不同形式混合资料遗传力的估计方法

本文探讨了用一种特殊形式资料估计遗传力的方法,亦可作为为扩大样本含量,充分利用不同来源且形式不同资料合并估计遗传力的方法。     

单元内混合家系相关法和阈性状法估计遗传力的比较研究

本文提出了一种估计遗传力的方法即单元内混合家系相关法,并用这种方法及阈性状分析法进行了猪肢蹄结实度的遗传力估计,结果表明,对于多阈性状,用单元内混合家系相关法估计的结果准确性好。     

相关遗传力抽样方差的估计

本文给出了单因子组和系统模型下有关相关传力及相关环境力抽样方差的估计方法。有关该参数在育种中的潜在应用其它与遗传相关之产间的相互关系也给予了一定的讨论。概括地来讲,相关遗传力具有遗传力和遗传相关的双重特征。遗传力是相关遗传力的一个特例而相关遗传力则是遗传力概念本身的扩展。用相关遗传力来表达性状间的相关遗传变异要比通常所用的遗传相关更准确一些。     

利用单元内方差分析法估计遗传参数的探讨

在遗传力的估计过程中,需将多种非遗传因素的影响从公畜间方差或者母畜间方差中剔除。在我国常使用的是盛志廉教授提出的单元内同胞相关法。本文对该法从理论上进行了更详细的证明,并将其推广到两层分类方差分析时的情况。同时还给出了当公母畜彼此间有亲缘关系时,利用单元内方差分析估计遗传力的方法。这些方法既可使遗传力的估计简便,又具有多因方差分析的功用。     

从遗传力到肠菌力：概念及研究进展

遗传力是数量遗传学中衡量性状遗传变异的重要参数之一,对动植物遗传育种、医学和进化生物学均具有重要意义。自1918年Fisher提出方差组分剖分思想后,遗传力的分析模型和估计方法不断迭代更新。近年来,一些研究者在研究肠道微生物与宿主表型关系的热点问题中,引入类似于遗传力的概念和估计方法,系统评估动物机体性状表现受肠道微生物因素的影响程度,本文将这一参数(microbiability,m2)译为"肠菌力"。文章简要介绍了遗传力估计的发展历程,概述了肠道菌群与宿主基因组的复杂关系,重点阐释了肠菌力的概念和估计方法,以期为肠道微生物组塑造宿主表型变异的研究提供一定的借鉴和参考。     

中国地鼠山医群体近交系E繁殖性状的遗传力估计

目的对中国地鼠山医群体近交系E的一些繁殖性状进行遗传力估计分析。方法采用平均信息约束最大似然法（AIREML）,利用WOMBAT软件进行处理。结果产仔数、离乳数、胎间隔2-1和胎间隔3-2的遗传力均较低,分别为0.05、0.096、0.182和0.116。结论中国地鼠山医群体近交系E繁殖性状的遗传力均属于低遗传力。     

混合家系遗传参数估计方法研究

针对混合家系遗传参数估计,本文在假定公畜方差组分和母畜方差组分相等这一理论基础上,通过对方差分析的期望均方组成分析,提出了新的遗传力估计方法,以及某些特殊情况下的近似估计方法。通过一个估测实例比较了几种遗传力估计方法,结果表明,本文方法与全同胞组分估计最为接近,而且遗传力标准误最小,本文近似估计方法的效果也较好。对各种方法而言,资料越不平衡其差异越大。本文方法可以在一定程度上弥补全同胞分析时,因实际资料的公母畜方差组分差异过大的缺陷,具有实际可行性。此外,由于本文方法是用单因方差分析解决二因方差分析问题,计算更为简便,并可免于计算混合家系平均亲缘相关系数。     

