分子亲缘系数矩阵的EXCEL计算程序

本文通过VBA语言编程，实现了分子亲缘系数矩阵及其逆阵计算的程序设计，提高了数据处理的准确性。尤其是该程序借助于已在国内广泛使用的Excel，使广大基层技术人员采用最佳线性无偏预测(BLUP)法进行家畜育种值评定更加方便可行。     

德国弗莱维赫牛对荷斯坦奶牛的改良应用

<正>近年来,黑龙江省奶业生产形势严峻。饲料价格不断上涨,奶价偏低,奶农的奶牛饲养成本不断提高,效益却大幅下降,甚至无利润可言。尤其对于     

德国弗莱维赫(Fleckvieh)牛和本地牛杂交F1代母牛生长发育性状测定及分析

[目的]为了研究德国弗莱维赫(Fleckvieh)牛与本地母牛杂交F_1代育成母牛生长发育性状和生长发育规律,为培育北大荒乳肉兼用牛品种,开展选育提高奠定基础。[方法]采用各批次测定体重校正到统一月龄,测定了其初生、4月龄(断奶)、12月龄及18月龄4个阶段的体重、体尺,并对各阶段表型值比较分析。[结果]德国弗莱维赫(Fleckvieh)牛与本地母牛杂交F_1代母牛平均日增重、胸围和体斜长性状,在初生至4月龄断奶阶段生长发育最快;从4月龄断奶至18月龄,与纯种德国弗莱维赫种公牛与澳系(澳大利亚)西门塔尔母牛杂交后代相比,在体重和体尺上有一定差异。[结论]需要不断地改良,以提高后代的生长发育性状,进一步提高生产性能。     

利用酵母双杂交技术筛选和鉴定非洲猪瘟病毒E120R蛋白的互作宿主蛋白

【目的】 探讨非洲猪瘟病毒（African swine fever virus，ASFV）衣壳蛋白E120R在病毒感染中的作用，确定与E120R蛋白互作的宿主蛋白。【方法】 将ASFV分离株CADC_HN09株E120R基因合成并克隆于pGBKT7表达载体，获得pGBKT7-E120R诱饵质粒，同时构建E120R基因截短表达质粒pGBKT7-E120R-1（1－61位氨基酸）和pGBKT7-E120R-2（62－122位氨基酸）。经毒性和自激活性检测后，通过酵母双杂交技术对骨髓巨噬细胞（BMDMs） cDNA均一化酵母文库进行初步筛选，以获得与ASFV E120R蛋白互作的蛋白。通过NCBI数据库进行序列比对并经免疫共沉淀试验验证，确定互作的宿主蛋白。筛选的宿主蛋白经webgenstal在线分析网站初步进行GO功能和KEGG通路富集分析，以确定所筛选的宿主蛋白参与的生物过程与信号通路。【结果】 诱饵质粒pGBKT7-E120R-2无毒性和自激活性，可用于文库筛选。通过酵母双杂交系统从BMDMs cDNA均一化酵母文库中初步筛选到46个阳性克隆并进行回转验证，经NCBI数据库序列比对分析共获得29个宿主蛋白。免疫共沉淀试验结果显示，多聚胞嘧啶结合蛋白2（PCBP2）和干扰素刺激基因15（ISG15）均与E120R蛋白存在互作。GO功能富集分析表明，所筛选的宿主蛋白可参与代谢过程、生物调节、应激反应等生物过程；KEGG通路富集分析表明，这些宿主蛋白可参与抗原呈递、铁死亡和坏死性凋亡等多条信号通路。【结论】 ASFV E120R蛋白可与宿主免疫应答、细胞死亡等信号通路相关的多种宿主蛋白互作，为进一步研究ASFV E120R蛋白在病毒感染过程中的作用提供了重要理论依据。     

Comparison of four direct algorithms for computing inbreeding coefficients

One widely used measure in genetic analyses of livestock species is the inbreeding coefficient. Computation costs of inbreeding coefficients are of importance for large populations. Very recently, a ‘direct’ method for computing inbreeding coefficients was modified using a relatively efficient method to construct lists of ancestors in which the integrity of chronological order within each ancestral path is kept. Using simulated data, the computational efficiency of the recently modified algorithm was investigated by comparing it with three other algorithms – the original direct algorithm, its previously modified algorithm and another direct algorithm. The recently modified algorithm became considerably faster than the original algorithm and its previous modification when the number of generations increased, and it was fast relative to the other direct algorithm when the average number of generations and family size were not large. When only animals born in the most recent year were evaluated with the knowledge of inbreeding coefficients for their ancestors, the recently modified algorithm outperformed the other algorithms, indicating its possible advantage in updating situations.     

