冬小麦粒叶比杂种优势及遗传效应分析

用9个冬小麦品种按5×4不完全双列杂交设计组配20个杂交组合,对小麦粒叶比的杂种优势和遗传效应进行分析。结果表明,小麦粒叶比表现出一定的杂种优势;一般配合力和特殊配合力方差均达极显著水平,说明亲本的粒叶比差异及杂交互作均对F1代产生遗传差异,该试验中石6021、农大99260080等的一般配合力较大,石6021×农大99260080、鲁麦14×济南17等组合的特殊配合力较大,产生了较强的杂种优势;粒叶比遗传符合加性-显性遗传模型,但以加性效应为主,其遗传决定度达87.65%,狭义遗传力为64.71%;在高粒叶比品种选育上应重视高粒叶比亲本筛选利用和杂交后代的早代选择。     

作物杂种后代基因型值和杂种优势的预测方法

本文提出了利用作物亲本和F_1预测杂种后代基因型值和杂种优势的统计分析方法.该方法运用加性-显性遗传模型,分析双列杂交试验资料,用MINQUE(1)法估算方差分量以及预测遗传效应值.由加性和显性效应预测值可进一步预测F_1,F_2,BC_1,BC_2,等不同世代的基因型值,在预测F_1群体平均优势和群体超亲优势的基础上,可以推导出其它各世代的杂种优势.提出了预测杂种后代保持超亲优势世代数的简单公式,根据杂交组合F_1群体平均优势和双亲相对遗传差异,便可预测该组合能在生产上直接利用的世代数.以棉花六个品种完全双列杂交试验资料为例,分析了各组合F_1和F_2的基因型值、超亲优势和保持5％超亲优势的世代数.     

作物杂种后代基因型值和杂种优良的预测方法

本文提出了利用作物亲本和Ｆ１预测杂种后代基因型值和杂种优势的统计分析方法。该方法运用加性－显性遗传模型,分析双列杂交试验资料,用ＭＩＮＱＵＥ（１）法估算方差分量以及预测遗传效应值。由加性和显笥效应预测值可进一步预测Ｆ１,Ｆ２,ＢＣ１,ＢＣ２,等不同世代的基因型值,在预测Ｆ１群体平均优势和 群丛超亲优势的基础上,可以推导出其它各世代的杂种优势。提出了预测杂种后代保持超亲优热世代数的简单公式,根据杂交组合Ｆ１群体平均优势和双亲相对遗传差异,便可预测该组合能的生产上直接利用的世代数。以棉花六个品种完全双列杂交试验资料为例,分析了各组合Ｆ１和Ｆ２的 基因型值、超亲优势和保持５％超亲优势的世代数。     

小麦蛋白质组分含量的配合力和遗传力分析

利用5个小麦亲本,按Griffing方法4组配一套完全双列杂交,研究小麦籽粒蛋白质组分的配合力和遗传力。结果表明,同一性状不同亲本的一般配合力效应和不同组合间的特殊配合力效应差异都较大。球蛋白、醇溶蛋白和谷蛋白含量的遗传主要受加性基因控制,清蛋白含量的遗传不存在加性基因作用,以显性基因作用为主。 Abstract：　A set of diallel crosses involving 5 wheat parents, according to the random model of Griffing Method 4, was made to study the combining ability and heritability of grain protein components in wheat. The results indicated that GCA effects of different parents for the same trait varied significantly. And SCA effects of different combination studied varied obviously. The inheritance of globulin, gliadin and glutenin contents were mainly controlled by additive genes. Dominant genes functioned mainly on albumin content without additive gene.     

冬小麦三种粒重性状的遗传研究

采用Griffing方法Ⅰ,利用6×6完全双列杂交,对冬小麦单株粒重、单穗粒重和千粒重三个性状的配合力、基因效应及遗传组成进行了研究,结果表明这三种粒重性状的遗传同时受基因加性效应、非加性效应和母体效应的共同作用;千粒重、株粒重、穗粒重的狭义遗传力分别为72%、63%和45%,前两个性状以基因加性效应为主,后一性状基因加性、显性效应相当;细胞质作用对千粒重影响较小,株粒重和穗粒重则存在明显的核质互作.     

小麦蛋白质组分含量的配合力和遗传力分析

利用5个小麦亲本,按Griffing方法4组配一套完全双列杂交,研究小麦籽粒蛋白质组分的配合力和遗传力。结果表明,同一性状不同亲本的一般配合力效应和不同组合间的特殊配合力效应差异都较大。球蛋白、醇溶蛋白和谷蛋白含量的遗传主要受加性基因控制,清蛋白含量的遗传不存在加性基因作用,以显性基因作用为主。 Abstract：　A set of diallel crosses involving 5 wheat parents, according to the random model of Griffing Method 4, was made to study the combining ability and heritability of grain protein components in wheat. The results indicated that GCA effects of different parents for the same trait varied significantly. And SCA effects of different combination studied varied obviously. The inheritance of globulin, gliadin and glutenin contents were mainly controlled by additive genes. Dominant genes functioned mainly on albumin content without additive gene.     

