An important, unresolved question in genome‐wide association studies is whether there are
predictable differences in power between single nucleotide polymorphism (SNP) and …

Use of mixed models is in the spotlight as an emerging method for genome-wide association
studies (GWASs). This study investigated the statistical power for identifying nucleotide …

Genomic selection holds a great promise to accelerate plant breeding via early selection
before phenotypes are measured, and it offers major advantages over marker-assisted …

Linear mixed models (LMM) that tests trait association one marker at a time have been the
most popular methods for genome-wide association studies. However, this approach has …

Background Genome-wide approaches to analyze single nucleotide polymorphism (SNP)
data have proliferated due to the increased availability and affordability of markers, but in …

Naturally occurring functionally variable alleles in specific genes within a population allows
the identification of which genes are involved in the determination of which phenotypes. The …

Genome-wide association studies (GWAS) have revolutionized the investigation of complex
traits over the past decade and have unveiled numerous useful genotype–phenotype …

Populations structured into genetic groups may display group-specific linkage
disequilibrium, mutations, and/or interactions between quantitative trait loci and the genetic …

Genome-wide association study (GWAS) has become an obvious general approach for
studying traits of agricultural importance in higher plants, especially crops. Here, we present …

Association analysis is a relatively novel approach in quantitative traits studies that allows
high resolution mapping and time efficient and direct application on breeding material. Since …