Uncovering candidate Nanog-Helper genes in early mouse embryo differentiation using differential entropy and network inference
Year: 2025
Type: article
Abstract: In the preimplantation mammalian embryo, stochastic cell-to-cell expression heterogeneity is followed by signal reinforcement to initiate the specification of Inner Cell Mass (ICM) cells into Epiblast (Epi). The expression of NANOG, the key transcription factor for the Epi fate, is necessary but not sufficient: coincident expression of other factors is required. To identify possible Nanog-helper genes, we analyzed gene expression variability in five time-stamped single-cell transcriptomic datasets using differential entropy, a quantitative measure of cell-to-cell heterogeneity. The entropy of Nanog displays a peak-shaped temporal pattern from the 16-cell to the 64-cell stage, consistent with its key role in Epi specification. By estimating the entropy profiles of the 21 genes common to all five datasets, we identified three genes - Pecam1, Sox2, and Hnf4a - whose variability in expression patterns mirrors that of Nanog. We further performed gene regulatory network inference using CARDAMOM, an algorithm that exploits temporal dynamics and transcriptional bursting. The results revealed that these three genes exhibit reciprocal activation with Nanog at the 32-cell stage. This regulatory motif reinforces fate-switching decisions and co-expression states. Our innovative analysis of single-cell transcriptomic data thus uncovers a likely role for Pecam1, Sox2, and Hnf4a as key genes that, when coincidentally expressed with Nanog, initiate ICM differentiation.
Source: Scientific Reports
Institutions: Université Libre de Bruxelles, École Normale Supérieure de Lyon, Centre National de la Recherche Scientifique, Inserm, Laboratoire de Biologie et Modélisation de la Cellule, Institut national de recherche en sciences et technologies du numérique, Institut Élie Cartan de Lorraine, Université de Lorraine, Université Clermont Auvergne, Institut Génétique, Reproduction et Développement
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4411078516
