Highly multiplexed spatial mapping of transcripts within tissues allows for investigation of the ... more Highly multiplexed spatial mapping of transcripts within tissues allows for investigation of the transcriptomic and cellular diversity of mammalian organs previously unseen. Here we explore a direct RNA (dRNA) detection approach incorporating the use of padlock probes and rolling circle amplification in combination with hybridization-based in situ sequencing chemistry. We benchmark a High Sensitivity Library Preparation Kit from CARTANA that circumvents the reverse transcription needed for cDNA-based in situ sequencing (ISS) via direct RNA detection. We found a fivefold increase in transcript detection efficiency when compared to cDNA-based ISS and also validated its multiplexing capability by targeting a curated panel of 50 genes from previous publications on mouse brain sections, leading to additional data interpretation such as de novo cell clustering. With this increased efficiency, we also found to maintain specificity, multiplexing capabilities and ease of implementation. Over...
Correlation between the expression of genes and principal components. A. Heat map representing th... more Correlation between the expression of genes and principal components. A. Heat map representing the correlation between the expression of every gene and the top 10 principal components' scores bins described in Figure 2D-E. Low correlations are labeled in blue while high correlations are shown in white, as shown in the color bar found in the right of the heat map.
Quality control and principal component analysis of bins in the mouse section. A. Distribution of... more Quality control and principal component analysis of bins in the mouse section. A. Distribution of the number of reads found on each bin. Dashed red line indicates the minimum number of reads/cell required and dashed green line indicates the maximum number of reads accepted. B. Distribution of the number reads found for each gene in the sample analyzed. The dashed red line indicates the minimum number of reads required for a gene to be included in further analysis. C. Percentage of variable explained by each principal component found when performing PCA on the bins accomplishing the QC requirements from Additional file 2A and Additional file 2B. D. Score of each of the bins for the top 10 principal components found in the binned dataset. Red indicates high score in a specific bin and blue indicates low score. Differentially expressed regions are found when exploring each of the 10 principal components.
Coronal brain region selected for analysis and KDE plots. A. Regions of interest (ROI) analyzed i... more Coronal brain region selected for analysis and KDE plots. A. Regions of interest (ROI) analyzed in Figure 2A (blue) and Figure 2.B-C/Additional file 1.D (yellow) displayed over the DAPI staining from the mouse coronal section explored in Gyllborg et al30. B. Regional localization of mouse brain coronal section, indicating the approximate location of the regions of interest (ROI) analyzed in Figure 2A (blue) and Figure 2B-C/Additional file 1.D (yellow). Image credit: Allen Brain Institute. C. Main gradient found de novo in the mouse coronal cortex ROI (blue square in Additional file 1A), which indicates the different gene expression found between the different layers of the mouse cortex. D. KDE plots of 14 of the genes studied in detail in yellow ROI defined in Additional File 1. A grayscale color map is used to represent the level of expression of the different genes, where white represents high expression while black represents lack of expression.
Background A range of spatially resolved transcriptomic methods has recently emerged as a way to ... more Background A range of spatially resolved transcriptomic methods has recently emerged as a way to spatially characterize the molecular and cellular diversity of a tissue. As a consequence, an increasing number of computational techniques are developed to facilitate data analysis. There is also a need for versatile user friendly tools that can be used for a de novo exploration of datasets. Results Here we present MATLAB-based Analysis toolbox for in situ sequencing (ISS) expression maps (Matisse). We demonstrate Matisse by characterizing the 2-dimensional spatial expression of 119 genes profiled in a mouse coronal section, exploring different levels of complexity. Additionally, in a comprehensive analysis, we further analyzed expression maps from a second technology, osmFISH, targeting a similar mouse brain region. Conclusion Matisse proves to be a valuable tool for initial exploration of in situ sequencing datasets. The wide set of tools integrated allows for simple analysis, using t...
