The mouse inner cell mass (ICM) segregates into the epiblast and primitive endoderm (PrE) lineages coincident with implantation of the embryo. The epiblast subsequently undergoes considerable expansion of cell numbers prior to gastrulation. To investigate underlying regulatory principles, we performed systematic single-cell RNA sequencing (seq) of conceptuses from E3.5 to E6.5. The epiblast shows reactivation and subsequent inactivation of the X chromosome, with Zfp57 expression associated with reactivation and inactivation together with other candidate regulators. At E6.5, the transition from epiblast to primitive streak is linked with decreased expression of polycomb subunits, suggesting a key regulatory role. Notably, our analyses suggest elevated transcriptional noise at E3.5 and within the non-committed epiblast at E6.5, coinciding with exit from pluripotency. By contrast, E6.5 primitive streak cells became highly synchronized and exhibit a shortened G1 cell-cycle phase, consistent with accelerated proliferation. Our study systematically charts transcriptional noise and uncovers molecular processes associated with early lineage decisions.

Conventional human embryonic stem cells are considered to be primed pluripotent but can be induced to enter a naive state. However, the transcriptional features associated with naive and primed pluripotency are still not fully understood. Here we used single-cell RNA sequencing to characterize the differences between these conditions. We observed that both naive and primed populations were mostly homogeneous with no clear lineage-related structure and identified an intermediate subpopulation of naive cells with primed-like expression. We found that the naive-primed pluripotency axis is preserved across species, although the timing of the transition to a primed state is species specific. We also identified markers for distinguishing human naive and primed pluripotency as well as strong co-regulatory relationships between lineage markers and epigenetic regulators that were exclusive to naive cells. Our data provide valuable insights into the transcriptional landscape of human pluripotency at a cellular and genome-wide resolution.

Summary: The brains of teleost fish show extensive adult neurogenesis and neuronal regeneration. The patterns of gene regulation during fish brain aging are unknown. The short‐lived teleost fish Nothobranchius furzeri shows markers of brain aging including reduced learning performances, gliosis, and reduced adult neurogenesis. We used RNA‐seq to quantify genome‐wide transcript regulation and sampled five different time points to characterize whole‐genome transcript regulation during brain aging of N. furzeri. Comparison with human datasets revealed conserved up‐regulation of ribosome, lysosome, and complement activation and conserved down‐regulation of synapse, mitochondrion, proteasome, and spliceosome. Down‐regulated genes differ in their temporal profiles: neurogenesis and extracellular matrix genes showed rapid decay, synaptic and axonal genes a progressive decay. A substantial proportion of differentially expressed genes (~40%) showed inversion of their temporal profiles in the last time point: spliceosome and proteasome showed initial down‐regulation and stress‐response genes initial up‐regulation. Extensive regulation was detected for chromatin remodelers of the DNMT and CBX families as well as members of the polycomb complex and was mirrored by an up‐regulation of the H3K27me3 epigenetic mark. Network analysis showed extensive coregulation of cell cycle/DNA synthesis genes with the uncharacterized zinc‐finger protein ZNF367 as central hub. In situ hybridization showed that ZNF367 is expressed in neuronal stem cell niches of both embryonic zebrafish and adult N. furzeri. Other genes down‐regulated with age, not previously associated with adult neurogenesis and with similar patterns of expression are AGR2, DNMT3A, KRCP, MEX3A, SCML4, and CBX1. CBX7, on the other hand, was up‐regulated with age.

A widespread modulation of gene expression occurs in the aging brain, but little is known as to the upstream drivers of these changes. MicroRNAs emerged as fine regulators of gene expression in many biological contexts and they are modulated by age. MicroRNAs may therefore be part of the upstream drivers of the global gene expression modulation correlated with aging and aging-related phenotypes. Here, we show that microRNA-29 (miR-29) is induced during aging in short-lived turquoise killifish brain and genetic antagonism of its function induces a gene-expression signature typical of aging. Mechanicistically, we identified Ireb2 (a master gene for intracellular iron delivery that encodes for IRP2 protein), as a novel miR-29 target. MiR-29 is induced by iron loading and, in turn, it reduces IRP2 expression in vivo, therefore limiting intracellular iron delivery in neurons. Genetically modified fish with neuro-specific miR-29 deficiency exhibit increased levels of IRP2 and transferrin receptor, increased iron content, and oxidative stress. Our results demonstrate that age-dependent miR-29 upregulation is an adaptive mechanism that counteracts the expression of some aging-related phenotypes and its anti-aging activity is primarily exerted by regulating intracellular iron homeostasis limiting excessive iron-exposure in neurons.

Biological systems respond to perturbations through the rewiring of molecular interactions, organised in gene regulatory networks (GRNs). Among these, the increasingly high availability of transcriptomic data makes gene co-expression networks the most exploited ones. Differential co-expression networks are useful tools to identify changes in response to an external perturbation, such as mutations predisposing to cancer development, and leading to changes in the activity of gene expression regulators or signalling. They can help explain the robustness of cancer cells to perturbations and identify promising candidates for targeted therapy, moreover providing higher specificity with respect to standard co-expression methods. Here, we comprehensively review the literature about the methods developed to assess differential co-expression and their applications to cancer biology. Via the comparison of normal and diseased conditions and of different tumour stages, studies based on these methods led to the definition of pathways involved in gene network reorganisation upon oncogenes’ mutations and tumour progression, often converging on immune system signalling. A relevant implementation still lagging behind is the integration of different data types, which would greatly improve network interpretability. Most importantly, performance and predictivity evaluation of the large variety of mathematical models proposed would urgently require experimental validations and systematic comparisons. We believe that future work on differential gene co-expression networks, complemented with additional omics data and experimentally tested, will considerably improve our insights into the biology of tumours.