Journal: Immunity

Article Title: The cytokine TNF promotes transcription factor SREBP activity and binding to inflammatory genes to activate macrophages and limit tissue repair

doi: 10.1016/j.immuni.2019.06.005

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: SureCell WTA 3′ Library Prep Kit for the ddSeq System , Illumina , Cat# 200142780.

Techniques: Purification, Control, Virus, Plasmid Preparation, Recombinant, Amplex Red Cholesterol Assay, cDNA Synthesis, SYBR Green Assay, Multiplex Assay, RNA Library Preparation, Microarray, Software

Journal: bioRxiv

Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

doi: 10.64898/2026.03.11.710939

Figure Lengend Snippet: a , UMAP of GCs, colored by seven GC subtypes (Progenitor, Preantral 1, Preantral 2, Mitotic 1, Mitotic 2, Antral Mural and Atretic). b , Feature plots of representative subtype markers on the UMAP. c , Monocle3 pseudotime trajectory inferred for GCs, with the principal graph overlaid and direction indicated from progenitor toward antral mural cells. d , Heatmap of representative genes showing coordinated expression changes along the progenitor-to-mural trajectory (expression shown as z-scores). e , Heatmap of Hallmark ssGSEA scores across granulosa subtypes (z-scored per gene set). f , H&E image of a Stereo-seq FF V1.3 mouse ovary section (6-8 weeks old), with representative regions (α–θ) indicated. Scale bar, 100 μm. g , Cell2location-based spatial mapping of GC subtypes at cell-bin resolution. h , Zoom-in views of representative regions (α, β, γ, and θ) showing H&E morphology and spatial expression of selected marker genes. Scale bar, 50 μm.

Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

Techniques: Expressing, Marker

Journal: bioRxiv

Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

doi: 10.64898/2026.03.11.710939

Figure Lengend Snippet: Spatial maps showing cell2location-predicted localization of each annotated cell subtype on the Stereo-seq FF V1.3 ovary section (6–8 weeks old), displayed separately by subtype. Scale bar, 100 μm

Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

Techniques:

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Inputs to CalicoST are transcript counts X 0 , allele counts Y 0 and D 0 , spatial coordinates S from one or more SRT slices or a 3D alignment of slices. b , CalicoST phases input alleles in Y 0 and D 0 using a database of haplotypes. Optionally, CalicoST infers tumor proportion per spot using the BAF. CalicoST jointly models transcript counts and allele counts as functions of allele-specific copy number states within each clone. CalicoST uses an HMM to model correlations between copy number states from adjacent genomic regions and a HMRF to model correlations between the cancer clones assigned to neighboring spatial locations. c , CalicoST infers allele-specific integer copy numbers for one or more cancer clones, a phylogeny relating these clones, a clone label, an optional tumor proportion for each spot and a phylogeographic model of the spatial expansion of cancer clones.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Accuracy of allele-specific copy numbers across 12 patients from HTAN (WashU cohort) inferred by CalicoST. Each bar represents an inferred cancer clone. b , Length distribution of CNAs identified by CalicoST from SRT data and identified by HATCHet2 from WES for the 9 patients with matched WES data of sufficient tumor purity. Blue bars are CalicoST, and orange bars are HATCHet2, with gray bars indicating the overlap of the two histograms. The median length is 77.4 Mb for CalicoST and 30 Mb for HATCHet2 (vertical dashed lines). c , Allele-specific integer copy numbers inferred by CalicoST from SRT data from a patient with CRC liver metastasis (HT230C1). Rows are cancer clones, and columns are genomic bins. Colors indicate allele-specific copy numbers. d , Allele-specific integer copy numbers inferred by CalicoST from SRT data from a patient with CRC liver metastasis (HT260C1). e , Observed RDR and BAF for chr8 of HT260C1. Points are colored by the inferred allele-specific copy numbers. Horizontal black lines indicate the RDR and BAF of the corresponding copy number states estimated by the HMM. f , Allele-specific integer copy numbers inferred by HATCHet2 from WES data of patient HT260C1. g , RDR and BAF values from WES data for bins from chromosome 8q and bins from other genomic regions with a value of {3,0} copy number state. Black points are expected RDR and BAF values for {3,0} and {2,1} states from HATCHet2 analysis.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) CalicoST-inferred cancer clones in PDAC patient HT270P1. Grayscale indicates the inferred tumor proportion within each spot, where more gray indicates a higher proportion of normal cells (lower tumor proportion). ( b ) RDR and BAF along the genome for each inferred clone in HT270P1. Each point represents a genomic bin and is colored by CalicoST-inferred allele-specific copy numbers. The red box highlights a unique deletion in clone 2. ( c – d ) Corresponding plots for PDAC patient HT288P1. Red boxes highlight deletions that are unique to one of the inferred clones.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: H&E images (top) and CalicoST-inferred tumor proportions (bottom) for breast cancer samples: ( a ) HT206B1, ( b ) HT339B1, ( c ) HT268B1, ( d ) HT265B1. The x- and y-axes represent spatial coordinates. The color bar indicates the inferred tumor proportions.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques:

