Project description:Two complementary protein extraction methodologies coupled with an automated proteomic platform were employed to analyze tissue-specific proteomes and characterize biological and metabolic processes in sweet potato. A total of 74,255 peptides corresponding to 4,321 nonredundant proteins were successfully identified. Data were compared to predicted protein accessions for Ipomea species and mapped on the sweet potato transcriptome and haplotype-resolved genome. A proteogenomics analysis successfully mapped 12,902 peptides against the transcriptome or genome, representing 90.4% of the total 14,275 uniquely identified peptides, predicted 741 new protein-coding genes, and specified 2726 loci where annotations can be further improved. Overall, 39,916 peptides mapped to 3,143 unique proteins in leaves, and 34,339 peptides mapped to 2,928 unique proteins in roots; 32% and 27% unique identified proteins were leaves- and roots-specific, respectively.