This repository contains the analysis and code developed in PS 756 - Quantitative Genetics course at South Dakota State University by Guilherme Olivera, Mandeep Singh & Subash Thapa. The project aims to conduct a Multi-Trial Analysis exploring Genotype x Environment Interaction (G x E), including various analysis methods and genomic selection approaches. The analysis uses two different open datasets, as outlined below.
The main objective of this project is to conduct a Multi Trial Analysis, covering:
- GxE Analysis (+ GGE Analysis)
- AMMI Analysis
- GGI Analysis
- FW Analysis
- Genomic Selection Approach with a focus on GxE interaction. The project consists of two main parts, each utilizing a different dataset for analysis.
Source: The open dataset made available by Dias et al. (2018) contains phenotypic data of five drought tolerance traits measured in 308 hybrids across eight environments contrasting for water availability. Subset: For practical purposes, a subgroup of 202 hybrids is used. Traits Analyzed: -Grain Yield (GY) -Ears per Plot (EPP) -Female Flowering Time (FFT) -Male Flowering Time (MFT) -Anthesis-Silking Interval (ASI)
Source: Crossa et al. (2013) and Montesinos-Lopez et al. (2016, 2017) contain data on 309 double-haploid maize lines tested in 3 environments with three replications for each line. Traits Analyzed: -Grain Yield (Yield) -Anthesis-Silking Interval (ASI) -Plant Height (PH)
The following methods were used for the analysis:
-GxE Analysis: Exploring the interaction between Genotype and Environment to understand how different genotypes perform across multiple environments.
-GGE (Genotype + Genotype x Environment): A graphical approach to visualize the interaction between genotypes and environments.
-AMMI (Additive Main Effects and Multiplicative Interaction): A statistical model for analyzing GxE interactions.
-GGI (Genotypic-Environment Interaction) Analysis: Analyzing the environmental stability of genotypes.
-FW (Factorial Weighted) Analysis: Exploring weighted factors to analyze the GxE interaction.
-Genomic Selection: Approaches that explore the influence of genetic factors on trait performance across environments, considering GxE.
R Packages: The analysis was conducted using the metan (Olivoto and Lucio, 2020) and statgenGxE reference manuals for conducting GxE and other related analyses. BMTME R Package: We also used the BMTME R package, developed by Montesinos-Lopez et al. (2019), with slight modifications for more comprehensive interpretations and additional analyses.