Single-cell RNA sequencing algorithms underestimate changes in transcriptional noise compared to single-molecule RNA imaging.

Abstract

Stochastic fluctuations (noise) in transcription generate substantial cell-to-cell variability. However, how best to quantify genome-wide noise remains unclear. Here, we utilize a small-molecule perturbation (5'-iodo-2'-deoxyuridine [IdU]) to amplify noise and assess noise quantification from numerous single-cell RNA sequencing (scRNA-seq) algorithms on human and mouse datasets and then compare it to noise quantification from single-molecule RNA fluorescence in situ hybridization (smFISH) for a panel of representative genes. We find that various scRNA-seq analyses report amplified noise-without altered mean expression levels-for ∼90% of genes and that smFISH analysis verifies noise amplification for the vast majority of tested genes. Collectively, the analyses suggest that most scRNA-seq algorithms (including a simple normalization approach) are appropriate for quantifying noise, although all algorithms appear to systematically underestimate noise changes compared to smFISH. For practical purposes, this analysis further argues that IdU noise enhancement is globally penetrant-i.e., homeostatically increasing noise without altering mean expression levels-and could enable investigations of the physiological impacts of transcriptional noise.