Chapter 9
Genome-Wide Association Studies in Arabidopsis thaliana:
Statistical Analysis and Network-Based Augmentation
of Signals
Tak Lee and Insuk Lee
Abstract
Genome-wide association studies (GWAS) have proven effective at identifying genetic variants and genes
that are associated with phenotypes in humans, animals, and plants. Since most phenotypes of plant species
are complex traits regulated by many genes and their functional interactions, GWAS are increasing in
popularity for genetic dissections of plant phenotypes. For the reference plant, Arabidopsis thaliana,
detailed information on genetic variations became available with the completion of the 1001 Genomes
Project, enabling highly resolved association mapping between chromosomal loci and complex traits.
Improvements have been made in the statistical analysis methods for testing the significance of genotypeto-phenotype associations, thereby substantially reducing the confounding effects of population structures.
Furthermore, there have been large efforts toward post-GWAS augmentation of signals via integration with
other types of information to overcome the limited statistical power of GWAS. This chapter describes the
stepwise procedure of GWAS in Arabidopsis, focusing on data analysis processes including preprocessing of
genotype and phenotype data, statistical analysis to identify phenotype-associated chromosomal loci,
identification of phenotype-associated genes based on the phenotype-associated loci, and finally networkbased augmentation of GWAS signals to identify additional candidate genes for the phenotype.
Key words Genome-wide association study, Arabidopsis thaliana, Genotype-to-phenotype association, Network-based augmentation
1 Introduction
A wide variety of interactions with the environment have shaped
robust yet highly complex genomes and their regulatory networks
in plant species. Since most, if not all, phenotypes in plants are
controlled by many genes and their interactions, genetic dissection
of complex plant traits such as stress response and organ development is still technically very challenging. Recently, mapping of
quantitative trait loci (QTL) has been substantially improved
owing to the availability of genome-wide markers and advanced
statistical methods for quantification of genotype-to-phenotype
Jose J. Sanchez-Serrano and Julio Salinas (eds.), Arabidopsis Protocols, Methods in Molecular Biology, vol. 2200,
https://doi.org/10.1007/978-1-0716-0880-7_9, © Springer Science+Business Media, LLC, part of Springer Nature 2021
187
Genome-Wide Association Studies in Arabidopsis thaliana:
Statistical Analysis and Network-Based Augmentation
of Signals
Tak Lee and Insuk Lee
Abstract
Genome-wide association studies (GWAS) have proven effective at identifying genetic variants and genes
that are associated with phenotypes in humans, animals, and plants. Since most phenotypes of plant species
are complex traits regulated by many genes and their functional interactions, GWAS are increasing in
popularity for genetic dissections of plant phenotypes. For the reference plant, Arabidopsis thaliana,
detailed information on genetic variations became available with the completion of the 1001 Genomes
Project, enabling highly resolved association mapping between chromosomal loci and complex traits.
Improvements have been made in the statistical analysis methods for testing the significance of genotypeto-phenotype associations, thereby substantially reducing the confounding effects of population structures.
Furthermore, there have been large efforts toward post-GWAS augmentation of signals via integration with
other types of information to overcome the limited statistical power of GWAS. This chapter describes the
stepwise procedure of GWAS in Arabidopsis, focusing on data analysis processes including preprocessing of
genotype and phenotype data, statistical analysis to identify phenotype-associated chromosomal loci,
identification of phenotype-associated genes based on the phenotype-associated loci, and finally networkbased augmentation of GWAS signals to identify additional candidate genes for the phenotype.
Key words Genome-wide association study, Arabidopsis thaliana, Genotype-to-phenotype association, Network-based augmentation
1 Introduction
A wide variety of interactions with the environment have shaped
robust yet highly complex genomes and their regulatory networks
in plant species. Since most, if not all, phenotypes in plants are
controlled by many genes and their interactions, genetic dissection
of complex plant traits such as stress response and organ development is still technically very challenging. Recently, mapping of
quantitative trait loci (QTL) has been substantially improved
owing to the availability of genome-wide markers and advanced
statistical methods for quantification of genotype-to-phenotype
Jose J. Sanchez-Serrano and Julio Salinas (eds.), Arabidopsis Protocols, Methods in Molecular Biology, vol. 2200,
https://doi.org/10.1007/978-1-0716-0880-7_9, © Springer Science+Business Media, LLC, part of Springer Nature 2021
187