基于多性状模型内蒙古绒山羊早期生长性状基因组预测准确性研究

内蒙古绒山羊是经过长期自然选择和人工选育后形成的优良家畜品种,是目前世界一流的绒肉兼用山羊。多性状动物模型被认为可以显著提高畜禽遗传评估的准确性,实现性状间的间接选择。本文基于内蒙古绒山羊个体的系谱、基因型、环境以及早期生长性状的表型记录,建立多性状动物模型,利用ABLUP、GBLUP、ssGBLUP三种方法进行早期生长性状(初生重、断乳重、断乳前平均日增重、周岁重)遗传参数及基因组育种值的估计,进一步利用五倍交叉验证方法评价基因组育种值估计准确性和可靠性。结果显示,3种方法估计的初生重遗传力为0.13～0.15,断乳重遗传力为0.13～0.20,日增重遗传力为0.11～0.14,周岁重遗传力为0.09～0.14,均属于中等偏低遗传力;断乳重和日增重、日增重和周岁重之间存在强的正遗传相关,相关系数分别为0.77～0.79和0.56～0.67,表型相关发现同样的规律;ABLUP、GBLUP和ssGBLUP法估计的初生重育种值准确性分别为0.5047、0.6694、0.7156,断乳重分别为0.6207、0.6456、0.7254;日增重分别为0.6110、0.6855、0.7357,周岁...     

浅谈抽样误差中的非抽样误差

在统计工作中,我们都知道抽样调查的结果受抽样误差和非抽样误差的影响,且非抽样误差占很大比重,本文就非抽样误差产生的成因和控制措施进行了论述。     

“三黄”鸡采精量和受精率的方差组分估计

用4种方法(Henderson方法Ⅰ、 MIVQUE、ML、REML)估计了两个“三黄”慢羽系的公鸡采精量和种蛋受精率的方差组分,并计算了它们与产蛋性状间的遗传相关。结果表明,采精量为中等到高遗传力性状(h2=0.29-0.3 9);受精率的遗传方差在品系之间存在着较大的差异,L系受精率性状的遗传力低,而Ⅰ系受精率为中等到高遗传力性状。采精量和受精率与开产日龄、 43周龄蛋重以及64周龄产蛋量间遗传相关不显著。此外,还对4种方差组分估计方法和两种数值转换方法的实际效果作了比较。     

Heritability of polychotomous characters

Characters with phenotypic expression consisting of a response in one of several mutually exclusive and exhaustive categories are considered. Formulae relating heritability in the discrete, outward scale to heritability in underlying normal and exponential scales are presented. For the normal case with two response categories, results reduce to the well-known formula for heritability of binary traits.     

Empirical and deterministic accuracies of across-population genomic prediction

Background

Differences in linkage disequilibrium and in allele substitution effects of QTL (quantitative trait loci) may hinder genomic prediction across populations. Our objective was to develop a deterministic formula to estimate the accuracy of across-population genomic prediction, for which reference individuals and selection candidates are from different populations, and to investigate the impact of differences in allele substitution effects across populations and of the number of QTL underlying a trait on the accuracy.

Methods

A deterministic formula to estimate the accuracy of across-population genomic prediction was derived based on selection index theory. Moreover, accuracies were deterministically predicted using a formula based on population parameters and empirically calculated using simulated phenotypes and a GBLUP (genomic best linear unbiased prediction) model. Phenotypes of 1033 Holstein-Friesian, 105 Groninger White Headed and 147 Meuse-Rhine-Yssel cows were simulated by sampling 3000, 300, 30 or 3 QTL from the available high-density SNP (single nucleotide polymorphism) information of three chromosomes, assuming a correlation of 1.0, 0.8, 0.6, 0.4, or 0.2 between allele substitution effects across breeds. The simulated heritability was set to 0.95 to resemble the heritability of deregressed proofs of bulls.

Results

Accuracies estimated with the deterministic formula based on selection index theory were similar to empirical accuracies for all scenarios, while accuracies predicted with the formula based on population parameters overestimated empirical accuracies by ~25 to 30%. When the between-breed genetic correlation differed from 1, i.e. allele substitution effects differed across breeds, empirical and deterministic accuracies decreased in proportion to the genetic correlation. Using a multi-trait model, it was possible to accurately estimate the genetic correlation between the breeds based on phenotypes and high-density genotypes. The number of QTL underlying the simulated trait did not affect the accuracy.

Conclusions

The deterministic formula based on selection index theory estimated the accuracy of across-population genomic predictions well. The deterministic formula using population parameters overestimated the across-population genomic accuracy, but may still be useful because of its simplicity. Both formulas could accommodate for genetic correlations between populations lower than 1. The number of QTL underlying a trait did not affect the accuracy of across-population genomic prediction using a GBLUP method.     

