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Phillips, N. E.

Publications and source records attributed to Phillips, N. E..

2 recordsLinked to original sources

The circadian oscillator analysed at the single-transcript level

The circadian clock is an endogenous and self-sustained oscillator that anticipates daily environmental cycles and coordinates physiology accordingly. While rhythmic gene expression of circadian genes is well-described in populations of cells, the single-cell mRNA dynamics of multiple core-clock genes remain largely unknown. Here we use single molecule fluorescence in-situ hybridization (smFISH) at multiple time points to measure pairs of core-clock transcripts, Rev-erb (Nr1d1), Cry1 and Bmal1, in mouse fibroblasts at single-molecule resolution. The mean mRNA level oscillates over 24 hours for all three genes, but mRNA numbers show considerable spread between cells. While transcript number scales with cell size for all genes, gene-to-gene correlations of mRNA number depends on the gene pair. To account for these features of the data, we develop a probabilistic model for multivariate smFISH mRNA counts that quantifies changes in transcriptional bursting across genes and over circadian time. We identify a mixture model of negative binomials as the preferred model of the mRNA count distributions, which accounts for cell-to-cell heterogeneity, notably in cell size. The paired count data and modelling allows the decomposition of mRNA variability into distinct noise sources, showing that circadian clock time contributes only a small fraction of the total variability in mRNA number between cells. Thus, our results highlight the intrinsic biological challenges in estimating circadian phase from single-cell mRNA counts and suggest that circadian phase in single cells is encoded post-transcriptionally.

systems biology↗

Gene-specific transcriptional memory in mammalian cell lineages

Phenotypically identical mammalian cells often display considerable variability in transcript levels of individual genes. How transcriptional activity propagates in cell lineages, and how this varies across genes is poorly understood. Here we combined live-cell imaging of short- lived transcriptional reporters in mouse embryonic stem cells with mathematical modelling to quantify the propagation of transcriptional activity over time and across cell generations. In sister cells we found mean transcriptional activity to be strongly correlated and transcriptional dynamics tended to be synchronous; both features control how quickly sister cells diverge in a gene-specific manner. Mean transcriptional activity was also highly correlated between mother and daughter cells, leading to multi-generational transcriptional memory whose duration scaled with the spread of transcriptional activities in the population. The resulting family-specific transcriptional levels suggest a potential role of transcriptional memory in patterning tissue gene expression.

cell biology↗