辣椒净光合速率Hayman双列杂交分析

用辣椒(Capsicum annuum L.)6个亲本,按(1/2)n(n-1)双列杂交法配制15个杂交组合,用Hayman双列杂交分析法估算不同开花结果时期净光合速率的遗传参数。阵列协方差(Wr)对阵列方差(Vr)的回归分析结果表明,辣椒开花结果前期、中期、后期净光合速率的遗传都不符合“加性-显性”模型。Wr Vr与亲本Yr间的相关分析表明含有更多高净光合速率,显性基因的亲本具有较大的Wr Vr值。遗传参数估算表明开花结果时期的净光合速率遗传是显性效应比加性效应更加重要,同时还存在显著上位性效应。狭义遗传力较小,开花结果中、后期杂种优势比前期明显。     

小麦千粒重的配合力分析

根据“格子方”实验设计所得资料,分析了小麦千粒重的杂种优势、亲本配合力和F_1组合遗传力。 资料表明,小麦千粒重遗传呈现完全显性到超显性,加性基因效应与显性效应大体上同等重要。一般配合力数值中等大小,广义遗传力数值中等而狭义遗传力偏低。     

冬小麦品种粒重叶比的遗传研究

本研究采用Griffing方法Ⅰ,利用6 × 6完全双列杂交,对6个不同类型的冬小麦品种粒重叶比的遗传进行了初步分析.结果表明粒重叶比的一般配合力(GCA)效应,特殊配合力(SCA)效应和反交(R)效应,均达到极显著水平,其均方比为1.94650.67001;粒重叶比的遗传以加性基因效应占优势,但反交效应和非加性基因效应也不可忽视;粒重叶比的广义遗传力(hB2)为97.79%,狭义遗传力(hN2)为58.53%.河农2552是较为理想的育种亲本.     

籼粳杂交稻穗部性状的遗传效应及其与环境互作

采用包括基因型与环境互作效应的加性显性加性×加性上位性遗传模型,分析了不同环境下籼粳杂交稻穗部性状的遗传特点.结果表明,除了主穗粒数的加性与环境互作和二次枝梗数的显性与环境互作不显著外,其他性状均存在显著和极显著的加性、显性、加性×加性上位性遗传效应及其与环境的互作效应,其中均以显性效应为主,显性与环境互作效应对枝梗性状的影响较为明显.遗传率分析表明,各性状的普通广义遗传率最大,互作遗传率也有一定作用.杂种优势预测表明,除了一次、二次枝梗数外,其他性状均表现正向的杂种优势,基因型与环境互作只影响杂种优势表达的程度,而不改变其方向.遗传效应预测值结果表明,IR6615837、IR6560085、明恢63和R6694个亲本可以明显改良杂交后代多数穗部性状,且环境影响程度较小,可作为优良亲本列于育种计划中.     

Analysis of genetic effects of nuclear–cytoplasmic interaction on quantitative traits: Genetic models for seed traits of plants

Two Genetic models (an embryo model and an endosperm model) were proposed for analyzing genetic effects of nuclear genes, cytoplasmic genes, maternal genes, and nuclear–cytoplasmic interaction (NCI) as well as their genotype by environment interaction for quantitative traits of plant seed. In these models, the NCI effects were partitioned into direct additive and dominance NCI components. Mixed linear model approaches were employed for statistical analysis. For both balanced and unbalanced diallel cross designs, Monte Carlo simulations were conducted to evaluate unbiasedness and precision of estimated variance components of these models. The results showed that the proposed methods work well. Random genetic effects were predicted with an adjusted unbiased prediction method. Seed traits (protein content and oil content) of Upland cotton (Gossypium hirsutum L.) were analyzed as worked examples to demonstrate the use of the models.     

The use of regression methods to study genotype-environment interactions: extending Griffing's model for diallel cross experiments and testing an empirical grouping method.

A model combining features of Griffing's diallel cross analysis with regression analysis for genotype-environment interactions is introduced using carp data of Moav et al. (1975) as an example. An analysis of variance based on this model provides information on the combining abilities of genetic effects and the interactions of these effects with environments from which inferences can readily be made on heterosis and heterosis-environment interactions. Applying the empirical grouping method of Lin and Thompson (1975) to these data (ignoring their diallel cross structure) established groups which were remarkably consistent with their members' crossing backgrounds.     

