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Datasets to build marker effect networks

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Datasets to build marker effect networks

Published Date

2023-01-23

Author Contact

Hirsch, Candice N
cnhirsch@umn.edu

Type

Dataset
Experimental Data
Field Study Data
Genomics Data

Abstract

This dataset contains the input files to build marker effect networks and identify markers associated with environmental adaptability. These networks are built by adapting commonly used software for building gene co-expression networks with marker effects across growth environments as the input data into the networks. Here, we provide grain yield data from 400 maize hybrids grown across nine environments in the U.S. Midwest, a set of ~10,000 non-redundant markers, and environmental data containing 17 weather parameters in 3-day intervals collected from planting date to the end of the season. For instructions on how to perform this analysis and analysis script, please see https://github.com/HirschLabUMN/meffs_networks. For more details on marker effect networks, please see preprint on https://www.biorxiv.org/content/10.1101/2023.01.19.524532v1.

Description

Files include yield data (raw and BLUEs) of maize hybrids across different growth environments, genotypic data of maize inbred lines (parental and RILs) and hybrids, and environmental covariates data. More detailed information for each file can be found in the README file.

Referenced by

Rafael Della Coletta, Sharon E. Liese, Samuel B. Fernandes, Mark A. Mikel, Martin O. Bohn, Alexander E. Lipka, Candice N. Hirsch. 2023. Linking genetic and environmental factors through marker effect networks to understand trait plasticity. bioRxiv.
https://doi.org/10.1101/2023.01.19.524532

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United States Department of Agriculture (2018-67013-27571)
Minnesota Agricultural Experiment Station

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Della Coletta, Rafael; Liese, Sharon E; Fernandes, Samuel B; Mikel, Mark A; Bohn, Martin O; Lipka, Alexander E; Hirsch, Candice N. (2023). Datasets to build marker effect networks. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/b1e0-q828.

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