玉米籽粒性状的遗传效应分析

采用二倍体胚和三倍体胚乳种子遗传模型及其分析方法,以5个玉米自交系及其配制的F1,F2,BC1,BC2世代为材料,研究5个玉米种子性状的胚直接效应、胚乳直接效应、母体效应和细胞质效应。分析结果表明,除粒宽外,各性状的遗传同时由细胞质效应和胚、胚乳、母体基因效应所控制,百粒重主要受胚乳和母体效应的影响,粒长的遗传以母体效应为主,粒宽和粒厚以胚乳效应为主。各部位籽粒百粒重的胚乳直接加性效应与母体加性效应的协方差达到显著或极显著水平,其余性状的胚、胚乳直接效应与母体效应间的协方差均不显著,通过母体植株的遗传表现可以对这些性状进行有效的选择。S22 是改良百粒重的优良亲本。 Abstract：The embryo,endosperm and cytoplasm effects of seven seed traits were studied by genetic model for diploid embryo and triploid endosperm plant seeds using five inbreds and their F1, F2, BC1 and BC2 generations. The estimates of genetic variance components indicated that the inheritance of all other kernel traits was controlled by the four effects except kernel width. The 100?kernel weight was mainly controlled by endosperm and maternal effects , and kernel length was controlled by the maternal effects,while endosperm conrrolled kernel width and kernel thickness. Except the significant or highly significant covariances between the endosperm direct additive and maternal additive effects for 100－kernel weight,all other traits between the embryo or endosperm direct effect and the maternal were not significant. So,maize inbreds could be developed by direct selection based on maternal plants for these traits. S22 was the best inbred of the improvement for kernel weight in this study.     

Mechanisms of chromatin-based epigenetic inheritance

Multi-cellular organisms such as humans contain hundreds of cell types that share the same genetic information(DNA sequences), and yet have different cellular traits and functions. While how genetic information is passed through generations has been extensively characterized, it remains largely obscure how epigenetic information encoded by chromatin regulates the passage of certain traits, gene expression states and cell identity during mitotic cell divisions, and even through meiosis. In this r...     

MIXED MODEL APPROACHES FOR ESTIMATING GENETIC VARIANCES AND COVARIANCES

The limitations of methods for analysis of variance(ANOVA)in estimating genetic variances are discussed. Among the three methods(maximum likelihood ML, restricted maximum likelihood REML, and minimum norm quadratic unbiased estimation MINQUE)for mixed linear models, MINQUE method is presented with formulae for estimating variance components and covariances components and for predicting genetic effects. Several genetic models, which cannot be appropriately analyzed by ANOVA methods, are introduced in forms of mixed linear models. Genetic models with independent random effects can be analyzed by MINQUE(1)method whieh is a MINQUE method with all prior values setting 1. MINQUE(1)method can give unbiased estimation for variance components and covariance components, and linear unbiased prediction (LUP) for genetic effects. There are more complicate genetic models for plant seeds which involve correlated random effects. MINQUE(0/1)method, which is a MINQUE method with all prior covariances setting 0 and all prior variances setting 1, is suitable for estimating variance and covariance components in these models. Mixed model approaches have advantage over ANOVA methods for the capacity of analyzing unbalanced data and complicated models. Some problems about estimation and hypothesis test by MINQUE method are discussed.     

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.     

The start of a human life program

正The genetic information of a human being is encoded in the genomic DNA of about 3 billion base pairs.Every new individual starts from a one-cell zygote,or called fertilized egg,carrying genetic and epigenetic information from the parents.The developmental process from one single cell to a whole organism depends on the differential regulation of the genetic information encoded     

两种常用数量性状连锁分析方法的原理和进展

在复杂性状疾病的家系连锁研究中,Haseman-Elston回归分析和方差组成模型是常用的两种数量性状连锁分析方法。前者主要针对同胞对的性状值差或和的平方进行回归分析;后者引用方差组成模型,将数量性状分解为遗传方差和环境方差,可估计二者对表型的影响。两种方法可应用于同胞对、核心家系或扩展家系,定位数量性状基因座。本文对这两种模型的原理、算法及其进展进行了综述,并给出了常用的统计软件包。 Abstract：In this article, we discussed two model-free methods for detecting genetic linkage for quantitative traits, Haseman-Elston regression approach and variance components approach. The former is a regression approach for detecting linkage based on the squared difference or squared sums in quantitative trait values of sib-pairs and their estimated marker IBD scores. The latter can jointly model covariate effects along with variance components, including genetic component and non-genetic sources of variability. We have outlined the model assumption, the algorithm and the extensions for the both methods.     

