基因和残余共差矩阵的结构方程建模,用于在肉牛中进行多路评估
Marcos Jun-Iti Yokoo1, Gustavo de Los Campos2, Vinícius Silva Junqueira3
1Embrapa Southeastern Livestock (CPPSE), Brazilian Agricultural Research Corporation (Embrapa), Rodovia Washington Luis, km 234, São Carlos 13560-970, SP, Brazil.
Animals : an open access journal from MDPI
|March 14, 2026
概括
结构方程模型 (SEM) 为肉牛遗传评估提供了有效的方法. 因子分析 (FA) 和递归 (REC) 模型为估计遗传参数和育种值提供了节的参数化.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 统计遗传学 统计遗传学
背景情况:
- 肉牛遗传评估面临着数据和特征复杂度不断增加的挑战.
- 估计遗传和残余 (共差) 矩阵是计算密集的.
- 有效估计繁殖价值需要节的模型.
研究的目的:
- 应用结构方程模型 (SEM) 进行肉牛遗传评估.
- 将因子分析 (FA) 和递归 (REC) 模型与标准多特征混合模型 (SMTM) 进行比较.
- 评估SEM对生长和尸体特征的效率和一致性.
主要方法:
- 使用了带有因子分析 (FA) 和递归 (REC) 结构的 SEM.
- 使用SMTM和SEM评估了2942头肉牛中的6个特征.
- 对比的参数化,重点是节和计算效率.
主要成果:
- FA2G和REC1模型捕获了与SMTM相比的遗传变异性.
- 在模型中,估计的繁殖值 (EBV) 之间发现了很高的相关性 (0.94-1.00).
- 与SMTM相比,FA2G和REC1模型显示出更大的节 (更少的参数) 和有利的信息标准.
结论:
- SEM,特别是FA和REC结构,为肉牛遗传评估提供了有效的,节的替代方案.
- 这些模型有效地表示协差模式,同时保持EBV的高一致性.
- SEM为复杂的遗传评估提供了一个计算高效的框架.
相关概念视频
Multiple Regression
4.2K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.2K
Multiple Allele Traits
38.6K
The Concept of Multiple Allelism
38.6K
Multiple Allele Traits
14.8K
14.8K
Mechanistic Models: Compartment Models in Individual and Population Analysis
317
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
317
Behavioral Genetics and Its Designs
1.2K
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
1.2K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
1.3K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
1.3K


