol dehydrogenase locus ADH3. A likelihood-ratio test for complete pleiotropy is significant, suggesting that the same quantitative-trait locus influences both risk of alcoholism and the amplitude of the P300 component.     

The Effects of Selection on Linkage Analysis for Quantitative Traits

The effects of within-sample selection on the outcome of analyses detecting linkage between genetic markers and quantitative traits were studied. It was found that selection by truncation for the trait of interest significantly reduces the differences between marker genotype means thus reducing the power to detect linked quantitative trait loci (QTL). The size of this reduction is a function of proportion selected, the magnitude of the QTL effect, recombination rate between the marker locus and the QTL, and the allele frequency of the QTL. Proportion selected was the most influential of these factors on bias, e.g., for an allele substitution effect of one standard deviation unit, selecting the top 80%, 50% or 20% of the population required 2, 6 or 24 times the number of progeny, respectively, to offset the loss of power caused by this selection. The effect on power was approximately linear with respect to the size of gene effect, almost invariant to recombination rate, and a complex function of QTL allele frequency. It was concluded that experimental samples from animal populations which have been subjected to even minor amounts of selection will be inefficient in yielding information on linkage between markers and loci influencing the quantitative trait under selection.     

Multivariate Extensions of the Mixed Model for Quantitative Traits

The mixed model for complex segregation analysis of quantitative data from three-generational nuclear families is extended to the multivariate case. Likelihood functions for hypothesis testing are derived for two types of conditional analysis of multiple traits: first when entry to the study depends on the index case's values of all the quantitative traits that are of interest, and second when entry depends on only one trait, but other correlated traits are to be studied simultaneously. Using direct products of covariance matrices, these functions are seen to be direct multivariate equivalence of the univariate functions.     

离散性状QTL区间定位的最大似然方法

采用最大似然区间定位法对阈模型与一般线性模型的QTL定位效率进行了比较,并对影响离散性状QTL检测效率的主要因素（QTL效应、性状的遗传力和表型发生率）进行了模拟研究,实验设计为多个家系的女儿设计．资源群体大小为500头。研究结果表明：在QTL参数估计及检验功效方面,阈模型方法具有较大的优势,对离散性状QTL定位的效率明显高于LM（Linear Model）方法,定位的准确性也较高。另外,性状遗传力、QTL效应的大小和性状表型发生率对QTL定位的准确度也有直接的影响,随着性状遗传力和表型发生率的提高,随着QTL效应的增大,QTL定位的效率也进一步提高。     

The Effects of Spontaneous Mutation on Quantitative Traits. I. Variances and Covariances of Life History Traits

We have accumulated spontaneous mutations in the absence of natural selection in Drosophila melanogaster by backcrossing 200 heterozygous replicates of a single high fitness second chromosome to a balancer stock for 44 generations. At generations 33 and 44 of accumulation, we extracted samples of chromosomes and assayed their homozygous performance for female fecundity early and late in adult life, male and female longevity, male mating ability early and late in adult life, productivity (a measure of fecundity times viability) and body weight. The variance among lines increased significantly for all traits except male mating ability and weight. The rate of increase in variance was similar to that found in previous studies of egg-to-adult viability, when calculated relative to trait means. The mutational correlations among traits were all strongly positive. Many correlations were significantly different from 0, while none was significantly different from 1. These data suggest that the mutation-accumulation hypothesis is not a sufficient explanation for the evolution of senescence in D. melanogaster. Mutation-selection balance does seem adequate to explain a substantial proportion of the additive genetic variance for fecundity and longevity.     

