Prediction of genetic values has been a focus of applied quantitative genetics since the
beginning of the 20th century, with renewed interest following the advent of the era of whole
genome-enabled prediction. Opportunities offered by the emergence of high-dimensional
genomic data fueled by post-Sanger sequencing technologies, especially molecular
markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to
confront new challenges. In particular, kernel methods are gaining consideration as a …