性状遗传力与QTL方差对标记辅助选择效果的影响

在采用动物模型标记辅助最佳线性无偏预测方法对个体育种值进行估计的基础上,模拟了在一个闭锁群体内连续对单个性状选择10个世代的情形,并系统地比较了性状遗传力和QTL方差对标记辅助选择所获得的遗传进展、QTL增效基因频率和群体近交系数变化的影响。结果表明：在对高遗传力和QTL方差较小的性状实施标记辅助选择时,可望获得更大的遗传进展;遗传力越高,QTL方差越大,则QTL增效基因频率的上升速度越快;遗传力较高时,群体近交系数上升的速度较为缓慢,而QTL方差对群体近交系数上升速度的影响则不甚明显。结合前人关于标记辅助选择相对效率的研究结果,可以认为：当选择性状的遗传力和QTL方差为中等水平时,标记辅助选择可望获得理想的效果。     

结合MOET技术的奶牛标记辅助选择方案比较

应用计算机模拟的方法比较利用遗传标记信息和/或超数排卵和胚胎移植(MOET)技术的一系列奶牛育种方案相对于传统育种方案的优越性. 模拟性状为产奶量, QTL作为已知遗传标记. 8个奶牛育种方案分别是：传统的后裔测定方案用STANPT表示; GASPT方案在青年公牛进入后裔测定前通过其自身QTL基因型进行预选择; MOETPT方案应用MOET技术产生青年公牛, 青年公牛预选择为家系内全同胞随机选择; GAMOPT方案结合了QTL预选择及MOET技术; COMBPT方案在GAMOPT方案基础上, 在个体育种值的评估中加入了QTL基因型效应; 另外对应后裔测定体系中MOETPT,GAMOPT,COMBPT方案设计了3个非后裔测定方案, 分别命名为MOET方案、GAMO方案及COMB方案. 动物个体通过相对应的动物模型进行育种值评估, 模拟针对产奶性状进行重叠世代连续17年的选择. 针对现役公牛、泌乳母牛、公牛母亲、公牛父亲和青年公牛5个不同群体, 对应用QTL信息和MOET技术对有利QTL基因频率、真实育种值、多基因值和累积遗传进展优势率产生的影响进行评估. 结果表明, 结合QTL信息和MOET技术的方案, 其真实育种值遗传进展显著高于其他方案, 仅应用QTL信息或MOET技术的单一改进方案间差异不显著, STANPT方案效率最低. 应用MOET技术的方案在第17年获得的多基因选择反应更大. 不同育种方案有利QTL基因频率增加速度在3个公畜群体中差异远大于泌乳母牛群体. GASPT,MOETPT,GAMOPT,COMBPT,MOET,GAMO 和COMB 方案相对STANPT方案, 累积遗传进展优势率在现役公牛群体中分别为8.42%, 3.59%, 14.58%, 18.54%, 4.12%, 14.12%和16.50%, 在泌乳母牛群体中分别为2.70%, 5.00%, 11.05%, 12.78%, 7.51%, 17.12%和25.38%.     

世代重叠群体多个QTL最优化选择

一种扩展的方法能够在一个世代重叠的群体内对多个数量性状位点选择进行最优化,目的是为了在整个计划期内获得最大的累积反应加权和。该模型允许群体有多个性别年龄组、公母畜间有不同的年龄组数、各年龄组有不同的遗传贡献。整个最优化问题被描述成一个多阶段系统优化控制问题,通过一个向前和向后的迭代循环解决。用一个世代重叠的实际育种猪群的参数来评价该方法的选择效果,并和标准QTL选择和常规BLUP选择进行比较。模拟结果表明,优化选择要优于标准QTL选择和常规BLUP选择。群体结构对优化选择的影响比较明显。优化QTL选择和标准QTL选择在世代重叠的群体内比在世代离散的群体内的选择优势更明显,相对于常规BLUP选择,能够获得更大的选择优势。在世代重叠群体内随着2岁公畜遗传贡献的增大,优化选择相对于常规BLUP选择的优势越明显。     

