Nolan is interested in leveraging these transcriptomic and epigenomic datasets toward improving genome annotation in maize. His research is to use publicly-available datasets to assess and incorporate multi-omics features into an annotation pipeline of maize variety B73. Additionally, he would like to explore a machine-learning approach to epigenomic-guided gene prediction.
Maize is one of the most important crops grown worldwide and the continued development of genomic resources in maize is crucial to improving our understanding of maize biology. This era of affordable sequencing permits exploration of genomes not only at the level of the genomic sequence, but also of transcriptomic, epigenomic, and chromatin features.