二探中国美利奴柯尔沁型细毛羊的选择指数

从中国美利奴柯尔沁型细毛羊毛密品系选育的需要出发,本文在现有育种参数和无约束指数的基 础上,进一步发展了约束指数和最宜指数;估计了各类指数选择下遗传改进的理论值;讨论了在包括净 毛量、剪毛后体重、配种受胎率和体侧毛长等性状的遗传型集合中,采用各类指数间接选择毛密度的可 能性。     

宁夏滩羊主要经济性状的遗传力

宁夏滩羊是我国珍贵的裘皮羊品种之一,所产二毛皮和羔皮的花穗清晰美观,轻柔保暖,结实耐用,深受我国各族劳动人民的喜爱。在国际贸易中也是独具风格的畅销产品。滩羊的主要经济性状多为数量性状,但有关滩羊性状的遗传参数过去没有研究报道。为了不断改进选种方法,提高滩羊二毛裘皮的品质,于1976、1977两年间,在盐池滩羊场和贺兰县暖泉农场,应用半同胞组内相关方法,对29头种公羊的1,455头羔羊的初生与二毛期主要经济性状进行了计算分析,求得初生体重、初生肩部自然毛长、初生肩部毛弯曲     

红花单株花产量选择指数的研究

本试验用9个栽培红花品种为材料,进行单株花产量选择指数的研究。结果表明,通过分枝高或株 高两性状进行相关选择可有效提高单株花产量。分枝高、单株有效果球数、开花期是决定单株花产量选 择效果的3个关键性状,综合选择时必须加以考虑。无效分枝数亦是影响单株花产量的重要因素之一, 选择时应予重视。用株高、分枝高、单株粒数、单株有效果球数、开花期、无效分枝数6个性伏组成的选 择指数对单株花产量进行选择的效果最好。用该选择指数对9个参试品种评审结果表明,张掖无刺为 最佳花用型品种,B-54为最差的低产花用品种。     

长期指数选择的遗传效果分析—计算机模拟研究

本文利用Monte Carlo模拟技术研究比较了普通选择指数、实际选择指数、约束指数和单性状选择四种方法的长期选择效果及对群体遗传结构的影响。50世代的结果表明:群体大小和遗传参数能明显影响长期指数选择的反应;实际指数选择是有效的,其总体效果好于普通指数;约束选择的早期反应虽低于普通指数,但后期效果好,而且对群体遗传结构影响较小。同时,指数选择使性状加性遗传方差和遗传力衰减变化,而遗传相关依指数公式的系数呈定向改变。建议多性状长期选择时应用实际指数法或约束指数法。     

微卫星标记OarAE101和BM1329承五个绵羊品种中的初步研究

选择与Booroola羊高繁殖力主效基因FecB紧密连锁的两个微卫星标记OarAE101和BM1329,分析其在小尾寒羊、湖羊、夏洛来羊、乌珠穆沁羊、多赛特羊和多赛特公羊×小尾寒羊母羊杂一代中的多态分布情况.结果表明微卫星标记OarAE101在5个绵羊品种中的等位基因数为5或4,BM1329在5个绵羊品种中的等位基因数均为4,OarAE101/BM1329在小尾寒羊、湖羊、夏洛来羊、乌珠穆沁羊、多赛特羊和多赛特公羊×小尾寒羊母羊杂一代中的多态信息含量值分别为0.57/0.54、0.62/0.67、0.61/0.59、0.62/0.66、0.56/0.67和0.62/0.68.小尾寒羊OarAE101基因型为107bp/113bp所对应的产羔数最小二乘平均值显著高于基因型为109bp/109bp和107bp/111bp所对应的最小二乘平均值(P＜0.05),产羔数最小二乘平均值在OarAE101其余基因型之间没有显著差异;OarAE101等位基因107bp与小尾寒羊产羔数有显著正相关,109bp和111bp与小尾寒羊产羔数有显著负相关.小尾寒羊BM1329基因型为146bp/158bp所对应的产羔数最小二乘平均值都显著高于其余3种基因型所对应的最小二乘平均值(P＜0.05),产羔数最小二乘平均值在BM1329其余3种基因型之间没有显著差异;BM1329等位基因146bp与小尾寒羊产羔数有显著正相关,148bp与小尾寒羊产羔数有显著负相关.     

