bioRxivSystems BiologyPreprint
Sorghum bicolor cultivars have divergent and dynamic gene regulatory networks that control the temporal expression of genes in stem tissue
Madara Hetti ArachchilageiD, John E. MulletiD, Amy Marshall‐ColóniD
Abstract
The genetic engineering of value-added traits such as the accumulation of bioproducts in high biomass C4 grass stems is one promising strategy to make plant-derived biofuels more economical for industrial use. A first step toward achieving this goal is to identify stem-specific promoters that can drive the expression of genes of interest with good temporal and spatial specificity. However, a comprehensive characterization of the spatial-temporal regulatory elements of stem tissue-specific promoters for C4 grasses has not been reported. Therefore, we performed an in-silico analysis on Sorghum bicolor cv BTx623 transcriptomes from multiple tissues over development to identify stem-expressed genes. The analysis identified 10 genes that are “Always-On-Stem-Specific,” 59 genes that are “Temporally-Stem-Specific during early development,” and 21 genes that are “Temporally-Stem-Specific during late development.” Promoter analysis revealed common and/or unique cis-regulatory elements in promoters of genes within each of the three categories. Subsequent gene regulatory network (GRN) analysis revealed that different transcriptional regulatory programs are responsible for the temporal activation of the stem-expressed genes. The analysis of temporal stem GRNs between sweet (cv Della) and grain (cv BTx623) sorghum varieties revealed genetic variation that could influence the regulatory landscape. This study provides new insights about sorghum stem biology, and information for future genetic engineering efforts to fine-tune the spatial-temporal expression of transgenes in C4 grass stems.Competing Interest StatementThe authors have declared no competing interest.View Full Text
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 6
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