米现象选择的表现:种群大小和基因型与环境相互作用对预测能力的影响
Hugues de Verdal1,2,3, Vincent Segura1,4, David Pot1,2
1AGAP Institut, Université Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France.
PloS one
|December 23, 2024
概括
使用近红外光谱 (NIRS) 数据的现象预测 (PP) 可以与米育种中的基因组预测 (GP) 准确性相匹配. 多环境数据是PP的关键.
科学领域:
- 植物育种和遗传学 植物育种和遗传学
- 农业科学 农业科学
- 定量遗传学 是一种定量遗传学.
背景情况:
- 基因组预测 (GP) 是植物育种中的标准工具.
- 使用近红外光谱学 (NIRS) 的现象预测 (PP) 提供了一个潜在的更快,更便宜的替代方案.
- 影响PP准确性的因素,特别是与GP相比,需要进行调查.
研究的目的:
- 调查培训人口规模,多环境数据和基因型x环境 (GxE) 对PP准确性的影响.
- 为了比较PP与GP对关键大米农学特征的预测准确度.
- 确定PP在育种计划中成为GP可行的替代品的最佳条件.
主要方法:
- 评估了包括花开时间,植物高度,产量和谷物含量在内的特征的预测准确性.
- 在不同培训人群大小,单个与多个环境数据以及具有/没有GxE效应的情况下评估了PP和GP.
- 使用了PP的高光谱NIRS数据和GP的分子标记数据.
主要成果:
- 培训人群规模和GxE效应对PP准确度的影响很小.
- 环境的数量是PP准确性的最关键因素.
- 当使用多环境数据时,PP实现了与GP可比的准确性,在单个环境中表现优于GP.
结论:
- 现象预测 (PP) 可以在米育种中实现基因组预测 (GP) 准确度,特别是使用多环境数据.
- PP在成本和吞吐量方面提供了显著的优势,可能减少育种周期时间.
- 在作物改进计划中,PP是一种有前途的工具,可以加速基因收益,前提是基因型具有NIRS测量.
相关概念视频
02:27Background and Environment Affect Phenotype
6.4K
Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
6.4K
01:21Frequency-dependent Selection
21.8K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
21.8K
01:46Types of Selection
40.1K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
40.1K
01:20Gene-Environment Interactions
249
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
249
02:46Chi-square Analysis
37.4K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
37.4K
01:25Multiple Regression
2.9K
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...
2.9K