# Genomic Prediction from Multi-Environment Trials of Wheat Breeding

## TL;DR

This paper explores how genomic prediction models can improve wheat breeding by considering both genetic and environmental factors in different regions.

## Contribution

The study introduces genomic prediction models that incorporate genotype × environment and epistatic interactions for wheat breeding.

## Key findings

- The FA + G and FA + G + GG models showed the best performance in genomic prediction.
- Prediction accuracy varied depending on the cross-validation and observation history of wheat lines.
- Including epistatic effects in the FA + G model improved prediction effectiveness.

## Abstract

Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However, the economic value of wheat lines is not only influenced by their additive component but also encompasses a non-additive part (e.g., additive × additive epistasis interaction). In this study, genomic prediction models were implemented in three target populations of environments (TPE) in South Asia. Four models that incorporate genotype × environment interaction (G × E) and genotype × genotype (GG) were tested: Factor Analytic (FA), FA with genomic relationship matrix (FA + G), FA with epistatic relationship matrix (FA + GG), and FA with both genomic and epistatic relationship matrices (FA + G + GG). Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests, leading us to infer that the FA + G model effectively captures certain epistatic effects. The wheat lines tested in sites in different TPE were predicted with different precisions depending on the cross-validation employed. In general, the best prediction accuracy was obtained when some lines were observed in some sites of particular TPEs and the worse genomic prediction was observed when wheat lines were never observed in any site of one TPE.