Nonlinear maternal effects on personality in a rodent species with fluctuating densities

Consistent among individual variation in behavior,or animal personality,is present in a wide variety of species.This behavioral variation is maintained by both genetic and environmental factors.Parental effects are a special case of environmental variation and are expected to evolve in populations experiencing large fluctuations in their environment.They represent a non-genetic pathway by which parents can transmit information to their offspring,by modulating their personality.While it is expected that parental effects contribute to the observed personality variation,this has rarely been studied in wild populations.We used the multimammate mouse Mastomys natalensis as a model system to investigate the potential effects of maternal personality on offspring behavior.We did this by repeatedly recording the behavior of individually housed juveniles which were born and raised in the lab from wild caught females.A linear correlation,between mother and offspring in behavior,would be expected when the personality is only affected by additive genetic variation,while a more complex relationship would suggests the presence of maternal effects.We found that the personality of the mother predicted the behavior of their offspring in a non-linear pattern.Exploration behavior of mother and offspring was positively correlated,but only for slow and average exploring mothers,while this correlation became negative for fast exploring mothers.This may suggests that early maternal effects could affect personality in juvenile M.natalensis,potentially due to density-dependent and negative frequency-dependent mechanisms,and therefore contribute to the maintenance of personality variation.     

Novel pleiotropic loci controlling panicle architecture across environments in japonica rice （Oryza sativa L.）

To identify quantitative trait loci (QTLs) controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat (SSR) markers and 254 recombinant inbred lines (RILs) derived from a cross between cultivars Xiushui 79 and C Bao. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%-35% of phenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle (NPB), two for panicle length (PL), two for spikelet density (SD), one for the number of secondary branches per panicle (NSB), one for secondary branch distribution density (SBD), and one for the number of spikelets per panicle (NS), respectively. qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously. qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively. qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTL × environment interactions were not significant for additive QTLs and additive × additive QTL pairs.     

云南红豆杉天然群体内同工酶遗传变异的研究

采用水平淀粉凝胶电泳技术,对分布于金沙江流域的云南红豆杉天然群体的10种酶系统同工酶的遗传变异进行了研究。在谱带遗传分析的基础上确定了15个酶基因座及其等位基因。其中有14个酶基因座属多态,只有一个单态基因座（ME－3）。14个多态基因座中,4个基因座遗传变异小,对该天然群体的遗传变异贡献不大,其余10个基因座遗传变异丰富,对该天然群体的遗传变异贡献大。该天然群体具有明显丰富的遗传变异性,多态基因座比率P=0.933,等位基因平均数A=2.90,平均期望杂合度He=0.290。紫杉醇含量与群体遗传变异有着密切的关系。 Abstract：Genetic variation of ten isoenzymes was studied within population of Taxus yun nanensis Cheng et L. K. Fu in the Jinsha River Valley using the method of hor izo ntal starch gel electrophoresis.On the basis of banding analysis,eight enzyme sy stems , presumablly coded by fifteen isoenzyme loci and their alleles were score d , and fourteen were polymorphic with only one monomorphic locus（ME－3）. Amon g them , four polymorphic loci with inevident genetic variation made little cont ribution to genetic variation of this population and other ten polymorphic loci with evident genetic variation made great contribution to genetic variation of this population . Isoenzyme data indicated high level of genetic variability in this population with P=0.933,A=2.90,He=0.290 . The taxol content had close r elation to genetic variation of population.     

