Segregation Analysis on Genetic System of Quantitative Traits in Plants

Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene and pure polygene inheritance model was a specific case of the general model.Based on the proposed theory,the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants.At present,this procedure can be used to evaluate the genetic effect of individual major genes (up to two to three major genes),the collective genetic effect of polygene,and their heritability value.This paper introduces how to establish the procedure,its main achievements,and its applications.An example is given to illustrate the steps,methods,and effectiveness of the procedure.     

The Design and Use of Variance Component Models in the Analysis of Human Quantitative Pedigree Data

The use of variance components and multivariate linear models in genetics applications has a long history that dates back to (at least) Fisher's seminal 1918 paper “The correlation between relatives on the supposition of Mendelian inheritance” [Phil. Trans. 52: 399–433]. Although extensions and elaborations of Fisher's insights have been offered in recent times, relatively few studies exist which examine the theoretical and operational properties variance component models possess in complicated genetic analysis settings. In this paper variance component models, as well as some of their properties (e.g., power, efficiency, and sample size considerations) are discussed in the context of each of the following genetic analysis settings: 1. the detection of general polygenic additive and dominance effects; 2. the detection of genetic effects in the presence of environmental effects (and vice versa); 3. the detection of pleiotropic gene action; 4. aspects of the detection of genotype by environment interaction; and 5. sequential tests for general hypotheses framed in the context of settings 1 through 4. Exposition of the proposed methods and results are facilitated through a special emphasis placed on pedigree covariance structure modeling.     

Segregation Analysis on Genetic System of Quantitative Traits in Plants

Based on the traditional polygene inheritance model of quantitative traits, the author suggests the major gene and polygene mixed inheritance model. The model was considered as a general one, while the pure major gene and pure polygene inheritance model was a specific case of the general model. Based on the proposed theory, the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants. At present, this procedure can be used to evaluate the genetic effect of individual major genes (up to two to three major genes), the collective genetic effect of polygene, and their heritability value. This paper introduces how to establish the procedure, its main achievements, and its applications. An example is given to illustrate the steps, methods, and effectiveness of the procedure. Translated from Hereditas, 2005, 27(1) (in Chinese)     

The Analysis of Quantitative Traits for Simple Genetic Models from Parental, F1 and Backcross Data

THE FOLLOWING MODELS ARE CONSIDERED FOR THE GENETIC DETERMINATION OF QUANTITATIVE TRAITS: segregation at one locus, at two linked loci, at any number of equal and additive unlinked loci, and at one major locus and an indefinite number of equal and additive loci. In each case an appropriate likelihood is given for data on parental, F(1) and backcross individuals, assuming that the environmental variation is normally distributed. Methods of testing and comparing the various models are presented, and methods are suggested for the simultaneous analysis of two or more traits.     

Genetic Distances Based on Quantitative Traits

Morphological data showing continuous distributions, polygenically controlled, may be particularly useful in intergroup classification below the species level; an appropriate distance analysis based on these traits is an important tool in evolutionary biology and in plant and animal breeding.--The interpretation of morphological distances in genetic terms is not easy because simple phenotypic data may lead to biased estimates of genetic distances. Convenient estimates can be obtained whenever it is possible to breed populations according to a suitable crossing design and to derive information from genetic parameters.--A general method for determining genetic distances is proposed. The procedure of multivariate analysis of variance is extended to estimate appropriate genetic parameters (genetic effects). Not only are optimal statistical estimates of parameters obtained but also the procedure allows the measurement of genetic distances between populations as linear functions of the estimated parameters, providing an appropriate distance matrix that can be defined in terms of these parameters. The use of the T2 statistic, defined in terms of the vector of contrasts specifying the distance, permits the testing of the significance of any distance between any pair of populations that may be of interest from a genetic point of view.--A numerical example from maize diallel data is reported in order to illustrate the procedure. In particular, heterosis effects are used as the basis for estimates of genetic divergence between populations.     

