Original cell cycle gene lists extracted from Whitfield and colleagues and Tirosh and colleagues studies and the final refined gene list.

Original cell cycle gene lists extracted from Whitfield and colleagues and Tirosh and colleagues studies and the final refined gene list.</p

AD risk gene loci mapping to predicted CNV locations in subclusters 5, 3, and 0.

The yellow highlights indicate chromosomal locations of classic AD risk gene loci. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Overrepresented cell cycle genes in subclusters 3 and 5 and corresponding pathway enrichment analyses.

Overrepresented cell cycle genes in subclusters 3 and 5 and corresponding pathway enrichment analyses.</p

Cell cycle gene reexpressing and senescent neurons exhibit compromised two-way communication with glia.

Dot plots illustrating the detailed results of the connectome analysis, which indicate the probabilities of communication between the indicated pairs of ligands and receptors according to the color label. The strength of the interaction, as indicated by the presence of a dot and the color between ligands expressed on glia and cell surface receptors expressed on neurons in various clusters, are shown on the left. Similarly, cell surface receptors expressed on glia and ligands expressed on neurons in various clusters are shown on the right. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Distribution of neuronal cells based on dataset source, sex, and disease status, as determined by cell cycle analysis in the integrated analysis setting.

(A) t-SNE plots of excitatory neuronal nuclei extracted from nondemented (ND) samples from different studies. (B) t-SNE plots of excitatory neuronal nuclei extracted from disease-affected (AD) samples from Mathys and colleagues and Lau and colleagues. (C) t-SNE plots of the excitatory neuronal nuclei distribution based on sex and disease status. (D) Violin plot illustrating the average feature counts of global transcriptomic profiles among excitatory neurons in different subclusters. (E) Violin plots presenting the cell cycle phase scores of all subclusters of excitatory neurons. Bolded violins highlighted in different phases indicate the subclusters that exhibit the most significant above-average cell cycle gene reexpression among all the subclusters. The corresponding significance values obtained for each subcluster compared to the rest of the others are shown in (F). The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Lists of genes located at the predicted copy number alteration regions in subcluster 5 and pathway enrichment analysis.

Lists of genes located at the predicted copy number alteration regions in subcluster 5 and pathway enrichment analysis.</p

Identification of cell cycle re-engaging postmitotic excitatory neurons in single-nucleus transcriptomic profiles.

(A) Schematic diagram illustrating the general layout and design of the bioinformatics analyses applied in this study. (B) t-SNE plot of a total of 34,140 nuclei derived from 24 unaffected, age (mean ± SD = 85.59 ± 4.20), and sex-matched (12 males and 12 females) prefrontal cortex samples from Brodmann area 10 [28]. The different cell types used are abbreviated as follows: excitatory neurons (Ex), oligodendrocytes (Oli), inhibitory neurons (In), astrocytes (Ast), microglia (Mic), endothelial cells (En), and oligodendrocyte progenitor cells (Opc). (C) Normalized expression levels of cell type-specific markers in all cell types mentioned above. (D) t-SNE plot of 32,685 postmitotic cell nuclei colored according to cell type (left panel) and subcluster number (right panel). (E) Schematic illustration of the cell cycle phase scoring workflow for each nucleus. (F) Violin plots showing the distribution of the cell cycle phase scores in all postmitotic cell subclusters. The bold highlights indicate the subcluster with the most significant differences above the average gene expression levels in any particular cell cycle phase. P values against other subclusters are shown on the right. (G) Estimation of copy number variants among all excitatory neurons via the InferCNV algorithm. The heatmap on the left shows the CNA regions identified by the HMM, i.e., regions of gain (red) and loss (blue) of expression along each chromosome, at various regions from the p-arm (left side of each box) to the q-arm (right side of each box) in all subclusters. The middle heatmap is an outcome of the Bayesian latent-mixture model implemented to identify the posterior probabilities of alteration status in each cell and whole CNA region. True positive predictions of CNV events were identified only in subcluster 13 (red: gain of copy number; blue: loss of copy number). On the far right are line plots illustrating in detail how gene expression levels on each chromosome are altered in subclusters 13 and 5 compared to a negative control (subcluster 2). The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. CNA, copy number alteration; CNV, copy number variation; HMM, hidden Markov model; t-SNE, t-distributed stochastic neighbor embedding.</p

Application of the bioinformatics analytical pipeline in the Parkinson’s disease (PD)/Lewy-body dementia (LBD) model.

(A) t-SNE plot of dopaminergic neurons extracted from healthy and diseased mid-brain samples; these nuclei were divided into 9 subclusters (0–8). (B) Violin plots showing the distribution of cell cycle phase scores in all dopaminergic neuronal nuclei subclusters. The bold highlights indicate the subcluster with the most significant above-average gene expression levels in any particular cell cycle phase; p values against other subclusters are shown. (C) Single-cell trajectory analysis with the Monocle 2.0 algorithm revealing the evolutionary relationship between 2 subclusters of cell cycle gene-expressing neurons. Locations of subclusters 2 and 5 on this trajectory are labeled, indicating that they are on the same trajectory of fate, with subcluster 2 located at the terminal. (D) Estimation of copy number variants among all the dopaminergic neuronal nuclei extracted via the InferCNV algorithm. True positives of copy number variation events were identified in subcluster 2 (red: gain of copy number. Blue: loss of copy number). (E) Dot plot showing the expression levels of 55 differentially expressed senescence genes defined by Hernandez-Segura and colleagues [47] among all dopaminergic neuronal subclusters. (F) Bar plot representing the numbers of DEGs between groups of nuclei from PD-LBD patients and nondemented samples in all subclusters of dopaminergic neuronal nuclei. (G) Functional enrichment analysis of both up- and down-regulated DEGs in subcluster 5/ES (PD-LBD vs ND) was performed on the Metascape platform. (H) Bar plot showing the disease enrichment analysis of both up- and down-regulated DEGs in the ES cohort (PD-LBD vs ND) with the DisGenNet database. The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (TIF)</p

Correlation plots between the cell number ratios of different neuronal clusters and the sample CERAD scores.

The metadata underlying this figure can be found at https://zenodo.org/doi/10.5281/zenodo.10604562. (JPG)</p

Single-cell trajectory analysis was performed using Monocle 2.0.

Cells on the trees are colored based on cell states, subcluster identities, cortical layer distributions, senescent neuronal cluster assignments, and pseudotime scales. Subclusters 3 and 5 were found along the same branch and were deemed to be the most similar to one another based on their pseudotime values. Subcluster 3, located at the terminal location of a branch, indicated terminal cell fate. The data represent findings from (A) nondemented (ND) or (B) disease-affected (AD) samples. (TIF)</p