Journal: Genome Biology

Article Title: Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue

doi: 10.1186/s13059-023-03066-w

Figure Lengend Snippet: Overview of the smFISH RNAscope experiment and DLPFC anatomy. a Illustration of RNAscope experimental design where a single DLPFC tissue block was used to generate 9 spatially adjacent slices. These 9 slices were hybridized with 3 RNAscope probe combinations noted as the AKT3 , ARID1B , and MALAT1 / POLR2A experiments (related to Additional file : Tables S4-S5). Candidate TREGs and POLR2A are shown in black, while GAD1 , SLC17A7 , and MBP are cell-type marker genes for inhibitory neurons (red), excitatory neurons (blue), and oligodendrocytes (orange), respectively. b Annotated image of DLPFC tissue, noting the location of gray matter (GM), white matter (WM), and sulcus. c Spatial distribution of cells expressing MBP for each sample. MBP is an oligodendrocyte cell type marker gene enriched in white matter

Article Snippet: Segmentation was optimized for each dye for each tissue section by adjusting several values with reference to the manufacturer’s guidelines: HALO 3.3 FISH-IF Step-by-Step guide (Indica Labs, version 2.1.4 July 2021) and Quantitative RNAscope Image Analysis Guide (Indica Labs).

Techniques: Blocking Assay, Marker, Expressing

Journal: Genome Biology

Article Title: Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue

doi: 10.1186/s13059-023-03066-w

Figure Lengend Snippet: Expression of TREGs in individual nuclei using smFISH with RNAscope. Representative high-magnification images showing the expression of candidate TREGs a AKT3 , b ARID1B , c HK gene POLR2A , and d MALAT1 and in human DLPFC. Insets show individual nuclei with high expression (yellow arrow), low expression (green arrow), or in rare cases (≤ 14% for candidate TREGs and 22% for POLR2A , Table ) no expression (purple arrow). Each puncta represents a single transcript, as illustrated in Fig. a. MALAT1 shows extremely high expression in the majority of nuclei such that individual puncta cannot be quantified (yellow arrow). Scale bar is 20 um

Article Snippet: Segmentation was optimized for each dye for each tissue section by adjusting several values with reference to the manufacturer’s guidelines: HALO 3.3 FISH-IF Step-by-Step guide (Indica Labs, version 2.1.4 July 2021) and Quantitative RNAscope Image Analysis Guide (Indica Labs).

Techniques: Expressing

Journal: Genome Biology

Article Title: Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue

doi: 10.1186/s13059-023-03066-w

Figure Lengend Snippet: Proportion of nuclei that displayed any TREG candidate or POLR2A puncta. Proportion of nuclei with a non-zero count in the DLPFC snRNA-seq data compared against the mean proportion of non-zero puncta in the nucleus and mean number of puncta observed in the RNAscope data for the candidate TREGs and POLR2A . Beta values are the slope of the linear fit of the number of puncta over ordered cell types and the 95% confidence interval. The standardized beta is the slope of the linear fit of the number of puncta divided by the standard deviation of the number of puncta for each gene. Standardized betas enable the comparison between snRNA-seq and RNAscope data. The standardized beta in snRNA-seq is − 1.33 (− 1.35, − 1.31). With RNAscope, AKT3 is the TREG that most similarly follows the trend across all genes in snRNA-seq (see also Fig. 7 ). Due to the inability to resolve individual puncta for MALAT1 , the observed trend (Additional file 2 : Fig. S10) is unreliable

Article Snippet: Segmentation was optimized for each dye for each tissue section by adjusting several values with reference to the manufacturer’s guidelines: HALO 3.3 FISH-IF Step-by-Step guide (Indica Labs, version 2.1.4 July 2021) and Quantitative RNAscope Image Analysis Guide (Indica Labs).

