Response to Selection Under Non-Random Mating I. Partitioning Genetic Variance

In analogy to the concept of breeding value defined for random mating equilibrium populations, the “transmittable genetic value” of an individual is defined as the average value of its expected progeny for any system of mating. The genotypic value is then characterised in terms of transmittable and residual genetic values and components of genetic variance redefined which can be estimated by the conventional procedure based on resemblance between relatives.     

Simultaneous Estimation of Additive and Mutational Genetic Variance in an Outbred Population of Drosophila serrata

How new mutations contribute to genetic variation is a key question in biology. Although the evolutionary fate of an allele is largely determined by its heterozygous effect, most estimates of mutational variance and mutational effects derive from highly inbred lines, where new mutations are present in homozygous form. In an attempt to overcome this limitation, middle-class neighborhood (MCN) experiments have been used to assess the fitness effect of new mutations in heterozygous form. However, because MCN populations harbor substantial standing genetic variance, estimates of mutational variance have not typically been available from such experiments. Here we employ a modification of the animal model to analyze data from 22 generations of Drosophila serrata bred in an MCN design. Mutational heritability, measured for eight cuticular hydrocarbons, 10 wing-shape traits, and wing size in this outbred genetic background, ranged from 0.0006 to 0.006 (with one exception), a similar range to that reported from studies employing inbred lines. Simultaneously partitioning the additive and mutational variance in the same outbred population allowed us to quantitatively test the ability of mutation-selection balance models to explain the observed levels of additive and mutational genetic variance. The Gaussian allelic approximation and house-of-cards models, which assume real stabilizing selection on single traits, both overestimated the genetic variance maintained at equilibrium, but the house-of-cards model was a closer fit to the data. This analytical approach has the potential to be broadly applied, expanding our understanding of the dynamics of genetic variance in natural populations.     

Genetic Architecture of Two Fitness-related Traits in Drosophila melanogaster: Ovariole Number and Thorax Length

In Drosophila melanogaster, ovariole number and thorax length are morphological characters thought to be associated with fitness. Maximum daily egg production in females is positively correlated with ovariole number, while thorax length is correlated with male reproductive success and female fecundity. Though both traits are related to fitness, ovariole number is likely to be under stabilizing selection, while thorax length appears to be under directional selection. Current research has focused on examining the sources of variation for ovariole number in relation to fitness, with a view towards elucidating how segregating variation is maintained in natural populations. Here, we utilize a diallel design to explore the genetic architecture of ovariole number and thorax length in nine isogenic lines derived from a natural population. The full diallel design allows the estimation of general combining ability (GCA), specific combining ability (SCA), and also describes variation due to reciprocal effects (RGCA and RSCA). Ovariole number and thorax length differed with respect to their genetic architecture, reflective of the independent selective forces acting on the traits. For ovariole number, GCA accounted for the majority (67.3%) of variation segregating between the lines, with no evidence of reciprocal effects or inbreeding depression; SCA accounted for a small percentage (3.9%) of the variance, suggesting dominance variation; no reciprocal effects were observed. In contrast, for thorax length, the majority of the non-error variance was accounted for by SCA (17.9%), with only one third as much variance (6.2%) due to GCA. Interestingly, RSCA (nuclear–extranuclear interactions) accounted for slightly more variation (7.5%) than GCA in these data. Thus, genetic variation for thorax length is largely in accord with predictions for a fitness trait under directional selection: little additive genetic variation and substantial dominance variation (including a suggestion of inbreeding depression); while the mechanisms underlying the maintenance of variation for ovariole number are more complex.     

Partition of Genetic Variance for Sub-Populations

The variance between and within backcrosses of two populations is partitioned on the base of (I) multinomially distributed numbers of effects of specific chromosomes taking (II) recombination into account and on the base of (III) normally distributed sums of gene effects. The method of estimation makes use of a specific structure of data with backcross parents taken from different generations of random mating reproduction of crosses between the two populations.     