标记辅助导入中不同前景和背景选择方法的比较

标记辅助导入是分子遗传信息应用于动物育种的一个重要方面,其目的是在标记信息的辅助下将一个品种（供体）中的一个或多个优良基因导入另一个品种（受体）,同时还要尽可能地保持受体群体原有的遗传背景。标记辅助导入的过程包括3个阶段,第一阶段是杂交,即供体与受体杂交产生F1代个体,第二阶段是回交,即F1个体以及后续各个世代的后代个体重复地与受体回交,以使受体的遗传背景得到恢复,第三阶段是横交,即重复回交后得到的个体彼此问交配,以便获得供体基因的纯合个体,使该基因在群体中固定。在回交和横交阶段,都要对参与交配的个体进行选择。在选择中,要分别进行前景选择和背景选择,前景选择是对供体基因的选择,选择携带有供体基因个体参加配种,从而使该基因在回交过程中不会丢失,并在横交过程中能尽快固定,背景选择是对受体遗传背景的选择,选择那些含有受体基因组比例较高的个体参加配种,从而加快恢复受体遗传背景的速度。本研究通过计算机模拟对不同的前景选择方法和不同的背景选择方法进行了比较。前景选择方法包括对受体基因的直接选择（假设该基冈可以直接测定）、利用单个连锁标记的间接选择和利用两侧标记的间接选择3种,背景选择方法包括随机选择、基因组相似性选择、指数选择和标记辅助BLUP（MBLUP）选择4种。研究结果表明,对于前景选择来说,对供体基因的直接选择能保证该基因在回交的各个世代中保持一个稳定的频率（0．25）并在横交阶段迅速固定（2个世代）,用两侧标记的间接选择也能得到类似的结果,但如果仅利用单个连锁标记进行选择,则会导致供体基因的频率在回交阶段中有所下降,并在横交阶段不能被固定。对于背景选择来说,如果最终的目的是要完全恢复受体的遗传背景,基因组相似性选择或标记指数选择是最好的选择方法,它们可使受体的遗传背景在回交3个世代后就恢复到98％以上,而随机选择或MBLUP选择需要至少5个世代的回交才能达到这个水平。但如果最终的目的只是要恢复受体的某些优良性状,则MBLUP选择是值得推荐的方法,它可使影响这些性状的受体基因频率在回交3个世代后就达到99％以上,而且还能在整个基因导入过程中给这些性状带来最大的遗传进展。虽然用标记指数选择也有相似的结果,但与之相比,MBLUP的成本要低得多,更具有实际可行性。     

杂交群体动物基因聚合

基因聚合是通过优化设计杂交方案,选择利用目标基因或与其紧密连锁的分子标记,通过世代选择实现将来源于多个不同群体的优势目标基因或基因型聚合到同一个理想个体中,进而达到生产出超级经济性状个体的目的。针对聚合不同目标基因个数,设计4类杂交方案——两群体、三群体、四群体级联、四群体对称。在相同的杂交方案中,比较基因型选择和表型选择策略,分析不同杂交组合、性状遗传力、初始基因频率、基础群体规模对聚合设计的影响,并筛选出最佳的聚合方案。研究结果表明,在较大的基础群体规模和较高初始群体基因频率下,获得聚合多个目标基因的理想个体的可能性较大。在四群体杂交方案中,亲本的杂交次序对于级联杂交比对称杂交的影响较大。模拟结果表明,运用基因型选择进行聚合育种优于表型选择。文章所开发设计的聚合模拟育种的统计分析方法和相应软件为指导杂交育种方案和选择策略的设计提供理论参考,同时,为进一步设计开发聚合设计模拟育种平台奠定基础。     

棉花数量性状基因定位研究进展

棉花的许多重要性状,包括产量、纤维品质、株型、抗病抗逆性、生理生化等都是数量性状,受遗传和环境因子的共同作用。近年来,随着分子生物学技术的进步,棉花基因组研究得到迅速发展,为棉花数量性状基因（quantitative trait locus,QTL）定位奠定了坚实的基础。概述了近十几年来棉花QTL定位研究及分子标记辅助选择的进展,结合研究实践指出了棉花QTL定位及标记辅助选择存在的问题,并对其发展方向做出了初步探讨。     

