Envirotyping is an essential technique used to unfold the non-genetic drivers associated with the phenotypic adaptation of living organisms. Here we introduce the EnvRtype R package, a novel toolkit developed to interplay large-scale envirotyping data (enviromics) into quantitative genomics. To start a user-friendly envirotyping pipeline, this package offers: (1) remote sensing tools for collecting (get_weather and extract_GIS functions) and processing ecophysiological variables (processWTH function) from raw environmental data at single locations or worldwide; (2) environmental characterization by typing environments and profiling descriptors of environmental quality (env_typing function), in addition to gathering environmental covariables as quantitative descriptors for predictive purposes (W_matrix function); and (3) identification of environmental similarity that can be used as an enviromic-based kernel (env_typing function) in whole-genome prediction (GP), aimed at increasing ecophysiological knowledge in genomic best-unbiased predictions (GBLUP) and emulating reaction norm effects (get_kernel and kernel_model functions). We highlight literature mining concepts in fine-tuning envirotyping parameters for each plant species and target growing environments. We show that envirotyping for predictive breeding collects raw data and processes it in an eco-physiologically-smart way. Examples of its use for creating global-scale envirotyping networks and integrating reaction-norm modeling in GP are also outlined. We conclude that EnvRtype provides a cost-effective envirotyping pipeline capable of providing high quality enviromic data for a diverse set of genomic-based studies, especially for increasing accuracy in GP across untested growing environments.

中文翻译：

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EnvRtype：一种在农业中相互作用环境学和定量基因组学的软件

环境分型技术是一种必不可少的技术，可用于展开与生物体表型适应相关的非遗传驱动因素。在这里，我们介绍EnvRtype R软件包，这是一种新颖的工具包，其开发目的是将大规模环境定型数据（环境经济学）与定量基因组学相互影响。为了启动用户友好的环境建模流程，此程序包提供：（1）遥感工具，用于从单个地点或全球范围内的原始环境数据收集（get_weather和extract_GIS函数）和处理生态生理变量（processWTH函数）；（2）除了收集环境协变量作为用于预测目的的定量描述符（W_matrix函数）外，还通过键入环境和对环境质量进行概要分析（env_typing函数）来进行环境表征；（3）鉴定可在全基因组预测（GP）中用作基于环境的内核（env_typing函数）的环境相似性，旨在增加基因组最佳无偏预测（GBLUP）中的生态生理知识并模拟反应规范效应（get_kernel和kernel_model函数）。我们将在针对每种植物物种和目标生长环境的环境参数微调中突出文献挖掘概念。我们表明，预测繁殖的环境分型可以收集原始数据并以生态生理智能的方式对其进行处理。还概述了其用于创建全球规模的环境建模网络和在GP中集成反应规范模型的示例。