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研究分析了辽宁绒山羊3个经济性状的相关性.根据山羊遗传连锁图谱和相关资料,选用7个微卫星座位,对40只辽宁绒山羊基因组DNA的遗传多样性进行检测,通过标记多态性与生产性状的最小二乘线性模型,进行分子标记与经济性状的相关分析.结果表明:7个微卫星座位中只有4个表现出了多态性.微卫星OarJMP8座位上AA、AD基因型个体羊绒纤维长度极显著高于其他基因型个体(P＜0.01),AD基因型个体产绒量显著高于其他基因型个体(P＜0.05);微卫星BM143座位上AC基因型个体羊绒纤维细度显著低于其他基因型个体(P＜0.05);微卫星OarAE101座位上AB基因型个体羊绒纤维长度和产绒量均显著高于其他基因型个体(P＜0.05);微卫星BM6506座位上从基因型个体产绒量极显著高于其它基因型个体(P＜0.01). 相似文献
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根据山羊遗传连锁图谱和相关资料,选用7个微卫星座位,对40只辽宁绒山羊基因组DNA的遗传多样性进行检测;通过标记多态性与生产性状的最小二乘线性模型,进行分子标记与经济性状的相关分析.结果表明,7个微卫星座位中只有4个表现出了多态性.微卫星OarJMP8座位上AA、AD基因型个体羊绒纤维长度显著高于其它基因型个体(P<0.05),AD基因型个体产绒量显著高于其它基因型个体(P<0.05);微卫星BM143座位上AC基因型个体羊绒纤维细度显著低于其它基因型个体(P<0.05);微卫星OarAE101座位上AB基因型个体羊绒纤维长度和产绒量均显著或极显著高于其它基因型个体(P<0.05,P<0.01);微卫星BM6506座位上从基因型个体产绒量极显著高于其它基因型个体(P<0.01). 相似文献
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随着基因组学时代的到来和各种生物技术的飞速发展 ,分子标记技术在鸡的育种和生产中愈来愈显示其重要性。近几年来 ,国内外学者对微卫星标记进行了广泛而深刻的研究 ,在基因作图、数量性状位点 ( QTL)定位、群体遗传距离测定、抗病品系的选育等方面得到了广泛应用。作为第三代分子标记的 SNPs,为探索鸡的某些疾病的产生机理和生产性能差异的遗传基础提供了新方法。1 微卫星标记微卫星是在生物体基因组以 2～ 6bp为其核心序列 ,头尾相连组成的串状重复序列。核心序列一般重复 1 0～ 2 0次 ,多态性的产生是因重复次数的不同造成的 ,通常… 相似文献
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微卫星标记在家禽育种中的应用 总被引：3，自引：0，他引：3
1974年，skinner在研究寄生蟹的卫星DNA时发现一种简单的串联重复序列，Ali等在1986年将合成的寡聚核苷酸用于人的指纹研究。1989年，Taetz利用PCK技术研究了微卫星的变异特性，提出微卫星有丰富的多态性。作为近十几年来发展起来的遗传标记，微卫星具有数量大，分布广泛均匀，多态信息含量高，检测快速方便等优点，受到广大研究者的青睐。本文旨在对微卫星标记的特性及其在家禽育种中的应用作一简要综述。 相似文献
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据相关研究报道,在澳洲无角陶赛特羊18号染色体末端微卫星标记CSSM18和TGLA122之间的区域有控制其肌肉生长发育的Callipyge和Canvell基因。研究选择了微卫星标记CSSMl8和TGLAl22之间的TGLA122、LS33、ILSTS54、MCMA26四个微卫星标记,测定了新疆引进的澳洲无角陶赛特羊所产后代163只羔羊早期生长发育性状指标,采用PCR—SSCP技术检测了上述4个标记在研究群体中的多态性,分析了研究群体中4个微卫星标记不同基因型与早期生长发育性状的相关性。结果显示：微卫星标记TGLA122的杂合度0．4301,多态信息含量0．2733,有效等位基因数1．3761;微卫星标记MCMA26的杂合度0．4824,多态信息含量0．3660,有效等位基因数1．577O;微卫星标记LS33的杂合度0．3283,多态信息含量0．2744,有效等位基因数1．3780。微卫星标记TGLA122的3种基因型（AA／BB／AB）对90日龄母羔臀宽影响显著（P〈0．05）,对其他生长指标均无显著影响;微卫星标记MCMA26的3种基因型（GG／Tr／GT）对60日龄母羔胸围和臀宽有显著影响,对其他生长指标均无显著影响;微卫星标记LS33的2种基因型（EE／EF）个体的体重和体尺均无显著性差异;微卫星标记ILSTS54在该群体中无多态性。 相似文献
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猪多经济性状的重建研究 总被引：2，自引：2，他引：0
本研究的目标是对猪多个经济性状进行性状重建,并对重建性状的遗传参数进行估计。本研究涉及性状重建的原始经济性状包括了生长、胴体和肉质3类共24个性状。性状重建利用主成分分析法,经统计分析后得到4个主成分作为新的重建性状。在对重建性状进行描述性统计处理基础上,进一步利用动物模型和DFREML算法估计了各性状的遗传力,得到第1、2、3和4主成分的遗传力分别为0.87、0.58、0.49和0.56。研究结果表明,通过性状重建不但可以实现多性状的降维处理,而且重建性状的遗传力有提高趋势,性状重建策略有望促进多性状育种的进程。 相似文献
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一般有多个性状影响家畜生产性能,且各性状相对经济价值不同,所以按单性状杂种优势来评价某杂交组合的优劣是不全面的。本文提出了综合杂种优势的概念和单杂交试验中综合杂种优势的多元分析方法。记杂种ij第1性状的杂种优势为hijl,其相对经济价值为W_1,若育种目标性状共有L个,我们把品系i与品系j杂交产生的杂种的综合优势定义为: 本文根据线性模型的理论给出了Hij的最优线性无偏估计(BLUE)及其置信区间。 相似文献
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Jiuxiu Ji Guorong Yan Dong Chen Shijun Xiao Jun Gao Zhiyan Zhang 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2019,136(3):217-228
The average daily gain (ADG) and body weight (BW) are very important traits for breeding programs and for the meat production industry, which have attracted many researchers to delineate the genetic architecture behind these traits. In the present study, single‐ and multi‐trait genome‐wide association studies (GWAS) were performed between imputed whole‐genome sequence data and the traits of the ADG and BW at different stages in a large‐scale White Duroc × Erhualian F2 population. A bioinformatics annotation analysis was used to assist in the identification of candidate genes that are associated with these traits. Five and seven genome‐wide significant quantitative trait loci (QTLs) were identified by single‐ and multi‐trait GWAS, respectively. Furthermore, more than 40 genome‐wide suggestive loci were detected. On the basis of the whole‐genome sequence association study and the bioinformatics analysis, NDUFAF6, TNS1 and HMGA1 stood out as the strongest candidate genes. The presented single‐ and multi‐trait GWAS analysis using imputed whole‐genome sequence data identified several novel QTLs for pig growth‐related traits. Integrating the GWAS with bioinformatics analysis can facilitate the more accurate identification of candidate genes. Higher imputation accuracy, time‐saving algorithms, improved models and comprehensive databases will accelerate the identification of causal genes or mutations, which will contribute to genomic selection and pig breeding in the future. 相似文献
