In order to determine various traits which need to be improved for improving the productive life span and longevity, purebred Sahiwal cows available at bull mother experimental farm and cattle breeding farm located at...In order to determine various traits which need to be improved for improving the productive life span and longevity, purebred Sahiwal cows available at bull mother experimental farm and cattle breeding farm located at Veterinary College, Durg, Chhattisgarh, India were used. For present investigation, 17 linear type traits were measured, scaled and scored as per the guidelines of International Committee for Animal Recording （2001）. The average score point （ASP） under 1-9 point scale score system along with respective observed group for different linear type traits were stature （6.88; taller）, chest width （5.30; intermediate）, body depth （4.11; intermediate）, rump angle （4.27; intermediate）, rump width （5.09; intermediate）, rear leg set-side view （4.55; intermediate）, rear leg set-rear view （5.95; intermediate）, foot angle （5.66; intermediate）, udder depth （5.71; intermediate）, rear udder height （4.90; intermediate）, udder balance （5.27; intermediate）, udder cleft （3.75; intermediate）, fore udder attachment （5.55; intermediate）, teat length （3.54; intermediate）, fore teat placement （5.33; intermediate）, rear teat placement （6.37; intermediate） and teat thickness （2.76; narrow）. For most of the traits, ASP which lies near midpoint （i.e. near five） is known to be ideal for dairy type cattle. Moreover, some traits also showed the presence of undesirable ASP. Hence, the traits such as body depth, rump angle, foot angle, udder depth, rear udder height, udder cleft, fore udder attachment, teat length, and teat thickness needs to be improved for improving the production sustainability and herd life of Sahiwal cattle. Thus, present investigation gives explicit clue to incorporate these conformation traits in selection program of this valuable germplasm commonly found in Southern part of Asia （India, Pakistan, Srilanka, etc.）.展开更多
Field pea(Pisum sativum L.) is an important protein-rich pulse crop produced globally. Increasing the lipid content of Pisum seeds through conventional and contemporary molecular breeding tools may bring added value t...Field pea(Pisum sativum L.) is an important protein-rich pulse crop produced globally. Increasing the lipid content of Pisum seeds through conventional and contemporary molecular breeding tools may bring added value to the crop. However, knowledge about genetic diversity and lipid content in field pea is limited. An understanding of genetic diversity and population structure in diverse germplasm is important and a prerequisite for genetic dissection of complex characteristics and marker-trait associations. Fifty polymorphic microsatellite markers detecting a total of 207 alleles were used to obtain information on genetic diversity, population structure and marker-trait associations. Cluster analysis was performed using UPGMA to construct a dendrogram from a pairwise similarity matrix. Pea genotypes were divided into five major clusters. A model-based population structure analysis divided the pea accessions into four groups. Percentage lipid content in 35 diverse pea accessions was used to find potential associations with the SSR markers. Markers AD73, D21, and AA5 were significantly associated with lipid content using a mixed linear model(MLM) taking population structure(Q) and relative kinship(K) into account. The results of this preliminary study suggested that the population could be used for marker-trait association mapping studies.展开更多