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。     

A comparison of different methods of half-diallel analysis

Summary A comparison among various forms of half-diallel analysis was made. The different half-diallel techniques used were: Griffing's model I, method 2 and 4, Morley-Jones' model; Walters and Morton's model, and Gardner and Eberhart's model. All these methods of diallel analysis were found to be interrelated. However, as the Gardner and Eberhart's model partitioned heterosis into different components as well as gave information about combining ability, this method had certainly some advantages over the others. The results further indicated the possibility of dominance variance being confounded with the additive variance of general combining ability.     

Using mating designs to uncover QTL and the genetic architecture of complex traits

Analysis of quantitative trait loci (QTL) affecting complex traits is often pursued in single-cross experiments. For most purposes, including breeding, some assessment is desired of the generalizability of the QTL findings and of the overall genetic architecture of the trait. Single-cross experiments provide a poor basis for these purposes, as comparison across experiments is hampered by segregation of different allelic combinations among different parents and by context-dependent effects of QTL. To overcome this problem, we combined the benefits of QTL analysis (to identify genomic regions affecting trait variation) and classic diallel analysis (to obtain insight into the general inheritance of the trait) by analyzing multiple mapping families that are connected via shared parents. We first provide a theoretical derivation of main (general combining ability (GCA)) and interaction (specific combining ability (SCA)) effects on F(2) family means relative to variance components in a randomly mating reference population. Then, using computer simulations to generate F(2) families derived from 10 inbred parents in different partial-diallel designs, we show that QTL can be detected and that the residual among-family variance can be analyzed. Standard diallel analysis methods are applied in order to reveal the presence and mode of action (in terms of GCA and SCA) of undetected polygenes. Given a fixed experiment size (total number of individuals), we demonstrate that QTL detection and estimation of the genetic architecture of polygenic effects are competing goals, which should be explicitly accounted for in the experimental design. Our approach provides a general strategy for exploring the genetic architecture, as well as the QTL underlying variation in quantitative traits.     

Combining ability of tropical maize lines for seed quality and agronomic traits

Studies of genetic effects of early selection of maize based on seed quality traits are rare, especially those that use materials from different heterotic groups. These studies are also useful in tropical environments and for the advancement of sustainable agriculture with cropping during seasons not commonly used for cultivation. We estimated, through diallel crosses, the predominant genetic effects on the expression of agronomic traits and seed quality and on the general combining ability of nine maize lines from commercial hybrids and the specific combining ability of hybrid combinations among them. In the evaluation of seed quality, seven tests were used: first count and final count of seed germination, seedling vigor classification, cold tolerance, seedling emergence rate in a sand seedbed, speed of emergence in a sand seedbed, and speed of emergence index. Plant height, first ear height and grain yield were the estimated agronomic traits. In the diallel analysis, method 3 (model I) proposed by Griffing was used. There was a greater significance of non-additive genetic effects in the genetic control of seed quality of the various lines. The Flash, Dekalb 350 and P 30F80 lines combined high seed quality and high grain yield. For growth during the normal planting season, the combinations CD 3121-1 x P 30F80, Speed x CD 3121-2, Dow 8330 x AG 8080 and Dekalb 350 x CD 3121-2 were the most promising for both seed quality and agronomic traits.     

Index selection on seed traits under direct, cytoplasmic and maternal effects in multiple environments

Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.     

Principles for Griffing's combining ability analysis

Griffing's diallel analysis is used in plant improvement programs to identify superior parents for crossing and for characterizing general, specific, and reciprocal effects. Eight different model/method combinations are commonly used in the analysis. The accuracy of the analysis is improved by using the appropriate model and method. In many instances, Model One with Method Three or Four is the most appropriate for obtaining unbiased estimates of combining abilities and gene action. The effective use of Griffing's analysis and the influence of several factors on this analysis are discussed. A personal computer program on this analysis is also made available to interested readers.     

大豆粒形性状的遗传效应分析

采用双子叶植物种子数量性状的遗传模型,分析了大豆品种双列杂交F1和F2种子的粒重、粒宽、粒厚和粒长／粒宽、粒长／粒厚、粒宽／粒厚粒形性状的遗传效应。结果表明：7种粒形性状同时受制于种子直接遗传效应,而且还不同程度的受制于母体和细胞质效应。其中,百粒重、粒长、粒长／粒宽、粒长／粒厚和粒宽／粒厚的遗传以细胞质效应为主;粒宽和粒厚以母体遗传效应为主。粒重、粒长和粒长／粒宽、粒宽／粒厚的种子直接遗传率和细胞质遗传率均属中等,对其4个性状选择可以在较高世代单株和单粒选择均有效果。粒宽和粒厚母体遗传率数值较大,对其性状应以母体单株为单位早代选择,以增加粒宽和粒厚。P2和P7可作为增加百粒重、粒长／粒宽、粒长／粒厚和粒宽／粒厚的理想亲本;P1、P4和P6分别是提高粒长、粒厚和粒宽的理想亲本。     

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.