scatac rna seq chromium next gem single cell multiome atac gene expression reagent kits  (10X Genomics)

Journal: bioRxiv

Article Title: Cell-type aware regulatory landscapes governing monoterpene indole alkaloid biosynthesis in the medicinal plant Catharanthus roseus

doi: 10.1101/2024.04.23.590703

Figure Lengend Snippet: A. Gene expression heatmap of the MIA biosynthetic genes across overexpression treatments. Each row is a biosynthetic gene or transporter, ordered from upstream to downstream. Color scale represents scaled expression (z score). Combo: the combinatory treatment in which IDW1 and IDM1/2/3 are co-infiltrated. B. Mean separation plots showing expression levels of D4H and DAT (in units of transcripts per million) in the 0.4 OD treatments. Each data point is a biological replicate. Error bars represent average and standard error. Black × indicates average. C. Bar graph showing percentage of genes that are most highly expressed in the idioblast. Expressed genes: all 18,523 expressed genes in this single cell multiome dataset. MYC2-ORCA3: 3,378 differentially expressed genes that are upregulated in the MYC2-ORCA3 overexpression treatment. IDM1: 1,057 differentially expressed genes that are upregulated in the 0.4 OD overexpression IDM1 treatment. D. Gene expression heatmap of IDM1 metabolic regulon (see also Supplementary Table 11). Color scale shows the average scaled expression of each gene at each cell cluster. Dot size indicates the percentage of cells where a given gene is detected. The predicted cell type for each cell cluster is annotated by the color strip below the x-axis. Box highlights genes specifically expressed in the idioblast.

Article Snippet: We first isolated intact nuclei (Supplementary Fig. 1B-I) from mature C. roseus leaves and constructed replicated single cell multiome (RNA-seq and assay for transposase accessible chromatin followed by sequencing [ATAC-seq]) libraries using the 10x Genomics Multiome Kit (Supplementary Table 2).

Techniques: Gene Expression, Over Expression, Expressing, Stripping Membranes

Journal: bioRxiv

Article Title: Single-cell and spatial multiomic inference of gene regulatory networks using SCRIPro

doi: 10.1101/2023.12.21.572934

Figure Lengend Snippet: SCRIPro takes single cell RNA-seq or spatial RNA-seq as input. SCRIPro first employs density clustering using a high coverage SuperCell strategy. While for spatial data, SCRIPro combines gene expression and cell spatial similarity information to a latent low-dimension embeddings via a graph attention auto-encoder. Then SCRIPro conducts in silico deletion analyses, utilizing matched scATAC-seq or reconstructed chromatin landscapes from public chromatin accessibility data, to assess the regulatory significance of TRs by RP model in each SuperCell. At last, SCRIPro combines TR expression and TR to generate TR-centered GRNs at the SuperCell resolution. The output of SCRIPro can be applied for TR target clustering, temporal GRN trajectory and spatial GRN trajectory.

Article Snippet: Single cell multiome ATAC-RNA-seq data is available from 10X genomics ( https://www.10xgenomics.com/resources/datasets/fresh-frozen-lymph-node-with-b-cell-lymphoma-14-k-sorted-nuclei-1-standard-2-0-0 ) Hair follicle SHARE-seq data was downloaded from the GEO database ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE140203 ).

Techniques: RNA Sequencing Assay, Expressing, In Silico

Journal: bioRxiv

Article Title: Single-cell and spatial multiomic inference of gene regulatory networks using SCRIPro

doi: 10.1101/2023.12.21.572934

Figure Lengend Snippet: A. SCRIPro identified 10 clusters on mouse brain spatial ATAC-RNA-seq (RNA). B. Heatmap of spatial variable TR clustering by 6 cell type regions. C. SCRIPro activity score of selected marker TR in spatial. D. SCRIPro predicts Sox2 and Mef2c target genes then builds GRNs, and utilizes these target genes for GO analysis. E. Wasserstein distance of Ligand and Notch1 receptor in different regions.

Article Snippet: Single cell multiome ATAC-RNA-seq data is available from 10X genomics ( https://www.10xgenomics.com/resources/datasets/fresh-frozen-lymph-node-with-b-cell-lymphoma-14-k-sorted-nuclei-1-standard-2-0-0 ) Hair follicle SHARE-seq data was downloaded from the GEO database ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE140203 ).

Techniques: RNA Sequencing Assay, Activity Assay, Marker