Discovery of Cellular Rejuvenation Targets Through Attractor-Based Analysis of Gene Regulatory Networks Along Aging Trajectories
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This dataset contains processed single-cell RNA sequencing data and Boolean network analysis results from human skin biopsies spanning donors aged 18 to 76 years. The original sequencing data was obtained from Zou et al. (2021) via the Human Cell Atlas Data Explorer.The dataset includes quality-controlled and normalized expression data for 47,060 cells across 25 cell types, with keratinocytes representing 80.4% of the population. Two distinct keratinocyte aging trajectories were identified through pseudotime analysis: Y_272 (representing aging as convergence toward a stable aged state) and Y_308 (representing aging as departure from a youthful state).For each trajectory, the dataset provides GeneSwitches results identifying genes with binary expression transitions during aging, SCENIC-derived gene regulatory networks, Boolean network models with attractor landscapes, and systematic perturbation analysis results. Key findings include identification of BACH2 knockdown as the dominant rejuvenation target for trajectory Y_272 and ASCL2 knockdown (alone or combined with ATF6) for trajectory Y_308.Source Data:** Zou, Zhiran, et al. "A single-cell transcriptomic atlas of human skin aging." Developmental Cell 56.3 (2021): 383-397.
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Publication Details
Subfield
Molecular Biology
Field
Biochemistry, Genetics and Molecular Biology
Domain
Life Sciences
Confidence Score
55%
Source
Scholar Data Model