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Analytic results obtained using simple models show that estimates of selection response of univariate experiments using animal models are completely dependent on the heritability used as prior when fixed effects are nested within generations, and both on the prior and on the true heritability parameter when fixed effects overlap across generations. Univariate animal model estimators of correlated changes of a trait not selected directly are usually biased. The absolute value of the estimate of the correlated response is smaller than the true value when the traits are only genetically correlated and larger than the expected value of zero when they are only environmentally correlated. The validity of the results derived from the analysis of simple models is confirmed using computer simulations, which illustrate the magnitude of the bias. It is emphasized that use of univariate animal models to estimate response in breeding programs whose breeding objectives include several correlated traits may lead to erroneous conclusions. 相似文献
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H. Uribe L. R. Schaeffer J. Jamrozik T. J. Lawlor 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2000,117(4):247-259
Random regression models were applied to eight conformation traits (i.e. stature, rump angle, thurl width, rear leg set, rear udder width, rear udder height, udder depth, and fore udder attachment) of Holstein cows from the northeastern United States. Covariates for fixed and random regressions included age and age‐squared for six of the traits, and two additional covariates were included for rear udder width and rear udder height. Other effects in the model were herd—year‐classifier and months in milk. Fixed covariates were nested within year of birth of the cow. Variance components were estimated using Bayesian theory and Gibbs sampling procedure. Estimated breeding values from the random regression models were compared to two single trait models. The first model utilized only the first classification record of the cow in first lactation, and the second model utilized all classifications of the cow in a simple repeatability model. Additive genetic merit for conformation traits changed with the age of the animal. Some traits were affected by age more than others. The single trait, single record model and the simple repeatability model were not appropriate in predicting breeding values at mature ages for rear udder width and rear udder height. 相似文献
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通过对湖北白猪新系90头样本的话体测定性状的9个变量与屠宰测定性状的10个变量之间的典型相关分析,得出了决定两组性状间相关关系的三对典型变量.湖北白猪活体测定性状与屠宰测定性状之间的相关主要是由:腹围、臀宽及活体膘厚与板油率密切相关,胸围、臀宽、臀长、臀围与屠宰率及后腿比例密切相关,及体长、胸围与瘦肉率和肥肉率间的较强相关所决定的.分析表明在湖北白猪新品系选育中,要加强胸围选择,注意保持适宜的体长.可以依据三个活体性状典型变量的信息利用达到改良屠宰性状的目的. 相似文献
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G. Freyer P. Sørensen C. Kühn R. Weikard 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2004,121(1):40-51
The primary aim of this study was to investigate the quantitative trait loci (QTL) on BTA6 that affect negatively correlated milk traits, using bivariate covariance component analysis of milk yield and fat (or protein) content, protein yield and fat content, and fat yield and protein content. A set of five different genetic models was adapted to differentiate trait‐specific QTL in close linkage from pleiotropy. Using a grand‐daughter design consisting of five half‐sib families from the German Holstein population and 298 sons genotyped for 16 microsatellite markers on BTA6, we found significant trait‐specific QTL for fat content and protein yield, 24 cM apart. Markers BM1329 and FBN12 bracketed the QTL for fat content, and the region between TGLA37 and FBN13 most likely harbours a QTL for protein yield. The analysis based on the close linkage model fully confirmed this result. Despite the pure QTL findings confirming results from the literature, distinguishing pleiotropic and closely linked QTL for competitive traits is a new aspect. Our multivariate analysis results did not suggest a pleiotropic QTL for the investigated negatively correlated traits. The QTL‐based trait correlations were discussed as an important aspect of modelling that needs to be considered in the future. 相似文献