Evolution of additive and nonadditive genetic variance in development time along a cline in Drosophila serrata

Abstract. Latitudinal clines provide natural systems that may allow the effect of natural selection on the genetic variance to be determined. Ten clinal populations of Drosophila serrata collected from the eastern coast of Australia were used to examine clinal patterns in the trait mean and genetic variance of the life-history trait egg-to-adult development time. Development time significantly lengthened from tropical areas to temperate areas. The additive genetic variance for development time in each population was not associated with latitude but was associated with the population mean development time. Additive genetic variance tended to be larger in populations with more extreme development times and appeared to be consistent with allele frequency change. In contrast, the nonadditive genetic variance was not associated with the population mean but was associated with latitude. Levels of nonadditive genetic variance were greatest in the region of the cline where the gradient in the change in mean was greatest, consistent with Barton's (1999) conjecture that the generation of linkage disequilibrium may become an important component of the genetic variance in systems with a spatially varying optimum.     

The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses

We use computer simulations to investigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome-wide association studies (GWAS) or regional heritability mapping (RHM) analyses based on full genome sequence data or SNP chips. We model a large population subject to mutation, recombination, selection, and drift, assuming a pleiotropic model of mutations sampled from a bivariate distribution of effects of mutations on a quantitative trait and fitness. The pleiotropic model investigated, in contrast to previous models, implies that common mutations of large effect are responsible for most of the genetic variation for quantitative traits, except when the trait is fitness itself. We show that GWAS applied to the full sequence increases the number of QTL detected by as much as 50% compared to the number found with SNP chips but only modestly increases the amount of additive genetic variance explained. Even with full sequence data, the total amount of additive variance explained is generally below 50%. Using RHM on the full sequence data, a slightly larger number of QTL are detected than by GWAS if the same probability threshold is assumed, but these QTL explain a slightly smaller amount of genetic variance. Our results also suggest that most of the missing heritability is due to the inability to detect variants of moderate effect (∼0.03–0.3 phenotypic SDs) segregating at substantial frequencies. Very rare variants, which are more difficult to detect by GWAS, are expected to contribute little genetic variation, so their eventual detection is less relevant for resolving the missing heritability problem.     

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。     

果蝇心脏发育基因调控的研究进展

果蝇心脏的发育是一个受到一系列基因共同调控的复杂过程,这些基因在脊椎动物和无脊椎动物果蝇中具有惊人的相似性,对于它们功能的研究将有助于揭示人类心脏发育的过程及分子控制机理.通过将果蝇作为一种重要的模式动物,对心脏发育基因调控的研究进展作一综述.     

二棱大麦熟期性状的遗传研究

以甘木二条等7个二棱大麦品种进行不完全双列杂交,对其亲本、F1和F2的抽穗期,灌浆期和成熟期三个性状以1992和1995年（播种年份）的两年资料,采用加性-显性-上位性（ADAA）模型进行遗传分析．遗传方差分量的比率估算表明,三个性状都存在上位性作用．除灌浆期外,其余二性状还受显性和加性效应的作用,并以加性为主．显性效应和加性效应与环境的互作均达显著水平,基因效应的预测值表明采用P3（黔浙1号）和P4（浙农大3号）较易获得早熟后代．     

On the Probabilities of Obtaining Negative Estimates of Genetic Variance Components

This paper derives the probabilities of obtaining negative estimates of additive and dominance genetic variances when one uses the traditional weighted least square method for estimating genetic variances as given in MATHER and JINKS (1971). The model considered involves P₁, P₂, F₂, B₁ (Backcross to P₁) and B₂ (Backcross to P₂). The results are derived under the ordinary assumptions as made in the genetic literatures. It is shown that unless the genetic effects are very large and environmental effects small, the probabilities of obtaining negative estimates of additive and dominance variances are in general quite large.     

