A Variance-Component Framework for Pedigree Analysis of Continuous and Categorical Outcomes

Variance-component methods are popular and flexible analytic tools for elucidating the genetic mechanisms of complex quantitative traits from pedigree data. However, variance-component methods typically assume that the trait of interest follows a multivariate normal distribution within a pedigree. Studies have shown that violation of this normality assumption can lead to biased parameter estimates and inflations in type-I error. This limits the application of variance-component methods to more general trait outcomes, whether continuous or categorical in nature. In this paper, we develop and apply a general variance-component framework for pedigree analysis of continuous and categorical outcomes. We develop appropriate models using generalized-linear mixed model theory and fit such models using approximate maximum-likelihood procedures. Using our proposed method, we demonstrate that one can perform variance-component pedigree analysis on outcomes that follow any exponential-family distribution. Additionally, we also show how one can modify the method to perform pedigree analysis of ordinal outcomes. We also discuss extensions of our variance-component framework to accommodate pedigrees ascertained based on trait outcome. We demonstrate the feasibility of our method using both simulated data and data from a genetic study of ovarian insufficiency.     

一般家系二分类性状的贝叶斯连锁分析方法

应用阈值模型和可逆的跳跃马尔可夫链方法提出一种适用于人类一般家系中复杂二分类性状基因定位的连锁分析方法,此方法可以同时估计易感基因位点的数目与位置。     

Analysis of Crossover Designs with a Categorical Response

In the analysis of two-period crossover designs, one frequently must consider the case of a categorical response with binary as a special case. These circumstances are considered in this paper and the proposed method—an extension of GART'S tests for the binary case—is similar to that of PIKE, CASAGRANDE and SMITH for the analysis of pair-matched case-control studies. The results are illustrated with a numerical example.     

基于贝叶斯统计的遗传连锁分析方法

贝叶斯学派是不同于经典数理统计的一个重要学派, 其发展的贝叶斯统计方法在现代科学的许多领域已有着广泛的应用。探讨了贝叶斯统计在遗传连锁分析中的应用, 包括遗传重组率的贝叶斯估计、遗传连锁的贝叶斯因子检验和基于马尔可夫链蒙特卡罗理论的遗传连锁图谱构建。用编制的SAS/IML程序进行了模拟研究和实例分析, 验证了贝叶斯方法在遗传连锁分析中的有效性和实用性。     

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.     

辽宁花生品种系谱分析及农艺性状的演变

分析了辽宁省1949-2012年育成的95个花生品种系谱及农艺性状的演变。结果表明:辽宁花生育成品种共涉及100个亲本,其中,来自辽宁的有45个,49个是育种单位的中间材料,鲁花12号、白沙1016、伏花生、豫花11号等是辽宁花生育成品种的骨干亲本。进入21世纪以来,辽宁省育成的花生品种株高、侧枝长逐渐增加,从变异区间来看,百仁重、出米率呈增加趋势,而粗蛋白与粗脂肪含量变化较小。在分析辽宁省花生育种背景的基础上,提出辽宁省花生育种上宜重视回交手段的利用,发展食用型品种,把抗旱、抗寒、抗病、抗虫、耐连作作为重要的育种目标,利用生物技术手段和野生资源加速育种进程,进一步拓宽辽宁花生品种的遗传基础。     

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.     

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。     

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.     

一个DMD家系的Bayes分析和RFLP连锁分析

本文对一个DMD家系中先证者之妹的致病基因携带者风险用3种方法进行估计。单纯根据系谱分析,其风险为50%;以CPK值为条件概率作Bayes分析,其风险为25%;用RFLP连锁分析,推断其风险仅为5%。将RFLP连锁分析的结果作为又一个条件概率进行Bayes分析,其风险估计又进一步准确到不超过2%。三者结合,得到了最佳的结果。     

Nonparametric Analysis of Ordered Categorical Data in Designs with Longitudinal Observations and Small Sample Sizes

For designs with longitudinal observations of ordered categorical data, a nonparametric model is considered where treatment effects and interactions are defined by means of the marginal distributions. These treatment effects are estimated consistently by ranking methods. The hypotheses in this nonparametric setup are formulated by means of the distribution functions. The asymptotic distribution of the estimators for the nonparametric effects are given under the hypotheses. For small samples, a rather accurate approximation is suggested. A clinical trial with ordered categorical data is used to motivate the ideas and to explain the procedures which are extensions of the Wilcoxon‐Mann‐Whitney test to factorial designs with longitudinal observations. The application of the procedures requires only some trivial regularity assumptions.     

Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree

The availability of genomewide dense markers brings opportunities and challenges to breeding programs. An important question concerns the ways in which dense markers and pedigrees, together with phenotypic records, should be used to arrive at predictions of genetic values for complex traits. If a large number of markers are included in a regression model, marker-specific shrinkage of regression coefficients may be needed. For this reason, the Bayesian least absolute shrinkage and selection operator (LASSO) (BL) appears to be an interesting approach for fitting marker effects in a regression model. This article adapts the BL to arrive at a regression model where markers, pedigrees, and covariates other than markers are considered jointly. Connections between BL and other marker-based regression models are discussed, and the sensitivity of BL with respect to the choice of prior distributions assigned to key parameters is evaluated using simulation. The proposed model was fitted to two data sets from wheat and mouse populations, and evaluated using cross-validation methods. Results indicate that inclusion of markers in the regression further improved the predictive ability of models. An R program that implements the proposed model is freely available.     