尿蛋白定性与定量检测结果的差异性和相关性分析

目的：探讨尿液干化学法及免疫透射比浊法检测尿白蛋白结果的差异性及相关性。方法：对514例住院患者随机尿标本进行尿液干化学法及免疫透射比浊法尿蛋白的检测。结果：尿液干化学法阳性率为82．1％,免疫透射比浊法阳性率为72．8％。两种方法检测结果均为阴性标本的符合率为98．9％,为（±）的标本二者符合率为69．7％,为㈩的标本二者符合率为75．6％,为（＋＋）的标本二者符合率为67．2％,为（卅）标本中二者符合率为42．5％,为（＋＋H）标本二者的符合率为37．5％。两种方法的检测结果有显著性差异（P〈O．05）;UmAlb／Ucr、NAG、和NAG／Ucr与UmAlb具有显著相关（P〈0．05）,且UmAlb／Ucr与UmAlb的相关性最高。两种方法所得等级结果比较,＋＋～卅之间差异有统计学意义（P〈0．05）,-～±、±～＋、＋～＋＋、＋＋＋～＋＋＋＋之间差异均无统计学意义（P〉0．05）。结论：尿蛋白定性与定量检测结果存在显著性差异,而UmAlb／Ucr与UmAlb相关性较高。在泌尿系统疾病的诊断中,检测尿中UmAlb比尿常规更有意义。     

尿蛋白定性与定量检测结果的差异性和相关性分析

目的:探讨尿液干化学法及免疫透射比浊法检测尿白蛋白结果的差异性及相关性。方法:对514例住院患者随机尿标本进行尿液干化学法及免疫透射比浊法尿蛋白的检测。结果:尿液干化学法阳性率为82.1%,免疫透射比浊法阳性率为72.8%。两种方法检测结果均为阴性标本的符合率为98.9%,为(±)的标本二者符合率为69.7%,为(+)的标本二者符合率为75.6%,为(++)的标本二者符合率为67.2%,为(+++)标本中二者符合率为42.5%,为(++++)标本二者的符合率为37.5%。两种方法的检测结果有显著性差异(P0.05);UmAlb/Ucr、NAG、和NAG/Ucr与UmAlb具有显著相关(P0.05),且UmAlb/Ucr与UmAlb的相关性最高。两种方法所得等级结果比较,++~+++之间差异有统计学意义(P0.05),-~±、±~+、+~++、+++~++++之间差异均无统计学意义(P0.05)。结论:尿蛋白定性与定量检测结果存在显著性差异,而UmAlb/Ucr与UmAlb相关性较高。在泌尿系统疾病的诊断中,检测尿中UmAlb比尿常规更有意义。     

Molecular Mapping and Character Tagging in Brassica juncea—I. Degree,Nature and Linkage Relationship of RFLPs and Their Association With Quantitative Traits

For molecular mapping and character tagging in Indian mustard (Brassica juncea), cultivar Varuna and exotic collection BEC 144 were chosen on the basis of morphological and molecular differences. High degree of RFLP was detected between them using genomic DNA clones of Pst! subgenomic library as probes. Of the 48 probe — enzyme combinations, 89.5% were polymorphic. Majority of the probes revealed duplicate loci and a high frequency of null alleles (71.4%). Segregation analysis in the F² population revealed significant deviation from expected 1:2:1 ratio for 32% of the markers. Using the computer package MAPMAKER, 15 markers could be placed in six linkage groups which covered a total length of 173.9 eM. Based on single factor analysis of variance, three significant marker-quantitative trait associations viz. BJG 59a primary branches/plant, BJG 42Gb - secondary branches/plant and BJG 433-days to f1owering could be identified. The BEC 144 alleles at the quantitative trait loci (QTL) in the marked genomic regions enhanced the trait expression. The putative gene action at these loci was found to be non-additive.     

Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection.     

Likelihood Formulation of Parent-of-Origin Effects on Segregation Analysis, Including Ascertainment

We developed a likelihood-based method for testing for parent-of-origin effect in complex diseases. The likelihood formulations model parent-of-origin effect and allow for incorporation of ascertainment, as well as differential male and female ascertainment probabilities. The results based on simulated data indicated that the estimates of parental effect (either maternal or paternal) were biased when ascertainment was ignored or when the wrong ascertainment model was used. The exception was single ascertainment, in which we proved that ignoring ascertainment does not bias the estimation of parental effect, in a simple parent-of-origin model. These results underscore the importance of considering ascertainment models when testing for parent-of-origin effect in complex diseases.     

