What is Transcriptional Bursting?
Imagine a factory where products are made in short, intense bursts rather than in a continuous flow. In the world of biology, something similar happens with gene expression, a process known as “transcriptional bursting.” Instead of being produced steadily, RNA (the messenger molecules that carry instructions from DNA to the cell’s machinery) is made in quick, sporadic bursts.
The Study
Researchers at the Karolinska Institute set out to explore this process more deeply by examining how RNA is transcribed in individual cells. They focused on fibroblasts, a type of cell found in connective tissue, from mice. To do this, they used a method to “label” newly made RNA so they could track when and how it was being produced. They looked at RNA from 10,000 individual cells, giving them a detailed view of the transcription process.
High-quality profiling of new RNAs in single cells with NASC-seq2
a, Plot showing the number of genes detected per K562 cell as a function of reads sequenced, for K562 cells processed with NASC-seq2 (613 individual cells) and NASC-seq (138 individual cells), respectively. The mean number of genes per method and sequencing depth is shown, together with error bars (1.96× s.e.m.). b, Illustration of large-scale NASC-seq2 experiment on F1 primary fibroblasts. Four technical replicates of primary fibroblast cultures were independently exposed to 4sU and collected for FACS and NASC-seq2 library construction. For transcriptional dynamics analyses, cells from all replicates were pooled. c, Uniform Manifold Approximation and Projection (UMAP) of primary fibroblasts, overlayed with contour plots, showing that assayed primary fibroblast cells did not show apparent patterns of heterogeneity. d, Boxplots showing the obtained signal-to-noise level (Pc/Pe) in fibroblasts with (n = 8,912) and without (n = 783) 4sU (2 h). The boxplots show the median and boundaries (first and third quartile), and the whiskers denote 1.5 times the interquartile range of the box. e, Density plot for the obtained power to call RNA molecules as new (y axis) against the reconstructed RNA molecule length (x axis). f, Contour plots showing the fraction of new RNA molecules per cell (x axis) against total detected RNA molecules per cell (y axis) for fibroblasts with and without 4sU. g, Scatter plot of burst frequency estimates (x axis) for mouse primary fibroblasts previously inferred from total RNA counts9 against the fraction of cells with new RNA (y axis) detected after 2-h 4sU exposure.
Key Findings
Burst Size is Controlled by Synthesis Rate: The size of the transcriptional bursts (how much RNA is made in each burst) is controlled by how quickly RNA is synthesized. Interestingly, the rate at which transcription pauses (the “off rate”) doesn’t seem to affect burst size as much.
RNA Polymerase II’s Role: The researchers confirmed that RNA polymerase II, the enzyme responsible for transcribing DNA into RNA, works in bursts across the entire genome. This supports the idea that transcriptional bursting is a widespread phenomenon in mammalian cells.
Co-Bursting is Rare: Some recent studies suggested that genes might often be transcribed in pairs, a process called “co-bursting.” However, this study found that such co-bursting is actually quite rare, except for certain gene pairs that are located close together on the genome, such as paralogues (genes that have similar sequences due to shared ancestry).
Why is this Important?
Understanding transcriptional bursting is important because it helps explain how genes are regulated within cells. The fact that genes are not continuously active but instead work in bursts adds a layer of complexity to gene regulation. It also has implications for understanding how cells respond to different signals and how variability in gene expression can affect cellular behavior.
Conclusion
This study provides new insights into the process of transcriptional bursting by showing that the size of these bursts is primarily controlled by how quickly RNA is made. It also challenges previous ideas about co-bursting, showing that it’s not as common as once thought. Overall, this research helps us better understand the dynamic nature of gene expression in cells.
Availability – The code for processing and analyses of NASC-seq2 data is deposited on GitHub (https://github.com/sandberg-lab/NASC-seq2).