Additional file 1 of A single-cell transcriptomic atlas of complete insect nervous systems across multiple life stages

Additional file 1: Supplementary Spreadsheets and Figures. All spreadsheets for marker genes contain the following columns: p-value (pval), average log2 fold-change (avg_log2FC), percent of cells in the cluster expressing the marker (pct.1), percent of cells outside the cluster expressing the marker (pct.2), the multiple test corrected p-value (p_val_adj), the cluster number (cluster), the gene name (gene), the flybase id (Fbgn_ID), gene long name (GeneName), datestamp of flybase snapshot inclusion (datestamp) and the Flybase gene snapshot for the gene in question, when available.(gene_snapshot_text). Supplementary_spreadsheet_1_Time_and_tissue_breakdown.ods. Spreadsheet detailing the number of cells per cluster and sample of origin, a stage by cell number breakdown and sequencing quality control metrics for each sequenced sample. Supplementary_spreadsheet_2_Ncells_and_gene_markers_per_cluster.xlsx. Spreadsheet containing one sheet per detected cluster with all the cluster defining markers resulting from running the FindAllMarkers algorithm as detailed in the methods. An additional sheet contains the number of cells per cluster. Supplementary_spreadsheet_3_Ncells_and_gene_markers_per_cluster_and_stage.xlsx. Spreadsheet containing one sheet per detected cluster with all the cluster defining markers at each stage, ie. 1h, 24h and 48h resulting from running the FindAllMarkers algorithm as detailed in the methods for the temporal analysis. An additional sheet contains the number of cells per cluster at each stage. Supplementary_spreadsheet_4_Ncells_and_gene_markers_per_cluster_and_tissue.xlsx. Spreadsheet containing one sheet per detected cluster with all the cluster defining markers for each tissue, ie. brain, CNS and VNC, resulting from running the FindAllMarkers algorithm as detailed in the methods for the temporal analysis. An additional sheet contains the number of cells per cluster detected in each tissue dissection. Supplementary_spreadsheet_5_Differential_expression_cluster_mature_neuron_classes.ods. Spreadsheet containing one sheet per mature neuron subtype and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to mature cell-types only: Cholinergic, Gabaergic, Glutamatergic, Kenyon Cells, Motor, Monoaminergic and Peptidergic neurons. Supplementary_spreadsheet_6_Differential_expression_cluster_big_classes.ods. Spreadsheet containing one sheet per major cell-type class and their defining markers: Immature neurons, Cholinergic neurons, Neuroprecursor cells, Gabaergic neurons, Glutamatergic neurons, Kenyon cells, Unknown neurons, Motorneurons, Glia, Hemocytes, Epithelia/trachea, Monoaminergic neurons, Peptidergic neurons and Ring Gland. Supplementary_spreadsheet_7_NPCs_markers_among.xlsx. Spreadsheet containing one sheet per Neuroprecursor cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Neuroprecursor clusters only. Supplementary_spreadsheet_8_Immature_neuron_markers_among.xlsx. Spreadsheet containing one sheet per Immature neuron cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Immature neuron clusters only. Supplementary_spreadsheet_9_Cholinergic_markers_among.xlsx. Spreadsheet containing one sheet per Cholinergic cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Cholinergic clusters only. Supplementary_spreadsheet_10_Gabaergic_markers_among.xlsx. Spreadsheet containing one sheet per Gabaergic cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Gabaergic clusters only. Supplementary_spreadsheet_11_Glutamatergic_markers_among.xlsx. Spreadsheet containing one sheet per Glutamatergic cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Glutamatergic clusters only. Supplementary_spreadsheet_12_Octopaminergic_markers_among.xlsx. Spreadsheet containing one sheet per Octopaminergic cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Octopaminergic clusters only. Supplementary_spreadsheet_13_Serotoninergic_markers_among.xlsx. Spreadsheet containing one sheet per Serotoninergic cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Serotoninergic clusters only. Supplementary_spreadsheet_14_Peptidergic_markers_among.xlsx. Spreadsheet containing one sheet per Peptidergic cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Peptidergic clusters only. Supplementary_spreadsheet_15_Kenyon-Cells_markers_among.xlsx. Spreadsheet containing one sheet per Kenyon cells cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Kenyon cells clusters only. Supplementary_spreadsheet_16_Glia_markers_among.xlsx. Spreadsheet containing one sheet per Glia cluster and their markers resulting from running the FindAllMarkers algorithm as detailed in the methods but restricting it to Glia clusters only. Supplementary_spreadsheet_17_Enriched_markers_per_cluster_48_vs_24h.xlsx. Spreadsheet containing one sheet per big cell-type class with all the markers enriched at 48h vs 24h resulting from running the FindAllMarkers algorithm as detailed in the methods for the temporal analysis but restricting it to 48 vs 24h. Supplementary_spreadsheet_18_selective_one_per_class_075-19.xlsx. Spreadsheet containing one sheet per cluster with all markers selective for that cluster when imposing a cut-off of log2 fold-change greater than 0.75 and the requirement of being detected in more than 19% of cells. Supplementary_spreadsheet_19_Identity_markers_and_refs.ods. Spreadsheet containing the list of all markers used to identify cell classes together with literature references. Supplementary_spreadsheet_20_Brain_only_atlas_markers.xlsx. Spreadsheet containing one sheet per cluster with all markers selective for that cluster when imposing a cut-off of log2 fold-change greater than 0.75 and the requirement of being detected in more than 19% of cells. In the Brain samples and the VNC samples it can be seen that there is a drastic increase