家畜多个显性性状半同胞家系选择的育种进展分析

本文提出了固定家畜多个不相连锁显性性状的半同胞家系选择体制,并从群体基因型频率、配子频率及表型频率等方面分析了该体制的育种进展．研究证明,半同胞家系选择效果取决于每头公畜交配母畜数K、母畜产仔数N及群体育种水平;K、N越大,群体育种水平越低,选择效果越好．当K=1时,半同胞家系选择就退化成全同胞家系选择;当K=1且N=1时,退化成“理想型横交固定”;当K较大且群体育种水平较低时半同胞家系选择效果与“多元测交”相当．最后讨论了半同胞家系选择在家畜育种实践中的应用问题.     

雌性根田鼠的亲属识别与配偶选择

在Y字型选择箱中进行3种不同熟悉处理的配偶选择实验以检验动情雌性根田鼠配偶选择时的亲属识别和近交回避。（1）动情雌鼠在熟悉雄性同胞和陌生非同胞之间嗅添频次和时间、及自我修饰时间的差异非常显著（P＜0.01),所作的脊柱前凸反应时间也有显著差异（P＜0.05),这些行为均多针对于陌生非同胞雄性。结果提示动情雌性根田鼠在熟知雄性同胞身份的条件下对陌生非亲属雄性的气味更感兴趣,在择偶中与非亲属雄性交配来实现近交回避。（2）动情雌鼠对陌生雄性非同胞的嗅添频次和时间及所作的脊柱前凸反应时间显著大于陌生同胞雄性（P＜0.05),而针对陌生雄性非同胞自我修饰时间非常显著地大于针对陌生雄性同胞（P＜0.01)。这说明动情雌性根田鼠在择偶时可以识别断奶后分离不熟悉的雄性亲属,而在交配行为上偏向于非亲属雄性。（3）动情雌鼠在熟悉雄性同胞和非同胞之间跃添时间差异明显（P＜0.05),嗅添频次的差异更甚（P＜0.01);所作的脊柱前凸反应时间和社交后自我修饰时间差异也非常显著（P＜0.01),这些行为也均都偏向于非同胞雄性;结果提示断奶后继续熟悉可维持动情雌鼠对雄性亲属的嗅觉识别记忆力,在交配行为上主动回避亲属雄性。故认为：断奶后嗅觉识别持久力是发情雌性根田鼠亲属识别的机制,亲属识别是最初发情的雌性根田鼠配偶选择中近交回避的首要途径和机制,熟悉性是维持雌性根田鼠配偶选择实现近交回避的机制和特征。     

夏谷主要性状遗传力、遗传相关和选择指数的初步研究

夏谷性状的遗传力以码数为最高,株高和千粒重次之,以单株产量和株穗重最低,而小区产量的遗传力(集团群体的诸性状的综合表现)却更高。因此在选种上采用产量对比选拔高产优系要比选择高产单株的效果为好。遗传相关可以排除环境的干扰,做为选择的依据决定取舍较为可靠。可以从选择遗传力最高的性状入手,间接地选择出遗传力较低的主要经济性状。选择指数公式中的权数,因性状组合的不同而异,据此产生的选择效果也不同,应该选用比直接选择具有更高效率的选择指数,以判别选择对象的优劣。     

绵羊ESR2基因组织表达及其多态性与产羔数关联分析

为了探究雌激素受体2 (Estrogen receptor 2, ESR2)基因在绵羊各组织的表达及其多态性与产羔数之间的关系,本研究利用半定量PCR和实时荧光定量PCR技术检测ESR2基因在不同繁殖力小尾寒羊群体组织中的相对表达量,同时采用Sequenom MassARRAY誖SNP技术对多羔品种绵羊(小尾寒羊,湖羊,策勒黑羊)和单羔品种绵羊(苏尼特羊,草原型藏羊,滩羊) ESR2基因g.73324006C>T位点进行检测,并与小尾寒羊产羔数进行关联分析。半定量PCR表明,ESR2基因在单、多羔小尾寒羊子宫中高表达,在其它组织中等或低丰度表达;单羔群体、多羔群体间荧光定量PCR表明,ESR2基因在单羔小尾寒羊垂体表达量显著高于多羔小尾寒羊(p<0.05);群体遗传学分析表明,g.73324006C>T在小尾寒羊群体中表现为低度多态(PIC<0.25),在滩羊群体中处于中度多态(0.25T在小尾寒羊群体处于哈代温伯格平衡状态(p>0.05);关联分析表明,g.73324006C>T位点多态性与小尾寒羊第一胎、第二胎、第三胎产羔数及平均产羔数均显著关联(p<0.05),CC型各胎产羔数均高于TC型。与FecB (A746G)基因组合后发现,GG-CC和AG-CC基因型母羊产羔数显著高于AA-TC、AA-CC、AG-TC基因型组合(p<0.05)。综上,ESR2与小尾寒羊产羔数密切相关,g.73324006C>T可作为绵羊产羔性状选育的潜在分子标记。     