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: The plots for CalicoST include the allele-specific CNAs from all inferred cancer clones, labeled as ‘clone 1’, ‘clone 2’, etc. The plots for HATCHet2, labeled as ‘WES’, are included for the nine patients for whom matched WES data is available and has sufficient tumor purity.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay, Labeling

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , b , Accuracy ( a ) and spatial coherence ( b ) comparison among CalicoST, Numbat, InferCNV and STARCH on CRC liver metastasis patient samples. Solid bars indicate predictions of allele-specific copy number states, and dotted bars indicate predictions of total copy number states. c , H&E image of a CRC liver metastasis sample HT260C1. d , Cancer clones inferred by CalicoST. x and y axes are spatial coordinates, and the grayscale represents the proportion of normal cells within each spot, as inferred by RCTD. Other colors indicate cancer clones. e , Cancer clones inferred by Numbat using the same color scheme as in d .

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Comparison, Starch, Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) Accuracy of the allele-specific copy number states inferred by CalicoST and Numbat on nine HTAN patients where ‘ground truth’ CNAs were inferred from matched WES data. ( b ) Spatial coherence of the cancer clones inferred by CalicoST and Numbat. The spatial coherence is evaluated by the z-score of joincount statistics, with higher values indicating a greater degree of spatial coherence. Each point represents a cancer clone within each slice of each patient (x-axis). As the two methods identify different numbers of clones, the two boxes include varying numbers of points for each patient. From left to right, the numbers of points in the boxplots are: HT112C1 (6 for CalicoST and 11 for Numbat), HT260C1 (3 for CalicoST and 6 for Numbat), HT265B1 (3 for CalicoST and 4 for Numbat), HT268B1 (10 for CalicoST and 39 for Numbat), HT270P1 (2 for CalicoST and 12 for Numbat), HT288P1 (2 for CalicoST and 6 for Numbat), HT306P1 (2 for CalicoST and 5 for Numbat). The upper and lower bounds of the box denote the 25% and 75% quantiles, the center line denotes the median, and the lower (upper) whiskers denote the smallest (largest) value within 1.5 times the IQR (interquartile range).

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Spatial distribution and phylogeographic tree of three cancer clones inferred by CalicoST in two adjacent slices from patient HT112C1 with CRC liver metastasis. The grayscale indicates the inferred proportion of normal cells within each spot. Diamonds are the spatial centroid of each clone or inferred ancestor, and arrows indicate the inferred directions of tumor development. The distance between two slices in the z -coordinate is enlarged for clearer visualization. b , Allele-specific copy number profiles for the three cancer clones and the corresponding phylogeny (right) with branches in the phylogeny labeled by the number of unique large LOH events that occur on the branch. c , Spatial distribution and phylogeographic tree of two cancer clones inferred by CalicoST in five adjacent slices from patient HT268C1 with breast cancer. Color scheme is the same as a . d , Inferred allele-specific copy numbers and tumor phylogeny.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay, Labeling

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Spatial distribution of cancer clones inferred jointly by CalicoST across five slices from a cancerous prostate. Positioning of five slices is according to ref. . Colors indicate inferred clones, including the normal clone in gray. Arrows represent the phylogeography of tumor evolution. b , Allele-specific copy number profiles for the five cancer clones and the corresponding phylogeny with branches in the phylogeny labeled by the number of unique large LOH events that occur on the branch. Colors indicate allele-specific copy numbers. The orientation and position of triangles indicate mirrored CNA events. c , BAF of each clone in chr6 and chr8. Colors indicate allele-specific copy numbers using the same color scheme as in b .