of immature neurons relative to mature neurons from 24 hrs to 48 hrs. In the Brain samples, at 24 hrs, the ratio of immature (4885) to mature neurons (8536) is 0.57; at 48 hrs the ratio of immature (12092) to mature neurons (9758) is 1.23 (2.2-fold increase). Supplementary_spreadsheet_21_VNC_only_atlas_markers.xlsx. Spreadsheet containing one sheet per cluster with all markers selective for that cluster when imposing a cut-off of log2 fold-change greater than 0.75 and the requirement of being detected in more than 19% of cells. In the Brain samples and the VNC samples it can be seen that there is a drastic increase of immature neurons relative to mature neurons from 24 hrs to 48 hrs. In the VNC samples, at 24 hrs, the ratio of immature (3146) to mature neurons (4885) is 0.64; At 48 hrs the ratio of mature (2173) to immature (3513) is 1.61 (2.5-fold increase). Supplementary_Figure_1_UMAP_plot_per_tissue.pdf. UMAP representation of the CNS cell type diversity discovered after reciprocal-PCA integration, dimensionality reduction and unsupervised clustering with Seurat and split by tissue of origin. In this 2D representation each dot represents a cell and their distribution in space is a function of their similarity in gene expression profile. Each cluster is color and number coded as depicted in the accompanying legend. Supplementary_Figure_2_Brain_independent_analysis.pdf. UMAP dimensional reduction plot with the annotated clustering resulting from the analysis of VNC samples only at 24 and 48h. Supplementary_Figure_3_VNC_independent_analysis.pdf. UMAP dimensional reduction plot with the annotated clustering resulting from the analysis of Brain samples only at 24 and 48h. Supplementary_Figure_4_endogenous-nSyb-feature_plot.pdf. Feature plot comparing the expression distribution of endogenous and UAS-GAL4 amplified expression of nSyb. Supplementary_Figure_5_feature_plot_nSyb_Repo_Notch.pdf. UMAP dimensional reduction showing the expression distribution of endogenous nSyb, repo and Notch. In this 2D representation each dot represents a cell and their distribution in space is a function of their similarity in gene expression profile. Color represents the expression of the gene for that particular cell. In each dotplot, the centered mean expression of a gene for each class is calculated and given a color ranging from blue (lowest expression) to red (highest expression), with white corresponding to 0. In this fashion different genes can be compared by their relative expression in the classes depicted irrespective of their absolute expression levels. The diameter of each dot is proportional to the number of cells expressing that gene in the class. Supplementary_Figure_6_cholinergic_markers_dotplot.pdf. Dotplot depicting Cholinergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_7_glutamatergic_markers_dotplot.pdf. Dotplot depicting Glutamatergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_8_gabaergic_markers_dotplot.pdf. Dotplot depicting Gabaergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_9_octopaminergic_markers_dotplot.pdf. Dotplot depicting Octopaminergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_10_serotoninergic_markers_dotplot.pdf. Dotplot depicting Serotoninergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_11_dopaminergic_markers_dotplot.pdf. Dotplot depicting Dopaminergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_12_peptidergic_markers_dotplot.pdf. Dotplot depicting Peptidergic markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_13_Cholinergic_among_markers_dotplot.pdf. Dotplot depicting Cholinergic markers showing an average log2 fold-change greater than one compared to the other Cholinergic clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_14_Glutamatergic_among_markers_dotplot.pdf. Dotplot depicting Glutamatergic markers showing an average log2 fold-change greater than one compared to the other Glutamatergic clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_15_cotransmitter_upset_number.pdf. Histogram with numbers and percent of cells expressing combinations of one, two, three and four fast acting neurotrasmitters compared to single neurotransmitter expressing ones. Supplementary_Figure_16_Gabaergic_among_markers_dotplot.pdf. Dotplot depicting Gabaergic markers showing an average log2 fold-change greater than one compared to the other Gabaergic clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_17_Octopaminergic_among_markers_dotplot.pdf. Dotplot depicting Octopaminergic markers showing an average log2 fold-change greater than one compared to the other Octopaminergic clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_18_Serotoninergic_among_markers_dotplot.pdf. Dotplot depicting Serotoninergic markers showing an average log2 fold-change greater than one compared to the other Serotoninergic clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_19_hemocytes_markers_dotplot.pdf. Dotplot depicting Hemocyte markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_20_ring-gland_markers_dotplot.pdf. Dotplot depicting Ring gland markers showing an average log2 fold-change greater than one compared to the other clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_21_Glia_among_markers_dotplot.pdf. Dotplot depicting Glia markers showing an average log2 fold-change greater than one compared to the other Glia clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_22_Immature_among_markers_dotplot.pdf. Dotplot depicting Immature neuron markers showing an average log2 fold-change greater than one compared to the other Immature clusters and present in at least more than 19% of the cells of the cluster. Supplementary_Figure_23_Npcs_among_markers_dotplot.pdf. Dotplot depicting Immature neuron markers showing an average log2 fold-change greater than one compared to the other Immature clusters and present in at least more than 19% of the cells of the cluster.