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Breakeven prices for recording of indicator traits to reduce the environmental impact of milk production 
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下载免费PDF全文 H. Hansen Axelsson J.R. Thomasen A.C. Sørensen L. Rydhmer M. Kargo K. Johansson W.F. Fikse 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2015,132(1):30-41
A breeding scheme using genomic selection and an indicator trait for environmental impact (EI) was studied to find the most effective recording strategy in terms of annual monetary genetic gain and breakeven price for the recording of indicator traits. The breakeven price shows the investment space for developing a recording system for an indicator trait. The breeding goal consisted of three traits – milk production, functional trait and environmental impact – with economic values of €83, €82 and €?83, respectively. The first scenario included only breeding goal traits and no indicator traits (NoIT). The other scenarios included all three breeding goal traits and one indicator trait (IT) for EI. The indicator traits were recorded on a large scale (stayability after first lactation and stature), medium scale (live weight and greenhouse gases (GHG) measured in the breath of the cow during milking) or small scale (residual feed intake and total enteric methane measured in a respiration chamber). In the scenario with stayability, the genetic gain in EI was over 11% higher than it was in NoIT. The breakeven price of recording stayability was €8 per record. Stayability is easy to record in the national milk recording system, and its use as an indicator trait for EI would not generate any additional recording costs. Therefore, stayability would be a good indicator trait to use to mitigate EI. The highest genetic gain in EI (23% higher compared to NoIT) was achieved when the GHG measured in the breath of the cow was used as indicator trait. The breakeven price for this indicator trait was €29 per record in the reference population. Ideally the recording of a specific indicator trait for EI would take place when: (i) the genetic correlation between the IT and EI is high; and (ii) the number of phenotypic records for the indicator trait is high enough to achieve a moderately high reliability of direct genomic values. 相似文献
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It is costly and time‐consuming to carry out dairy cattle selection on a large experimental scale. For this reason, sire and cow evaluations are almost exclusively based on field data, which are highly affected by a large array of environmental factors. Therefore, it is crucial to adjust for those environmental effects in order to accurately estimate the genetic merits of sires and cows. Index selection is a simple extension of the ordinary least squares under the assumption that the fixed effects are assumed known without error. The mixed‐model equations (MME) of Henderson provide a simpler alternative to the generalized least squares procedure, which is computationally difficult to apply to large data sets. Solution to the MME yields the best linear unbiased estimator of the fixed effects and the best linear unbiased predictor (BLUP) of the random effects. In an animal breeding situation, the random effects such as sire or animal represent the animal's estimated breeding value, which provides a basis for selection decision. The BLUP procedure under sire model assumes random mating between sires and dams. The genetic evaluation procedure has progressed a long way from the dam‐daughter comparison method to animal model, from single trait to multiple trait analysis, and from lactational to test‐day model, to improve accuracy of evaluations. Multiple‐trait evaluation appears desirable because it takes into account the genetic and environmental variance‐covariance of all traits evaluated. For these reasons, multiple‐trait evaluation would reduce bias from selection and achieve a better accuracy of prediction as compared to single‐trait evaluation. The number of traits included in multiple‐trait evaluation should depend upon the breeding goal. Recent advances in molecular and reproductive technologies have created great potential for quantitative geneticists concerning genetic dissection of quantitative traits, and marker‐assisted genetic evaluation and selection. 相似文献