Based on the genetic models for triploid endosperm traits and on the methods for mapping diploid quantitative traits loci (QTLs), the genetic constitutions, components of means and genetic variances of QTL controlling...Based on the genetic models for triploid endosperm traits and on the methods for mapping diploid quantitative traits loci (QTLs), the genetic constitutions, components of means and genetic variances of QTL controlling endosperm traits under flanking marker genotypes of different generations were presented. From these results, a multiple linear regression method for mapping QTL underlying endosperm traits in cereals was proposed, which used the means of endosperm traits under flanking marker genotypes as a dependent variable, the coefficient of additive effect (d) and dominance effect (h1 and/or h2) of a putative QTL in a given interval as independent variables. This method can work at any position in a genome covered by markers and increase the estimation precision of QTL location and their effects by eliminating the interference of other relative QTLs. This method can also be easily used in other uneven data such as markers and quantitative traits detected or measured in plants and tissues different either in generations or at chromosomal ploidy levels, and in endosperm traits controlled by complicated genetic models considering the effects produced by genotypes of both maternal plants and seeds on them.展开更多
Simple linear regression analysis has been used to map QTL for quantitative traits. Many traits of biological interest and/or economical importance in various species show binary phenotypic distributions (e.g., presen...Simple linear regression analysis has been used to map QTL for quantitative traits. Many traits of biological interest and/or economical importance in various species show binary phenotypic distributions (e.g., presence or absence). It has been shown that such a binary trait also can be analyzed with the simple linear regression, subject to virtually no loss in power compared to the generalized linear model analysis. Binary trait is a special case of a multiple categorical trait (e.g., low, medium or high). We propose a mechanism to decompose a multiple categorical trait into an array of correlated binary variables. The categorical trait turned multiple binary traits are analyzed with a multivariate linear regression method. Turning the problem of categorical trait mapping into that of multivariate mapping allows the exploration of pleiotropic effects of QTL for different categories. Efficiency of the method is verified through a series of simulation experiments.展开更多
【目的】揭示基于动物模型最佳线性无偏预测(animal model best linear unbiased prediction,AM-BLUP)的选择指数对杜洛克猪生长及繁殖性状的选育效果。【方法】在采用AM-BLUP方法估计个体目标性状育种值基础上,以达100 kg体质量日龄(...【目的】揭示基于动物模型最佳线性无偏预测(animal model best linear unbiased prediction,AM-BLUP)的选择指数对杜洛克猪生长及繁殖性状的选育效果。【方法】在采用AM-BLUP方法估计个体目标性状育种值基础上,以达100 kg体质量日龄(相对权重0.7)和100 kg活体背膘厚(相对权重0.3)为主选性状构建选择指数,对1个闭锁的杜洛克猪群开展持续7年(2013—2019年)的选育,系统分析选育期间猪群6个生长及繁殖性状表型值、估计育种值(estimated breeding value,EBV)、选择指数及近交系数的变化。【结果】相较于2013年,2019年猪群达100 kg体质量日龄、100 kg活体背膘厚和30~100 kg料重比分别极显著缩短4.45 d、降低0.52 mm和降低0.05(P<0.01);初产和经产母猪的总产仔数分别提高0.99头(P<0.05)和1.02头(P>0.05),产活仔数分别提高0.72头和0.49头(P>0.05),21日龄窝重分别降低0.39 kg和提高6.20 kg(P>0.05);主选性状达100 kg体质量日龄和100 kg活体背膘厚的EBV分别极显著降低3.447和0.533(P<0.01),选择指数极显著提高23.62(P<0.01),除30~100 kg料重比外,其余辅选性状的EBV均获得了不同程度改进。选育结束时,群体平均近交系数为3.1973%,年均增量为0.4904%。【结论】基于AM-BLUP的指数选择可有效改良猪的生产性状,但不同性状的具体选择进展会因其遗传特性的不同而异。展开更多
