作物品种间杂种优势遗传分析的新方法

本文提出了分析双列杂交试验资料的两个遗传模型。第一个模型包括加性、显性和母体效应;第二个模型只包括简单的加性和显性效应。还介绍了分析杂种优势、估算遗传方差分量以及预测遗传效应值的相应统计分析方法。用所介绍的遗传模型和分析方法以及常用的Griffing配合力分析方法,分析了棉花6个品种双列杂交的产量性状,并进一步比较了不同方法的分析结果。采用本文所介绍的遗传模型和分析方法,可以克服用Griffing的配合力模型及其方法分析杂种优势和配合力遗传表现所存在的局限性。     

Methods for the study of cytoplasmic effects on quantitative traits

Summary The methods used to study cytoplasmic effects in quantitative traits often do not measure quantitative genetic parameters, while those that do are either complicated or do not take into account situations where the expression of cytoplasmic effects does not persist, but decreases in advanced generations. We present two simple models that take cytoplasmic effects and the quantitative genetic parameters into account. One of the models (A) is for cases where cytoplasmic effects remain constant through successive generations, and the second model (B) is for traits where cytoplasm-genotype interactions are present. This model also takes into account the decreasing persistence of cytoplasmic effects with advancing generations, which is often reported in the literature.     

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.     

Maternal and genetic contributions to geographical variation in Rana temporaria larval life-history traits

The relative importance of genetic, environmental, and maternal effects as determinants of geographical variation in vertebrate life-histories has not often been explored. We examined the role of genetic and maternal effects as determinants of population divergence in survival and three important larval life-history traits (growth rate, age, and size at metamorphosis) using reciprocal crosses between two latitudinally separated populations of the common frog ( Rana temporaria Linnaeus). Genetic effects were important in all three traits as indicated by the significant effect of male origin, but there was also evidence for nonadditive genetic contributions on metamorphic size and growth rate. Likewise, maternal effect contributions to population divergence were large, partially environment dependent, and apparently acting primarily through egg size in two of three traits. These results suggest that both genetic and maternal effects are important determinants of geographical variation in amphibian life-histories, and that much of the differentiation resulting from maternal effects is mediated through variation in egg size. © 2002 The Linnean Society of London, Biological Journal of the Linnean Society , 2002, 76 , 61–70.     

The role of maternal and paternal effects in the evolution of parental quality by sexual selection

Genetic models of maternal effects and models of mate choice have focused on the evolutionary effects of variation in parental quality. There have been, however, few attempts to combine these into a single model for the evolution of sexually selected traits. We present a quantitative genetic model that considers how male and female parental quality (together or separately) affect the expression of a sexually selected offspring trait. We allow female choice of males based on this parentally affected trait and examine the evolution of mate choice, parental quality and the indicator trait. Our model reveals a number of consequences of maternal and paternal effects. (1) The force of sexual selection owing to adaptive mate choice can displace parental quality from its natural selection optimum. (2) The force of sexual selection can displace female parental quality from its natural selection optimum even when nonadaptive mate choice occurs (e.g. runaway sexual selection), because females of higher parental quality produce more attractive sons and these sons counterbalance the loss in fitness owing to over-investment in each offspring. (3) Maternal and paternal effects can provide a source of genetic variation for offspring traits, allowing evolution by sexual selection even when those traits do not show direct genetic variation (i.e. are not heritable). (4) The correlation between paternal investment and the offspring trait influenced by the parental effects can result in adaptive mate choice and lead to the elaboration of both female preference and the male sexually selected trait. When parental effects exist, sexual selection can drive the evolution of parental quality when investment increases the attractiveness of offspring, leading to the elaboration of indicator traits and higher than expected levels of parental investment.     

Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches

The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long‐term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation‐derived maternal links and microsatellite‐derived paternal links; (ii) Pedigree 2, using SNP‐derived assignment of both maternity and paternity; and (iii) whole‐genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.     

How to separate genetic and environmental causes of similarity between relatives

Related individuals often have similar phenotypes, but this similarity may be due to the effects of shared environments as much as to the effects of shared genes. We consider here alternative approaches to separating the relative contributions of these two sources to phenotypic covariances, comparing experimental approaches such as cross-fostering, traditional statistical techniques and more complex statistical models, specifically the 'animal model'. Using both simulation studies and empirical data from wild populations, we demonstrate the ability of the animal model to reduce bias due to shared environment effects such as maternal or brood effects, especially where pedigrees contain multiple generations and immigration rates are low. However, where common environment effects are strong, a combination of both cross-fostering and an animal model provides the best way to avoid bias. We illustrate ways of partitioning phenotypic variance into components of additive genetic, maternal genetic, maternal environment, common environment, permanent environment and temporal effects, but also show how substantial confounding between these different effects may occur. Whilst the flexibility of the mixed model approach is extremely useful for incorporating the spatial, temporal and social heterogeneity typical of natural populations, the advantages will inevitably be restricted by the quality of pedigree information and care needs to be taken in specifying models that are appropriate to the data.     