使用哈迪-温伯格不平衡检验对QTL进行关联分析(英文)

多位点单体型的可用性对于数量性状位点(QTL)的遗传分析提供了有价值的工具。QTL定位可以通过检测极端群体中一个标记位点的哈迪-温伯格不平衡(HWD)来实现.本文拓展了HWD检验到多个标记位点,通过选择基因型对QTL进行单体型关联分析.我们用分析方法调查了不同遗传率,不同样本大小和不同样本选择阈值对HWD检验的统计功效影响.结果表明HWD检验具有高的功效.一个基于血管紧张素转换酶(ACE)基因的10个SNPs单体型频率的模拟研究用来评估HWD检验的性质.     

人类混血群体连锁不平衡的遗传学模型与基因定位

人类混血群体可以说是混合群体的一种特例．在无选择、无突变、无限随机交配群体的假定前提下,研究了亲本群体的基因频率对混血群体及其衍生后代群体连锁不平衡结构的影响,导出了各群体连锁不平衡值的表达式,建立了一个估计基因间重组率的简便方法;同时, 采用估算分子标记与QTL之间连锁不平衡系数的统计分析方法,分析了人类混血群体及其衍生后代群体QTL检测与估计的关系,建立了该关系的系列理论公式．研究结果表明,本方法不仅适用于人类疾病(包括复杂遗传疾病)基因定位,而且适合于人类正常基因的定位,同时也适用于人类普通多基因性状的QTL分析．     

基于分离亚群体QTL定位的模拟研究

在数量性状QTL的精细定位中, 通过数量性状目标QTL的近等基因系可构建分离群体。在目标QTL效应较大的情况下, 数量性状表型值可反映目标QTL的基因型。若目标QTL附近的标记密度大时, 大样本才能定位该QTL。但是, 这增加了试验费用。为节约试验经费, 若只利用QTL纯合隐性基因型植株的分子标记信息, 也可比较准确地定位该QTL。利用极大似然法, 分别推导出F2、BC、DH以及RIL群体中重组率及其标准误的估计公式。Monte Carlo模拟研究表明, 基于定位群体中全部数据或隐性纯合基因型数据所获得的重组率估计值是一致的, 且在相同样本容量条件下, 二者精度相当。     

侧翼标记基因型方差组分随不同选择强度的变化

从实际角度看,选择在用于标记-QTL连锁分析的实验群体中是较普遍存在的。为获得QTL位置及其效应的无偏估计,有必要研究选择对连锁分析实验所造成的影响。该文在侧翼标记情况下利用广泛使用的半同胞设计提出了3种方差组分,即标记组间方差、组内多基因方差和组内重组方差及其构成。着重从理论上研究了各方差组分在不同选择强度下的变化规律,阐明了选择对各方差组分的效应。结果表明,各方差组分对选择强度的变化很敏感。随着选择强度的增加,所有方差组分都以二次曲线方式有不同程度的下降。比较而言,标记组间方差组分下降最快,标记组内多基因方差下降较慢,组内重组方差下降最慢。这意味着QTL连锁分析功效的降低。所以在实际群体中应采取必要措施尽量避免选择的发生,从而消除选择对QTL连锁分析的负面效应。     

Within-family marker-assisted selection for aquaculture species

A within-family marker-assisted selection scheme was designed for typical aquaculture breeding schemes, where most traits are recorded on sibs of the candidates. Here, sibs of candidates were tested for the trait and genotyped to establish genetic marker effects on the trait. BLUP breeding values were calculated, including information of the markers (MAS) or not (NONMAS). These breeding values were identical for all family members in the NONMAS schemes, but differed between family members in the MAS schemes, making within-family selection possible. MAS had up to twice the total genetic gain of the corresponding NONMAS scheme. MAS was somewhat less effective when heritability increased from 0.06 to 0.12 or when the frequency of the positive allele was < 0.5. The relative efficiency of MAS was higher for schemes with more candidates, because of larger fullsib family sizes. MAS was also more efficient when male:female mating ratio changed from 1:1 to 1:5 or when the QTL explained more of the total genetic variation. Four instead of two markers linked to the QTL increased genetic gain somewhat. There was no significant difference in polygenic genetic gain between MAS and NONMAS for most schemes. The rates of inbreeding were lower for MAS than NON-MAS schemes, because fewer full-sibs were selected by MAS.     

