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Biology subjects

Gallant, C. J.

Publications and source records attributed to Gallant, C. J..

2 recordsLinked to original sources

Nuclear gene proximity and protein interactions shape transcript covariances in mammalian single cells

Single-cell RNA sequencing studies into gene co-expression patterns could yield important new regulatory and functional insights, but have so far been limited by the confounding effects of cell differentiation and the cell cycle. We apply a tailored experimental design that eliminates these confounders, and report >80,000 intrinsically covarying gene pairs in mouse embryonic stem cells. These covariances form a network with biological properties, outlining known and novel gene interactions. We provide the first evidence that miRNAs naturally induce transcriptome-wide covariances, and compare the relative importance of nuclear organization, transcriptional and post-transcriptional regulation in defining covariances. We find that nuclear organization has the greatest impact, and that genes encoding for physically interacting proteins specifically tend to covary, suggesting importance for protein complex stoichiometry. Our results lend support to the concept of post-transcriptional RNA operons, but we further present evidence that nuclear proximity of genes on the same or even distinct chromosomes also provides substantial functional regulation in mammalian single cells.

systems biology↗

Combined mRNA and protein single cell analysis in a dynamic cellular system using SPARC

Combined measurements of mRNA and protein expression in single cells enables in-depth analysis of cellular states. We present single-cell protein and RNA co-profiling (SPARC), an approach to simultaneously measure global mRNA and large sets of intracellular protein in individual cells. Using SPARC, we show that mRNA expression fails to accurately reflect protein abundance at the time of measurement in human embryonic stem cells, although the direction of changes of mRNA and protein expression are in agreement during cellular differentiation. Moreover, protein levels of transcription factors better predict their downstream effects than do the corresponding transcripts. We further show that changes of the balance between protein and mRNA expression levels can be applied to infer expression kinetic trajectories, revealing future states of individual cells. Finally, we highlight that mRNA expression may be more varied among cells than levels of the corresponding proteins. Overall, our results demonstrate that mRNA and protein measurements in single cells provide different and complementary information regarding cell states. Accordingly, SPARC can offer valuable insights in gene expression programs of single cells.

cell biology↗