Association analyses that exploit the natural diversity of a genome to map at very high
resolutions are becoming increasingly important. In most studies, however, researchers must …

Software programs that conduct genome-wide association studies and genomic prediction
and selection need to use methodologies that maximize statistical power, provide high …

Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to
various agro-climatic conditions is important to world food security. Here we have identified ∼…

Mixed linear model (MLM) methods have proven useful in controlling for population structure
and relatedness within genome-wide association studies. However, MLM-based methods …

Flowering time is a complex trait that controls adaptation of plants to their local environment
in the outcrossing species Zea mays (maize). We dissected variation for flowering time with a …

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled
by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population …

The goal of many plant scientists' research is to explain natural phenotypic variation in terms
of simple changes in DNA sequence. Traditionally, linkage mapping has been the most …

Along with the development of high-throughput sequencing technologies, both sample size
and SNP number are increasing rapidly in genome-wide association studies (GWAS), and …

Genome-wide association study (GWAS) and genomic prediction/selection (GP/GS) are the
two essential enterprises in genomic research. Due to the great magnitude and complexity of …

Whereas breeders have exploited diversity in maize for yield improvements, there has been
limited progress in using beneficial alleles in undomesticated varieties. Characterizing …