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay, Labeling

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) UMAP of gene expression in spots from five slices of a multi-section prostate cancer patient (without applying any batch effect correction or integration tools). Each point represents a spot, colored by the slice location. ( b ) UMAP of gene expression from five slices, with each spot (point) colored according to the clone assignment from CalicoST. Grayscale indicates the inferred tumor proportion, with more gray representing a higher proportion of normal cells. ( c ) BAF along the genome for spots assigned to clone 5 from three slices (H1 4, H1 5, and H2 5) from the right portion of the prostate. Each point represents a genomic bin, colored by the inferred allele-specific copy numbers from CalicoST.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Gene Expression

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: Each spot is colored by the clone inferred by CalicoST, with gray indicating normal spots. Spots containing the variant allele of the somatic SNV are marked by a black cross. Spots containing the reference allele are marked by a gray circle. The first five SNVs are inferred to be truncal SNVs present in both the left and right sides of the prostate, while the sixth SNV (bottom right) is inferred to be present in only the left side.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Variant Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) Spatial organization of normal (clone 0) and three tumor clones (clones 1-3) inferred by CalicoST on a human melanoma sample sequenced using Slide-tags. ( b ) Compar- ison of cell type labels for each location from and clone labels inferred by CalicoST. ( c ) Allele-specific copy numbers inferred by CalicoST for each clone. ( d ) RDR and BAF along the genome for clones 1 and 2. Colors indicate the allele-specific copy number of the corresponding genomic bin. Red box highlights a LOH event on chr3q that is unique to clone 2.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a , Optic lobe cross-section , with drawings of unicolumnar (orange shades) and multicolumnar (blue) neurons. Dashed lines: boundaries between layers. A: anterior, L: lateral, M: medial, P: posterior. b, Approach followed to produce the adult dataset. c, Pearson correlation between the average gene expression of the adult dataset clusters (x-axis) and the transcriptome of isolated Lawf1 neurons (Methods). d, tSNE visualization of the final adult dataset, using 120 principal components calculated on the log-normalized integrated gene expression. The 61 identified neuronal clusters are labeled by their standard abbreviation, G1–16: glial clusters, LQ: low-quality cells, G/LQ1–4: glial clusters with some features of low-quality cells, *: clusters with less confident annotations . e, Approximate time frames of different steps of optic lobe development, and tSNE visualizations of the pupal datasets. Colors match to the adult dataset as classified by the neural network. f, Multi-task neural network classifier used at each stage to sequentially match developing cells to the adult clusters, as detailed in .

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Gene Expression, Isolation, Labeling

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a. The proportions of UMIs from mitochondrial genes per cell (n = number of cells in each library, indicated on the right) and the total number of cells passing filters in each of the 15 libraries comprising the adult dataset. Names indicated correspond to the names in the Seurat object provided (Adult.rds, GSE142787). Boxplots display the first, second and third quartiles. Whiskers extend from the box to the highest or lowest values in the 1.5 inter-quartile range, and outlying datapoints are represented by a dot. b, Origin of the cells in the final adult clusters, colored as in (a). Green arrows: clusters whose unique library distribution can be explained by variable contamination from surrounding tissues (cluster 3 is photoreceptors, 112 is likely Kenyon Cells from the central brain) or the number of lamina neuropils dissociated (clusters 107, 108, 109 are lamina neurons). Red arrows: clusters likely enriched in low quality transcriptomes, as they are enriched in cells from libraries with high number of mitochondrial genes (38, 120, 192) or high number of cells sequenced (102, likely corresponding to multiplets). Brackets: Glial clusters, some of them enriched in libraries with high number of mitochondrial genes as ambient RNA is more similar to RNA from glial vs . neuronal cells . c, Number of clusters obtained with different pairs of clustering parameters. Red rectangle: pair of parameters used. d, Left: Legend as in . Right: Number of isolated neuronal type transcriptomes matching to 1–5 of our adult clusters, for each pair of parameters in (c), which we used as a measure of the biological relevance of our clusters. Matching was defined by the presence of a correlation gap above 0.05 (Methods). We took into account any correlation gap between the 6 best correlated clusters, since similar cell types or overclustering can affect the size of the first correlation gap as illustrated on the left graphs. Red rectangle: pair of parameters used. e, tSNE visualization of the adult optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cell colors indicate the cluster they belonged to before we merged artificially split clusters (red circles, Methods). f, Heatmap showing scaled log-normalized non-integrated expression of the top20 cluster markers between the merged clusters. Merged clusters had almost indistinguishable gene expression patterns, but often differed by their proportions of UMI from mitochondrial genes per cell or the expression levels of the genes highlighted in red, which are enriched in the “ambient RNA cluster” 192 (see also ).