Bayesian Linkage Analysis of Categorical Traits for Arbitrary Pedigree Designs

Background

Pedigree studies of complex heritable diseases often feature nominal or ordinal phenotypic measurements and missing genetic marker or phenotype data.

Methodology

We have developed a Bayesian method for Linkage analysis of Ordinal and Categorical traits (LOCate) that can analyze complex genealogical structure for family groups and incorporate missing data. LOCate uses a Gibbs sampling approach to assess linkage, incorporating a simulated tempering algorithm for fast mixing. While our treatment is Bayesian, we develop a LOD (log of odds) score estimator for assessing linkage from Gibbs sampling that is highly accurate for simulated data. LOCate is applicable to linkage analysis for ordinal or nominal traits, a versatility which we demonstrate by analyzing simulated data with a nominal trait, on which LOCate outperforms LOT, an existing method which is designed for ordinal traits. We additionally demonstrate our method''s versatility by analyzing a candidate locus (D2S1788) for panic disorder in humans, in a dataset with a large amount of missing data, which LOT was unable to handle.

Conclusion

LOCate''s accuracy and applicability to both ordinal and nominal traits will prove useful to researchers interested in mapping loci for categorical traits.     

Maximum Likelihood Analysis of Rare Binary Traits under Different Modes of Inheritance

Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of sires/number of dams within sires (10/10, 30/30, 100/30). Major gene effects of at least one SD of the liability were detected with satisfactory power under the mixed model of inheritance, except for the smallest design. Parameter estimates were empirically unbiased with acceptable standard errors, except for the smallest design, and allowed to distinguish clearly between the genetic models. Distributions of the likelihood ratio statistic were evaluated empirically, because asymptotic theory did not hold. For each simulation model, the Average Information Criterion was computed for all models of analysis. The model with the smallest value was chosen as the best model and was equal to the true model in almost every case studied.     

Parameter Estimation and Quantitative Parametric Linkage Analysis with GENEHUNTER-QMOD

Objective: We present a parametric method for linkage analysis of quantitative phenotypes. The method provides a test for linkage as well as an estimate of different phenotype parameters. We have implemented our new method in the program GENEHUNTER-QMOD and evaluated its properties by performing simulations. Methods: The phenotype is modeled as a normally distributed variable, with a separate distribution for each genotype. Parameter estimates are obtained by maximizing the LOD score over the normal distribution parameters with a gradient-based optimization called PGRAD method. Results: The PGRAD method has lower power to detect linkage than the variance components analysis (VCA) in case of a normal distribution and small pedigrees. However, it outperforms the VCA and Haseman-Elston regression for extended pedigrees, nonrandomly ascertained data and non-normally distributed phenotypes. Here, the higher power even goes along with conservativeness, while the VCA has an inflated type I error. Parameter estimation tends to underestimate residual variances but performs better for expectation values of the phenotype distributions. Conclusion: With GENEHUNTER-QMOD, a powerful new tool is provided to explicitly model quantitative phenotypes in the context of linkage analysis. It is freely available at http://www.helmholtz-muenchen.de/genepi/downloads.     

Quantitative Genetics of DROSOPHILA MELANOGASTER. I. Sexual Dimorphism in Genetic Parameters for Wing Traits

Sexual dimorphism in genetic parameters is examined for wing dimensions of Drosophila melanogaster. Data are fit to a quantitative genetic model where phenotypic variance is a linear function of additive genetic autosomal variance (common to both sexes), additive genetic X-linked variances distinct for each sex, variance due to common rearing environment of families, residual environmental variance, random error variance due to replication, and variance due to measurement error and developmental asymmetry (left vs. right sides). Polygenic dosage compensation and its effect on genetic variances and covariances between sexes is discussed. Variance estimates for wing length and other wing dimensions highly correlated with length support the hypothesis that the Drosophila system of dosage compensation will cause male X-linked genetic variance to be substantially larger than female X-linked variance. Results for various wing dimensions differ, suggesting that the level of dosage compensation may differ for different traits. Genetic correlations between sexes for the same trait are presented. Total additive genetic correlations are near unity for most wing traits; this indicates that selection in the same direction in both sexes would have a minor effect on changing the magnitude of difference between sexes. Additive X-linked correlations suggest some genotype x sex interactions for X-linked effects.     

