  We introduce a simple approach to understanding the relationship between
single nucleotide polymorphisms (SNPs), or groups of related SNPs, and the
phenotypes they control. The pipeline involves training deep convolutional
neural networks (CNNs) to differentiate between images of plants with reference
and alternate versions of various SNPs, and then using visualization approaches
to highlight what the classification networks key on. We demonstrate the
capacity of deep CNNs at performing this classification task, and show the
utility of these visualizations on RGB imagery of biomass sorghum captured by
the TERRA-REF gantry. We focus on several different genetic markers with known
phenotypic expression, and discuss the possibilities of using this approach to
uncover genotype x phenotype relationships.