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Isolation, Gene Expression, Expressing

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a, Pearson correlation between the average log-normalized non-integrated expression of the top10 cluster markers of the adult dataset clusters (x-axis) and the transcriptome of isolated Repo+ (glial marker) or Elav+ (neuronal marker) populations. LQ = clusters containing a proportion of cells with features of lower quality transcriptomes. b, Violin plots of features tending to be higher (proportions of UMI from mitochondrial genes) or lower (number of UMIs or genes per cell) in low quality cells , . c, Heatmap showing the scaled log-normalized non-integrated expression of the top5 cluster markers of the adult dataset. The first 5 neuronal adult clusters (1 to 6, cluster 1 and 2 having been merged) are plotted for reference as they clearly have specific gene expression patterns. Clusters 38, 85, 102 and 120 present much less defined gene expression patterns and likely contain low quality neuronal transcriptomes (see also ). Clusters 188 and 189 could be further separated in two groups with different gene expression patterns, as illustrated by the dashed line in the insert. Cluster 191 expresses several markers found in no other clusters and likely correspond to neither glia nor optic-lobe neuron. Cluster 192 expresses mainly low levels of glia-specific genes, without specific markers. It likely corresponds to ambient RNA, which would be enriched in RNA from burst glial cells.

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Expressing, Isolation, Marker, Gene Expression

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a, Pearson correlation between the average log-normalized non-integrated expression of the top10 cluster markers of the adult dataset clusters (x-axis) and the transcriptome of isolated neurons , . We represented Dm3, Tm9, T4 and T5 before their split into Dm3a/b, Tm9v/d, T4/T5ab and T4/T5cd. When two transcriptomes were published for a given neuronal type, the one presenting the highest correlation gap is displayed in this figure. R1–8: average gene expression of all photoreceptors . KC: Kenyon Cells, cluster 112 therefore likely corresponds to contamination from the central brain. b, Legend as in (a). We indicated several matching clusters to highlight the high similarity between LC cells transcriptomes, which explains the lower correlation gaps observed for these neurons. c, Left: Legend as in (a). Right: mixture modelling of Pm3 markers (y axis). Clusters are spread on the x-axis, with the probability of expression of the markers figured by the size of the black dots.

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Expressing, Isolation, Gene Expression

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a-b, tSNE visualization of the P70 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells colors indicate the clusters they belonged to according to unsupervised clustering (a), or the adult clusters they were classified as by the neural network (b, same as in ). Black circles indicate high granularity regions, where less frequent cell types were grouped together by unsupervised clustering but could be resolved accurately by the neural network (b). c, Same as in (a-b) but cells are named and colored by the adult cluster they were classified as by Seurat label transfer (Methods). d, tSNE visualizations (same as c) including only the cells that were assigned inconsistent identities by Seurat and the neural network. Highest rates of inconsistencies were observed in the center (LQ cells), in L1 and L2 clusters (red ellipses), in most glia clusters (green ellipses), the TE neurons and a glia-like cluster (identity 214, ) with no adult correspondence (blue ellipses). e-f, tSNE visualizations of 56,902 cells sequenced from whole fly brains , using 120 principal components calculated on the log-normalized gene expression. e, Cells are named and colored by the clusters they were classified as by our neural network. f, Cells are named by the cluster identities from the original study and colored by the confidence score they received from our neural network. Black circles mark the following central brain clusters (from left to right): Poxn, OPN, clock neurons and dopaminergic neurons, that all received low scores from the neural network. Kenyon cells (red circles) were assigned with high confidence as our adult dataset was contaminated by them (cluster 112).

