恩格斯生态自然观对我国生态文明建设的启示

人与自然之间的关系问题是生态环境的根本问题,人既有自然属性又有社会属性,人与自然界既对立又统一,人们改造与利用自然界必须遵循客观发展规律,实现人与自然和谐共处。恩格斯的生态自然观对实现我国人与自然的和谐共处,建设美丽生态中国具有重要的现实意义。因此,要以恩格斯生态自然观为指导,积极开展生态文明教育,树立环保意识;大力倡导绿色消费模式,推动绿色发展。     

Drought Stress in Grain Legumes during Reproduction and Grain Filling

Water scarcity is a major constraint limiting grain legume production particularly in the arid and semi‐arid tropics. Different climate models have predicted changes in rainfall distribution and frequent drought spells for the future. Although drought impedes the productivity of grain legumes at all growth stages, its occurrence during reproductive and grain development stages (terminal drought) is more critical and usually results in significant loss in grain yield. However, the extent of yield loss depends on the duration and intensity of the stress. A reduction in the rate of net photosynthesis, and poor grain set and grain development are the principal reasons for terminal drought‐induced loss in grain yield. Insight into the impact and resistance mechanism of terminal drought is required for effective crop improvement programmes aiming to improve resistance to terminal drought in grain legumes. In this article, the impact of terminal drought on leaf development and senescence, light harvesting and carbon fixation, and grain development and grain composition is discussed. The mechanisms of resistance, management options, and innovative breeding and functional genomics strategies to improve resistance to terminal drought in grain legumes are also discussed.     

不同林龄枫香子代性状变异与家系选择

对布设在安徽祁门县的首批84个枫香子代测定林，分析比较了9年生与3年生两个不同林龄胸径、树高性状的遗传力和遗传增益等参数，并开展了优良家系选择。结果表明不同时期入选的家系名称、数量及名次出现较大差异，大部分家系胸径、树高性状的家系遗传力、单株遗传力及遗传增益等参数估值，表现为随林龄增大而降低。研究结果为枫香良种选育的适宜林龄提供了参考依据。     

辽葱5号的选育

辽葱5号是以玉田县五叶齐大葱为母本、朝阳鳞棒葱为父本进行有性杂交，对杂交后代进行季节穿梭选择的方法，即用3年时间进行了3个世代的以株为单位的混合选择及以株系为单位的选择，最后留选1个经济性状整齐、生殖性状稳定的雄性可育母系，经系内混合授粉育成的大葱新品种。该葱生长旺盛、秋葱产量高、葱白较长、叶片直立性好、抗紫斑病能力较强，适合长季节栽培，生育期在120d以上，属中晚熟品种。冬贮干葱可食用率高，适宜北方各省、区种植。     

具有交易费用和马氏调制的均值-方差组合选择

研究了均值-方差准则下，最优投资组合选择问题.投资者为了增加财富它可以在金融市场上投资.金融市场由一个无风险资产和n个带跳的风险资产组成，并假设金融市场具有马氏调制，买卖风险资产时，考虑交易费用.目标是，在终值财富的均值等于d的限制下，使终值财富的方差最小，即均值-方差组合选择问题.应用随机控制的理论解决该问题，获得了最优的投资策略和有效边界.     

Landscape Zonation, benefit functions and target-based planning: Unifying reserve selection strategies

The most widespread reserve selection strategy is target-based planning, as specified under the framework of systematic conservation planning. Targets are given for the representation levels of biodiversity features, and site selection algorithms are employed to either meet the targets with least cost (the minimum set formulation) or to maximize the number of targets met with a given resource (maximum coverage). Benefit functions are another recent approach to reserve selection. In the benefit function framework the objective is to maximize the value of the reserve network, however value is defined. In one benefit function formulation value is a sum over species-specific values, and species-specific value is an increasing function of representation. This benefit function approach is computationally convenient, but because it allows free tradeoffs between species, it essentially makes the assumption that species are acting as surrogates, or samples from a larger regional species pool. The Zonation algorithm is a recent computational method that produces a hierarchy of conservation priority through the landscape. This hierarchy is produced via iterative removal of selection units (cells) using the criterion of least marginal loss of conservation value to decide which cell to remove next. The first variant of Zonation, here called core-area Zonation, has a characteristic of emphasizing core-areas of all species. Here I separate the Zonation meta-algorithm from the cell removal rule, the definition of marginal loss of conservation value utilized inside the algorithm. I show how additive benefit functions and target-based planning can be implemented into the Zonation framework via the use of particular kinds of cell removal rules. The core-area, additive benefit function and targeting benefit function variants of Zonation have interesting conceptual differences in how they treat and trade off between species in the planning process.     

