Genotype × Environment Interacion in multi-environment Trials using shrinkage factors for ammi models

Shrinkage factors applied to the additive main effects and multiplicative interaction (AMMI) models improve prediction of cultivar responses in multi-environment trials (MET). Estimates of shrinkage factors based on the eigenvalue partition (EVP) method may get a further improvement in the predictions of cell means. Objectives of this work were: (1) to compare the EVP-based shrinkage method with unshrunken AMMI, best linear unbiased predictor (BLUP) and other shrunken method (herein named CCC), when they were applied to five maize MET and simulation data; (2) to assess by cross validation the equation which estimates the standard error of predicted means (SEPM) based on the EVP theory; (3) to estimate the genotype × environment interaction (GEI) variance components after applying the EVP shrinkage method to the five maize MET. Empirical data of five maize MET and simulation data were used for cross validation of the methods using the root mean square predictive difference (RMSPD) criterion. The RMSPD of the shrunken EVP predicted cell means was generally smaller than those of the other methods, suggesting that the EVP method was generally better predictor than the other methods. The truncated AMMI was the worst among the four methods studied. The EVP-based equation, which predicts the SEPM, was a good predictor as determined by the RMSPD cross validation criterion, with the advantage that it does not need one replication for validation. Estimates of mean squares, and GEI and error variances associated with the GEI effects were smaller for the shrunken EVP predicted effects than for the original data. This revised version was published online in July 2006 with corrections to the Cover Date.     

Genetic and statistical models for estimating genetic parameters of maize seedling resistance to Fusarium graminearum Schwabe root rot

Root lodging is an important problem in corn fields. Fungi recovered from roots include seedling blight and stalk rot pathogens. The objective of this work was to study the inheritance of maize seedling resistance to pathogens causing maize lodging. The Fusarium graminearum strain, 241 Fr1, was isolated from maize lodged plants and identified as the most pathogenic isolate for root rotting. Nine inbred lines of maize and their diallel F₁ crosses plus control genotypes were studied. Seedlings were inoculated at the stage of four-leaves. Disease severity was measured as percentage of the root rotted area. Highly significant differences between inoculated and non-inoculated genotypes were found. Four genetic models and two statistical approaches—the mixed model for the best linear unbiased prediction (BLUP) and the general linear model (GLM)—were used for the analysis. Favorable heterosis of resistance of hybrids over inbreds was the most important effect detected. The general combining ability (GCA) effects were significant for all genetic models and statistical methods studied, and a good agreement existed among the GCA estimates by the different methods. The type of gene action, either additive or dominance, showed a large variation among the parental inbreds and hybrids. Selection of additive effects based exclusively on inbred lines is not sufficient to confer resistance to hybrids, additional selection should be practiced on hybrids to look for favorable dominance effects. This revised version was published online in July 2006 with corrections to the Cover Date.     

Genomic selection in hybrid breeding

While hybrid breeding is widely applied in outbreeding species, for many self‐pollinating crop plants, it has only recently been established. This may have had its reason in the limitations of methods available for hybrid performance prediction, in particular when established heterotic pools were absent. Genomic selection has been suggested as a promising approach to resolve these limitations. In our review, we briefly introduce the principles of genomic selection as an extension of marker‐assisted selection using genome‐wide high‐density molecular marker data and discuss the advantages and limitations of currently used algorithms. Including the outcome from a recent extended approach to hybrid wheat as a timely example, we summarize current progress in empirical studies on the application of genomic selection for prediction of hybrid performance. Here, we put emphasis on the factors affecting the accuracy of prediction, pointing in particular to the relevance of relatedness, genotype x environment interaction and experimental design. Finally, we discuss future research needs and potential applications.     

基于Web的陕北白绒山羊辅助育种管理系统的设计与实现

针对陕北白绒山羊多性状选择育种研究处于起步阶段的现状,以动物模型BLUP法为核心的多性状复合育种技术体系为依托,在Windows XP平台下利用ASP技术和SQL Server 2000数据库开发了一套基于Web的陕北白绒山羊辅助育种管理系统-ABMS.该系统能实时地管理分布在不同地域种羊场的生产性能测定信息,并能方便地导入和导出选择性状的育种数据.ABMS在陕北白绒山羊种羊场实际应用中体现了技术先进、易于操作、网络化管理等特点,其推广和应用对实现种羊场育种工作和生产管理的自动化,具有极大的促进作用.     

林木育种值预测方法的应用与分析

育种值预测是遗传评价的核心。为了能恰当地选用适当方法估算林木育种值,本文概述了当前林木育种值预测的主要方法、原理及其在日本落叶松家系（亲本）及个体育种值预测和优良基因型选择中的应用。通过对各种预测方法应用结果的分析表明:对于平衡或近似平衡数据和无亲缘关系（或可忽略）的非平衡数据,最佳线性预测（BLP）、最佳线性无偏预测（BLUP）法均可以取得很高的预测精度,但考虑到计算的简便性,BLP法更为适用;对于有亲缘关系或具有不同遗传固定效应的候选材料,BLUP法更为适用;对于多性状联合选择,选择指数仍是理想的方法。最后对育种值预测方法的适用情况及存在问题进行了讨论。      

Potential of genomic selection in rapeseed (Brassica napus L.) breeding

Genomic selection employs genome‐wide marker data to predict genomic breeding values. In this study, a population consisting of 391 lines of elite winter oilseed rape derived from nine families was used to evaluate the prospects of genomic selection in rapeseed breeding. All lines have been phenotyped for six morphological, quality‐ and yield‐related traits and genotyped with genome‐wide SNP markers. We used ridge regression best linear unbiased prediction in combination with cross‐validation and obtained medium to high prediction accuracies for the studied traits. Our results illustrate that among‐family variance contributes to the prediction accuracy and can lead to an overestimation of the prospects of genomic selection within single segregating families. We also tested a scenario where estimation of effects was carried out without individuals from the family in which breeding values were predicted, which yielded lower but nevertheless attractive prediction accuracies. Taken together, our results suggest that genomic selection can be a valuable genomic approach for complex agronomic traits towards a knowledge‐based breeding in rapeseed.     

