iScienceApr 20, 2026

Random gene activity limits how well single-cell RNA can reveal circadian clock timing

Circadian Biology Weekly Brief ↗PubMed ↗DOI ↗

Updated Jun 27, 2026

Abstract

Essence

Transcriptional noise made single-cell RNA snapshots unreliable for circadian clock-phase decoding, while averaging cells restored phase estimates.

Evidence

Multiplexed smFISH in mouse fibroblasts, Gaussian-process inference, simulations, and scRNA-seq analysis tested core and non-core clock genes and found robust RNA-based phase estimation only after coarse graining.

Caveat

The limit is shown for RNA measurements in mouse fibroblasts and simulations, so it may not cover other cell types, modalities, or non-RNA phase markers.

Simplified

The circadian clock drives rhythmic physiological variations, making accurate clock-phase measurement essential. Single-sample phase inference from bulk RNA is an exciting alternative to time-series methods, but its applicability to single cells remains unclear. Using multiplexed smFISH to quantify up to six core-clock genes in mouse fibroblasts, combined with a Gaussian process-based algorithm, we show that even with minimal technical dropouts, transcriptional noise in core-clock genes prevents reliable single-cell phase estimation. Simulations predict that measuring50 low-noise, clock-like oscillatory genes is required for accurate single-cell inference. In scRNA-seq data, non-core genes were too noisy, and adding hundreds of them did not improve accuracy. Remarkably, averaging smFISH counts from only three core-clock genes across70 cells enabled robust phase estimation. In desynchronized fibroblasts, spatially heterogeneous phases indicating local inter-cellular coupling were revealed only upon averaging, not at single-cell resolution. Coarse graining is, therefore, essential for circadian phase inference from RNA measurements alone. ∼ ∼