Emerging issues in genomic selection

Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit the computation of P-values from genomic best linear unbiased prediction (GBLUP), where models can be arbitrarily complex but restricted to genotyped animals only, and single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top-ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as 1 SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. Although many issues in GS have been solved, many new issues that require additional research continue to surface.     

国外生猪育种体系简析及对我国生猪育种的几点思考

选择是生猪育种的核心,而准确地选择和选种依赖于完善和成熟的育种体系。国际养猪发达国家(国际育种企业)对育种体系不断完善,长期进行生长、繁殖和肉品质等各类性状的表型测定,运用多场联合评估和基因组选择等方法不断提高遗传评估的准确性,不断挖掘新的育种性状,并进行测定、评估和选育,实现了种猪群体持续的遗传改良和综合性能的不断提升。本文对欧美发达国家(国际育种企业)的生猪育种技术体系进行了综述,以期为我国的生猪育种工作提供参考,并促进我国生猪种业的创新发展。     

一种适用于单胎动物多品种选择的基因组关系矩阵

旨在提出一种新型基因组关系矩阵并验证其在多品种联合群体中的模拟应用效果。本研究利用QMsim软件模拟牛的表型数据和基因型数据;利用Gmatrix软件构建常规G阵;利用R语言构建新型G阵,新型G阵在常规G阵的基础上,将多品种联合群体的非哈代-温伯格平衡位点考虑在内;利用DMU软件使用“一步”法模型计算基因组估计育种值（estimated genomic breeding value,GEBV）;比较不同情况下使用两种G阵的GEBV预测准确性。结果表明,在不同遗传力及QTL数下,不对新型G阵使用A₂₂阵加权就能达到常规G阵使用A₂₂阵加权时的GEBV预测准确性。在系谱部分缺失时,新型G阵不加权较常规G阵加权时GEBV预测准确性高。证明,在系谱有部分缺失时,新型G阵对多品种GEBV的预测有一定优势。     

参考群筛选方法及规模对基因型填充准确性的影响

为探究基于A矩阵期望遗传关系最大化（maximizing the expected genetic relationship for matrix A,RELA）、基于A矩阵目标群体遗传方差最小化（minimized the target population genetic variance for matrix A,MCA）、平均亲缘关系最大化（the highest mean kinship coefficients,KIN）、随机选择（random selection,RAN）、共同祖先筛选（common ancestor,CA）等不同参考群筛选方法及参考群规模对基因型填充准确性的影响。本研究使用矮小型黄羽肉鸡作为试验群体,采用鸡600K SNP芯片（Affymetrix Axion HD genotyping array）进行基因分型,测定435羽子代公鸡45、56、70、84、91日龄体重。利用Beagle软件将低密度SNP芯片填充为高密度SNP芯片数据,比较不同参考群筛选方法、参考群规模对基因型填充准确性的影响,以及填充芯片基因组预测准确性。结果表明,使用Beagle 4.0结合系谱信息进行填充效果最佳,其次为Beagle 4.0,而Beagle 5.1填充效果最差。使用MCA方法筛选参考群进行基因型填充准确性最高,使用RAN方法筛选参考群进行基因型填充准确性最低,MCA、RELA、CA 3种方法基因型填充准确性差别较小。相比其他方法,使用MCA方法筛选个体作为参考群将低密度SNP芯片填充至高密度SNP芯片进行基因组选择的预测准确性较高,与真实高密度SNP芯片的基因组预测准确性相差甚微。随着参考群规模增大,基因型填充准确性也随之增加,但增速逐渐下降,最后趋于平缓。综上所述,可以通过参考群筛选方法构建参考群以及控制参考群规模,以保证基因型填充和基因组预测准确性并节省成本,本研究为基因型填充在畜禽遗传育种中的应用提供技术参考。