Epigenetic control of meiotic recombination in plants

Meiotic recombination is a deeply conserved process within eukaryotes that has a profound effect on patterns of natural genetic variation. During meiosis homologous chromosomes pair and undergo DNA double strand breaks generated by the Spo11 endonuclease. These breaks can be repaired as crossovers that result in reciprocal exchange between chromosomes. The frequency of recombination along chromosomes is highly variable, for example, crossovers are rarely observed in heterochromatin and the centromeric regions. Recent work in plants has shown that crossover hotspots occur in gene promoters and are associated with specific chromatin modifications, including H2 A.Z. Meiotic chromosomes are also organized in loop-base arrays connected to an underlying chromosome axis, which likely interacts with chromatin to organize patterns of recombination.Therefore, epigenetic information exerts a major influence on patterns of meiotic recombination along chromosomes, genetic variation within populations and evolution of plant genomes.     

Developmental interactions and the constituents of quantitative variation

Development is the process by which genotypes are transformed into phenotypes. Consequently, development determines the relationship between allelic and phenotypic variation in a population and, therefore, the patterns of quantitative genetic variation and covariation of traits. Understanding the developmental basis of quantitative traits may lead to insights into the origin and evolution of quantitative genetic variation, the evolutionary fate of populations, and, more generally, the relationship between development and evolution. Herein, we assume a hierarchical, modular structure of trait development and consider how epigenetic interactions among modules during ontogeny affect patterns of phenotypic and genetic variation. We explore two developmental models, one in which the epigenetic interactions between modules result in additive effects on character expression and a second model in which these epigenetic interactions produce nonadditive effects. Using a phenotype landscape approach, we show how changes in the developmental processes underlying phenotypic expression can alter the magnitude and pattern of quantitative genetic variation. Additive epigenetic effects influence genetic variances and covariances, but allow trait means to evolve independently of the genetic variances and covariances, so that phenotypic evolution can proceed without changing the genetic covariance structure that determines future evolutionary response. Nonadditive epigenetic effects, however, can lead to evolution of genetic variances and covariances as the mean phenotype evolves. Our model suggests that an understanding of multivariate evolution can be considerably enriched by knowledge of the mechanistic basis of character development.     

Maintaining heritable variation via sex-limited temporally fluctuating selection: a phenotypic model accommodating non-Mendelian epigenetic effects

Using a phenotypic model, we show that significant heritable variation can be maintained in a population subjected to temporally fluctuating selection if only one sex is subject to selection. In fact, more variation is maintained with sex-limited selection at a given selection intensity than if both sexes are subject to half that selection intensity. This result is commensurate with existing population genetic models. However, genetic models may be inappropriate for sexually selected traits because many of them may be of non-genetic origin, such as maternal effects or – more likely –epigenetic effects. Phenotypic models obviate this problem by accommodating both genetic and epigenetic effects, as well as maternaleffects. Our phenotypic model of sex-limited temporally fluctuating selection shows that substantial heritable variation can be maintained and therebyprovides impetus to develop population epigenetic models.     

Morphometrics and the role of the phenotype in studies of the evolution of developmental mechanisms

Developmental mechanisms are usually assumed to evolve by natural selection of the morphological traits they produce. Therefore, information on phenotypic traits is an important component of comparative studies of development. Morphometrics permits the rigorous quantitative analysis of variation in organismal size and shape, and is increasingly being used in developmental contexts. The new methods of morphometrics combine a geometric concept of shape with the procedures of multivariate statistics, and constitute a powerful and flexible set of tools for analyzing morphological variation. This paper briefly reviews these methods and provides examples of their application in studies of genetic variation and developmental modularity. The results of morphometric analyses can be readily interpreted in relation to the geometry and anatomical structure of the parts under study. Genetic studies of shape in the mouse mandible found two recurrent patterns in environmental and genetic variation from different origins, suggesting that the development system 'channels' the phenotypic expression of variation in similar ways. Moreover, by analyzing the correlations of left-right asymmetries of morphometric traits, it is possible to delimit the spatial extent of developmental modules. These methods complement the experimental approaches of developmental biology and genetics, and can be expected to be especially fruitful in combination with them.     