RAPD分析在绢丝昆虫亲缘关系研究中的应用：Ⅱ．柞蚕品种间的遗传差异

采用RAPD技术,对5个柞蚕品种的遗传差异进行比较研究,结果表明,所采用40个随机引物中,有27个引物扩增谱清晰且重复性较好,扩增总片段数253条,单个引物的扩增片段数在4－16之间,片段大小在0．33－3．0kb之间。不同柞蚕品种间的遗传差异较小,遗传距离（D）在0．066－0．1659之间,根据D值,由UPGMA聚类分析软件绘制了它们的分子进化树。     

51个红松子代家系苗期生长变异研究

为选育生长快、成活率高的优良红松子代家系,以吉林省龙井市开山屯林场的51个红松初级种子园子代家系为材料,对其苗高、地径、成活率及存活率进行测定分析。结果表明：除4年生地径的区组与家系交互作用外,各性状在家系间均达显著差异水平（P<0.05）;各性状表型变异系数变化范围为6.85%～29.89%;各性状的遗传力较高,除4年生地径（0.34）和存活率（0.37）外,遗传力均超过0.50,属于高遗传力;高变异系数,高遗传力,有利于家系的评价选择;相关性分析结果表明,各性状间相关关系均达极显著正相关水平。利用布雷津多性状综合评价法对51个红松子代家系进行评价,以10%的入选率,PK29、PK38、PK21、PK37和PK48五个家系入选。入选家系4年生苗高和地径平均值分别为29.26和0.93 cm,分别比总平均值高3.51和0.06 cm,遗传增益分别为10.08%和2.33%。本研究可以为红松优良家系评价提供理论基础和材料。     

RAPD分析在绢丝昆虫亲缘关系研究中的应用I.蓖麻蚕品种间的遗传差异

用RAPD技术对蓖麻蚕基因组DNA进行多态性研究,分析了5个蓖麻蚕品种间的遗传差异。结果表明,所采用的40个随机引物中,有27个引物扩增谱带清晰且重复性较好,扩增总片段数达243个,单个引物的扩增片段数在4～17之间,平均为9条,片段大小在0.33～3.0kb之间。不同蓖麻蚕品种间的遗传距离(D)在0.0683～0.1603之间,根据D值,由UPGMA聚类分析软件绘制了它们的聚类分子树。 Abstract：Random amplified Polymorphic DNA (RAPD) was used to analyze the genetic diversity among eri sickworm. The genetic variance of five erisickworm was studied. The result showed that: 27 of 40 arbitrary primers could amplify clearly with repeatable bands.243 fragments were obtained.Each primer gave 4～17 bands and the average was 9.The length of the band was 0.33～3.0kb. The genetic distance (D) value between different breeds of Eri Silkworm was 0.0683～0.1603. The D value was used to construct a dendrogram by UPGMA.     

Comparative Studies on the Estimation of Genetic Variances by Several Variance Components Estimation Method

Using a quantitative genetic model, this paper compares four different methods for estimating genetic variance components. Given various genetic parameters, data were generated and estimates computed. The number of negative estimates, the sample mean, the sample variance, and the sample mean squared error were computed for each method. It is shown that, if the genetic values are not very small, the traditional MATHER -JINKS method is at least as good as any other method. The ML method might be preferable only if the genetic values are very small and the number of loci large.     

基于SSR标记的不同优势等级云南松遗传多样性分析

基于SSR分子标记技术,按树高和胸径（地径）因子将样地内的植株分为优势木、中等木和劣势木3类,对不同生长优势等级云南松林木的遗传多样性变异特征进行了研究。结果表明：在林冠层,优势木的有效等位基因数、Shannon's信息指数、观测杂合度和期望杂合度分别为2.083、0.762、0.290和0.423,略高于中等木和劣势木;在更新层,有效等位基因数、Shannon's信息指数、观测杂合度和期望杂合度分别为2.063、0.774、0.272和0.410,除观测杂合度外,其余3个指标也均表现为优势木略高于中等木和劣势木。从差异显著性检验来看,不同生长优势等级云南松林木间的遗传多样性差异不显著,即林木生长分化对遗传多样性的影响不明显。     

