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
Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, ...Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.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
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 National Basic Research Program of China (No. 2006CB101708)National Science and Technology Supporting Item of China (No. 2006BAD10A00).
文摘Crop seeds are important sources of protein, oil, and carbohydrates for food, animal feeds, and industrial products. Recently, much attention has been paid to quality and functional properties of crop seeds. However, seed traits possess some distinct genetic characteristics in comparison with plant traits, which increase the difficulty of genetically improving these traits. In this study, diallel analysis for seed models with genotype by environment interaction （GE） effect was applied to estimate the variance-covariance components of seed traits. Mixed linear model approaches were used to estimate the genetic covariances between pair-wise seed and plant traits. The breeding values （BV） were divided into two categories for the seed models. The first category of BV was defined as the combination of direct additive, cytoplasmic, and maternal additive effects, which should be utilized for selecting stable cultivars over multi-environments. The three genetic effects, together with their GE interaction, were included in the second category of BV for selecting special lines to be grown in specific ecosystems. Accordingly, two types of selection indices for seed traits, i.e., general selection index and interaction selection index, were developed and constructed on the first and the second category BV, respectively. These proposed selection indices can be applied to solve the difficult task of simultaneously improving multiple seed traits in various environments. Data of crop seeds with regard to four seed traits and four yield traits based on the modified diallel crosses in Upland cotton （Gossypium hirsutum L.） were used as an example for demonstrating the proposed methodology.
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.