Optimization of a crossing system using mate selection

A simple model based on one single identified quantitative trait locus (QTL) in a two-way crossing system was used to demonstrate the power of mate selection algorithms as a natural means of opportunistic line development for optimization of crossbreeding programs over multiple generations. Mate selection automatically invokes divergent selection in two parental lines for an over-dominant QTL and increased frequency of the favorable allele toward fixation in the sire-line for a fully-dominant QTL. It was concluded that an optimal strategy of line development could be found by mate selection algorithms for a given set of parameters such as genetic model of QTL, breeding objective and initial frequency of the favorable allele in the base populations, etc. The same framework could be used in other scenarios, such as programs involving crossing to exploit breed effects and heterosis. In contrast to classical index selection, this approach to mate selection can optimize long-term responses.     

Verification of yield QTL through realized molecular marker- assisted selection responses in a barley cross

Verification of putative quantitative trait loci (QTL) is an essential step towards implementing the use of marker-assisted selection (MAS) in cultivar improvement. In a previous study with 150 doubled haploid lines derived from the 6-row cross Steptoe/Morex (S/M), four regions (QTL1–4) of the barley genome were associated with differential genotypic expression for grain yield across environments. The objectives of this study were to verify the value of these four QTL for selection and to compare the efficiency of alternative MAS strategies using these QTL vs. conventional phenotypic selection for grain yield. A total of 92 DHLs derived from the S/M cross that were not used in the original mapping efforts were used for QTL verification. Confirmation of QTL effects was first accomplished by assessing yield differences between individuals carrying alternative alleles at each putative locus in three environments. QTL1 on chromosome 3 was confirmed as the most important and consistent locus to determine yield across sites, with the S allele being favorable. The M allele at QTL3 on chromosome 6 was beneficial for grain yield across sites, but to a lesser degree than QTL1. Magnitudes of allele effects at QTL2 (chromosome 2) and QTL4 (chromosome 7) were highly influenced by the environment where the genotypes were grown. Verification of QTL effects was best achieved by comparing realized selection response. Genotypic (MAS) and tandem genotypic and phenotypic selection were at least as good as phenotypic selection. Consistent selection responses were detected for QTL1 alone and together with QTL3. Genotypic selection for lines carrying the S allele at QTL1 resulted in the identification of high-yielding genotypes. Selection responses increased when the M allele at QTL3 was combined with the S allele at QTL1. Significant qualitative QTL × environment interactions for QTL2 and QTL4 were detected through differential realized selection responses at different sites. Without a thorough understanding of the physiological and agronomic particulars of any QTL and the target environment, MAS for QTL showing qualitative interactions should be minimized This revised version was published online in June 2006 with corrections to the Cover Date.     

A method for marker-assisted selection based on QTLs with epistatic effects

A method for marker-assisted selection (MAS) based on quantitative trait loci (QTLs) with epistatic effects is proposed. The efficiency of such method is investigated by simulations under a wide range of situations. In the presence of epistasis, MAS generally yields longer persistence response than that based exclusively on additive or additive and dominance. Neglecting epistasis could result in considerable loss in response, and more pronounced at later generations. In addition to population size and trait heritability, genetic variance configurations play an important role in determining both the short- and long-term efficiencies of MAS. MAS using breeding values not only achieves higher response, but also tends to have smaller standard error than other methods in most cases. Errors in QTL detection cause distinct reductions in responses to MAS in most cases. It is thus concluded that verifications of putative QTL and its magnitude of effect and accurate map chromosome location are imperative to realize the potentials of MAS.     

