玉米籽粒性状的遗传模型研究

用１０个遗传上和籽粒形态性状上具有差异的玉米自交系,依多种可能的交配方法获得亲本Ｐ１、Ｐ２、Ｆ１（Ｐ１× Ｐ２）、Ｆ２、Ｂ１（Ｆ１×Ｐ１）、Ｂ２（Ｆ１× Ｐ２）及其相应反交ＲＦ１、ＲＦ２、ＲＢ１、ＲＢ２共１０个种子世代。种植２年。依广义遗传模型建立包括种子胚乳加性、胚乳显性、母体加性、母体显性和细胞质效应的遗传模型,运用种子数量性状的精细鉴别法［１］和混合模型分析法［２,３］,对粒长、粒宽、粒长宽比、粒厚及百粒重作了性状表达遗传机制的鉴别与探讨。单个组合的遗传模型精细测验表明,５个籽粒性状的遗传主要受母体显性和胚乳基因型（包括加性和灵性）的控制,一个组合的粒宽、粒厚和百粒重上还检测到细胞质效应。对２５对 Ｆ１正反交组合世代均值依ＭＩＮＱＵＥ法分析的结果表明,５个籽粒性状的遗传方差中,母体遗传方差占６０％以上,胚乳基因型方差低于４０％,粒长和百粒重还有细胞质效应,约占１０％～３０％。可见,籽粒性状的遗传特点是受多套遗传系统控制,其中以母体基因型的作用最大。     

胚乳性状的遗传模型和世代平均数

谷类作物的胚乳是三倍体组织,胚乳性状受3N遗传控制。本文分析了胚乳性状的遗传特征,建立了相应的遗传模型,推导了世代群体的平均数分量,并提出了研究胚乳性状基因效应的一些简单的交配设计。     

胚和胚乳基因效应对水稻幼苗生物量的影响研究

本文利用和胚乳遗传模型[研究了水稻早期胚后生长生物量性状的遗传控制,结果表明：在两个时期水稻幼苗生物量性状中,除了第16天时根鲜重（RFW）主要受到胚乳显性效应控制外,叶鲜重（LFW）,叶干重（LDW）,根干重（RDW）主要受到胚基因显性效应和胚乳基因加性效应的控制,胚加性和乳乳加性效应占总遗传方差的40－54％,说明对生物量性状进行早期选择有效,各个性状都检测到显著的胚狭义遗传率和胚乳狭义遗传率,说明在早期世代即可估计选择进程,对亲本的遗传效应值的预测表明,对根部性状的选择在第8天进行比较合适,并以亲本P1,P3和P6较好,它们既可提高RFW又可提高RDW,而对地上部分性状的选择在第16天时进行比较合适,并以P4,P9和P10为最好。     

麦芽品质性状的遗传模型及其分析方法

本文提出分析大麦芽品质性状世代平均数的遗传模型,根据麦芽性状的特点,该模型将控制麦芽性状的总遗传效应分解为萌动胚基因效应和胚乳基因效应。     

籼稻糙米厚度的发育遗传研究

应用包括３套遗传体系基因效应的数量性状发育遗传模型,分析了１２个籼稻亲本在４个不同稻米发育时期的糙米厚性状。结果表明,三倍体胚乳、二倍体母体植株基因的加性和显性效应以及细胞质效应均可以明显影响各个稻米发育时期的糙米厚度,其中灌浆始期以二倍体母体植株效应为主,灌浆中后期以三倍体胚乳效应为主,成熟期则以细胞质效应为主。在４个不同发育时期中,控制糙米厚的基因加性效应和显性效应交替为主。胚乳显性方差和母体     

谷类作物胚乳的遗传

胚乳是谷类作物种子的重要组成部分。一个完整的种子除了胚、种皮和果皮外,其余部分就是胚乳。由于它们最初发起的组织部位不同,其遗传行为也大不相同。有时仅从种子本身就可以观察到几种不同的遗传现象,如花粉直感、不同位点数基因的剂量效应和体细胞遗传等。正因为有这些复杂的遗传形式,在遗传学教学和实际应用中胚乳遗传常被忽视,并与2n体细胞的性状遗传相混淆。为了弄清这些复杂的遗传现象及种子各组成彼此间在遗传行为上的内在关系,本文特就这方面的内容作较系统介绍。 (一)胚乳的遗传及其与胚遗传的区别胚乳是双受精的产物。在正常情况下,谷类     

