植物数量性状遗传体系的分离分析方法研究

在传统的数量性状多基因遗传模型基础上提出主基因-多基因遗传模型具普遍性,纯主基因或纯多基因遗传模型只是其特例。由此初步建立了植物数量性状遗传体系分离分析方法。目前该方法可以检验2～3个主基因的个别遗传效应、多基因整体的遗传效应和两者的遗传率。本文介绍这种分离分析方法的研究经过、主要进展及应用效果,并以实例说明其分析步骤、方法和效果。     

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)     

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 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.     

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。     

数量性状发育遗传模型及其分析方法的研究进展

发育遗传模型是同时反映性状遗传和发育本质、提供影响遗传变异及调整发育进程的有关因素的信息的模型。建立在群体遗传学基础上的直接效应模型适用于单一基因控制的简单性状。渐成模型将遗传变异分解成直接分量和渐成分量(母体效应和互作效应),能更好地反映有机体遗传和发育的生物学机制。生长轨迹模型有效地综合了复杂性状各分量的发育动态,可获得连续的、综合的、详细的、动态的发育信息。条件遗传分析方法不仅可以估算特定时间段的净效应,且可将净效应分解为不同遗传分量,了解各效应分量的相对贡献。 Abstract：Developmental genetic models and analysis methods for quantitative traits are presented.Developmental genetic models should reflect the genetic and developmental essence,and provide the information of the factors influencing the genetic variation and the developmental process.Direct effect models,which based on the population genetics,may be suitable to analyze simple traits with single gene.Epigenetic models can decompose the whole genetic variation into direct and epigenetic components (maternal effects and epigenetic interaction effects),so that biological mechanism can be better understood.Growth trace models effectively synthesize the developmental dynamics of components of complex traits.With them,continuous,compositive,detailed,and dynamic information of development is available.Conditional analysis method can not only estimate the net effects in a specific time interval,but also depose them into genetic components and help to appreciate the contributions of different effects.     

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。     

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.     

数量性状的核质互作遗传效应分析:二倍体植株遗传模型

提出了能分析二倍体植株数量性状核质互作效应的遗传模型,该模型把控制数量性状总的遗传效应分为核效应、质效应和核质互作效应,以及它们分别与环境作用的效应。其中,核质互作效应可进一步分解为加性核质互作与显性核质互作。基于平衡与非平衡两种双列杂交试验设计,蒙特卡罗模拟结果表明:采用混合线性模型方法进行统计分析,可以有效地估计各项遗传效应值及其方差分量。此外,运用该模型对棉花的4个数量性状(单株铃数、衣分、2.5%跨长和麦克隆值)进行了遗传分析。     

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.     

基于ISSR标记和数量性状的火龙果种质材料遗传多样性分析

为鉴定火龙果种质材料的亲缘关系,筛选优良亲本,提高育种效率,采用ISSR分子标记技术,对25份火龙果种质材料进行遗传背景研究,将植株及果实的20个数量性状数据标准化后,采用欧氏距离计算种质间遗传距离进行比较分析。结果显示,7条ISSR引物共检测到97个位点,其中多态性位点数为93个,多态性条带比例为95.88%。基于分子标记的UPGMA聚类分析,在阈值为0.54处可将25份种质材料分为6大组群,各种质材料的相似系数分布在0.41～0.86之间。20个数量性状的变异系数在12.35%～51.66%之间,Ward法聚类分析在欧式距离为5处,可将25份种质聚为6个组群。两种分类结果并不一致,但均显示出火龙果种质丰富的遗传多样性,可根据分类结果及育种目的筛选适宜亲本。     

Quantitative Genetic Analysis of Temperature Regulation in MUS MUSCULUS. I. Partitioning of Variance

Heritabilities (from parent-offspring regression) and intraclass correlations of full sibs for a variety of traits were estimated from 225 litters of a heterogeneous stock (HS/Ibg) of laboratory mice. Initial variance partitioning suggested different adaptive functions for physiological, morphological and behavioral adjustments with respect to their thermoregulatory significance. Metabolic heat-production mechanisms appear to have reached their genetic limits, with little additive genetic variance remaining. This study provided no genetic evidence that body size has a close directional association with fitness in cold environments, since heritability estimates for weight gain and adult weight were similar and high, whether or not the animals were exposed to cold. Behavioral heat conservation mechanisms also displayed considerable amounts of genetic variability. However, due to strong evidence from numerous other studies that behavior serves an important adaptive role for temperature regulation in small mammals, we suggest that fluctuating selection pressures may have acted to maintain heritable variation in these traits.     

Variance Component Analysis of Allozyme Frequency Data from Eastern Populations of DROSOPHILA MELANOGASTER

Gene frequency variation at eight polymorphic allozyme loci in Drosophila melanogaster populations in North Carollina and the east coast of the United States were analyzed utilizing the variance component estimation procedures suggested by Cockerham (1969, 1973). These variance components were used to estimate correlations of genes within small geographic regions. The average (over loci) correlation between genes in the same individual within subpopulations was estimated to be 0.033. That between genes in the same subpopulation in different individuals was estimated to be very small, although significantly different from zero. The macrogeographic variation measured by the correlation of genes sampled from the same local region was large for some loci and smaller for others. this variation was also analyzed by correlation with latitude and longitude. Several previously recognized clines were identified as were several new clines.--These results were interpreted as indicating either some degree of nonrandom mating and local breeding unit isolation or a low frequency of null alleles. The geographic and temporal variation has no simple interpretation.     

Genetic Diversity of Tomistoma schlegelii Inferred from mtDNA Markers

The genetic diversity of the endangered crocodile Tomistoma schlegelii was characterized using the protein coding ND 6-tRNA^glu-cyt b and the cytochrome b-control region (cyt b-CR) markers. Concatenate data revealed six haplotypes with an overall haplotype diversity of 0.769 ± 0.039; nucleotide diversity was 0.00535 ± 0.00172. A nearest-neighbor analysis showed that all individuals clustered with four geographic regions (Sumatra, Peninsular Malaysia, Sarawak, and East Kalimantan) and were genetically differentiated. With the exception of the individuals from haplotype H2, which occurred in both Peninsular Malaysia and Sarawak, all other haplotypes were geographically distinct. The H4 lineage, which was found to be the most divergent, clustered exclusively in the basal clade in all phylogenetic trees, and the haplotype network was unconnected at the 95% reconnection limit, suggesting further investigation to establish its possible status as a distinct evolutionary significant unit or a cryptic species.     

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.