高粱抗旱性状的遗传相关和选择效果

对高粱进行遗传相关及选择指数分析,确定了二级枝梗数+二级枝梗粒数+三级枝梗数+抽穗期脯氨酸含量构成的选择指数,遗传进度有显著增加,是旱地高粱育种应采用的较为理性的选择方案。同时通过对不同品种、不同时期、不同环境条件下,叶片内脯氨酸含量的分析结果表明：水分胁迫处理刺激脯氨酸积累的差异,因而可把脯氨酸含量在缺水植株中的增加,作为一种抗旱标志或抗旱机制来考虑。     

Bayesian Multi-Trait Analysis Reveals a Useful Tool to Increase Oil Concentration and to Decrease Toxicity in Jatropha curcas L.

The biggest challenge for jatropha breeding is to identify superior genotypes that present high seed yield and seed oil content with reduced toxicity levels. Therefore, the objective of this study was to estimate genetic parameters for three important traits (weight of 100 seed, oil seed content, and phorbol ester concentration), and to select superior genotypes to be used as progenitors in jatropha breeding. Additionally, the genotypic values and the genetic parameters estimated under the Bayesian multi-trait approach were used to evaluate different selection indices scenarios of 179 half-sib families. Three different scenarios and economic weights were considered. It was possible to simultaneously reduce toxicity and increase seed oil content and weight of 100 seed by using index selection based on genotypic value estimated by the Bayesian multi-trait approach. Indeed, we identified two families that present these characteristics by evaluating genetic diversity using the Ward clustering method, which suggested nine homogenous clusters. Future researches must integrate the Bayesian multi-trait methods with realized relationship matrix, aiming to build accurate selection indices models.     

Bias in the prediction of genetic gain due to mass and half-sib selection in random mating populations

The prediction of gains from selection allows the comparison of breeding methods and selection strategies, although these estimates may be biased. The objective of this study was to investigate the extent of such bias in predicting genetic gain. For this, we simulated 10 cycles of a hypothetical breeding program that involved seven traits, three population classes, three experimental conditions and two breeding methods (mass and half-sib selection). Each combination of trait, population, heritability, method and cycle was repeated 10 times. The predicted gains were biased, even when the genetic parameters were estimated without error. Gain from selection in both genders is twice the gain from selection in a single gender only in the absence of dominance. The use of genotypic variance or broad sense heritability in the predictions represented an additional source of bias. Predictions based on additive variance and narrow sense heritability were equivalent, as were predictions based on genotypic variance and broad sense heritability. The predictions based on mass and family selection were suitable for comparing selection strategies, whereas those based on selection within progenies showed the largest bias and lower association with the realized gain.     

The efficiency of close inbreeding to reduce genetic adaptation to captivity

Although ex situ conservation is indispensable for thousands of species, captive breeding is associated with negative genetic changes: loss of genetic variance and genetic adaptation to captivity that is deleterious in the wild. We used quantitative genetic individual-based simulations to model the effect of genetic management on the evolution of a quantitative trait and the associated fitness of wild-born individuals that are brought to captivity. We also examined the feasibility of the breeding strategies under a scenario of a large number of loci subject to deleterious mutations. We compared two breeding strategies: repeated half-sib mating and a method of minimizing mean coancestry (referred to as gc/mc). Our major finding was that half-sib mating is more effective in reducing genetic adaptation to captivity than the gc/mc method. Moreover, half-sib mating retains larger allelic and adaptive genetic variance. Relative to initial standing variation, the additive variance of the quantitative trait increased under half-sib mating during the sojourn in captivity. Although fragmentation into smaller populations improves the efficiency of the gc/mc method, half-sib mating still performs better in the scenarios tested. Half-sib mating shows two caveats that could mitigate its beneficial effects: low heterozygosity and high risk of extinction when populations are of low fecundity and size and one of the following conditions are met: (i) the strength of selection in captivity is comparable with that in the wild, (ii) deleterious mutations are numerous and only slightly deleterious. Experimental validation of half-sib mating is therefore needed for the advancement of captive breeding programs.     