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。     

长期人工选择对群体遗传结构的影响——一项计算机模拟研究 Ⅱ.长期选择对群体遗传方差的作用

本文给出了显性与超显性模型下加性方差的分剖公式,为研究选择作用下基因间关系的变化提供了有力的方法。并模拟研究了群体大小、连锁强度与遗传力水平对遗传方差变化的影响。小群体中遗传方差在世代间波动很大;大群体中则稳定下降、波动较小。选择作用下平衡加性方差下降很快,特别是高遗传力性状。紧密连锁在小群体中一方面降低选择反应,一方面维持了更多的加性方差,从而使得预测长期选择反应甚为困难。     

谷类作物胚乳性状遗传控制的鉴别

谷类作物种子胚乳生状的遗传表达,可能受三倍体的胚乳基因型和／或二倍体的母体基因型控制,还可能存在细胞质效应。Ｆｏｏｌａｄ等和Ｐｏｏｎｉ等提出的分析模型,由于遗传参数的系数间存在线性相关,不能有效地区分上述遗传控制系统。本文的交配设计和相应统计方法,可对一胚乳生状是否存在胚乳基因型,母体基因型蔌细腻质效应分别作出测验,从而可确定合适遗传模型和估计有关遗传参数。这些方法也可方便地推广于鉴别非谷作物种子     

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.     

胚乳性状数量基因的定位方法

将三倍体胚乳性状的数量遗传模型和二倍体性状数量基因（QTL）图构建方法相结合,导出双侧标记基因型下有关胚乳性状QTL的遗传组成、平均数和遗传方差分量,据之提出以某一区间双侧标记基因型胚乳性状的平均值为依变数,以该区间内任一点假定存在的QTL的加性效应d、显性效应h1和／或h2的系数为自变数,进行有重复观察值的多元线性回归分析,根据多元线性回归的显著性测验该点是否存在QTL,并估计出QTL的遗传效应。给定区间内任一点,皆可以此进行分析,从而可在整条染色体上作图,并以之确定QTL的数目和最可能位置,同时,在检测某一区间时,利用多元线性回归方法将该区间外可能存在的QTL的干扰进行统计控制,以提高QTL检测的精度。此外,还讨论了如何将之推广应用于其他类型的DNA不对应资料以及具复杂遗传模型的胚乳性状资料。     

Variance component analysis of bristle characters in local populations of Drosophila melanogaster.

The genetic variabilities of sternopleural and abdominal bristle numbers existing in local natural populations were assessed. Using second chromosome lines of Drosophila melanogaster extracted from three natural populations in Japan (the Ishigakijima, Ogasawara and Aomori populations), experiments were conducted to estimate the components of genetic variances, additive and dominance variances. The following results were obtained: For both sternopleural and abdominal bristle numbers, the additive genetic variances (sigma 2A) were much larger than the dominance variances (sigma 2D) especially in the southern populations. For example, in the Ishigakijima population, for females sternopleural bristle numbers of the inversion-free chromosome group, the additive and dominance variances were estimated to be 1.255 +/- 0.2034 and 0.0552 +/- 0.0180, respectively. The magnitudes of the estimates of additive genetic variances were nearly equal from north to south. By comparing the additive genetic variances of the inversion-free chromosome group with those of the In(2L)t-carrying chromosome group, it was inferred that sufficient number of generations to achieve the equilibrium state has not passed since the introduction of a single or a small number of the In(2L)t-carrying chromosomes to the Ishigakijima population.     

