新疆褐牛基因外显子多态性及其与SCS和泌乳性状关联性分析

【目的】探索ERAP2,Cwc27,PPFIBP2,THADA,ZNF804B和AMHR2基因多态性与新疆褐牛体细胞评分及泌乳性状的相关性,旨在寻找与新疆褐牛体细胞评分及泌乳性状相关的分子标记。【方法】以新疆乌鲁木齐种牛场、新疆天山畜牧生物工程股份有限公司共169头新疆褐牛母牛为试验对象,以2008—2015年间的生产性能测定记录(包括乳脂率、乳蛋白率、总固体含量、乳糖率和体细胞计数等)和305 d产奶量为试验数据,基于课题组前期15头中国荷斯坦牛DNA混池重测序的结果筛选外显子区域10个SNPs,采用基质辅助激光电离飞行时间质谱法(sequenom mass Array genotype)分型技术验证10个SNP位点的遗传多态性,运用SAS8.1软件GLM过程对这10个SNP突变与新疆褐牛体细胞评分(SCS)、305 d产奶量、乳脂率、乳蛋白率、乳糖率和总固体的关联程度进行统计分析。【结果】10个SNP位点均具有多态性,χ~2检验表明群体中9个SNP位点符合Hardy-Weinberg平衡状态。关联分析结果表明ERAP2基因两个位点(T98741711C和G98736141A)均与新疆褐牛305 d产奶量达到极显著关联(P0.001),其中TT型和GG型个体的产奶量最高;PPFIBP2(C45667492G)位点与新疆褐牛乳糖率达到显著关联(P0.005),其中GG型个体的乳糖率最高;Cwc27(T14533269A)位点与新疆褐牛乳脂率和总固体含量达到显著关联(P0.005),与SCS达到极显著关联(P0.001),其中TT型个体的乳脂率和总固体含量均最高,AA型个体的SCS极显著高于AT和TT型;AMHR2(C26758055G)位点与新疆褐牛乳蛋白率和总固体含量达到极显著关联(P0.001),其中GG型个体显著高于CC和GC型个体。连锁不平衡分析与单倍型构建的结果发现10个SNPs构建了两个单倍型模块,其中SNP1和SNP2位点之间处于连锁不平衡状态(r20.3),SNP4和SNP10位点之间处于强连锁不平衡状态(r20.6),随后分析了单倍型与SCS和泌乳性状之间的相关性,发现单倍型与新疆褐牛SCS和泌乳性状无显著关联(P0.001)。【结论】初步发现了ERAP2,Cwc27,PPFIBP2和AMHR2与新疆褐牛SCS和泌乳性能相关,结果可为新疆褐牛产奶性状的分子标记辅助选育提供参考和依据。     

Genetic mapping using 1.4M SNP array refined loci for fatty acid composition traits in Chinese Erhualian and Bamaxiang pigs

Chinese indigenous pigs display marked genetic and phenotypic differences compared with western commercial pigs. In this study, we tested the association between 660K SNPs and longissimus muscle fatty acid composition traits in Chinese Erhualian (n = 331) and Bamaxiang (n = 315) pigs based on a customized 1.4 million SNP array. We identified a total of 64 significant associations for 20 fatty acid composition traits at the p‐value threshold of 1 × 10^?6 among which 42 associations in low linkage disequilibrium (r² < .2) with previously reported loci were considered novel. We substantially improved the strength and precision of the associations at four previously detected loci near FADS2, ELOVL7, ELOVL6 and FASN genes, facilitating follow‐up candidate gene studies. Moreover, we also identified loci near ABCD2, ACSBG1, ELOVL5, HPGDS, DAGT2, ACAD10 and ACSL1 genes with function relevant to metabolism of fatty acids. In this study, valuable genetic variants and candidate genes associated with fatty acid composition traits were identified in Erhualian and Bamaxiang pigs. Some identified loci could be used to improve pork nutrition in pig breeding practice. Using the SNP array with higher marker density and less ascertainment bias improved QTL detection power and precision in Chinese indigenous pigs.     

