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 obtain these data for high-resolution time series. Although bulk RNA-seq can be performed in a high-resolution time series, RNA-seq using whole leaves measures 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 assemble an atlas of cell-type-specific changes in gene expression over time for Arabidopsis (Arabidopsis thaliana). We inferred how the relative transcript concentrations of different cell types vary across diurnal and developmental timescales. Importantly, this analysis revealed 3 subgroups of mesophyll cells with distinct temporal profiles of expression. Finally, we developed tissue-specific gene networks that form a community resource: an Arabidopsis Leaf Time-dependent Atlas (AraLeTa). This 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 at certain developmental stages. AraLeTa is available at https://regulatorynet.shinyapps.io/araleta/.
