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Transcript‑guided Targeted Cell Enrichment for Scalable Single‑Cell RNA Sequencing

ABSTRACT: Rare cell populations—often comprising less than 0.01% of all cells—play crucial roles in development, aging, and disease, yet standard single-cell sequencing methods typically miss them. To address this gap, here we developed EnrichSci, a microfluidic‑free, combinatorial indexing platform that integrates Hybridization Chain Reaction-RNA FISH with the high‑throughput EasySci pipeline for targeted cell enrichment and scalable single‑cell RNA sequencing. EnrichSci uses FACS to selectively enrich nuclei labeled by custom transcript modules and delivers full gene body coverage at under $0.001 per cell and tens of millions of cells per run. We applied EnrichSci to map the full oligodendrocyte lineage, uncovering age-related loss of precursor states and expansion of reactive mature subpopulations (C4b⁺ Serpina3n⁺). Through gene- and exon- level differential analyses, we revealed subtype-specific molecular changes in aging. In summary, by coupling transcript-guided enrichment with ultra scalable single-cell sequencing platform, EnrichSci offers a versatile approach for decoding the dynamic regulatory landscapes in rare cell types across diverse tissues and conditions.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE295135 | GEO | 2025/07/30

REPOSITORIES: GEO

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Project description:Prior studies applied single-cell approaches to explore gene expression changes in aged brains; however, they were limited by relatively shallow sampling of brain cell populations, and thus failed to characterize the detailed molecular signatures and dynamics of rare cell types associated with aging and diseases. Here, we set out to investigate the age-dependent transcriptional and chromatin dynamics across diverse brain cell types. With EasySci, an extensively improved single-cell combinatorial indexing strategy, we profiled ~1.5 million single-cell transcriptomes with full gene body coverage and ~400,000 single-cell chromatin accessibility profiles across mouse brains spanning different ages, genotypes, and both sexes. With a novel computational framework designed for characterizing cellular subtypes based on the expression of both genes and exons, we identified > 300 cell subtypes and deciphered the underlying molecular programs and spatial locations of rare cell types (e.g., pinealocytes, tanycytes). Leveraging the data, we generated a global readout of age-dependent cell population dynamics with great cellular subtype resolution, providing insights into expanded cell types (e.g., rare astrocytes and vascular leptomeningeal cells in olfactory bulb, reactive microglia and oligodendrocytes) and depleted cell types (e.g., neuronal progenitors, neuroblasts, committed oligodendrocyte precursors) in development and ageing. Furthermore, we explored cell-type-specific responses to genetic perturbations associated with Alzheimer’s disease and discovered rare cell types depleted (e.g., mt-Cytb+, mt-Rnr2+ choroid plexus epithelial cells) or enriched (e.g., Col25a1+ Ndrg1+ interbrain and midbrain neurons) in both AD models. Key findings are consistent between males and females, validated across the transcriptome, chromatin accessibility, and spatial analysis. In summary, these data comprise a rich resource for exploring cell-type-specific population dynamics and the underlying molecular mechanisms in the mammalian aging process.

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Transcript‑guided Targeted Cell Enrichment for Scalable Single‑Cell RNA Sequencing

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