Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress

Authors: HAYFORD, RITA - Orise Fellow; HALEY, OLIVIA - Orise Fellow; Cannon, Ethalinda; Portwood, John; GARDINER, JACK - University Of Missouri; Andorf, Carson; Woodhouse, Margaret

Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/22/2024
Publication Date: 5/30/2024
Citation: Hayford, R.K., Haley, O., Cannon, E.K., Portwood Ii, J.L., Gardiner, J.M., Andorf, C.M., Woodhouse, M.H. 2024. Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress. BMC Genomics. https://doi.org/10.1186/s12864-024-10443-7.
DOI: https://doi.org/10.1186/s12864-024-10443-7

Interpretive Summary: Environmental stress factors are becoming more common due to climate variability, significantly affecting global maize yield. Gene expression studies provide insights into the mechanisms underlying stress response in maize, though the functions of many genes are still unknown. MaizeGDB has outlined a data-driven approach to determine which genes confer tolerance to biotic and abiotic stress. We also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments. These results will help researchers understand the function of multiple stress response genes in maize.

Technical Abstract: Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress. We mapped high-quality RNA-Seq expression reads from 25 different publicly available datasets generated from the B73 cultivar to the recent version of the reference genome B73 (B73v5) and deduced stress-related functional annotation of maize gene models. We conducted a robust meta-analysis of the transcriptome profiles from the datasets to identify maize loci responsive to both abiotic and biotic stress. Using phylostratigraphic analysis, we also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments. These results will help facilitate the functional annotation of multiple stress response gene models and annotation in maize.