基于RGxEStat的基因-环境交互作用显著性及稳定性分析

摘要

基因型与环境互作（GxE）通过影响基因型在不同环境中的表现，降低了目标环境下表型预测的准确性。深入解析GxE互作机制有助于揭示遗传优势或缺陷在特定环境条件下如何被表达或抑制，从而指导遗传选择并优化育种策略。本文重点介绍两种GxE互作研究模型：其一是基于混合效应模型的显著性分析，用于判定基因或GxE互作是否对表型性状产生显著影响；其二是稳定性分析，深入探究基因与环境间的交互关系以及基因型在不同环境中的相对优劣。此外，本文推出由作者团队开发的轻量级交互工具RGxEStat，该工具集成上述模型的构建、求解与可视化功能，旨在使育种家和农学家无需学习复杂的SAS或R编程即可通过友好界面实现高效育种数据分析，显著加速研究周期。代码与数据集详见https://github.com/mason-ching/RGxEStat。

English

Genotype-by-Environment (GxE) interactions influence the performance of genotypes across diverse environments, reducing the predictability of phenotypes in target environments. In-depth analysis of GxE interactions facilitates the identification of how genetic advantages or defects are expressed or suppressed under specific environmental conditions, thereby enabling genetic selection and enhancing breeding practices. This paper introduces two key models for GxE interaction research. Specifically, it includes significance analysis based on the mixed effect model to determine whether genes or GxE interactions significantly affect phenotypic traits; stability analysis, which further investigates the interactive relationships between genes and environments, as well as the relative superiority or inferiority of genotypes across environments. Additionally, this paper presents RGxEStat, a lightweight interactive tool, which is developed by the authors and integrates the construction, solution, and visualization of the aforementioned models. Designed to eliminate the need for breeders and agronomists to learn complex SAS or R programming, RGxEStat provides a user-friendly interface for streamlined breeding data analysis, significantly accelerating research cycles. Codes and datasets are available at https://github.com/mason-ching/RGxEStat.

基于RGxEStat的基因-环境交互作用显著性及稳定性分析

Significance and Stability Analysis of Gene-Environment Interaction using RGxEStat

摘要

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