A comprehensive view of cell-type-specific temporal dynamics in human and mouse brains

Abstract

Progenitor cells play fundamental roles in preserving optimal organismal functions under normal, aging, and disease conditions. However, progenitor cells are incompletely characterized, especially in the brain, partly because conventional methods are restricted by inadequate throughput and resolution for deciphering cell-type-specific proliferation and differentiation dynamics in vivo. Here, we developed TrackerSci, a new technique that combines in vivo labeling of newborn cells with single-cell combinatorial indexing to profile the single-cell chromatin landscape and transcriptome of rare progenitor cells and track cellular differentiation trajectories in vivo. We applied TrackerSci to analyze the epigenetic and gene expression dynamics of newborn cells across entire mouse brains spanning three age stages and in a mouse model of Alzheimer's disease. Leveraging the dataset, we identified diverse progenitor cell types less-characterized in conventional single cell analysis, and recovered their unique epigenetic signatures. We further quantified the cell-type-specific proliferation and differentiation potentials of progenitor cells, and identified the molecular programs underlying their aging-associated changes (e.g., reduced neurogenesis/oligodendrogenesis). Finally, we expanded our analysis to study progenitor cells in the aged human brain through profiling ~800,000 single-cell transcriptomes across five anatomical regions from six aged human brains. We further explored the transcriptome signatures that are shared or divergent between human and mouse oligodendrogenesis, as well as the region-specific down-regulation of oligodendrogenesis in the human cerebellum. Together, the data provide an in-depth view of rare progenitor cells in mammalian brains. We anticipate TrackerSci will be broadly applicable to characterize cell-type-specific temporal dynamics in diverse systems.

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

“…Then we identified potential marker genes for pericytes using Monocle. 47 We filtered the significant pericyte marker genes (q-value <0.05) to a subset of seven genes (Table 1), by applying the following criteria: a high expression in pericytes (>700 TPM), but a low expression in any other cell types (<400 TPM). We further excluded two genes from this list, because the second highest expression was in smooth muscle cells.…”

“…After clustering the vascular cells from the human brain samples, we identified subclusters correlating with pericytes, smooth muscle cells, endothelial cells and perivascular fibroblasts (Figure 1C). Then we identified potential marker genes for pericytes using Monocle 47 . We filtered the significant pericyte marker genes (q‐value <0.05) to a subset of seven genes (Table 1), by applying the following criteria: a high expression in pericytes (>700 TPM), but a low expression in any other cell types (<400 TPM).…”

“…We also used a second human nuclei dataset from literature, 47 which contained five distinct anatomical regions from the human brain (cerebellum, hippocampus, inferior parietal regions, motor cortex and superior and medial temporal gyrus) to investigate anatomical differences between human brain regions. Furthermore, we used the ~1.5 million mouse single nuclei data from the EasySci publication 40 to study the evolutional conservation of these markers between humans and mice.…”

Evolution of plant cell-type-specificcis-regulatory elements

“…Prior studies uncovered the prevalence of CREs in plants, highlighting their dynamic nature throughout evolution and their involvement in regulating gene expression via distinct chromatin pathways [3][4][5][6][7][8] . Across diverse cell types, gene expression is intricately regulated by multipl 9 e distinct CREs, each exerting control within specific cell or tissue types or during particular developmental stages and environmental cues [10][11][12] . Several studies have identified CREs functioning in a cell-type-specific manner within various plant species 9,[13][14][15][16][17][18][19] .…”

“…Prior studies highlighted the dynamic nature of CREs throughout evolution and their involvement in regulating gene expression via distinct chromatin pathways [4][5][6][7][8][9] . Across diverse cell types, gene expression is intricately regulated by multiple distinct CREs, each exerting control within specific cell or tissue type or particular developmental stage and environmental cue [10][11][12] . Environmental sensing and adaptation, in plants, relies heavily upon epidermal cells 13 .…”