Cell-type-specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems.

Fu J, McKinley B, James B, Chrisler W, Markillie LM, Gaffrey MJ, Mitchell HD, Riaz MR, Marcial B, Orr G, Swaminathan K, Mullet J, Marshall-Colon A

Published: 7 February 2024 in The Plant journal : for cell and molecular biology
Keywords: cell specificity, gene regulatory network, laser capture microdissection, secondary cell wall, sorghum, stem
Pubmed ID: 38407828
DOI: 10.1111/tpj.16690

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell-type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type-specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type-specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data (https://mc-lab.shinyapps.io/lcm-dataset/).

Department of Energy - Biological and Environmental Research program DE-AC05-76RL01830
Department of Energy - Center for Advanced Bioenergy and Bioproducts Innovation DE-SC0018420
Department of Energy - Great Lakes Bioenergy Research Center DE-SC0018409