Genomic studies have the potential to characterize differences in sequence or gene expression across the whole genome. There is great potential to harness genomic datasets to develop models to explain and predict phenotypic variation. The Springer lab has collaborations with Steve Briggs, Erich Grotewold and Chad Myers that aim to connect variation in transcriptome data with gene regulatory networks. Our goal is to develop models that integrate gene expression profiles and genetic variation data to explain phenotypic differences. These projects will develop resources to assist with the characterization of QTL and breeding efforts for a variety of traits. This research has been supported by the National Science Foundation and the United State Department of Agriculture.

• Check our maizeGRN website