Application of approximate variances of variance components and their ratios in genetic tests

The application and underlying assumptions of formulae used to estimate the variance of variance components and ratios of variance components are fully described for (1) variance components estimated using Henderson's Method 3 (HM3) and Restricted Maximum Likelihood (REML) and (2) ratios of variance components commonly used in genetic tests — biased and unbiased heritabilities. A first-order Taylor series approximation is often used to estimate the variance of a ratio of two random variables (e.g., heritability), however the formula is complicated, thus making calculations prone to errors. Dickerson's approximation is considerably simpler, though relatively rarely used. In case studies using data from 148 slash pine full-sib progeny tests, Dickerson's method was found to be slightly more conservative than the Taylor series approximation when estimating the variance of heritability estimates, regardless of test size, age, or the trait (volume, which is a continuous trait, and rust resistance, which is a bernoulli trait). Both the Taylor series and Dickerson approximations compared favorably with an empirical estimate of the variance of heritability estimates, however there is some evidence of small-sample bias associated with the use of the asymptotic variance-covariances from REML variance component estimation.This is Florida Agricultural Experiment Station Journal Series No. R-03964 of the Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611, USA     

使用多因素易患性阈值模型评估双相情感障碍的遗传度缺失

为了评估双向情感障碍的遗传度缺失,文章通过查询美国国家人类基因组研究所(National Human Genome Research Institute,NHGRI)的gwascatalog目录,检索出所有已发现的双相情感障碍易感变异,使用多因素易患性阈值模型计算每个易感变异对双相情感障碍遗传度的解释度。将所有易感变异遗传度解释度求和得到双相情感障碍已知易感变异对遗传度的总解释度,使用此总解释度评估双相情感障碍的遗传度缺失。结果显示,已知双相情感障碍易感变异对双相情感障碍遗传度的合计解释度为38.34%,尚有61.66%的遗传度无法被已有易感变异解释,属于遗传度缺失。双相情感障碍38.34%的遗传度解释度较早前国外同类研究大幅度提高,表明随着新的双相情感障碍易感变异被不断发现,双相情感障碍遗传度缺失得到大幅度减小。但双相情感障碍遗传度缺失依然存在且数目较大的事实也表明双相情感障碍尚存在许多未知的分子遗传学机制有待进一步阐明。     

Theory for the number of genes affecting quantitative characters

Summary A general expression for gene number estimation which encompasses the conventional formula was derived. It provides a basis for gene number estimation from the data of recurrent selection experiments that are not of sufficient duration to measure total response to selection.Gene number estimates are considerably more reliable when heritability is high. The effect of heritability on sampling variance is particularly important when gene number is large.Generally the most effective ways of decreasing the variance of a gene number estimate will be 1) to increase the number of generations in a primary selection program, 2) to increase the number of generations in the two way selection program and 3) to increase population size.From a thesis submitted by the author in partial fulfillment of the requirements for the Ph.D. degree. Received March, 1975. Work supported by Public Health Service Grant GM 16074, by the Minnesota Agricultural Experiment Station and by National Institutes of Environmental Health Sciences Grant No. 5T32 ES07011-02.Former Research Assistant, Genetics and Cell Biology, University of Minnesota; Currently Post-doctoral Fellow in Environmental Health Measurement and Statistics.     

Realized Sampling Variances of Estimates of Genetic Parameters and the Difference between Genetic and Phenotypic Correlations

A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.     

Genetic parameters for bone strength, osteochondrosis and meat percentage in Finnish Landrace and Yorkshire pigs

Osteochondrosis (OC) is a major factor causing joint problems that affect animal welfare and pork production profitability. Strong bones are also important in the slaughtering process, especially as broken bones can lead to rejections of parts of the carcass. In this study, 326 Finnish Yorkshire and 464 Finnish Landrace test station pigs were examined post mortem for bone strength and osteochondral lesions. The objective was to estimate genetic parameters for OC and bone strength and their genetic and phenotypic correlations with carcass meat percentage. Two formulas were used for lean meat percentage, the first one (Hennessy meat-%) comprising two fat thickness measurements and one muscle depth measurement, and the second one (test station meat-%) also including the weight of lean meat in ham. Finnish Yorkshire had stronger bones than Finnish Landrace on average, but also more OC in the proximal end of the humerus (36%) and the distal end of the femur (51%) than Finnish Landrace (29% and 31% OC in the humerus and femur, respectively). By using the data on both breeds, the OC heritability estimated was 0.05 in the humerus and 0.26 in the femur. The estimated heritability of bone strength was also moderate (0.26). Test station meat-% showed higher heritability (0.40) than meat-% based on the Hennessy formula (0.29). Genetic correlations between meat percentage and the other studied traits were weak and associated with high standard errors. The results show that a mild form of OC is common in both Finnish pig breeds; bone strength and OC in the distal end of the femur are moderately heritable and can be improved through selection; and selection for high meat percentage does not seem to affect bone strength or OC.     

