Here we describe the proteome of the fungus Hemileia vastatrix by label free mass spectrometry (LC–MS/MS). H. vastatrix is the causal agent of coffee rust disease, causing great economic losses in this crop. The objective of our work was to identify H. vastatrix proteins potentially involved in host colonization and infection, by exploring the shotgun proteomics approach. A total of 742 proteins were identified and are associated with several crucial molecular functions, biological processes, and cellular components. The proteins identified contribute to a better understanding of the metabolism of the fungus and may help identify target proteins for the development of specific drugs in order to control coffee rust disease. All data can be accessed at the Centre for Computational Mass Spectrometry – MassIVE MSV000087665 -https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=cc71ad75f767451abe72dd1ce0019387

The lack of reference genomes for non-model species hinders our understanding of aluminum (Al) tolerance and accumulation. We present the first high-quality genome assembly of Qualea grandiflora Mart. (Vochysiaceae), an Al-accumulating species endemic to the Brazilian Cerrado. Multi-omics analyses (transcriptomic, proteomic, and metabolomic) reveal that Al is essential for its growth and development. Using a paired-end library and ABySS v2.0, we assembled a genome containing 38,034 annotated genes (63.1% "complete"). Functional annotation via SwissProt/KOG and Blast2GO identified 11 gene families linked to Al response, including ALMT, MATE, ABC, and NRAT1. GO analysis further highlighted enriched processes related to Al metabolism, notably SAM synthetase genes upregulated in roots, which are critical for DNA/RNA methylation and cell wall formation. By establishing Q. grandiflora as a genomic model for native Al hyperaccumulation species, this study provides a foundational resource for researching detoxification and ecological adaptations in metallophytes. The annotated sequence is available via NCBI (BioProject PRJNA786741), supported by leaf transcriptomic data from PRJNA358394.