Cell ReportsSystems BiologyPeer-reviewed journal article
Single-cell multiomics reveals the oscillatory dynamics of mRNA metabolism and chromatin accessibility during the cell cycle
Maulik K. NariyaiD, David Santiago‐AlgarraiD, Olivier TassyiD, Marie CerciatiD, Tao YeiD, Andrea RibaiD, Nacho MolinaiD
Abstract
The cell cycle is a tightly regulated process that requires precise temporal expression of hundreds of cell cycledependent genes. However, the genome-wide dynamics of mRNA metabolism throughout the cell cycle remain uncharacterized. Here, we combined single-cell multiome sequencing, biophysical modeling, and deep learning to quantify rates of mRNA transcription, splicing, nuclear export, and degradation. Our approach revealed that both transcriptional and post-transcriptional processes exhibit distinct oscillatory waves at specific cell cycle phases, with post-transcriptional regulation playing a prominent role in shaping mRNA accumulation. We also observed dynamic changes in chromatin accessibility and transcription factor binding footprints, identifying key regulators underlying the oscillatory dynamics of mRNA. Taken together, our approach uncovered a high-resolution map of RNA metabolism dynamics and chromatin accessibility, offering new insights into the temporal control of gene expression in proliferating cells. HighlightsO_LIFourierCycle combines single-cell multiome sequencing, deep learning, and biophysical modeling to quantify gene-specific rates of mRNA metabolism during the cell cycle C_LIO_LIRates of mRNA transcription, nuclear export, and degradation show gene-specific oscillatory waves at distinct cell cycle phases. C_LIO_LIPost-transcriptional regulation, including mRNA degradation and nuclear export, plays a prominent role in shaping mRNA accumulation during the cell cycle C_LIO_LIDynamics of chromatin accessibility and transcription factor binding footprints uncover key regulators underlying the transcriptional control of gene expression C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/575159v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1d2d315org.highwire.dtl.DTLVardef@2031aaorg.highwire.dtl.DTLVardef@19cc54eorg.highwire.dtl.DTLVardef@15d9105_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: scRNA-seq
- assay: scATAC-seq
- assay: multiome
- research focus: gene regulatory network inference
- research focus: trajectory inference
- research focus: differential expression
- research focus: cell type annotation
- approach: deep learning
- approach: statistical model
- Citations
- 4
- FWCI
- 1.20
- Field percentile
- top 23%
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