A Panoramic View of Cell Population Dynamics in Mammalian Aging

To elucidate the aging-associated cellular population dynamics throughout the body, here we present PanSci, a single-cell transcriptome atlas profiling over 20 million cells from 623 mouse tissue samples, encompassing a range of organs across different life stages, sexes, and genotypes. This comprehensive dataset allowed us to identify more than 3,000 unique cellular states and catalog over 200 distinct aging-associated cell populations experiencing significant depletion or expansion. Our panoramic analysis uncovered temporally structured, organ- and lineage-specific shifts of cellular dynamics during lifespan progression. Moreover, we investigated aging-associated alterations in immune cell populations, revealing both widespread shifts and organ-specific changes. We further explored the regulatory roles of the immune system on aging and pinpointed specific age-related cell population expansions that are lymphocyte-dependent. The breadth and depth of our 'cell-omics' methodology not only enhance our comprehension of cellular aging but also lay the groundwork for exploring the complex regulatory networks among varied cell types in the context of aging and aging-associated diseases.

A high-throughput single-cell RNA expression profiling method identifies human pericyte markers

AIMS

We sought to identify and optimise a universally available histological marker for pericytes in the human brain. Such a marker could be a useful tool for researchers. Further, identifying a gene expressed relatively specifically in human pericytes could provide new insights into the biological functions of this fascinating cell type.

METHODS

We analysed single-cell RNA expression profiles derived from different human and mouse brain regions using a high-throughput and low-cost single-cell transcriptome sequencing method called EasySci. Through this analysis, we were able to identify specific gene markers for pericytes, some of which had not been previously characterised. We then used commercially (and therefore universally) available antibodies to immunolabel the pericyte-specific gene products in formalin-fixed paraffin-embedded (FFPE) human brains and also performed immunoblots to determine whether appropriately sized proteins were recognised.

RESULTS

In the EasySci data sets, highly pericyte-enriched expression was notable for SLC6A12 and SLC19A1. Antibodies against these proteins recognised bands of approximately the correct size in immunoblots of human brain extracts. Following optimisation of the immunohistochemical technique, staining for both antibodies was strongly positive in small blood vessels and was far more effective than a PDGFRB antibody at staining pericyte-like cells in FFPE human brain sections. In an exploratory sample of other human organs (kidney, lung, liver, muscle), immunohistochemistry did not show the same pericyte-like pattern of staining.

CONCLUSIONS

The SLC6A12 antibody was well suited for labelling pericytes in human FFPE brain sections, based on the combined results of single-cell RNA-seq analyses, immunoblots and immunohistochemical studies.

A global view of aging and Alzheimer's pathogenesis-associated cell population dynamics and molecular signatures in human and mouse brains

Conventional methods fall short in unraveling the dynamics of rare cell types related to aging and diseases. Here we introduce EasySci, an advanced single-cell combinatorial indexing strategy for exploring age-dependent cellular dynamics in the mammalian brain. Profiling approximately 1.5 million single-cell transcriptomes and 400,000 chromatin accessibility profiles across diverse mouse brains, we identified over 300 cell subtypes, uncovering their molecular characteristics and spatial locations. This comprehensive view elucidates rare cell types expanded or depleted upon aging. We also investigated cell-type-specific responses to genetic alterations linked to Alzheimer's disease, identifying associated rare cell types. Additionally, by profiling 118,240 human brain single-cell transcriptomes, we discerned cell- and region-specific transcriptomic changes tied to Alzheimer's pathogenesis. In conclusion, this research offers a valuable resource for probing cell-type-specific dynamics in both normal and pathological aging.

Tracking cell-type-specific temporal dynamics in human and mouse brains

Progenitor cells are critical in preserving organismal homeostasis, yet their diversity and dynamics in the aged brain remain underexplored. We introduced TrackerSci, a single-cell genomic method that combines newborn cell labeling and combinatorial indexing to characterize the transcriptome and chromatin landscape of proliferating progenitor cells in vivo. Using TrackerSci, we investigated the dynamics of newborn cells in mouse brains across various ages and in a mouse model of Alzheimer's disease. Our dataset revealed diverse progenitor cell types in the brain and their epigenetic signatures. We further quantified aging-associated shifts in cell-type-specific proliferation and differentiation and deciphered the associated molecular programs. Extending our study to the progenitor cells in the aged human brain, we identified conserved genetic signatures across species and pinpointed region-specific cellular dynamics, such as the reduced oligodendrogenesis in the cerebellum. We anticipate that TrackerSci will be broadly applicable to unveil cell-type-specific temporal dynamics in diverse systems.

Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens

We present a combinatorial indexing method, PerturbSci-Kinetics, for capturing whole transcriptomes, nascent transcriptomes and single guide RNA (sgRNA) identities across hundreds of genetic perturbations at the single-cell level. Profiling a pooled CRISPR screen targeting various biological processes, we show the gene expression regulation during RNA synthesis, processing and degradation, miRNA biogenesis and mitochondrial mRNA processing, systematically decoding the genome-wide regulatory network that underlies RNA temporal dynamics at scale.

PerturbSci-Kinetics: Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens

Here we described PerturbSci-Kinetics, a novel combinatorial indexing method for capturing three-layer single-cell readout (i.e., whole transcriptomes, nascent transcriptomes, sgRNA identities) across hundreds of genetic perturbations. Through PerturbSci-Kinetics profiling of pooled CRISPR screens targeting a variety of biological processes, we were able to decipher the complexity of RNA regulations at multiple levels (e.g., synthesis, processing, degradation), and revealed key regulators involved in miRNA and mitochondrial RNA processing pathways. Our technique opens the possibility of systematically decoding the genome-wide regulatory network underlying RNA temporal dynamics at scale and cost-effectively.