Malachy Campbell
Cornell University

With the advent of high-throughput phenotyping and the growth of ‘omics data, the focus of many genetic studies has transitioned from one or a few traits to many, often highly correlated, traits. Effectively utilizing these data for genomic inference and/or prediction remains a major challenge. Here, I will discuss the extension of conventional quantitative genetic frameworks to accommodate these data, with particular emphasis on longitudinal traits in rice and metabolomics in oat.