Implications of multilocus inheritance for gene-disease association studies

The impact of multilocus inheritance on the power of candidate gene association studies and the parameters derived therefrom is considered. Both case-control and family-based control designs are included. When the background heritability H (i.e., residual correlation) among sibs for the disease in question is high, the power of multiplex affected sibships versus singletons is diminished compared with the situation when background heritability is low. Thus, multiplex families for association studies are most advantageous for low heritability disorders. Estimates of genotype relative risk (GRR) are also distorted in multiplex sibships compared with singletons based on background heritability. In a case-control study, GRR is inflated in multiplex families, with the degree of inflation decreasing with background heritability. By contrast, in a TDT (parental control) study, GRR is deflated in multiplex families, with the degree of deflation increasing with background heritability (and no deflation when H is 0). Considering identical twins, the difference in genotype frequencies between concordant versus discordant MZ twin pairs for the candidate gene is large when the heritability is low, but modest when the heritability is high.     

The contribution of risk factors to blood pressure heritability estimates in young adults: the East flanders prospective twin study.

The heritability of blood pressure estimated in previous studies may be confounded by the influence of potential blood pressure risk factors. We applied the classical twin design to estimate the contribution of these covariates to blood pressure heritability. The study consisted of 173 dizygotic and 251 monozygotic twin pairs aged 18-34 years, randomly selected from the East Flanders Prospective Twin Survey. In a standardized examination, blood pressure and anthropometry was measured, a questionnaire was completed, and a fasting blood sample was taken. In univariate and bivariate modeling, diastolic and systolic heritability were estimated both unadjusted and adjusted for potential risk factors. Also, covariate interaction was modeled. Bivariate analysis gave heritability estimates of 0.63 (95%CI 0.55-0.59), 0.74 (95%CI: 0.68-0.79), and 0.78 (95%CI: 0.70-0.84) for diastolic, systolic, and cross-trait heritability, respectively. The remaining variances could be attributed to unique environmental influences. These heritability estimates did not change substantially in univariate analyses or after adjustment for risk factors. A sex-limitation model showed that the heritability estimates for women were significantly higher than for men, but the same genetic factors were operating across sexes. Sex and cigarette smoking appeared to be statistically significant interaction terms. The heritability of blood pressure is relatively high in young adults. Potential risk factors of blood pressure do not appear to confound the heritability estimates. However, gene by sex by smoking interaction is indicated.     

Identity-by-descent-based heritability analysis in the Northern Finland Birth Cohort

For most complex traits, only a small proportion of heritability is explained by statistically significant associations from genome-wide association studies (GWAS). In order to determine how much heritability can potentially be explained through larger GWAS, several different approaches for estimating total narrow-sense heritability from GWAS data have recently been proposed. These methods include variance components with relatedness estimates from allele-sharing, variance components with relatedness estimates from identity-by-descent (IBD) segments, and regression of phenotypic correlation on relatedness estimates from IBD segments. These methods have not previously been compared on real or simulated data. We analyze the narrow-sense heritability of nine metabolic traits in the Northern Finland Birth Cohort (NFBC) using these methods. We find substantial estimated heritability for several traits, including LDL cholesterol (54 % heritability), HDL cholesterol (46 % heritability), and fasting glucose levels (39 % heritability). Estimates of heritability from the regression-based approach are much lower than variance component estimates in these data, which may be due to the presence of strong population structure. We also investigate the accuracy of the competing approaches using simulated phenotypes based on genotype data from the NFBC. The simulation results substantiate the downward bias of the regression-based approach in the presence of population structure.