Techniques: Standard Deviation, Comparison

Journal: Genome Biology

Article Title: Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue

doi: 10.1186/s13059-023-03066-w

Figure Lengend Snippet: Boxplots of total RNA nuclear expression in the nucleus across cell types. a Distribution of total nuclear RNA expression (estimated with the sum of total UMIs per nucleus) in DLPFC snRNA-seq data across excitatory neurons (Excit), inhibitory neurons (Inhib), and oligodendrocytes (Oligo). b Distribution of the number of puncta quantified by RNAscope for each observed gene across the same cell types as in a . The number of puncta by RNAscope estimates the total RNA expression by snRNA-seq (Fig. a). POLR2A was only evaluated in excitatory neurons and oligodendrocytes as it was multiplexed with MALAT1 and GAD1 was omitted

Article Snippet: Segmentation was optimized for each dye for each tissue section by adjusting several values with reference to the manufacturer’s guidelines: HALO 3.3 FISH-IF Step-by-Step guide (Indica Labs, version 2.1.4 July 2021) and Quantitative RNAscope Image Analysis Guide (Indica Labs).

Techniques: Expressing, RNA Expression, Inhibition

Journal: Cancers

Article Title: Unique Spatial Immune Profiling in Pancreatic Ductal Adenocarcinoma with Enrichment of Exhausted and Senescent T Cells and Diffused CD47-SIRPα Expression

doi: 10.3390/cancers12071825

Figure Lengend Snippet: CD8+ T lymphocytes in the tumor center (TC) and the invasive front (IF) exhibit an exhausted phenotype. ( A ) RNAscope analysis to examine the co-expression of HAVCR2 (green) and/or PDCD1 (red) and CD8A (yellow) in PDAC patients. Representative confocal micrographs in PDAC patients without (w/o) neoadjuvant therapy and PDAC patients who received neoadjuvant chemotherapy. Dashed line delineates the invasive front (IF). Yellow asterisks depict cancer glands. Double arrowheads indicate CD8A -positive cells co-expressing HAVCR2/PDCD1 and single arrowheads depict only CD8A expressing T lymphocytes. Scale bar: 100 μm ( B ) Quantification of CD8+ T lymphocytes expressing HAVCR2/PDCD1 mRNA in PDAC patients who did not receive neoadjuvant therapy. ** p -value < 0.01. Data are expressed as mean ± STDEV (N = 5). ( C ) Quantification of CD8+ T lymphocytes expressing HAVCR2/PDCD1 mRNA in PDAC patients who received neoadjuvant chemotherapy. ** p -value < 0.01. Data are expressed as mean ± STDEV (N = 3). Tumor center (TC), invasive front (IF), normal parenchyma adjacent to the tumor (NAT).

Article Snippet: A restricted funding was received by GlaxoSmithKline to support RNAscope analysis.

Techniques: RNAscope, Expressing

Journal: bioRxiv

Article Title: Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

doi: 10.1101/2023.04.20.537710

Figure Lengend Snippet: ( A ) Flowchart of experimental design and data analysis. Human ITC tissues from 3 original AD donors plus additional male donor Br8549 were subjected to multiplexed staining using RNAscope smFISH combined with immunofluorescence (FISH-IF) to detect genes of interest (GOIs) and Aβ plaques. Images were analyzed with HALO image analysis software to assess spatial relationships between Aβ and cells expressing GOI. The FISH-IF module of HALO was used for image segmentation and quantification of Aβ and GOIs. The proximity analysis module was used to determine a distance between Aβ and cells expressing or not expressing GOIs. The outputs of the two modules were integrated to measure the gene expression of GOIs within a predefined proximity of Aβ at cellular resolution. ( B ) Schematic describing proximity analysis. An Aβ-associated microenvironment was demarcated by approximating the Visium spot grid-line system in which the center of a single Visium spot is 127.5µm away from its neighboring spot. This distance was further subdivided into 6 evenly spaced intervals, resulting in a total of 7 bins to finely resolve the spatial gene expression gradients of GOIs. The proximity between Aβ and nearby cells expressing and not expressing GOIs was measured and used to classify into the 7 bins for quantifying the average GOI gene expression. ( C ) RNA-protein co-detection of Aβ and IDI1 , C3 , NINJ1 , PPP3CA reveals the spatial distribution patterns of Aβ (cyan) and GOIs (magenta) at lower (Top, scale bar: 50µm) and higher magnifications (Bottom, scale bar: 12.5µm). Proximity lines indicate the distance between Aβ and nearby cells expressing GOIs (max: 127.5µm). ( D ) Bar plots show quantification of gene expression levels for GOIs in across 7 consecutive bins representing increased distance from Aβ, as modeled in . Gene expression levels were determined with log2 (X+1) transformation where X represents the counts of puncta in a single cell for a given GOI. Data are mean ± SEM. The first bin was compared to all the rest by default for statistical tests (Kruskal-Wallis test, * p <0.05, & p <0.005, and # p <0.0001). The bracket denotes statistical testing between two specified bins. Violin plots are provided in describing the cellular distribution and numbers counted for each bin.

