EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture

Area of Science:

• Genomics
• Environmental Science
• Bioinformatics

Background:

• Envirotyping is crucial for understanding non-genetic influences on organism adaptation.
• Integrating large-scale environmental data (enviromics) into quantitative genomics is challenging.

Purpose of the Study:

• Introduce EnvRtype, a novel R package for user-friendly envirotyping.
• Facilitate the integration of enviromics into quantitative genomics for predictive breeding.

Main Methods:

• Utilizes remote sensing for collecting and processing ecophysiological variables.
• Characterizes environments and generates quantitative environmental descriptors.
• Identifies environmental similarity for enviromic-based kernels in genomic prediction.

Main Results:

• EnvRtype provides a pipeline for collecting and processing raw environmental data.
• Enables environmental characterization and covariable generation.
• Develops enviromic kernels for genomic best-unbiased prediction (GBLUP) and reaction norm modeling.

Conclusions:

• EnvRtype offers a cost-effective pipeline for high-quality enviromic data.
• Enhances genomic prediction accuracy in untested environments.
• Supports diverse genomic studies by integrating reaction norm modeling.