Ontogenetic changes in genetic variances of age-dependent plasticity along a latitudinal gradient

The expression of phenotypic plasticity may differ among life stages of the same organism. Age-dependent plasticity can be important for adaptation to heterogeneous environments, but this has only recently been recognized. Whether age-dependent plasticity is a common outcome of local adaptation and whether populations harbor genetic variation in this respect remains largely unknown. To answer these questions, we estimated levels of additive genetic variation in age-dependent plasticity in six species of damselflies sampled from 18 populations along a latitudinal gradient spanning 3600 km. We reared full sib larvae at three temperatures and estimated genetic variances in the height and slope of thermal reaction norms of body size at three points in time during ontogeny using random regression. Our data show that most populations harbor genetic variation in growth rate (reaction norm height) in all ontogenetic stages, but only some populations and ontogenetic stages were found to harbor genetic variation in thermal plasticity (reaction norm slope). Genetic variances in reaction norm height differed among species, while genetic variances in reaction norm slope differed among populations. The slope of the ontogenetic trend in genetic variances of both reaction norm height and slope increased with latitude. We propose that differences in genetic variances reflect temporal and spatial variation in the strength and direction of natural selection on growth trajectories and age-dependent plasticity. Selection on age-dependent plasticity may depend on the interaction between temperature seasonality and time constraints associated with variation in life history traits such as generation length.     

AN ANALYSIS OF SELECTIONAL RESPONSE IN RELATION TO A POPULATION BOTTLENECK

Selection for increased morphometric shape (ratio of wing length to thorax width) was compared between control (nonbottlenecked) populations and bottlenecked populations founded with two male–female pairs of flies. Contrary to neutral expectation, selectional response was not reduced in bottlenecked populations, and the mean realized heritabilities and additive genetic variances were higher for the bottlenecked lines than for the nonbottlenecked lines. Additive genetic variances based on these realized heritabilities were consistent with independent estimates of genetic variances based on parent–offspring covariances. Joint scaling tests applied to the crosses between selected lines and their controls revealed significant nonadditive components of genetic variance in the ancestor, which were not detected in the crosses involving bottlenecked lines. The nonbottlenecked lines responded principally by changes in one trait or the other (wing length or thorax width) but not in both, and regardless of which trait responded, larger trait size was dominant and epistatic to smaller size. Stabilizing selection for morphometric shape in the ancestor likely molded the genetic architecture to include nonadditive genetic effects.     

Sampling Variances of Heterozygosity and Genetic Distance

Mathematical formulae for the sampling variances of average heterozygosity and Nei's genetic distance are developed. These sampling variances are decomposed into their two components, i.e. the inter-locus and intra-locus variances. The relationship between the number of loci and the number of individuals per locus to be examined for estimating average heterozygosity and genetic distance is also discussed. The utility of the inter-locus variance of heterozygosity for studying the mechanism of maintenance of genetic variability in populations is indicated.     

Variance of Neutral Genetic Variances within and between Populations for a Quantitative Character

The variances of genetic variances within and between finite populations were systematically studied using a general multiple allele model with mutation in terms of identity by descent measures. We partitioned the genetic variances into components corresponding to genetic variances and covariances within and between loci. We also analyzed the sampling variance. Both transient and equilibrium results were derived exactly and the results can be used in diverse applications. For the genetic variance within populations, sigma 2 omega, the coefficient of variation can be very well approximated as [formula: see text] for a normal distribution of allelic effects, ignoring recurrent mutation in the absence of linkage, where m is the number of loci, N is the effective population size, theta 1(0) is the initial identity by descent measure of two genes within populations and t is the generation number. The first term is due to genic variance, the second due to linkage disequilibrium, and third due to sampling. In the short term, the variation is predominantly due to linkage disequilibrium and sampling; but in the long term it can be largely due to genic variance. At equilibrium with mutation [formula: see text] where u is the mutation rate. The genetic variance between populations is a parameter. Variance arises only among sample estimates due to finite sampling of populations and individuals. The coefficient of variation for sample gentic variance between populations, sigma 2b, can be generally approximated as [formula: see text] when the number of loci is large where S is the number of sampling populations.     

Dissecting total genetic variance into additive and dominance components of purebred and crossbred pig traits