A fast algorithm for computing inbreeding coefficients in large populations

Inbreeding coefficients of animals are required in many genetic analyses of livestock records. A modification of Colleau's indirect algorithm to compute inbreeding coefficients in large populations is presented. With overlapping generations, the modified algorithm evaluated all progeny of each sire simultaneously in one back and forth exploration of a reduced pedigree. Simulation for a relatively large number of generations, different number of sires, family sizes and mating designs showed that Colleau's algorithm was faster (from 1.2 to 143 times) than two other algorithms under comparison (Tier, modified Meuwissen and Luo), in all situations investigated. Modifying Colleau's algorithm considerably decreased computation time (from 50 to 89%), resulting in a very fast algorithm. The number of sires mostly affected computational efficiency of the modified algorithm, whereas family size and mating design had virtually no effect. In the updating situation, when only animals born in the last year were evaluated, given known inbreeding coefficients for the other, the modified algorithm was also fast compared with the other three algorithms. Memory requirements for the algorithms were also discussed.     

Networks of inbreeding coefficients in a selected population of rabbits

The correlation between pedigree and genomic-based inbreeding coefficients is usually discussed in the literature. However, some of these correlations could be spurious. Using partial correlations and information theory, it is possible to distinguish a significant association between two variables which is independent from associations with a third variable. The objective of this study is to implement partial correlations and information theory to assess the relationship between different inbreeding coefficients using a selected population of rabbits. Data from pedigree and genomic information from a 200K SNP chip were available. After applying filtering criteria, the data set comprised 437 animals genotyped for 114,604 autosomal SNP. Fifteen pedigree- and genome-based inbreeding coefficients were estimated and used to build a network. Recent inbreeding coefficient based on runs of homozygosity had 9 edges linking it with different inbreeding coefficients. Partial correlations and information theory approach allowed to infer meaningful associations between inbreeding coefficients and highlighted the importance of the recent inbreeding based on runs of homozygosity, but a good proxy of it could be those pedigree-based definitions reflecting recent inbreeding.     

Generation intervals and inbreeding coefficients in the Finnish Hound and the Finnish Spitz

SUMMARY: The population structure of two Finnish hunting dog breeds was examined, by calculating generation intervals and inbreeding coefficients. Data sets consisted of registers, including 84338 Finnish Hounds and 28370 Finnish Spitzes. The mean values for paternal generation intervals were 5.8 years in the Hound and 5.7 years in the Spitz. The mean values for maternal generation intervals were 5.0 and 4.5 years in the two breeds, respectively. The average inbreeding coefficient was 3.12% in the Finnish Hound and 7.16% in the Finnish Spitz. The use of intense inbreeding had decreased during the last few years, especially in the Spitz. The expected average inbreeding coefficients, calculated on the basis of random mating simulations, were usually somewhat lower than the observed in both breeds. This implies that linebreeding or mild inbreeding has been used as a breeding method. ZUSAMMENFASSUNG: Generationsintervall und Inzuschtkoeffizienten in Finnischen Spitz und Bracken Hunden Die Populationsstruktur der beiden Finnischen Jagdhunderassen wurde in Hinblick auf Generationsintervall und Inzucht untersucht. Die Daten umfa?ten Registration von 84338 Bracken und 28370 Spitz. Das v?terliche Generationsintervall war 5, 8 Jahre bei Bracken und 5, 7 bei Spitz, das mütterliche 5, 0 und 4, 7 Jahre. Der durchschnittliche Inzuchtkoeffizient war 3, 12% beim Finnischen Bracken und 7, 16% beim Finnischen Spitz. Enge Inzucht hat in den letzten Jahren abgenommen, besonders beim Spitz. Die erwartete Inzucht wurde anhand von Simulation zuf?lliger Paarung gesch?tzt und ergab etwas geringere Werte als die tats?chliche in beiden Rassen. Das deutet auf praktizierte Linienzucht und geringe Inzucht in der Zuchtarbeit.     

A performance programmed method for computing inbreeding coefficients from large data sets for use in mixed-model analyses

Coefficients of inbreeding are commonly used in mixed-model methods for forming inverses of Wright's numerator relationship matrix and transformation matrices used in variance component estimation and national cattle evaluation. Computation of exact coefficients of inbreeding from very large data sets has been believed to be too expensive or too difficult a task to perform. Approximate methods have been used instead. The effects of using approximation methods for inbred data that appear in national cattle data sets are demonstrated. An algorithm is given for the computation of inbreeding coefficients for large data sets. The algorithm feasibly computes inbreeding coefficients for large data sets even on small computing architectures.     