多个连锁数量性状位点的多性状最优化选择

一种扩展的方法能够在多个世代对具有多个数量性状位点的多性状选择进行最优化。这种方法的基础是在目标雨数中用综合遗传值替代单个性状遗传值,并在整个规划期内最大化所有世代选择反应的加权和。利用多阶段系统优化控制理论,整个最优化问题通过一个向前和向后的迭代循环解决。用一个实际育种猪群的育种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。结果表明,优化选择要优于标准QTL选择和常规BLUP选择。经济权重对优化选择的影响较明显,随着达100kg日龄赋予的经济权重的增加,优化选择的优势越明显。优化选择通过两种方式增加总选择反应：1）选择早期减少一部分QTL选择反应;2）对达100kgH龄给予更大的权重。选择后期优化累积贴现选择比优化终端选择给予达100kgH龄更大的权重。     

Breeding for Biomass Yield in Switchgrass Using Surrogate Measures of Yield

Development of switchgrass (Panicum virgatum L.) as a dedicated biomass crop for conversion to energy requires substantial increases in biomass yield. Most efforts to breed for increased biomass yield are based on some form of indirect selection. The objective of this paper is to evaluate and compare the expected efficiency of several indirect measures of breeding value for improving sward-plot biomass yield of switchgrass. Sward-plot biomass yield, row-plot biomass, and spaced-plant biomass were measured on 144 half-sib families or their maternal parents from the WS4U-C2 breeding population of upland switchgrass. Heading date was also scored on row plots and anthesis date was scored on spaced plants. Use of any of these indirect selection criteria was expected to be less efficient than direct selection for biomass yield measured on sward plots, when expressed as genetic gain per year. Combining any of these indirect selection criteria with half-sib family selection for biomass yield resulted in increases in efficiency of 14 to 36%, but this could only be achieved at a very large cost of measuring phenotype on literally thousands of plants that would eventually have no chance of being selected because they were derived from inferior families. Genomic prediction methods offered the best solution to increase breeding efficiency by reducing average cycle time, increasing selection intensity, and placing selection pressure on all additive genetic variance within the population. Use of genomic selection methods is expected to double or triple genetic gains over field-based half-sib family selection.     

Selection index updating

Summary When traits become evident at different ages or there are large differences in the costs of measuring various traits, selection by independent culling levels may give a higher aggregate economic return than index selection because not all traits need to be measured on all individuals. The problems with optimum independent culling selection is that general solutions are not possible and numerical integration is needed for specific cases. Recently, Xu and Muir (1991) developed a new independent culling level procedure by use of orthogonal transformation of the original characters. With their procedure, explicit solutions for optimum truncation points are possible without numerical integration. As such, the procedure is proficient for any number of stages, and generalized theoretical comparisons of alternative breeding strategies are possible. However, their procedure was limited to the case where selection is for one character at each stage. In this paper, our previous results are extended to the general case of multi-stage index selection, called selection index updating. This procedure is called selection index updating because as traits become available in latter stages, each subsequent index contains all of the traits available up to that stage.The procedure is to develop sequential indices for each stage such that correlations among indices at different stages are zero. Optimum culling points are obtained for the updating procedure by using Xu and Muir's (1991) iterative equations. Due to the property of orthogonality of the updated indices, aggregate gain can be partitioned into gains due to various stages of selection. Partitioning of aggregate economic gain is useful to breeders who desire to adjust individual trait selection intensity based on facilities available at that stage. Methods are discussed to modify the procedure to obtain maximum aggregate economic return per unit of cost associated with obtaining measures on each trait. An application of multi-stage selection is demonstrated using a set of data for Rhode Island Red layer type chickens. A second example demonstrates the use of multi-stage selection optimized with respect to aggregate economic gain and costs associated with obtaining measurements.Journal Paper No. 12813 of the Purdue University Agricultural Experiment Station     

Relative efficiency of the genotypic value and combining ability effects on reciprocal recurrent selection