Identification of main effect and epistatic QTLs controlling initial flowering date in cultivated peanut(Arachis hypogaea L.)

Initial flowering date(IFD) is closely related to mature period of peanut pods. In present study, a population of recombinant inbred lines(RIL) derived from the cross between Silihong(female parent) and Jinonghei 3(male parent) was used to map QTLs associated with IFD. The RIL population and its two parental cultivars were planted in two locations of Hebei Province, China from 2015 to 2018(eight environments). Based on a high-density genetic linkage map(including 2 996 SNP and 330 SSR markers) previously constructed in our laboratory, QTLs were analyzed using phenotypic data and the best linear unbiased prediction(BLUP) value of initial flowering date by inclusive composite interval mapping(ICIM) method. Interaction effects between every two QTLs and between individual QTL and environment were also analyzed. In cultivated peanut, IFD was affected by genotypic factor and environments simultaneously, and its broad sense heritability(h2) was estimated as 86.8%. Using the IFD phenotypic data from the eight environments, a total of 19 QTLs for IFD were detected, and the phenotypic variation explained(PVE) by each QTL ranged from 1.15 to 21.82%. Especially, five of them were also detected by the BLUP value of IFD. In addition, 12 additive QTLs and 35 pairs of epistatic QTLs(62 loci involved) were identified by the joint analysis of IFD across eight environments. Three QTLs(qIFDB04.1, qIFDB07.1 and qIFDB08.1) located on chromosome B04, B07 and B08 were identified as main-effect QTL for IFD, which had the most potential to be used in peanut breeding. This study would be helpful for the early-maturity and adaptability breeding in cultivated peanut.     

民猪产仔数性状四个候选基因效应分析

为了更全面地探讨民猪高繁殖力的遗传基础,以期为民猪的分子标记保种提供依据,选择ESR、FSHβ、PRLR和EGF等四个基因作为民猪产仔数的候选基因,采用PCR-SSCP法进行了各基因多态性检测,利用系谱、标记信息与表型值记录,建立线性混合模型,对各基因位点对民猪产仔数的影响进行了BLUP分析。结果表明:①四个基因位点在民猪保种群体中均存在多态性,但与Hardy-Weinberg平衡状态下的基因型频率相比较发现,只有ESR基因的基因型分布差异不显著(P>0.05),说明四个基因的基因型频率在民猪保种群中大多处于不稳定状态。②在忽略基因位点间互作的条件下,各基因位点均与民猪产仔数无显著相关(P>0.05),即各基因位点的效应均不显著。     

基于BLUP和GBLUP方法估计北京油鸡胴体和肉质性状遗传参数的差异

旨在比较不同方法对遗传参数估计的差异,为未来北京油鸡胴体和肉质性状选育方法的制定提供参考依据。本研究利用传统最佳线性无偏预测（best linear unbiased prediction,BLUP）和基因组最佳线性无偏预测（genomic best linear unbiased prediction,GBLUP）两种方法对北京油鸡的胴体和肉质等性状进行了遗传参数估计。从系谱较为完整的北京油鸡群体中,选择100日龄体重相近的公鸡615只,测定其100日龄体重（BW）、屠宰率（EP）、胸肌率（BMP）、腿肌率（LMP）、腹脂率（AFP）、嫩度（T,以剪切力值表示）和肌内脂肪（IMF）等性状,并用SNP芯片（Illumina,60K）进行个体基因分型。结果表明,除IMF和剪切力（SF）遗传力基于两种方法的估值存在较大差异外,其余性状利用两种方法得到的遗传力估值差异较小;除嫩度外,GBLUP方法估计的遗传力均低于BLUP方法。所有胴体相关性状中,除屠宰率遗传力为低遗传力外,其余性状均属于中等遗传力性状。嫩度呈现低遗传力,而IMF基于BLUP法和GBLUP法的估计遗传力分别为中等（h² =0.256）和低遗传力（h² =0.107）。基于BLUP方法,IMF与BW、BMP和SF 3个性状间均呈高度遗传负相关（-0.572、-0.420、-0.682）,与EP的遗传相关为中度负相关（-0.234）,与AFP的遗传相关为中度正相关（0.420）;基于GBLUP方法,IMF与BW、BMP和SF 3个性状间均呈高度遗传负相关（-0.808、-0.725、-0.784）,与EP的遗传相关为高度负相关（-0.626）,与AFP的遗传相关为低度正相关（0.097）。综上,对于某些性状,基于传统的BLUP方法与新的GBLUP方法得到的遗传力与遗传相关估值存在较大差异,实际育种工作中,为提高育种效率,需要综合考虑。     

混合模型方程组求解的一种快速算法

本文介绍了改进的CHOLESKY分解的原理与优点及其在混合模型方程组求解中的应用,讨论了混合模型方程组约束条件对本方法的影响,以及分子亲缘关系矩阵求逆的一种算法,利用这些算法算出了包头黄河奶牛埸十九头种公牛的育种值。最后根据上述算式给出了正定对称方程组求解和正定对称矩阵求逆的BASIC程序。