不同近交程度对藏獒体尺生长发育的影响

通过近交对河曲藏獒体尺生长发育影响的详细分析,发现随着近交系数的增加,体长、体高、胸围和管围都趋近于正态分布。近交系数为0．0652的藏獒,2—3月龄体长和3月龄管国有较大生长强度,2月龄体高生长强度不及近交系数0．0893组,体长、胸围和管围没有明显下降趋势。藏獒近交系数大于0.0652,除了体高生长强度外,其他体尺生长发育出现近交衰退趋势。     

Computing inbreeding coefficients and the inverse numerator relationship matrix in large populations of honey bees

The inbreeding coefficients are considered in breeding decisions, and the inverse numerator relationship matrix A ^?1 is a prerequisite for breeding value estimation. Polyandry and haploid males are among the specifics of relationships between honey bees. Brascamp and Bijma (2014) averaged out the manifold possible relationships among honey bees that appear to have the same parents in a pedigree and assigned a single entry in A to animals that behave as a unit, for example, the workers of a hive. Their methods of calculation connected full‐sibs in the variance matrix of the Mendelian sampling terms D , via nonzero off‐diagonal elements. This impedes the inversion of A and the closely connected calculation of inbreeding coefficients, because efficient algorithms for this task take D to be a diagonal matrix. Memory limitations necessitate their use for large data sets. We adapted the quickest of them to the block diagonal matrix D , that is postulated for the honey bee. To our knowledge, the presented algorithm is the first one that facilitates the method of Brascamp and Bijma (2014) on large data sets.     

Heritabilities and genetic correlations of economic traits in Iranian native fowl and estimated genetic trend and inbreeding coefficients

1. Genetic parameters were estimated in a base population of a closed experimental strain of fowl. Data were obtained on 21 245 Iranian native hens (breeding centre for Fars province) subject to 8 successive generations of selection. This population had been selected for body weight at 12 weeks of age (BW12) and egg number during the first 12 weeks of the laying period (EN), mean egg weight (EW) at weeks 28, 30 and 32, and age at sexual maturity (ASM). 2. The method of multi-traits restricted maximum likelihood with an animal model was used to estimate genetic parameters. Resulting heritabilities for BW12, EN, EW and ASM were 0.68 +/- 0.02, 0.40 +/- 0.02, 0.64 +/- 0.02 and 0.49 +/- 0.02, respectively. 3. Genetic correlations between BW12 and EN, EW and ASM were 0.11 +/- 0.33, 0.54 +/- 0.21 and -0.12 +/- 0.03, respectively. Genetic correlations between EN and EW and ASM were -0.09 +/- 0.03 and -0.85 +/- 0.01, respectively, while between EW and ASM, it was 0.05 +/- 0.03. 4. The overall predicted genetic gains, after 7 generations of selection, estimated by the regression coefficients of the breeding value on generation number were equal to 22.7, 0.17, 0.04 and -1.38, for BW12, EN, EW and ASM, respectively. 5. A pedigree file of 21 245 female and male birds was used to calculate inbreeding coefficients and their influence on production and reproduction traits. Average inbreeding coefficients for all birds, inbred birds, female birds and male birds were 0.048, 0.673, 0.055 and 0.047%, respectively. Regression coefficients of BW12, ASM, EN and EW on inbreeding coefficient for all birds were equal to 0.51 +/- 0.001, 0.31 +/- 0.003, -0.51 +/- 0.003 and 0.03 +/- 0.001, respectively.     

Effects of models with finite loci, selection, dominance, epistasis and linkage on inbreeding coefficients based on pedigree and genotypic information

Considering the effects of selection, dominance, epistasis and linkage, a stochastic computer simulation was performed to study how well inbreeding coefficients calculated from pedigree (f_ped) and genotypic frequencies (f_het) correspond to the inbreeding coefficient that is defined as the proportion of autozygous loci in the modelled genome (i.e. the level of autozygosity, f_aut). Although in random mating populations all three inbreeding coefficients show almost (with slight deviations in models with two loci) the same expectation, they represent three separate variables. First, f_aut, f_ped and f_het responded differently to selection, dominance, epistasis and linkage. Second, they did not have the same standard deviations, which means that the effects of random drift, especially in models under selection, were not affecting all three coefficients in the same way. Finally, they were not always defined in the same domain. With selection as the most important factor responsible for the observed discrepancies, the bias (discrepancy) was present in both directions, thus leading to overestimation or underestimation of the observed level of autozygosity depending on the genetic model, linkage and initial gene frequency. Variation of the autozygosity level (between replicates) was increased notably in models with additive inheritance under selection and was an additional potential source of bias. Thus, when the trait is, to a large extent, controlled by a finite number of loci and when selection is present, the bias in the estimation of the autozygosity is likely to occur and caution is necessary whenever conclusions are based on inbreeding coefficients estimated from the pedigree or decrease in heterozygosity.