Ribosome profiling elucidates differential gene expression in bundle sheath and mesophyll cells in maize.
Prakitchai ChotewutmontriAlice BarkanPublished in: Plant physiology (2022)
The efficiencies offered by C4 photosynthesis have motivated efforts to understand its biochemical, genetic, and developmental basis. Reactions underlying C4 traits in most C4 plants are partitioned between two cell types, bundle sheath (BS), and mesophyll (M) cells. RNA-seq has been used to catalog differential gene expression in BS and M cells in maize (Zea mays) and several other C4 species. However, the contribution of translational control to maintaining the distinct proteomes of BS and M cells has not been addressed. In this study, we used ribosome profiling and RNA-seq to describe translatomes, translational efficiencies, and microRNA abundance in BS- and M-enriched fractions of maize seedling leaves. A conservative interpretation of our data revealed 182 genes exhibiting cell type-dependent differences in translational efficiency, 31 of which encode proteins with core roles in C4 photosynthesis. Our results suggest that non-AUG start codons are used preferentially in upstream open reading frames of BS cells, revealed mRNA sequence motifs that correlate with cell type-dependent translation, and identified potential translational regulators that are differentially expressed. In addition, our data expand the set of genes known to be differentially expressed in BS and M cells, including genes encoding transcription factors and microRNAs. These data add to the resources for understanding the evolutionary and developmental basis of C4 photosynthesis and for its engineering into C3 crops.
Keyphrases
- deep learning
- induced apoptosis
- single cell
- rna seq
- gene expression
- machine learning
- cell cycle arrest
- genome wide
- transcription factor
- endoplasmic reticulum stress
- electronic health record
- cell death
- cell proliferation
- bone marrow
- climate change
- big data
- quality improvement
- pi k akt
- cell therapy
- arabidopsis thaliana
- antibiotic resistance genes
- genome wide identification