Reciprocal recurrent selection (RRS) has been successfully applied to maize breeding for more than 60 years. Our objective was to assess the relative efficiency of the genotypic value and the effects of general and specific combining abilities (GCA and SCA) on selection. The GCA effect reflects the number of favorable genes in the parent. The SCA effect primarily reflects the differences in the gene frequencies between the parents. We simulated three traits, three classes of populations, and 10 cycles of half- and full-sib RRS. The RRS is a highly efficient process for intra- and interpopulation breeding, regardless of the trait or the level of divergence among the populations. The RRS increases the heterosis of the interpopulation cross when there is dominance, and it decreases the inbreeding depression in the populations and the genetic variability in the populations and in the hybrid. When there is not dominance and the populations are not divergent, the RRS also determines population differentiation. The half-sib RRS, which is equivalent to selection based on the GCA effect, is more efficient than the full-sib RRS based on the genotypic value, regardless of the trait or the level of improvement of the populations. The full-sib RRS based on the SCA effect is not efficient for intra- and interpopulation breeding.     

Mendelian sampling terms as a selective advantage in optimum breeding schemes with restrictions on the rate of inbreeding

Quadratic indices are a general approach for the joint management of genetic gain and inbreeding in artificial selection programmes. They provide the optimal contributions that selection candidates should have to obtain the maximum gain when the rate of inbreeding is constrained to a predefined value. This study shows that, when using quadratic indices, the selective advantage is a function of the Mendelian sampling terms. That is, at all times, contributions of selected candidates are allocated according to the best available information about their Mendelian sampling terms (i.e. about their superiority over their parental average) and not on their breeding values. By contrast, under standard truncation selection, both estimated breeding values and Mendelian sampling terms play a major role in determining contributions. A measure of the effectiveness of using genetic variation to achieve genetic gain is presented and benchmark values of 0.92 for quadratic optimisation and 0.5 for truncation selection are found for a rate of inbreeding of 0.01 and a heritability of 0.25.     

Single versus subdivided population strategies in breeding against an adverse genetic correlation

In advanced conifer breeding programmes, the simultaneous genetic improvement of adversely correlated traits constitutes a major challenge. Population subdivision strategies have been proposed to deal with breeding objective uncertainty, to reduce inbreeding depression in production populations and to reduce genetic correlation adversity. We used Monte Carlo simulations based on a finite locus model to study the effect of a two-breeding-population strategy applying selection for each trait in each breeding population on the genetic correlation and on genetic gains in breeding populations (BP) and the production population (PP) within a time frame of ten generations. A single-BP and a two-subline strategy both applying multitrait index selection with equal trait weights were used as references. Two BP strategy simulations indicated that simultaneous genetic gain for the two traits could be achieved in the PP despite adverse pleiotropy. The adversity of the genetic correlations decreased in BPs of the two-BP strategy, in contrast to single-BP and subline strategies, but the adversity reduction came at the cost of a lower rate of aggregated (summed) genetic gain in the PP for the two-BP strategy compared to the single-BP or subline strategies. The subline strategy exhibited increased genetic gain in the PP at equal levels of inbreeding as intended. Two BP strategies could be useful to develop breeds specialised on different traits and to simultaneously reduce adverse genetic correlations. However, if the aggregated genetic gain should be maximised, the single-BP strategy appears a better choice.     

An Experimental Evaluation of Genetic Correlation

Heritability and genetic correlations realized from both single-trait and antagonistic index selection were compared with paternal half-sib estimates. Primary attention was focused on the genetic correlation between six-week body weight and six-week tail length. Parameters realized from single-trait selection were in excellent agreement with paternal half-sib estimates. However, the realized genetic correlation between six-week body weight and six-week tail length obtained from index selection was significantly greater than the other estimates. Differential inbreeding levels and realized selection intensities were considered and rejected as being causative factors for these results. Linkage disequilibrium probably was not a factor either, as the base population had been randomly mated and randomly selected with a large effective population size for many generations. It was concluded that with antagonistic index selection, the pleiotropic effects of genes may be more powerful in retarding response in aggregate genotype than current theory would suggest. Replication of all selected and control lines allowed the use of between-line estimators of sampling variances of realized genetic parameters in the above comparisons. Generally, standard errors of realized genetic parameters were much smaller than corresponding paternal half-sib standard errors. Thus, selection was an efficient method of estimation.