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Gene Expression

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: tSNE visualizations of all optic lobe single-cell transcriptomes acquired for this study, using 120 principal components calculated on the log-normalized integrated gene expression. The cells are named and colored consistently at all stages by the neural network classifications with manual adjustments as detailed in . Blue ellipses: Dm3 and Tm9 neuronal subtypes, which could only be resolved at P50 and earlier.

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Gene Expression

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a-b, tSNE visualization of the P70 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are named by the unsupervised cluster they were assigned to and colored by (a) the confidence score they received from the neural network (NN) or by (b) the log-normalized non-integrated expression of Fs (green), dimm (blue), and skl (red), which are co-expressed in TE neurons (red ellipses). c , Violin plot of log-normalized non-integrated prt expression in all clusters at P50. TE neuron clusters are indicated by circle. d , R10D10-Gal4 co-expression with anti-Prt staining in a P50 optic lobe (n=15 neurons). Scale bar: 10 μm. e , FLEXAMP memory cassette labeling of R10D10-Gal4 in an adult optic lobe (n=28 brains) with anti-NCad staining. Scale bar: 30 μm. f, R10D10-Gal4 expression pattern in L3 optic lobe (n=15 brains), with anti-NCad, anti-Bsh and anti-Hth staining. Arrow: Bsh + , Hth - neurons labeled by R10D10-Gal4 . Scale bar: 30 μm. g-h, R10D10-Gal4 sparse expression at P30 (n=40 neurons), with anti-NCad, anti-Bsh and anti-Hth staining. Scale bars = 5 μm (g) and 15 μm (h). d/pMe: distal/proximal Medulla, Lo: Lobula, Lp: Lobula plate. I , Co-labeling of R10D10-LexA expression and bsh-Gal4 FLEXAMP memory cassette with anti-nCad staining in a P50 optic lobe (n=13 brains). Dashed ellipses: TE neurons. Scale bar: 20 μm.

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Gene Expression, Expressing, Staining, Labeling

Journal: Nature

Article Title: Neuronal diversity and convergence in a visual system developmental atlas

doi: 10.1038/s41586-020-2879-3

Figure Lengend Snippet: a-b, tSNE visualization of the P15 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are named by the unsupervised cluster they were assigned to and colored by (a) the confidence score they received from the neural network or by (b) the log-normalized non-integrated expression of dpn (green), ase (blue), and grim (red). Circles match to those of . c, UMAP visualization of the P15 optic lobe single-cell transcriptomes, using 120 principal components calculated on the log-normalized integrated gene expression. Cells are colored by the log-normalized non-integrated expression of nerfin-1 (green), Hey (blue), and vfl (red) d, UMAP visualization of Tm3 and T1 cells (above and below the dashed line, respectively) from all stages sequenced in this study, using 25 principal components calculated on the log-normalized non-integrated gene expression. Cells are colored by their developmental stage. e, Ventral and dorsal Transient Extrinsic (TE) neurons as well as transient photoreceptors (PRs) line the edges of all optic lobe neuropils and express Follistatin ( Fs ). Moreover, TE and at least 3 other neuronal types express Wnt4 in the ventral medulla/lobula but express Wnt10 in the dorsal part of these neuropils. f, The transcriptome of neurons from the same neuronal type but produced days apart converge towards a similar transcriptomic state, which they reach by P30. Moreover, the inter-neuronal type transcriptomic diversity is highest during P40-P70.

Article Snippet: To produce an exhaustive catalog of neurons in the adult optic lobe ( – ), we obtained 109,743 single-cell transcriptomes (Methods) using the Chromium system (10x Genomics).

Techniques: Gene Expression, Expressing, Produced