Statistical Methods for Linkage Analysis of Complex Traits from High-Resolution Maps of Identity by Descent

A multilocus model for complex traits is described that generalizes the additive and multiplicative models and hence allows simultaneously for both heterogeneity and gene interaction (epistasis). Statistical methods of linkage analysis are discussed under the assumption that identity by descent data from a dense set of polymorphic markers are available. Three methods, single locus search, simultaneous search and conditional search, are described and compared.     

梨分子遗传图谱构建及生长性状的QTL分析

利用鸭梨和京白梨杂交得到的F1(145株)实生苗为作图群体,通过对AFLP和SSR两种分子标记的遗传连锁分析,应用Joinmap 3.0作图软件,368个AFLP标记、34个SSR标记构建了分属18个连锁群的梨分子遗传连锁图谱,各连锁群的LOD值在4.0～7.0范围之间,图谱总长度覆盖梨基因组1395.9cM,平均图距为3.8cM.采用区间作图法,对该群体与生长性状相关的调查数据进行QTL分析,检测到与新梢生长量、新梢茎粗、节间长度、节间数量、树干径、树高及皮孔密度7个农艺性状连锁的QTL位点35个,其中主效QTL位点11个(LOD≥3.5).与生长性状相关的农艺性状QTL位点多集中在LG16连锁群上.     

Mutation in KERA Identified by Linkage Analysis and Targeted Resequencing in a Pedigree with Premature Atherosclerosis

Aims

Genetic factors explain a proportion of the inter-individual variation in the risk for atherosclerotic events, but the genetic basis of atherosclerosis and atherothrombosis in families with Mendelian forms of premature atherosclerosis is incompletely understood. We set out to unravel the molecular pathology in a large kindred with an autosomal dominant inherited form of premature atherosclerosis.

Methods and Results

Parametric linkage analysis was performed in a pedigree comprising 4 generations, of which a total of 11 members suffered from premature vascular events. A parametric LOD-score of 3.31 was observed for a 4.4 Mb interval on chromosome 12. Upon sequencing, a non-synonymous variant in KERA (c.920C>G; p.Ser307Cys) was identified. The variant was absent from nearly 28,000 individuals, including 2,571 patients with premature atherosclerosis. KERA, a proteoglycan protein, was expressed in lipid-rich areas of human atherosclerotic lesions, but not in healthy arterial specimens. Moreover, KERA expression in plaques was significantly associated with plaque size in a carotid-collar Apoe^−/− mice (r² = 0.69; p<0.0001).

Conclusion

A rare variant in KERA was identified in a large kindred with premature atherosclerosis. The identification of KERA in atherosclerotic plaque specimen in humans and mice lends support to its potential role in atherosclerosis.     

A Bayesian Nonparametric Approach for Mapping Dynamic Quantitative Traits

In biology, many quantitative traits are dynamic in nature. They can often be described by some smooth functions or curves. A joint analysis of all the repeated measurements of the dynamic traits by functional quantitative trait loci (QTL) mapping methods has the benefits to (1) understand the genetic control of the whole dynamic process of the quantitative traits and (2) improve the statistical power to detect QTL. One crucial issue in functional QTL mapping is how to correctly describe the smoothness of trajectories of functional valued traits. We develop an efficient Bayesian nonparametric multiple-loci procedure for mapping dynamic traits. The method uses the Bayesian P-splines with (nonparametric) B-spline bases to specify the functional form of a QTL trajectory and a random walk prior to automatically determine its degree of smoothness. An efficient deterministic variational Bayes algorithm is used to implement both (1) the search of an optimal subset of QTL among large marker panels and (2) estimation of the genetic effects of the selected QTL changing over time. Our method can be fast even on some large-scale data sets. The advantages of our method are illustrated on both simulated and real data sets.     

Testing Linkage Hypotheses in Hybrid Analysis of Alternatively Distributed Behavioral Traits with Incomplete Penetrance

The use of polymorphic microsatellite markers for mapping alternatively distributed behavioral traits with incomplete penetrance was studied with special reference to inheritance of predisposition to catalepsy in mice. Using only backcrosses as a segregating population, the major gene for catalepsy was with high likelihood mapped to region 30–75 cM of murine chromosome 13. It was also established that this gene determines 20% of the trait penetrance whereas the remaining 31% of the observed penetrance are accounted for by numerous polygenes.     

Sequential Designs for Genetic Epidemiological Linkage or Association Studies A Review of the Literature

Objectives. The cost of a genetic linkage or association study is largely determined by the number of individuals to be recruited, phenotyped, and genotyped. The efficiency can be increased by using a sequential procedure that reduces time and cost on average. Two strategies for sequential designs in genetic epidemiological studies can be distinguished: One approach is to increase the sample size sequentially and to conduct multiple significance tests on accumulating data. If significance or futility can be assumed with a certain probability, the study is stopped. Otherwise, it is carried on to the next stage. The second approach is to conduct early linkage analyses on a coarse marker grid, and to increase marker density in later stages. Interim analyses are performed to select interesting genomic areas for follow up. The aim of this article is to give a review on sequential procedures in the context of genetic linkage and association studies. Methods. A systematic literature search was performed in the Medline and the Linkage Bibliography databases. Articles were defined as relevant if a sequential design was proposed or applied in genetic linkage or association studies. Results. The majority of proposed study designs is developed to meet the demands of specific studies and lacks a theoretical foundation. A second group of procedures is based on simulation results and principally restricted to the specific simulated situations. Finally, some theoretically founded procedures have been proposed that are discussed in detail. Conclusions. Although interesting and promising procedures have been suggested, they still lack realizations for practical purposes. In addition, further developments are required to adapt sequential strategies for optimal use in genetic epidemiological studies.