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Genome-wide association analysis of phenotypic plasticity in the maize nested association mapping population

License: GNU General Public License v3.0

R 86.00% Shell 14.00%
maize gwas gxe phenotypic-plasticity

nam_phenotypic_plasticity's Introduction

Distinct genetic architectures for phenotype means and plasticities in Zea mays

Citation

Kusmec, A., S. Srinivasan, D. Nettleton, and P.S. Schnable. (2017) Distinct genetic architectures for phenotype means and plasticities in Zea mays. Nature Plants, 3: 715-23. (https://www.nature.com/articles/s41477-017-0007-7)

You may also be interested in this accompanying perspective.

Introduction

This project uses data on 23 phenotypes measured on ~5,000 maize inbred lines in 4-11 environments (location-years) to study phenotypic plasticity. We found that the candidate genes for average phenotype across environments and for response to environments are different in Zea mays.

Description

Prior to running any of the scripts in the repository, please run 00.install_packages.R to install all R packages required to reproduce these analyses. The necessary directory structure has been preserved through the use of .gitignore files. For the raw data files, please see the paper for links.

  1. phenotypes: These scripts process raw phenotypic data and perform Bayesian Finlay-Wilkinson regression to quantify phenotypic plasticity.
  2. gwas: These scripts perform GWAS for phenotypic plasticity, apply multiple testing correction, and generate lists of significant genetic markers and candidate genes.
  3. enrichment: These scripts summarize the GWAS results, phenotype distributions, and perform enrichment for gene ontology annotations.
  4. networks: These scripts examine gene ontology enrichment results based on a Zea mays protein-protein interaction network. These scripts will need to be supplemented with analyses in Cytoscape as detailed in the manuscript.
  5. h2_rg: These scripts calculate genomic heritability based on annotations of genetic markers and compute additive genetic heritabilities using a multi-trait mixed model.
  6. structure: These scripts summarize population structure and the rate of linkage disequilibrium decay in the population under study.
  7. comparisons: These scripts conduct comparisons between the results of this study and two other studies, one of which explicitly studied phenotypic variability across environments.
  8. figures: These scripts create composite main text and supplementary figures.

License

This repository is free and open source for use in research and is licensed under the terms of GNU GPLv3.

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