Maternal genetic effects on adaptive divergence between anadromous and resident brook charr during early life history

The importance of directional selection relative to neutral evolution may be determined by comparing quantitative genetic variation in phenotype (Q(ST)) to variation at neutral molecular markers (F(ST)). Quantitative divergence between salmonid life history types is often considerable, but ontogenetic changes in the significance of major sources of genetic variance during post-hatch development suggest that selective differentiation varies by developmental stage. In this study, we tested the hypothesis that maternal genetic differentiation between anadromous and resident brook charr (Salvelinus fontinalis Mitchill) populations for early quantitative traits (embryonic size/growth, survival, egg number and developmental time) would be greater than neutral genetic differentiation, but that the maternal genetic basis for differentiation would be higher for pre-resorption traits than post-resorption traits. Quantitative genetic divergence between anadromous (seawater migratory) and resident Laval River (Québec) brook charr based on maternal genetic variance was high (Q(ST) > 0.4) for embryonic length, yolk sac volume, embryonic growth rate and time to first response to feeding relative to neutral genetic differentiation [F(ST) = 0.153 (0.071-0.214)], with anadromous females having positive genetic coefficients for all of the above characters. However, Q(ST) was essentially zero for all traits post-resorption of the yolk sac. Our results indicate that the observed divergence between resident and anadromous brook charr has been driven by directional selection, and may therefore be adaptive. Moreover, they provide among the first evidence that the relative importance of selective differentiation may be highly context-specific, and varies by genetic contributions to phenotype by parental sex at specific points in offspring ontogeny. This in turn suggests that interpretations of Q(ST)-F(ST) comparisons may be improved by considering the structure of quantitative genetic architecture by age category and the sex of the parent used in estimation.     

Shifting patterns in genetic control at the embryo-alevin boundary in brook charr

Maternal inputs to offspring early in development are initially high but the process of development suggests that ontogenetic shifts in the importance of maternal genetic variation relative to other sources should occur. We investigated additive genetic variance and covariance for direct (animal), sire, and maternal effects on embryonic length (EL), yolk sac volume (YSV), and alevin (after yolk sac resorption) length (AL) for 460 embryonic and 460 alevin brook charr (Salvelinus fontinalis) in 23 half-sib families (12 sires, 23 dams). There were no additive genetic effects of sires or individual animals on their own phenotype using sire-dam and maternal-animal models for YSV or EL (h(a)2 < 0.05). However, at the alevin stage we detected low but significant heritability for AL (h(a)2 = 0.14 +/- 0.11). Conversely, maternal genetic effects were high for both embryonic traits (h(EL)2 = 0.61 +/- 0.05; h(YSU)2 = 0.57 +/- 0.06) but faded rapidly for postresorption length (h(AL)2 = 0.18 +/- 0.04). Maternal effects in the sire-dam model corresponded highly with those in the animal-dam model. We did not detect significant genetic covariance between progeny and dams for preresorption traits or between sires and dams for any trait. However, following resorption of the yolk sac, the genetic value of dams for AL was negatively correlated with that of individual progeny (r(m,a) = -0.38 +/- 0.13), suggesting trade-offs and/or stabilizing selection between maternal and animal genetic trait value. This finding was supported by models of dam fecundity on offspring length and dam weight in phenotypic space. Heritability estimates using simple regression of embryo phenotype on adult parental phenotype produced upwardly biased estimates of genetic variance (h2 > 1.0). We propose that development through the embryo-alevin boundary may be a major point in salmonids for ontogenetic changes in the genetic architecture of embryo size from maternal genetic effects to those of the individual organism, and that maternal-offspring conflicts in resource allocation related to size may be partially indicated by negative genetic covariance.     

母体遗传效应对青海细毛羊生产性能遗传参数估计的影响

为了研究母体遗传效应对青海细毛羊生长性状、产毛性状的影响,文章采用平均信息最大约束似然法应用不同混合动物模型估计青海细毛羊生产性状的遗传参数,并采用似然比检验对不同模型进行比较分析。各模型中均包括固定效应、个体直接加性遗传效应、残差效应;随机效应为:个体永久环境效应、母体遗传效应、母体永久环境效应。不同模型对随机效应作了不同考虑:模型1不考虑个体永久环境效应、母体遗传效应、母体永久环境效应;模型2考虑母体永久环境效应;模型3考虑母体遗传效应;模型4考虑母体遗传效应和母体永久环境效应;模型5考虑个体永久环境效应和母体遗传效应;模型6考虑个体永久环境效应、母体遗传效应、母体永久环境效应。各模型估计的初生重遗传力为:0.1896~0.3781;断奶重遗传力为:0.2537~0.2890;周岁重遗传力范围:0.2244~0.3225;成年羊体重遗传力范围:0.2205~0.3983;产毛量遗传力为:0.1218~0.1490;羊毛细度遗传力为:0.0983~0.4802;羊毛长度遗传力为:0.1170~0.1311。与模型1相比,模型3对于初生重、断奶重差异显著(P<0.01),对于周岁重、成年羊体重各模型与模型1的似然比检验差异不显著(P>0.05);与模型6相比,模型4、5对于羊毛细度差异显著(P<0.01),模型4对羊毛长度差异显著(P<0.05),对于产毛量各模型与模型6似然比检验差异不显著(P>0.05)。生长性状中初生重、断奶重受母体遗传效应影响显著,周岁重、成年羊体重受母体遗传效应影响不显著;产毛性状中羊毛细度、长度受母体遗传效应影响显著,产毛量受母体遗传效应影响较弱。