基于数据挖掘分析何泽云教授治疗CKD的用药规律

目的 基于数据挖掘方法分析何泽云教授治疗慢性肾脏疾病（chronic kidney disease,CKD）的用药规律。方法 收集何泽云教授治疗CKD病例336份,处方1 110张,采用SPSS 17.0及数据挖掘软件clementine 12.0分别对处方进行频次分析和关联规则分析。结果 单味药使用频次由高到低依次是白茅根、山药、黄精、熟地黄、黄芪,使用频率最高的类别是补益类药物（总频率达49.6%）;关联规则分析结果显示,支持度较高的药对依次为白茅根-山药、白茅根-麦冬、白茅根-黄精、白茅根-熟地黄、白茅根-黄芪、山药-黄精、山药-熟地黄。结论 何泽云教授以培元固本,健脾补肾为基本治疗大法,辅以固精、滋阴、泄浊之法论治CKD,数据挖掘方法对于中医临床经验总结具有重要实用价值,为中医治疗CKD用药筛选及中药研发提供思路。     

建国初期农民协会的积极作用对重建农民协会的启示

分析了建国初期农民协会的积极作用,结合当前农村实际,提出重建农民协会,以期通过农民协会整合农村的建设力量,协调农村的干群关系,维护农民的权益,促进农村的政治文明建设,推进社会主义农业现代化。     

农村专业技术协会人力资本团队满意影响因素实证分析——基于湖北省5市（县）118个会员的调查数据

利用湖北省荆州市、松滋市、潜江市、宜昌市及襄誉市的5个市（县）118个会员的调查数据,基于Logit模型对农村专业技术协会人力资本团队满意影响因素进行了实证分析。     

艾比湖湿地植物种间关系研究

应用X2检验、Pearson相关分析和Spearman秩相关分析研究了艾比湖湿地主要植物种的种间关系。总体关联度显示植物种间独立性较强;在19个主要植物种之间,呈显著正相关植物种对数较少,共计15对,为总种对的8.77%;显著负相关植物种对极少,Spearman秩相关检验中为5对,占总对数的2.92%,X2检验中只有1对;研究结果清楚地反映了植物种间关系以及它们在资源利用和生态位上的差异。     

关联规则挖掘在奶牛营养研究中的应用

【目的】揭示隐含在奶牛营养分析结果数据中影响奶牛瘤胃乙酸/丙酸的关联关系和因素,为奶牛营养研究和奶牛养殖提供参考。【方法】选用奶牛营养分析结果的100条数据,应用改进的关联挖掘算法DMApriori算法,对奶牛营养分析结果中瘤胃乙酸/丙酸低于或高于正常值的情况进行了关联分析。【结果】饲喂一般牧草黑白花牛的瘤胃乙酸/丙酸低于正常值的可信度为70%;当前体质量在598～698 kg的奶牛多为黑白花牛,可信度为75%;日产奶量在10～20 kg的奶牛多为黑白花牛,可信度为70%;乳脂率在3%～4%的奶牛大多为黑白花牛,可信度为88%。【结论】通过对奶牛营养分析中的大量数据进行关联规则挖掘,提取蕴含在这些大量数据中有意义、有价值的信息,可以为奶牛营养研究和养殖的规划调整提供科学依据。     

Performance analysis on improved PDA AI for moving target tracking

Aim at the problem that the EO imaging tracking system is inconsistent with the model of probabilistic data association with amplitude information (PDA AI), which supposes that the greater the amplitude value is, the greater the probability of being the tracked target will be, a modified PDA AI (MPDA AI) is presented . Based on the fact that the amplitude and the motion of the interested target are consistent in a short period, the MPDA AI models the amplitude information and the motion information of the target as well as their consistency with Markov stationary signal to analyze the association procedure of motion and amplitude. The lower bounds of Cramer Rao estimation error for PDA AI and MPDA AI are calculated and discussed in detail. The theoretical analysis and experimental results show that estimating the target motion with the MPDA AI will be more accurate and more reliable than estimating with the original PDA AI.     

Power of a genome scan to detect and locate quantitative trait loci in cattle using dense single nucleotide polymorphisms

There is increasing use of dense single nucleotide polymorphisms (SNPs) for whole‐genome association studies (WGAS) in livestock to map and identify quantitative trait loci (QTL). These studies rely on linkage disequilibrium (LD) to detect an association between SNP genotypes and phenotypes. The power and precision of these WGAS are unknown, and will depend on the extent of LD in the experimental population. One complication for WGAS in livestock populations is that they typically consist of many paternal half‐sib families, and in some cases full‐sib families; unless this subtle population stratification is accounted for, many spurious associations may be reported. Our aim was to investigate the power, precision and false discovery rates of WGAS for QTL discovery, with a commercial SNP array, given existing patterns of LD in cattle. We also tested the efficiency of selective genotyping animals. A total of 365 cattle were genotyped for 9232 SNPs. We simulated a QTL effect as well as polygenic and environmental effects for all animals. One QTL was simulated on a randomly chosen SNP and accounted for 5%, 10% or 18% of the total variance. The power to detect a moderate‐sized additive QTL (5% of the phenotypic variance) with 365 animals genotyped was 37% (p < 0.001). Most importantly, if pedigree structure was not accounted for, the number of false positives significantly increased above those expected by chance alone. Selective genotyping also resulted in a significant increase in false positives, even when pedigree structure was accounted for.