[目的]肉羊的宰前活重和屠宰性状直接影响其经济价值,本研究分析多羔绵羊新品种群的屠宰性状及其与宰前活重的关系,对新品种选育和生产推广具有参考作用。[方法]测定6、12月龄(各月龄20只羊,公母各半)多羔绵羊的宰前活重(live body weig...[目的]肉羊的宰前活重和屠宰性状直接影响其经济价值,本研究分析多羔绵羊新品种群的屠宰性状及其与宰前活重的关系,对新品种选育和生产推广具有参考作用。[方法]测定6、12月龄(各月龄20只羊,公母各半)多羔绵羊的宰前活重(live body weight,LBW)、胴体重(carcass weight,CW)、净肉重(meat weight,MW)和眼肌面积(eye muscle area,EMA)。对3项屠宰性状与宰前活重进行线性回归分析,分别建立活重与3项屠宰性状间的回归关系。[结果]公母羊屠宰率均在50%以上,除屠宰率外,多羔绵羊12月龄的屠宰性状均高于6月龄。6月龄多羔绵羊宰前活重和屠宰率相比国内其他优良绵羊品种均属较高水平。在各月龄间,活重与胴体重、净肉重和眼肌面积间存在极显著的回归关系。[结论]多羔绵羊生长发育快、产肉性能高,可用宰前活重估算各月龄的相关屠宰性状值。展开更多
全基因组关联分析(genome-wide association study,GWAS)是定位基因组中与性状显著关联的变异位点的有效方法。随着表型记录的完善、高通量基因型分型技术的发展,以及统计方法的改进,全基因组关联分析在人类疾病、动物植物遗传等领域得...全基因组关联分析(genome-wide association study,GWAS)是定位基因组中与性状显著关联的变异位点的有效方法。随着表型记录的完善、高通量基因型分型技术的发展,以及统计方法的改进,全基因组关联分析在人类疾病、动物植物遗传等领域得到了广泛的应用。假阳性是影响全基因组关联分析结果可靠性的重要因素之一。为了控制假阳性,除了校正P值,GWAS模型从最简单的方差分析(或用于质量性状的卡方检验)到加入固定效应协变量的普通线性模型(general linear model,GLM),再到加入随机效应的混合线性模型(mixed linear model,MLM)持续改进,控制了多种混杂因素导致的假阳性。将个体的遗传效应拟合为由基因组亲缘关系矩阵(genomic relationships matrix,GRM)定义的随机效应是目前常用的方法。由于MLM的参数估计大量消耗计算资源,研究人员不断尝试模型求解优化和GRM的构建优化(GRM的构建优化同时也提高了计算效率),最终将基于MLM计算的时间复杂度由O(MN3)逐步改进到O(MN),实现了计算速度与统计功效的飞跃。针对质量性状病例对照比失衡带来的假阳性问题,研究人员进一步对广义混合线性模型(generalized linear mixed model,GLMM)进行了校正。本文较全面地介绍了GWAS的基本原理和发展,着重阐述了GWAS中MLM模型的改进和优化细节,同时,列举了GWAS在农业中的应用,包括在植物、动物和微生物方面的研究成果,以及基于单倍型的GWAS应用。最后,从进一步提高GWAS统计功效和GWAS试验设计2个角度对GWAS未来的发展进行了展望。展开更多
文摘In order to determine various traits which need to be improved for improving the productive life span and longevity, purebred Sahiwal cows available at bull mother experimental farm and cattle breeding farm located at Veterinary College, Durg, Chhattisgarh, India were used. For present investigation, 17 linear type traits were measured, scaled and scored as per the guidelines of International Committee for Animal Recording （2001）. The average score point （ASP） under 1-9 point scale score system along with respective observed group for different linear type traits were stature （6.88; taller）, chest width （5.30; intermediate）, body depth （4.11; intermediate）, rump angle （4.27; intermediate）, rump width （5.09; intermediate）, rear leg set-side view （4.55; intermediate）, rear leg set-rear view （5.95; intermediate）, foot angle （5.66; intermediate）, udder depth （5.71; intermediate）, rear udder height （4.90; intermediate）, udder balance （5.27; intermediate）, udder cleft （3.75; intermediate）, fore udder attachment （5.55; intermediate）, teat length （3.54; intermediate）, fore teat placement （5.33; intermediate）, rear teat placement （6.37; intermediate） and teat thickness （2.76; narrow）. For most of the traits, ASP which lies near midpoint （i.e. near five） is known to be ideal for dairy type cattle. Moreover, some traits also showed the presence of undesirable ASP. Hence, the traits such as body depth, rump angle, foot angle, udder depth, rear udder height, udder cleft, fore udder attachment, teat length, and teat thickness needs to be improved for improving the production sustainability and herd life of Sahiwal cattle. Thus, present investigation gives explicit clue to incorporate these conformation traits in selection program of this valuable germplasm commonly found in Southern part of Asia （India, Pakistan, Srilanka, etc.）.