The partition of the total genetic variance into its additive and non-additive components can differ from trait to trait, and between purebred and crossbred populations. A quantification of these genetic variance components will determine the extent to which it would be of interest to account for dominance in genomic evaluations or to establish mate allocation strategies along different populations and traits. This study aims at assessing the contribution of the additive and dominance genomic variances to the phenotype expression of several purebred Piétrain and crossbred (Piétrain × Large White) pig performances. A total of 636 purebred and 720 crossbred male piglets were phenotyped for 22 traits that can be classified into six groups of traits: growth rate and feed efficiency, carcass composition, meat quality, behaviour, boar taint and puberty. Additive and dominance variances estimated in univariate genotypic models, including additive and dominance genotypic effects, and a genomic inbreeding covariate allowed to retrieve the additive and dominance single nucleotide polymorphism variances for purebred and crossbred performances. These estimated variances were used, together with the allelic frequencies of the parental populations, to obtain additive and dominance variances in terms of genetic breeding values and dominance deviations. Estimates of the Piétrain and Large White allelic contributions to the crossbred variance were of about the same magnitude in all the traits. Estimates of additive genetic variances were similar regardless of the inclusion of dominance. Some traits showed relevant amount of dominance genetic variance with respect to phenotypic variance in both populations (i.e. growth rate 8%, feed conversion ratio 9% to 12%, backfat thickness 14% to 12%, purebreds-crossbreds). Other traits showed higher amount in crossbreds (i.e. ham cut 8% to 13%, loin 7% to 16%, pH semimembranosus 13% to 18%, pH longissimus dorsi 9% to 14%, androstenone 5% to 13% and estradiol 6% to 11%, purebreds-crossbreds). It was not encountered a clear common pattern of dominance expression between groups of analysed traits and between populations. These estimates give initial hints regarding which traits could benefit from accounting for dominance for example to improve genomic estimated breeding value accuracy in genetic evaluations or to boost the total genetic value of progeny by means of assortative mating.     

Including Dominance Effects in the Genomic BLUP Method for Genomic Evaluation

We evaluated the performance of GBLUP including dominance genetic effect (GBLUP-D) by estimating variances and predicting genetic merits in a computer simulation and 2 actual traits (T4 and T5) in pigs. In simulation data, GBLUP-D explained more than 50% of dominance genetic variance. Moreover, GBLUP-D yielded estimated total genetic effects over 1.2% more accurate than those yielded by GBLUP. In particular, when the dominance genetic variance was large, the accuracy could be substantially improved by increasing the number of markers. The dominance genetic variances in T4 and T5 accounted for 9.6% and 6.3% of the phenotypic variances, respectively. Estimates of such small dominance genetic variances contributed little to the improvement of the accuracies of estimated total genetic effects. In both simulation and pig data, there were nearly no differences in the estimates of additive genetic effects or their variance between GBLUP-D and GBLUP. Therefore, we conclude GBLUP-D is a feasible approach to improve genetic performance in crossbred populations with large dominance genetic variation and identify mating systems with good combining ability.     

THE HERITABLE BASIS OF VARIATION IN LARVAL DEVELOPMENTAL PATTERNS WITHIN POPULATIONS OF THE WOOD FROG (RANA SYLVATICA)

This study compares the heritable basis of variation in larval developmental patterns of mountain and lowland populations of the wood frog, Rana sylvatica. Additive genetic variances, heritabilities, and genetic correlations for larval developmental time and size at metamorphosis are estimated from half-sib and full-sib crosses. Considerable additive-genetic variances and high heritabilities are revealed for developmental time in both the mountain and the lowland population. There was a high level of additive-genetic variance and high heritability for body size at metamorphosis in the mountain population, but these were very low in the lowland population. The genetic correlations between developmental rate and larval body size are negative for the mountain population and near zero for the lowland population. It is argued that the differences in genetic structure between these two populations reflect differences in the selective regimes of their respective environments.     

POPULATION STRUCTURE OF MORPHOLOGICAL TRAITS IN CLARKIA DUDLEYANA. II. CONSTANCY OF WITHIN-POPULATION GENETIC VARIANCE

Recent quantitative genetic studies have attempted to infer long-term selection responsible for differences in observed phenotypes. These analyses are greatly simplified by the assumption that the within-population genetic variance remains constant through time and over space, or for the multivariate case, that the matrix of additive genetic variances and covariances (G matrix) is constant. We examined differences in G matrices and the association of these differences with differences in multivariate means (Mahalanobis D²) among 11 populations of the California endemic annual plant, Clarkia dudleyana. Based on nine continuous morphological traits, the relationship between Mahalanobis D² and a distance measure summarizing differences in G matrices reflected no concomitant change in (co)variances with changes in means. Based on both broad- and narrow-sense analyses, we found little evidence that G matrices differed between populations. These results suggest that both the additive and nonadditive (co)variances for traits have remained relatively constant despite changes in means.