Journal of Experimental BotanyEvolutionary BiologyPeer-reviewed journal article
Integrative analysis of CAM photosynthesis reveals its impact on primary metabolism in Yucca
David WickelliD, Richard FieldiD, Karl WeitziD, Rosalie ChuiD, Jesse B. TrejoiD, Nikola TolićiD, Nathalie Munoz MunoziD, Hope N. HundleyiD, Emily SavageiD, Anna LipzeniD, Jim Leebens‐MackiD, Karolina HeydukiD
Abstract
Crassulacean Acid Metabolism (CAM) is an adaptation that temporally separates carbon uptake at night from photosynthesis during the day. CAM has evolved repeatedly across vascular plants, as its emergence may depend on simple regulatory changes to deeply conserved metabolic pathways. Modern CAM research relies heavily on interpretation of transcriptomic data, though regulation occurs at multiple levels following transcription. Additionally, while most research to date has focused on a handful of genes and metabolites in the core CAM pathway, the co-option of conserved regulatory and functional genes is bound to have wide ranging effects on other aspects of primary metabolism. In this study, we integrate transcriptomic, proteomic, and metabolomic data to compare primary metabolism between the CAM species Yucca aloifolia and closely related C3 species, Y. filamentosa. We observe minimal correlation between protein abundance and mRNA expression, suggesting significant post-transcriptional regulation in CAM species. We also find evidence of shifts in gene expression and metabolite accumulation outside of the central CAM pathway suggesting that the shift to CAM has cascading effects across primary metabolism, especially nitrogen metabolism. Our findings provide insights into the metabolic shifts associated with CAM evolution and highlight the complexity of its regulation at multiple biological levels.
- organism: plant (other)
- assay: proteomics
- assay: metabolomics
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: metabolism & bioenergetics
- approach: statistical model
- approach: experimental assay
- Citations
- 1
- FWCI
- 1.72
- Field percentile
- top 16%
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