基金supported by the Natural Sciences and Engineering Research Council of Canada Collaborative Research and Development and Lefsrud Seeds (CRDRJ385395-09)
文摘Field pea(Pisum sativum L.) is an important protein-rich pulse crop produced globally. Increasing the lipid content of Pisum seeds through conventional and contemporary molecular breeding tools may bring added value to the crop. However, knowledge about genetic diversity and lipid content in field pea is limited. An understanding of genetic diversity and population structure in diverse germplasm is important and a prerequisite for genetic dissection of complex characteristics and marker-trait associations. Fifty polymorphic microsatellite markers detecting a total of 207 alleles were used to obtain information on genetic diversity, population structure and marker-trait associations. Cluster analysis was performed using UPGMA to construct a dendrogram from a pairwise similarity matrix. Pea genotypes were divided into five major clusters. A model-based population structure analysis divided the pea accessions into four groups. Percentage lipid content in 35 diverse pea accessions was used to find potential associations with the SSR markers. Markers AD73, D21, and AA5 were significantly associated with lipid content using a mixed linear model(MLM) taking population structure(Q) and relative kinship(K) into account. The results of this preliminary study suggested that the population could be used for marker-trait association mapping studies.
基金the National Natural Science Foundation(No.39900080).
文摘Based on the genetic models for triploid endosperm traits and on the methods for mapping diploid quantitative traits loci (QTLs), the genetic constitutions, components of means and genetic variances of QTL controlling endosperm traits under flanking marker genotypes of different generations were presented. From these results, a multiple linear regression method for mapping QTL underlying endosperm traits in cereals was proposed, which used the means of endosperm traits under flanking marker genotypes as a dependent variable, the coefficient of additive effect (d) and dominance effect (h1 and/or h2) of a putative QTL in a given interval as independent variables. This method can work at any position in a genome covered by markers and increase the estimation precision of QTL location and their effects by eliminating the interference of other relative QTLs. This method can also be easily used in other uneven data such as markers and quantitative traits detected or measured in plants and tissues different either in generations or at chromosomal ploidy levels, and in endosperm traits controlled by complicated genetic models considering the effects produced by genotypes of both maternal plants and seeds on them.
基金Item supported by national natural sciencefoundation( No.30471236)
文摘Simple linear regression analysis has been used to map QTL for quantitative traits. Many traits of biological interest and/or economical importance in various species show binary phenotypic distributions (e.g., presence or absence). It has been shown that such a binary trait also can be analyzed with the simple linear regression, subject to virtually no loss in power compared to the generalized linear model analysis. Binary trait is a special case of a multiple categorical trait (e.g., low, medium or high). We propose a mechanism to decompose a multiple categorical trait into an array of correlated binary variables. The categorical trait turned multiple binary traits are analyzed with a multivariate linear regression method. Turning the problem of categorical trait mapping into that of multivariate mapping allows the exploration of pleiotropic effects of QTL for different categories. Efficiency of the method is verified through a series of simulation experiments.
文摘全基因组关联分析(genome-wide association study,GWAS)是定位基因组中与性状显著关联的变异位点的有效方法。随着表型记录的完善、高通量基因型分型技术的发展,以及统计方法的改进,全基因组关联分析在人类疾病、动物植物遗传等领域得到了广泛的应用。假阳性是影响全基因组关联分析结果可靠性的重要因素之一。为了控制假阳性,除了校正P值,GWAS模型从最简单的方差分析(或用于质量性状的卡方检验)到加入固定效应协变量的普通线性模型(general linear model,GLM),再到加入随机效应的混合线性模型(mixed linear model,MLM)持续改进,控制了多种混杂因素导致的假阳性。将个体的遗传效应拟合为由基因组亲缘关系矩阵(genomic relationships matrix,GRM)定义的随机效应是目前常用的方法。由于MLM的参数估计大量消耗计算资源,研究人员不断尝试模型求解优化和GRM的构建优化(GRM的构建优化同时也提高了计算效率),最终将基于MLM计算的时间复杂度由O(MN3)逐步改进到O(MN),实现了计算速度与统计功效的飞跃。针对质量性状病例对照比失衡带来的假阳性问题,研究人员进一步对广义混合线性模型(generalized linear mixed model,GLMM)进行了校正。本文较全面地介绍了GWAS的基本原理和发展,着重阐述了GWAS中MLM模型的改进和优化细节,同时,列举了GWAS在农业中的应用,包括在植物、动物和微生物方面的研究成果,以及基于单倍型的GWAS应用。最后,从进一步提高GWAS统计功效和GWAS试验设计2个角度对GWAS未来的发展进行了展望。
