Gould, R. A. | bioRxiv Science

bioRxiv2026

Architectural fragility of gene regulatory networks underlies hematopoietic stem cell aging

Hematopoietic stem and progenitor cell (HSPC) aging contributes to immune dysfunction and age-associated disease, but its regulatory mechanisms remain unclear. Here, we present the largest single-cell multiome atlas of human circulating HSPCs to date, with >380,000 paired RNA and ATAC profiles across 77 donors. Beyond recapitulating established hallmarks of HSPC aging, we reconstructed a high-resolution gene regulatory network and identified a global rewiring in which stress-response and myeloid transcription factor (TF) programs expand, while self-renewal and lymphoid lineage-defining circuitry collapses. We associate these phenotypes with increased cis-regulatory entropy, including elevated transcriptomic noise, weakened peak-to-gene coupling, and chromatin peak broadening. This rewiring is selective, where TFs with GC-rich, promoter-proximal architectures are preserved or amplified, and complex, distal enhancer-dependent identity networks are eroded. Thus, these findings suggest that progressive entropic destabilization of gene regulatory architecture simultaneously drives stress hyperactivation, myeloid bias, and identity loss in aging HSPCs.

genomics↗

bioRxiv2020

Accurate transcription start sites enable mining for the cis-regulatory determinants of tissue specific gene expression

Across tissues, gene expression is regulated by a combination of determinants, including the binding of transcription factors (TFs), along with other aspects of cellular state. Recent studies emphasize the importance of both genetic and epigenetic states - TF binding sites and binding site chromatin accessibility have emerged as potentially causal determinants of tissue specificity. To investigate the relative contributions of these determinants, we constructed three genome-scale datasets for both root and shoot tissues of the same Arabidopsis thaliana plants: TSS-seq data to identify Transcription Start Sites, OC-seq data to identify regions of Open Chromatin, and RNA-seq data to assess gene expression levels. For genes that are differentially expressed between root and shoot, we constructed a machine learning model predicting tissue of expression from chromatin accessibility and TF binding information upstream of TSS locations. The resulting model was highly accurate (over 90% auROC and auPRC), and our analysis of model contributions (feature weights) strongly suggests that patterns of TF binding sites within [~]500 nt TSS-proximal regions are predominant explainers of tissue of expression in most cases. Thus, in plants, cis-regulatory control of tissue-specific gene expression appears to be primarily determined by TSS-proximal sequences, and rarely by distal enhancer-like accessible chromatin regions. This study highlights the exciting future possibility of a native TF site-based design process for the tissue-specific targeting of plant gene promoters.

genomics↗