QTL×环境互作对标记辅助选择响应的影响

基因型×环境互作是植物数量性状的普通属性和遗传育种改良的关注重点.采用Monte Carlo模拟方法研究了基因型×环境互作对标记辅助选择(Marker-assisted selection,简称MAS)响应的影响,揭示了育种上利用QTL(Quantitafivetrait locus,简称QTL)应当同时考虑其环境互作效应.存在基因型×环境互作下,MAS比普通表型选择更有效.特别以选育广适应性的品种为目标,MAS的优越性更明显.基于单个环境QTLs的MAS,QTL×环境互作效应通常降低了一般选择响应,一般选择响应累积量的降低程度与改良性状的QTL×环境互作效应大小相关.基于多个环境QTLs的MAS,不但产生较高的一般选择响应,而且获得的一般选择响应不受其QTL×环境互作效应大小的影响.但在某一特定环境下获得的总体选择响应仅与改良性状的总遗传率大小有关,普通遗传率和基因型与环境互作遗传率的相对变化对其影响很小.还比较研究了单地和穿梭选择对MAS遗传响应的影响.植物育种者应谨慎将某一环境的QTL信息用于实施另一环境的育种研究.     

Marker assisted selection for the improvement of two antagonistic traits under mixed inheritance

A Monte Carlo simulation was used to investigate the potential of Marker Assisted Selection (MAS) in a multiple-trait situation. Only additive effects were considered. The base population was assumed to be in linkage equilibrium and, next, the population was managed over 15 discrete generations, 10 males and 50 females were chosen out of the 100 candidates of each sex. Performance for two traits was simulated with an overall heritability of a given trait equal to 0.25 or 0.10 and the overall genetic correlation between traits was generally equal to -0.4 except in one case where it was equal to 0. The model involved one biallelic QTL, accounting for 10 or 20% of the genetic variance of a given trait, plus polygenes. Initial allelic frequencies at the QTL were generally equal to 0.5 but in one case were equal to 0.1 and 0.9. A marker with 120 different alleles in the 60 founder parents was simulated in the vicinity of the QTL. Two values of the recombination rate between these two loci were considered, 0.10 and 0.02. The genetic evaluation was based on a multiple-trait BLUP animal model, accounting (MAS) or not (conventional BLUP) for marker information. Two sets of simulations were run: (1) a "missing data"case, with males having no record for one of the traits, and (2) a "secondary trait"case, with one trait having a weight in the aggregate genotype 4 times less than the other trait and the QTL acting only on this secondary trait. In the first set, evaluation methods were found to mainly affect the accuracy of overall genetic values prediction for the trait with missing data. In comparison with BLUP, MAS led to an extra overall genetic response for the trait with missing data, which was strongly penalised under the conventional BLUP, and to a deficit in response for the other trait. This more balanced evolution of the two traits was obtained, however, at the expense of the long-term overall cumulated response for the aggregate genotype, which was 1 to 2.5% lower than the one obtained under the conventional BLUP. In the second set of simulation, in the case of low initial frequency (0.1) of the QTL allele favourable to the secondary trait, MAS was found to be substantially more efficient to avoid losing this allele than BLUP only when the QTL had a large effect and the marker was close. More benefits should be expected from MAS with more specific applications, such as early selection of animals, or by applying dynamic procedures i.e. letting the respective weights to QTL and polygenic values in the selection criterion vary across generation.     

Impacts of QTL × Environment Interactions on Genetic Response to Marker-Assisted Selection

Genotype × environment (GE) interaction is a common characteristic for quantitative traits, and has been a subject of great concern for breeding programs. Simulation studies were conducted to investigate the effects of GE interaction on genetic response to marker-assisted selection (MAS). In our study we demonstrated that MAS is generally more efficient than phenotypic selection in the presence of GE interaction, and this trend is more pronounced for developing broadly adaptable varieties. The utilization of different QTL information dramatically influences MAS efficiency. When MAS is based on QTLs evaluated in a single environment, the causal QTL × environment (QE) interactions usually reduce general response across environments, and the reduction in the cumulative general response is a function of the proportion of QE interactions for the trait studied. However, MAS using QTL information evaluated in multiple environments not only yields higher general response, but the general response obtained is also reasonably robust to QE interactions. The total response achieved by MAS in a specific environment depends largely on the total heritability of traits and is slightly subject to relative changes between general heritability and GE interaction heritability. Two breeding strategies, breeding experiments conducted in one environment throughout and in two environments alternately, were also examined for the implementation of marker-based selection. It was thus concluded that plant breeders should be cautious to utilize QTL information from only one environment and execute breeding studies in another.     