The Effects of R- and K-Selection on Components of Variance for Two Quantitative Traits

The genetic and environmental components of variance for two quantitative characters were measured in the descendants of Drosophila melanogaster populations which had been grown for several generations at densities of 100, 200, 300, and 400 eggs per vial. Populations subject to intermediate densities had a greater proportion of phenotypic variance available for selection than populations from either extreme. Selection on either character would be least effective under pure r-selection, a frequent attribute of selection programs.     

爆裂玉米胚乳数量性状的遗传研究

采用三倍体胚乳种子遗传模型及其分析方法,研究了4个爆裂玉米膨爆特性的胚乳直接效应、母体效应和细胞质效应。结果表明,百粒重、膨化体积的遗传同时由3套遗传体系所控制,百粒重的细胞质、膨化体积的母体和细胞质遗传率较高。爆花率和膨化倍数受胚乳和母体2套遗传体系的影响,且遗传率相近。爆花率和膨化倍数的直接和母体杂种优势均为负值。要组配出优良爆裂玉米杂交种,必须首先选育出膨爆特性突出的自交系,同时还要注意不同自交系的恰当组配。在6个供试自交系中,必须首先选育出膨爆特性突出的自交系,同时还要注意不同自交系的恰当组配。在6个供试自交系中,P3,P4适宜用作母本,P5则适宜作父本。     

引进美洲红点鲑群体遗传多样性微卫星的分析

为了解引进种美洲红点鲑种群遗传结构和种质资源现状,本研究利用15个微卫星标记对其养殖群体遗传多样性进行了分析。结果表明:在30个个体中,15对微卫星引物除1对扩增产物为单态外,其余14对在美洲红点鲑群体内扩增均出现了多态,14个多态性位点等位基因数目为3～7不等,共检测到等位基因数为69个,平均有效等位基因数为3.03;期望杂合度在0.540～0.809之间,平均期望杂合度为0.664;多态信息含量在0.360～0.719之间,平均多态信息含量为0.578,表明引进的美洲红点鲑遗传多样性水平较高,具有良好的选育潜力,可以作为良好的育种材料。     

Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata

In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected.     

Dissecting Genetic Architecture Underlying Seed Traits in Multiple Environments

The seeds of flowering plants develop from double fertilization and play a vital role in reproduction and supplying human and animal food. The genetic variation of seed traits is influenced by multiple genetic systems, e.g., maternal, embryo, and/or endosperm genomes. Understanding the genetic architecture of seed traits is a major challenge because of this complex mechanism of multiple genetic systems, especially the epistasis within or between different genomes and their interactions with the environment. In this study, a statistical model was proposed for mapping QTL with epistasis and QTL-by-environment (QE) interactions underlying endosperm and embryo traits. Our model integrates the maternal and the offspring genomes into one mapping framework and can accurately analyze maternal additive and dominant effects, endosperm/embryo additive and dominant effects, and epistatic effects of two loci in the same or two different genomes, as well as interaction effects of each genetic component of QTL with environment. Intensive simulations under different sampling strategies, heritabilities, and model parameters were performed to investigate the statistical properties of the model. A set of real cottonseed data was analyzed to demonstrate our methods. A software package, QTLNetwork-Seed-1.0.exe, was developed for QTL analysis of seed traits.     

The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation''s effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation''s effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits.     

玉米SSR遗传图谱的构建及产量性状基因定位

利用中国农大培育的高产,多抗性玉米杂交组合农大3138的F2：3家系为材料,构建了具有80对SSR标记的玉米遗传图谱,标记间平均距离25．42,覆盖玉米基因组的2033.4cm,采用随机区组田间设计,考察了230个家系的穗长,秃尖长,穗粗,穗行数,千粒重,穗重,单株粒重,利用区间作图法分析了影响各性状的数量性状基因座位（QTL）,共检测到30个QTLs,单个性状的QTLs为3－5个,QTLs解释变异量占总变异量的比例变化范围为9．5％－55．3％。     

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.     