Statistics for Nonparametric Linkage Analysis of X-Linked Traits in General Pedigrees

We have compared the power of several allele-sharing statistics for "nonparametric" linkage analysis of X-linked traits in nuclear families and extended pedigrees. Our rationale was that, although several of these statistics have been implemented in popular software packages, there has been no formal evaluation of their relative power. Here, we evaluate the relative performance of five test statistics, including two new test statistics. We considered sibships of sizes two through four, four different extended pedigrees, 15 different genetic models (12 single-locus models and 3 two-locus models), and varying recombination fractions between the marker and the trait locus. We analytically estimated the sample sizes required for 80% power at a significance level of.001 and also used simulation methods to estimate power for a sample size of 10 families. We tried to identify statistics whose power was robust over a wide variety of models, with the idea that such statistics would be particularly useful for detection of X-linked loci associated with complex traits. We found that a commonly used statistic, S(all), generally performed well under various conditions and had close to the optimal sample sizes in most cases but that there were certain cases in which it performed quite poorly. Our two new statistics did not perform any better than those already in the literature. We also note that, under dominant and additive models, regardless of the statistic used, pedigrees with all-female siblings have very little power to detect X-linked loci.     

Genome-Wide Linkage Analysis Identifies Loci for Testicle and Ovary Traits in Chickens

Development of testes or ovaries is critical to chicken breeders. Understanding the genetic mechanisms influencing the development of the testes and ovaries could enhance selection efforts which target reproductive traits. The linkage analysis was conducted within an F2 population derived from Beijing-You chickens and a commercial broiler line. The results have identified one quantitative trait loci (QTL, designated T1) for bilateral testicular weight (TW) and the percentage of TW to carcass weight, and five QTLs (designated O1–O5) for ovary weight (follicle-free, OW) and the percentage of OW to carcass weight. For the testes traits, QTL T1 is located between 6.55 and 8.56 Mb on GGA13. Especially, the gene gamma-amino butyric acid A receptor, alpha 1 (GABRA1) located near the T1 peak. For ovarian traits, QTL O2 was located at 29.31 Mb on GGA7. G protein-coupled receptor 39 (GPR39) present at the O2 peak was expressed at higher levels within the reproductive tract. It is also involved in the regulation of several reproductive functions. Other QTL peaks and the genes’ function in the ovary and testes need to be evaluated. The QTLs and the genes identified in this study could provide valuable information for establishing reproductive traits in chickens, and need further investigation.     

多基因离散性状QTL连锁分析方法

动物中有许多重要的离散性状,与常规的数量性状类似,其遗传基础受多基因控制并受到环境因子的修饰。由于多基因离散性状的表型特殊性,利用常规的QTL连锁分析方法很难获得理想的统计效果,相应地发展了许多基于广义线性模型框架内的非线性方法。本文就目前离散性状的QTL连锁分析方法作简要综述,并对可预期的改进方法进行了展望。     

Problems of the Qualitative and Quantitative Analysis of Plant Volatiles

Russian Journal of Bioorganic Chemistry - Strategies for the analysis of plant volatiles have changed significantly over the past 15–20 years due to the introduction of new approaches to...     

双交组合种子性状的遗传模型及蒙特卡罗模拟分析

将Cockerham广义遗传模型的建模原理应用于双交方式的交配设计,针对二倍体种子和三倍体胚乳数量性状的遗传特点,提出了2个适用于分析种子品质性状的加性-显性-细胞质-母体模型,介绍了相应的统计分析方法,并进行了蒙特卡罗模拟分析。