HERITABILITY OF FITNESS COMPONENTS IN A WILD BIRD POPULATION

Consistently with the prediction that selection should deplete additive genetic variance ( V_A ) in fitness, traits closely associated to fitness have been shown to exhibit low heritabilities ( h ²= V_A /( V_A + V_R )). However, empirical data from the wild indicate that this is in fact due to increased residual variance ( V_R ), rather than due to decreased additive genetic variance, but the studies in this topic are still rare. We investigated relationships between trait heritabilities, additive genetic variances, and traits' contribution to lifetime reproductive success (≈fitness) in a red-billed gull ( Larus novaehollandiae ) population making use of animal model analyses as applied to 15 female and 13 male traits. We found that the traits closely associated with fitness tended to have lower heritabilities than traits less closely associated with fitness. However, in contrast with the results of earlier studies in the wild, the low heritability of the fitness-related traits was not only due to their high residual variance, but also due to their low additive genetic variance. Permanent environment effects—integrating environmental effects experienced in early life as well as nonadditive genetic effects—on many traits were large, but unrelated to traits' importance for fitness.     

西方蜜蜂产浆量的动态遗传研究

应用条件和非条件遗传效应分析方法对3个西方蜜蜂(Apis mellifera L.)品种的蜂群产浆量、台浆量和台基接受率进行了发育遗传研究。结果表明：蜂群产浆量、台浆量在各个时期均存在显著或极显著的基因型方差,台基接受率在大部分时期存在显著或极显著的基因型方差,说明这3个性状主要由遗传因素决定。条件遗传分析发现,在某些无法检测到非条件方差的时期存在显著水平的条件方差,证明在产浆期的不同阶段,3个性状都有基因的新表达。同一性状不同时期的遗传相关分析表明：蜂群产浆量以及台浆量在各个时期均检测到显著或极显著的基因型相关,台基接受率在大多时期存在显著的基因型相关,表明控制产浆量和台浆量早期表现的遗传效应总是以相同的方式调节后期的表现,而台基接受率则不然。成对性状之间的相关研究表明：蜂群产浆量和台浆量之间在各个时期存在显著或极显著的遗传相关,说明2性状基因效应之间的协同作用是一致的,而蜂群产浆量和台基接受率之间在大多时期存在显著的遗传相关,但在一些时期没有相关,2性状之间的基因效应协同作用较差。     

On the Additive and Dominant Variance and Covariance of Individuals Within the Genomic Selection Scope

Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or “breeding” values of individuals are generated by substitution effects, which involve both “biological” additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the “genotypic” value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts.     

二棱大麦茎杆特性的ADAA模型的遗传研究

以二棱大麦(Hordeum,distichum L.)甘木二条等7个品种进行半双列杂交,对1992年和1997年的亲本、F     

Changes in Variance Components of Flanking Marker Genotypes Under Varying Selection Intensities

Selection is practically ubiquitous during marker-QTL linkage analysis with an experimental population. Thus, it is necessary to investigate the impacts of selection upon linkage analyses in order to obtain unbiased estimates of QTL position and effect. In this article, by exploiting flanking markers through the widely applied half-sib design, we have developed the structures of three variance components, i.e., variance component between marker genotypes, polygenic variance component and recombinant variance component within marker genotypes. Changes in these variance components under varying selection intensities were investigated in this study to formulate the effects of selection on various variance components. Results showed clearly that all variance components presented were quite sensitive to changes in selection intensity. As selection intensity increased, all variance components declined by differing extents in a quadratic fashion. Comparatively speaking, the variance between marker genotypes decreased most drastically, followed by the polygenic variance within marker genotypes and then the recombinant variance within marker genotypes, which suggested a decrease of power for QTL linkage analysis. Therefore, steps should be taken to avoid as much as possible the presence of selection in real populations, so as to further eliminate the negative effects of selection on QTL linkage analysis.