中国貉随机扩增多态DNA及其亚种分化关系

对来自陕西、云南、越南、安徽和广西等地的８只中国貉（Ｎｙｃｔｅｒｅｕｔｅｓｐｒｏｃｙｏｎｉｄｅｓ）进行随机扩增多态ＤＮＡ分析。应用２８个１０ｂｐ的随机引物,平均每只貉获得的ＲＡＰＤ标记数约为１３０条。遗传距离计算结果显示,中国貉个体间的平均遗传距离指数值为１１．２０％,最大值为１４．９３％,最小值为２．９４％。以赤狐（Ｖｕｌｐｅｓｖｕｌｐｅｓ）为外群,应用ＰＨＹＬＩＰ３．０计算软件包中的ＵＰＧＭＡ和ＮＪ聚类方法构建分子系统树。结果表明,不同地理群体间的中国貉存在遗传分化;中国貉可分为４组：（１）广西貉,（２）安徽貉,（３）陕西貉,（４）云南貉和越南貉。其中安徽貉和广西貉间的关系稍近,陕西貉则与云南貉－越南貉稍近。对合中国貉的形态分类、地理分布、ｍｔＤＮＡ多态分析以及进化遗传学的观点,认为陕西貉、广西貉和安徽貉可能与云南貉－越南貉具有等同的分类地位。     

植物根构型的定量分析

植物根系具有锚定植株、吸收和运输土壤中的水分及养分、合成和贮藏营养物质等重要功能。根构型是根系在土壤中的空间造型和分布。对植物根构型进行定量分析,有助于人们了解根系结构和根系功能在生态系统中的重要作用。本文对植物根构型的概念及其定量分析研究进展进行了概述,并介绍了植物根构型的主要研究方法和定量分析技术。     

Genetic Diversity and Relationships Among Siberian and Far Eastern Larches Inferred from RAPD Analysis

Genetic diversity of larches from six geographically distant regions, Tomsk, Irkutsk, Ulan-Ude (Siberia), and Blagoveshchensk, Khabarovsk, Yuzhno-Sakhalinsk (Far East) was examined by means of RAPD analysis. Tree DNA samples were compared using 457 RAPD loci (97% of which were polymorphic), identified with 17 primers of random sequences. In the samples examined, 32 to 49% of the genes were in heterozygous state, mean expected heterozygosity (H_exp) varied from 0.1373 to 0.1891, and the genetic distances (D_N) for different sample pairs varied from 0.0361 to 0.1802. The main population parameters were determined for Larix sibirica Ledeb., L. gmelinii(Rupr.) Rupr., and L. kamtschatica (Rupr.) Carr. Analysis of the genetic relationships showed that L. kamtschatica was characterized by highest genetic differentiation from the other larches examined, while larches from Primorskii krai were genetically close toL. sibirica.     

Analysis of Molecular Variance Inferred from Metric Distances among DNA Haplotypes: Application to Human Mitochondrial DNA Restriction Data

We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as phi-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and phi-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.     

Genetic Diversity of Chinese Native Pigs Inferred from Protein Electrophoresis

We examined protein polymorphism of 20 nativepig breeds in China and 3 introduced pig breeds. Thirtyloci have been investigated, among which six loci werefound to be polymorphic. Especially, the polymorphismof malate dehydrogenase (MDH), adenylate kinase(AK), and two new alleles of adenosine deaminase (ADA)had not been reported in domestic pigs and wild pigs.The percentage of polymorphic loci (P), the meanheterozygosity (H), and the mean number ofalleles (A) are 0.200, 0.065, and 1.300, respectively.The degree of genetic variability of Chinese pigs as awhole was higher than that of goats, lower than thatof cattle and horses, and similar to that ofsheep. Using the gene frequencies of the 30 loci, Nei'sgenetic distance among the 20 native breeds in China and3 introduced pig breeds was calculated by theformula of Nei. The program NEIGHBOR in PHYLIP3.5c was chosen to construct an UPGMA tree and a NJtree. Our results show that, of the total geneticvariation found in the native pig breeds in China, 31%(0.31) is ascribable to genetic differencesamong breeds. About 69% of the total genetic variationis found within breeds. Most breeds are in linkagedisequilibrium. The patterns of genetic similaritiesbetween the Chinese native pig breeds were notin agreement with the proposed pig type classification.