Article Snippet: The FISH-IF module and proximity analysis module (version 2.1.5) in HALO were utilized to assess the gene expression changes of genes of interest (GOIs) in the proximity of nearby Aβ plaques with reference to the manufacturer’s guidelines: HALO 3.3 FISH-IF Step-by-Step guide (Indica labs, Version 2.1.4 July 2021) and Digital Quantitative RNAscope Image Analysis Guide (Indica labs).

Techniques: Staining, Immunofluorescence, Software, Expressing, Transformation Assay

Journal: bioRxiv

Article Title: Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

doi: 10.1101/2023.04.20.537710

Figure Lengend Snippet: ( A ) Tissue-wide image segmentation and spatial analysis of Aβ and cells expressing GOIs (GOI expressors) using gene IDI1 and Br3854 as a representative example. RNAscope FISH-IF staining image (left) showing the distribution of Aβ (cyan) and GOI expressors ( IDI1I expressors; magenta) throughout the entire tissue section. Based on the high density of Aβ plaques, the gray matter (GM) was manually annotated (white dashed line) and selectively incorporated into downstream image analyses. The raw staining image was computationally processed using the FISH-IF module in the HALO image analysis software to segment Aβ plaques and IDI1 expressors (middle). Subsequent spatial analysis measured the proximity between Aβ and IDI1 expressors with proximity lines (brown) drawn between the segmented objects distanced less than 127.5µm, a predetermined radius based on the Visium spot grid that defined the Aβ-associated microenvironment. Scale bar, 1mm. ( B ) Higher-magnification raw input image of Aβ and IDI1 expressors. Scale bar, 25µm. ( C ) Higher-magnification demonstration of FISH-IF module segmentation of Aβ plaques and IDI1 expressors, independently. Due to the varied pixel intensities within Aβ plaques, a single Aβ plaque (cyan) was divided into multiple fragments upon segmentation (Aβ segmentation). The IDI1 transcript signals (magenta) were segmented as individual puncta ( IDI1 segmentation), which were then counted to measure gene expression within single cells. IDI1 expressors were identified based on the presence of the segmented IDI1 signals in nuclei (blue) and estimated cytoplasm (gray). The puncta outside of the nucleus and cytoplasm was not able to be quantified with this module. ( D ) Higher-magnification view of spatial analysis to determine the proximity between the centroids of the segmented fragments of Aβ plaques and neighboring IDI1 expressors, with proximity lines (white) drawn between objects at a maximum of 127.5µm apart.

Article Snippet: The FISH-IF module and proximity analysis module (version 2.1.5) in HALO were utilized to assess the gene expression changes of genes of interest (GOIs) in the proximity of nearby Aβ plaques with reference to the manufacturer’s guidelines: HALO 3.3 FISH-IF Step-by-Step guide (Indica labs, Version 2.1.4 July 2021) and Digital Quantitative RNAscope Image Analysis Guide (Indica labs).

Techniques: Expressing, Staining, Software