Steer, C. J. | bioRxiv Science

bioRxiv2025

Novel Single-Cell Multiomics Approach to Analyze Replication Timingand Gene Expression in Mouse Preimplantation Embryos

Analysis of a cells replication timing (RT) provides insight into how genes replicate, early or late, during the S-phase of the cell cycle. RT is cell-type specific, inheritable, and has been correlated to gene expression in normal and diseased states. However, most studies have been limited to somatic cells. Very little is known about RT control in early mouse embryos, and how it correlates with the start of transcription during zygote gene activation (ZGA), at the 2-cell stage. In this study, we developed a novel in-house single-cell multiomics approach to simultaneously analyze RT and gene expression in individual cells of the mouse 1-cell, 2-cell, and 4-cell embryos. We detected that RT was established at the 1-cell stage prior to ZGA. Surprisingly, we observed that the coordinated RT and gene expression control was different in early totipotent embryos, compared to previously published studies in somatic cells. Late replicating regions correlated with higher gene expression and open chromatin in the early developing embryos. Lastly, we performed an integrated pseudo time trajectory analysis combining RT and gene expression information per cell.

developmental biology↗

bioRxiv2025

Development of a Novel Single Cell Multiomics Approach for Simultaneous Analysis of Replication Timing and Gene Expression

Replication timing (RT) allows us to analyze temporal patterns of genome-wide replication, i.e., if genes replicate early or late during the S-phase of the cell cycle. RT has been linked to gene expression in normal and diseased acute and chronic states such as cancer. However, studies done to date focused on bulk cell populations that required tens of thousands of cells for RT analysis. Here, we developed an affordable novel single cell (sc)-multiomics approach to simultaneously analyze RT and gene expression from cells or nuclei. We used this approach to generate sc-RT profiles and sc-gene expression data from the well-established human liver cancer cell line, HepG2. We demonstrated that as few as 17 mid S-phase cells were sufficient to produce cell-type specific pseudo bulk RT profiles that had a high correlation to previously published HepG2 bulk RT profiles. The sc-RT profiles allowed us to visualize how individual cells progressed through genome replication. We were also able to demonstrate high-resolution correlations between RT and gene expression within each individual cell, which to our knowledge, has not been reported. We observed trends that were conserved between individual cells, as well as cell-to-cell variations, which were not possible to detect with the bulk RT studies.

genomics↗