The exponential rise in genome sequences has subsequently led to the increase in the importance of assigning functional annotations to genes. Annotating gene functions to genome assemblies is necessary to make assembly resources useful for biological inference. Many annotation tools have been developed, including the Gene Ontology Meta Annotator for Plants (GOMAP; https://dill-picl.org/projects/gomap/), a tool developed by our lab. GOMAP is a high-throughput genome-scale annotation tool and pipeline of plants that combines sequence-similarity, domain-presence, and mixed-method based approaches to annotate gene ontology (GO) terms to given protein sequences. The output generated is a single aggregate dataset representing the gene functions of a genome. In this study, we annotated the newly resequenced Zea mays B73 genome, B73v5, using GOMAP. Maize is the most widely planted crop in the world and a well-known model system for the study of gene function, and B73 serves as an important genome to allow for characterization of the species pan-genome and the extent of structural variation. Ultimately, three categories, or sub-ontologies, of GO terms are assigned to the genes in the genome, namely cellular component, molecular function, and biological process. With GOMAP, we assign these GO terms to maize B73v5 to construct gene functions for the genome. We compare our resulting dataset with that of previously annotated B73v3 and B73v4 datasets. B73v5 exhibited 8-15% more biological process term assignments, 4-11% less cellular component term assignments, and 4% less molecular function term assignments comparatively. Additionally, the differences in GO terms were investigated in each dataset. We find that GOMAP is a beneficial tool for GO-based genome annotation and ultimately for comparative functional genomics.