Developmental quantitative genetic models of evolutionary change

Discussions about evolutionary change in developmental processes or morphological structures are predicated on specific quantitative genetic models whose parameters predict whether evolutionary change can occur, its relative rate and direction, and if correlated change will occur in other related and unrelated structures. The appropriate genetic model should reflect the relevant genetical and developmental biology of the organisms, yet be simple enough in its parameters so that deductions can be made and hypotheses tested. As a consequence, the choice of the most appropriate genetic model for polygenically controlled traits is a complex tissue and the eventual choice of model is often a compromise between completeness of the model and computational expediency. Herein, we discuss several developmental quantitative genetic models for the evolution of development and morphology. The models range from the classical direct effects model to complex epigenetic models. Further, we demonstrate the algebraic equivalency of the Cowley and Atchley epigenetic model and Wagner's developmental mapping model. Finally, we propose a new multivariate model for continuous growth trajectories. The relative efficacy of these various models for understanding evolutionary change in developmental and morphological traits is discussed. © 1994 Wiley-Liss, Inc.     

Study of Natural Genetic Variation in Early Fitness Traits Reveals Decoupling Between Larval and Pupal Developmental Time in <Emphasis Type="Italic">Drosophila melanogaster</Emphasis>

Characterizing the relationships between genotype and phenotype for developmental adaptive traits is essential to understand the evolutionary dynamics underlying biodiversity. In holometabolous insects, the time to reach the reproductive stage and pupation site preference are two such traits. Here we characterize aspects of the genetic architecture for Developmental Time (decomposed in Larval and Pupal components) and Pupation Height using lines derived from three natural populations of Drosophila melanogaster raised at two temperatures. For all traits, phenotypic differences and variation in plasticity between populations suggest adaptation to the original thermal regimes. However, high variability within populations shows that selection does not exhaust genetic variance for these traits. This could be partly explained by local adaptation, environmental heterogeneity and modifications in the genetic architecture of traits according to environment and ontogenetic stage. Indeed, our results show that the genetic factors affecting Developmental Time and Pupation Height are temperature-specific. Varying relationships between Larval and Pupal Developmental Time between and within populations also suggest stage-specific modifications of genetic architecture for this trait. This flexibility would allow for a somewhat independent evolution of adaptive traits at different environments and life stages, favoring the maintenance of genetic variability and thus sustaining the traits’ evolvabilities.     

A unified approach to the evolutionary consequences of genetic and nongenetic inheritance

Inheritance-the influence of ancestors on the phenotypes of their descendants-translates natural selection into evolutionary change. For the past century, inheritance has been conceptualized almost exclusively as the transmission of DNA sequence variation from parents to offspring in accordance with Mendelian rules, but advances in cell and developmental biology have now revealed a rich array of inheritance mechanisms. This empirical evidence calls for a unified conception of inheritance that combines genetic and nongenetic mechanisms and encompasses the known range of transgenerational effects, including the transmission of genetic and epigenetic variation, the transmission of plastic phenotypes (acquired traits), and the effects of parental environment and genotype on offspring phenotype. We propose a unified theoretical framework based on the Price equation that can be used to model evolution under an expanded inheritance concept that combines the effects of genetic and nongenetic inheritance. To illustrate the utility and generality of this framework, we show how it can be applied to a variety of scenarios, including nontransmissible environmental noise, maternal effects, indirect genetic effects, transgenerational epigenetic inheritance, RNA-mediated inheritance, and cultural inheritance.     