Simultaneous selection of major and minor genes: use of QTL to increase selection efficiency of coleoptile length of wheat (Triticum aestivum L.)

Plant breeders simultaneously select for qualitative traits controlled by one or a small number of major genes, as well as for polygenic traits controlled by multiple genes that may be detected as quantitative trait loci (QTL). In this study, we applied computer simulation to investigate simultaneous selection for alleles at both major and minor gene (as QTL) loci in breeding populations of two wheat parental lines, HM14BS and Sunstate. Loci targeted for selection included six major genes affecting plant height, disease resistance, and grain quality, plus 6 known and 11 “unidentified” QTL affecting coleoptile length (CL). Parental line HM14BS contributed the target alleles at two of the major gene loci, while parental line Sunstate contributed target alleles at four loci. The parents have similar plant height, but HM14BS has a longer coleoptile, a desirable attribute for deep sowing in rainfed environments. Including the wild-type allele at the major reduced-height locus Rht-D1, HM14BS was assumed to have 13 QTL for increased CL, and Sunstate four; these assumptions being derived from mapping studies and empirical data from an actual HM14BS/Sunstate population. Simulation indicated that compared to backcross populations, a single biparental F₁ cross produced the highest frequency of target genotypes (six desired alleles at major genes plus desired QTL alleles for long CL). From 1,000 simulation runs, an average of 2.4 individuals with the target genotype were present in unselected F₁-derived doubled haploid (DH) or recombinant inbred line (RIL) populations of size 200. A selection scheme for the six major genes increased the number of target individuals to 19.1, and additional marker-assisted selection (MAS) for CL increased the number to 23.0. Phenotypic selection (PS) of CL outperformed MAS in this study due to the high heritability of CL, incompletely linked markers for known QTL, and the existence of unidentified QTL. However, a selection scheme combining MAS and PS was equally as efficient as PS and would result in net savings in production and time to delivery of long coleoptile wheats containing the six favorable alleles.     

Phenotypic versus marker-assisted selection for stalk strength and second-generation European corn borer resistance in maize

Maize (Zea mays L.) stalk lodging is breakage of the stalk at or below the ear, which may result in loss of the ear at harvest. Stalk lodging is often intensified by the stalk tunneling action of the second-generation of the European corn borer (2-ECB) [Ostrinia nubilalis (Hübner)]. Rind penetrometer resistance (RPR) has been used to measure stalk strength and improve stalk lodging resistance, and quantitative trait loci (QTL) have been identified for both RPR and 2-ECB damage. Phenotypic recurrent selection (PS) increases the frequency of favorable alleles over cycles of selection. Several studies have indicated that marker-assisted selection (MAS) is also a potentially valuable selection tool. The objective of this study was to compare the efficiency of PS versus MAS for RPR and 2-ECB. Marker-assisted selection for high and low RPR was effective in the three populations studied. Phenotypic selection for both high and low RPR was more effective than MAS in two of the populations. However, in a third population, MAS for high RPR using QTL effects from the same population was more effective than PS, and using QTL effects from a separate population was just as effective as PS. Marker-assisted selection for resistance and susceptibility to 2-ECB using QTL effects from the same population was effective in increasing susceptibility, but not in increasing resistance. Marker-assisted selection using QTL effects from a separate population was effective in both directions of selection. Thus, MAS was effective in selecting for both resistance and susceptibility to 2-ECB. These results demonstrated that MAS can be an effective selection tool for both RPR and 2-ECB resistance. These results also validate the locations and effects of QTL for RPR and 2-ECB resistance identified in earlier studies.Communicated by D. Hoisington