Structural variants (SVs) are known to have large functional impacts on phenotypes of
agricultural interest, but they have yet to be routinely used for GWAS. Apart from the difficulty …

Genome-wide association study (GWAS) has become a widely accepted strategy for
decoding genotype-phenotype associations in many species thanks to advances in next …

Genome-wide association mapping studies (GWAS) based on Big Data are a potential
approach to improve marker-assisted selection in plant breeding. The number of available …

High-throughput genotyping boosts genome-wide association studies (GWAS) in crop
species, leading to the identification of single-nucleotide polymorphisms (SNPs) associated …

Association mapping based on the linkage disequilibrium provides a promising tool to
identify genes responsible for quantitative variations underlying complex traits. Presented …

Key message Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which
control yield-related traits in maize. The candidate gene GRMZM2G098557 was further …

Simple Summary Genome-wide association studies (GWAS) have successfully detected
many SNPs related to complex quantitative traits. However, SNPs significantly associated …

Both genome‐wide association studies (GWAS) and genomic selection (GS) are done using
phenotypic and genomic data. The phenotypic data are usually based on multi‐environment …

Genome‐wide association studies (GWAS) have developed into a powerful and ubiquitous
tool for the investigation of complex traits. In large part, this was fueled by advances in …

The duplicated and the highly repetitive nature of the maize genome has historically
impeded the development of true single nucleotide polymorphism (SNP) markers in this …