Single-Cell RNA Sequencing of Batch Chlamydomonas Cultures Reveals Heterogeneity in their Diurnal Cycle Phase

Abstract

The photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of the facility with which it can be cultured in the laboratory. Genomic and systems biology approaches have previously been used to describe how the transcriptome responds to environmental changes, but this analysis has been limited to bulk data, representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing in the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample algae communities in the wild. Second, scRNA-seq successfully separated single cells into non-overlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest cell division to economize resources. Notably, these groups of cells recapitulated known patterns observed with bulk RNA-seq, but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We propose that bulk RNA-seq data represent an average of varied cell states that hides underappreciated heterogeneity.One-sentence summaryWe show that single-cell RNA-seq (scRNA-seq) can be applied to Chlamydomonas cultures to reveal the that heterogenity in bulk cultures is largely driven by diurnal cycle phasesThe author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantcell.org) is: Matteo Pellegrini (matteop@mcdb.ucla.edu)

The biology of time: dynamic responses of cell types to developmental, circadian and environmental cues

“…Hopefully, future studies will reveal which cell-specific clocks are sensing and gating these environmental cues, and how they are transmitted across tissues. At least in the case of Chlamydomonas, single-cell sequencing uncovered a later diurnal phase in irondeficient cells (Ma et al, 2021) that is consistent with the long period observed in Arabidopsis plants under ironlimiting conditions (Chen et al, 2013;Hong et al, 2013;Salom e et al, 2013). This certainly argues for considering individual cell phase when determining the cell state, especially in multicellular organisms where phase response is likely dependent on cell identity.…”

“…In systems with just one cell‐type identity, changes in cell state can be clearly detected. For example, through single‐cell sequencing of Chlamydomonas cell culture over time, the transcriptional changes driven by iron limitation and the circadian clock could be easily discerned (Ma et al., 2021). However, in multicellular systems, where many different cell identities exist, it is more difficult to dissociate cell identity from cell state.…”

scPrisma: inference, filtering and enhancement of periodic signals in single-cell data using spectral template matching

“…scPrisma detects and filters the diurnal cycle in Chlamydomonas. (A) PCA representation of cells in spectrally enhanced cyclic signal of the iron replete (Fe+) experiment [27]. Each plot represents 1/6 of the 24 hours cycle.…”

“…To demonstrate the use of scPrisma for more complex systems with diverse prior knowledge, we next turn our attention to scRNA-seq data collected for Chlamydomonas (green algae), grown under two contrasting conditions, iron replete (Fe+) and iron deficient (Fe-) [27]. In both conditions, a signal in the gene expression of the Chlamydomonas that reflects the 24 hours diurnal cycle was previously detected [27]. To evaluate progression of cells along the diurnal cycle, we used marker genes corresponding to different cycle phases obtained from bulk RNA-sequencing [44] (Supplementary A.5).…”

Systems-wide Analysis Revealed Shared and Unique Responses to Moderate and Acute High Temperatures in the Green Alga Chlamydomonas reinhardtii

“…The dataset was filtered for genes that met minimum read count cutoffs of at least 10 mapped reads in at least 10% of the samples, resulting in 15,541 genes for downstream analyses. Two-dimensional Uniform Manifold Approximation and Projection (UMAP) was used to reveal clusters of RNA-seq data (Ma et al, 2021).…”