An Arabidopsis leaf expression atlas across diurnal and developmental scales

Abstract

Mature plant leaves are a composite of distinct cell types, including epidermal, mesophyll and vascular cells. Notably the proportion of these cells, and the relative transcript concentrations within different cell types may change over time. While gene expression data at a single-cell level can provide cell-type specific expression values, it is often too expensive to perform this on high resolution time series. Although bulk RNA-seq can be performed in a high resolution time series, the RNA-seq in whole leaves measures the average gene expression values across all cell types in each sample. In this study, we combined single cell RNA-seq data with time-series data from whole leaves to infer an atlas of cell type-specific gene expression changes over time for Arabidopsis thaliana. We inferred how relative transcript concentrations of cell types vary across diurnal and developmental time scales. Importantly this analysis revealed three sub-groups of mesophyll cells that have distinct temporal profiles of expression. Finally, we develop tissue-specific gene networks that form a new community resource: An Arabidopsis Leaf Time-Dependent Atlas (AraLeTa), which allows users to extract gene networks that are confirmed by transcription factor binding data and specific to certain cell types, at certain times of day and certain developmental stages, which is available at: https://regulatorynet.shinyapps.io/araleta/.