评估使用统计和机器学习方法来估计使用基因组信息在13种牛品种中纯种和杂种动物的品种组成
Frontiers in genetics
|June 5, 2023
概括
使用基因组数据可以实现准确的牛品种组成预测. 混合和SNP-BLUP方法都显示出高精度,将SNP-BLUP集成到现有的基因组评估中是一个强大的解决方案.
科学领域:
- 动物遗传学动物遗传学
- 生物信息学是一种生物信息学.
- 量化遗传学 量化遗传学
背景情况:
- 基因组信息可以准确预测牛品种组成,这对于遗传评估,交配计划和质量控制至关重要.
- 对比预测方法和基因型密度的影响对于优化牛养殖中基因组应用至关重要.
研究的目的:
- 为了比较Admixture软件和SNP-BLUP之间的品种组成预测准确度.
- 评估低密度基因型面板的稳定性,以预测品种组成.
主要方法:
- 利用了来自13种牛品种的49,213个自体SNP的数据库.
- 采用混合和SNP-BLUP方法来预测品种组成.
- 使用不同SNP密度的纯种和杂种种群的验证准确性.
主要成果:
- 使用所有SNP,添加剂和SNP-BLUP显示出极小的差异 (0.04绝对平均差异).
- 与纯种 (≥2,000) 相比,交叉品种需要更多的SNP (≥3,000) 进行准确的预测.
- 低密度面板 (<2,000个SNP) 导致更高的预测差异,特别是在SNP-BLUP.
结论:
- 用Admixture和SNP-BLUP来预测品种组成非常准确,特别是有足够的SNP (≥3,000).
- 可以将SNP-BLUP集成到现有的基因组评估管道中,不需要单独的软件.
- 可以使用低密度面板,但需要仔细考虑SNP数量以获得最佳准确度.
相关概念视频
02:54Evolutionary Relationships through Genome Comparisons
5.9K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.9K
01:29Modern Molecular Taxonomy
56
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
56
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
85
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
85
01:35Pedigree Analysis
84.5K
Overview
84.5K
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
67
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...
67
02:02Genomics
36.5K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
36.5K