Maize genomes to fields (G2F): 2014–2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets

Abstract

Objectives: Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F's genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014-2017. Data description:Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield Within the Genomes to Fields Maize Project

“…In cases where a weather element did not require calibration, the data were simply copied from the regular data column. A more detailed description of the captured environmental information can be found in AlKhalifah et al ( 2018 ) and McFarland et al ( 2020 ).…”

High density genotype storage for plant breeding in the Chado schema of Breedbase

“…The second dataset loaded is a VCF containing 924 Manihot esculenta samples genotyped with 287,952 GBS markers and is available in the Breedbase instance https://cassavabase.org/breeders_toolbox/protocol/6 [ 28 ]. The third dataset loaded is a VCF containing 1,325 Zea mays samples genotyped with 955,690 GBS markers and is available in the Breedbase instance https://imagebreed.org/breeders_toolbox/protocol/5 [ 29 ].…”

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits

“…We used data on maize hybrids from the Genomes-To-Fields Initiative experiments to demonstrate how MegaLMM can leverage genetic correlations across locations in multi-environment trials. We downloaded the agronomic data from the 2014-2017 field seasons from the CyVerse data repository (McFarland et al 2020) and corresponding genomic data. We used TASSEL5 (Bradbury et al…”