Evolvability and Robustness in Color Displays: Bridging the Gap between Theory and Data

Evolution of diet-derived sexual ornaments—some of the most spectacular and diverse traits in the living world—highlights the gap between modern evolutionary theory and empirical data on the origin and inheritance of complex environment-dependent traits. Specifically, current theory offers little insight into how strong environmental contingency of diet-dependent color biosynthesis and environmental variability in precursor supply can be reconciled with extensive evolutionary elaboration, diversification, and convergence of diet-dependent displays among animal taxa. Moreover, biosynthetic pathways of diet-derived displays combine seemingly irreconcilable robustness, lability, and modularity to facilitate elaboration under variable environmental conditions. Here I show that an ontogenetic decrease in the predictability of an association between organismal and environmental components of color biosynthesis and the corresponding evolutionary transition from short-term epigenetic inheritance of peripheral biosynthetic components to genetic inheritance of the most reliable upstream components link the causes of developmental variation with the causes of inheritance in diet-derived displays. Using carotenoid-based colors as an empirical model, I outline general principles of a testable evolutionary framework of diversification and functional robustness of diet-derived displays, and suggest that such a framework provides insight into the foundational question of evolutionary biology—how to connect causes of within-generation developmental variation with causes of among-generation and among-taxa variation and thus with causes of evolution?     

Variation and constraint in plant evolution and development

The goal of this short review is to consider the interrelated phenomena of phenotypic variation and genetic constraint with respect to plant diversity. The unique aspects of plants, including sessile habit, modular growth and diverse developmental programs expressed at the phytomer level, merit a specific examination of the genetic basis of their phenotypic variation, and how they experience and escape genetic constraint. Numerous QTL studies with wild and domesticated plants reveal that most phenotypic traits are polygenic but vary in the number and effect of the loci contributing, from a few loci of large effects to many with small effects. Further, somatic mutations, developmental plasticity and epigenetic variation, especially gene methylation, can contribute to increases in phenotypic variation. The flip side of these processes, genetic constraint, can similarly be the result of many factors, including pleiotropy, canalization and genetic redundancy. Genetic constraint is not only a mechanism to prevent change, however, it can also serve to direct evolution along certain paths. Ultimately, genetic constraint often comes full circle and is released through events such as hybridization, genome duplication and epigenetic remodeling. We are just beginning to understand how these processes can operate simultaneously during the evolution of ecologically important traits in plants.     

Pleiotropic Effects of methoprene-tolerant(Met), a Gene Involved in Juvenile Hormone Metabolism, on Life History Traits in Drosophila melanogaster

Life history theory assumes that there are alleles with pleiotropic effects on fitness components. Although quantitative genetic data are often consistent with pleiotropy, there are few explicit examples of pleiotropic loci. The Drosophila melanogaster gene Methoprene-tolerant (Met) may be such a locus. The Met gene product, a putative juvenile hormone receptor, facilitates the action of juvenile hormone (JH) and JH analogs; JH affects many life history traits in arthropods. Here we use quantitative complementation to investigate effects of Met mutant and wildtype alleles on female developmental time, onset of reproduction, and fecundity. Whereas the alleles did not differ in their effects on developmental time, we detected allelic variation for the onset of reproduction and for age-specific fecundity. Alleles influenced phenotypic co-variances among traits (developmental time and onset of reproduction; onset of reproduction and both early and late fecundity; early and late fecundity), suggesting that alleles of Met vary in their pleiotropic effects upon life history. Furthermore, the genetic covariance between developmental time and early fecundity attributed to alleles of Met was negative, indicating consistent pleiotropic effects among alleles on these traits. The allelic effects of Met support genetic models where pleiotropy at genes associated with hormone regulation can contribute to the evolution of life history traits.     

Epigenetics for ecologists

There is now mounting evidence that heritable variation in ecologically relevant traits can be generated through a suite of epigenetic mechanisms, even in the absence of genetic variation. Moreover, recent studies indicate that epigenetic variation in natural populations can be independent from genetic variation, and that in some cases environmentally induced epigenetic changes may be inherited by future generations. These novel findings are potentially highly relevant to ecologists because they could significantly improve our understanding of the mechanisms underlying natural phenotypic variation and the responses of organisms to environmental change. To understand the full significance of epigenetic processes, however, it is imperative to study them in an ecological context. Ecologists should therefore start using a combination of experimental approaches borrowed from ecological genetics, novel techniques to analyse and manipulate epigenetic variation, and genomic tools, to investigate the extent and structure of epigenetic variation within and among natural populations, as well as the interrelations between epigenetic variation, phenotypic variation and ecological interactions.