With the emergence of high throughput single cell techniques, the understanding of cellular diver... more With the emergence of high throughput single cell techniques, the understanding of cellular diversity in biologically complex processes has rapidly increased. The next step towards comprehension of e.g. key organs in the mammal development is to obtain spatiotemporal atlases of the cellular diversity. However, targeted cell typing approaches relying on existing single cell data achieve incomplete and biased maps that could mask the molecular and cellular heterogeneity present in a tissue slide. Here we applied spage2vec, a de novo approach to spatially resolve and characterize cellular diversity during human heart development. We obtained well defined spatial maps of tissue samples from 4.5 to 9 post conception weeks, not biased by probabilistic cell typing approaches. We found previously unreported molecular diversity within cardiomyocytes and epicardial cells and identified their characteristic expression signatures by matching them with specific subpopulations found in single cel...
Highly multiplexed spatial mapping of multiple transcripts within tissues allows for investigatio... more Highly multiplexed spatial mapping of multiple transcripts within tissues allows for investigation of the transcriptomic and cellular diversity of mammalian organs previously unseen. Here we explore the possibilities of a direct RNA (dRNA) detection approach incorporating the use of padlock probes and rolling circle amplification in combination with hybridization-based in situ sequencing (HybISS) chemistry. We benchmark a dRNA targeting kit that circumvents the standard reverse transcription limiting, cDNA-based in situ sequencing (ISS). We found a five-fold increase in transcript detection efficiency when compared to cDNA-based ISS and also validated its multiplexing capability by targeting a curated panel of 50 genes from previous publications on mouse brain sections, leading to additional data interpretation such as de novo cell typing. With this increased efficiency, we maintain specificity, multiplexing capabilities and ease of implementation. Overall, the dRNA chemistry shows ...
Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-c... more Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-cell RNA-sequencing data, providing an additional dimension to investigate spatial cell typing and cell atlases, disease architecture or even data driven discoveries. The field of spatially resolved transcriptomic technologies is emerging as a vital tool to profile gene-expression, continuously pushing current methods to accommodate larger gene panels and larger areas without compromising throughput efficiency. Here, we describe a new version of the in situ sequencing (ISS) method based on padlock probes and rolling circle amplification. Modifications in probe design allows for a new barcoding system via sequence-by-hybridization chemistry for improved spatial detection of RNA transcripts. Due to the amplification of probes, amplicons can be visualized with standard epifluorescence microscopes with high-throughput efficiency and the new sequencing chemistry removes limitations bound by se...
SummaryThe lung contains numerous specialized cell-types with distinct roles in tissue function a... more SummaryThe lung contains numerous specialized cell-types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a first comprehensive topographic atlas of early human lung development. We report 83 cell states, several spatially-resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated scRNA-Seq and spatial transcriptomics into a web-based, open platform for interactive exploration. To illustrate the utility of our approach we show distinct states of secretory and neuroendocrine cells, largely overlapping with the programs activated either during lung fibrosis or small cell lung cancer progression. We define the origin of uncharacterized airway fibroblasts associated with airway smooth muscle in bronchovascular bundles, and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas pr...
Highly multiplexed spatial mapping of transcripts within tissues allows for investigation of the ... more Highly multiplexed spatial mapping of transcripts within tissues allows for investigation of the transcriptomic and cellular diversity of mammalian organs previously unseen. Here we explore a direct RNA (dRNA) detection approach incorporating the use of padlock probes and rolling circle amplification in combination with hybridization-based in situ sequencing chemistry. We benchmark a High Sensitivity Library Preparation Kit from CARTANA that circumvents the reverse transcription needed for cDNA-based in situ sequencing (ISS) via direct RNA detection. We found a fivefold increase in transcript detection efficiency when compared to cDNA-based ISS and also validated its multiplexing capability by targeting a curated panel of 50 genes from previous publications on mouse brain sections, leading to additional data interpretation such as de novo cell clustering. With this increased efficiency, we also found to maintain specificity, multiplexing capabilities and ease of implementation. Over...
Correlation between the expression of genes and principal components. A. Heat map representing th... more Correlation between the expression of genes and principal components. A. Heat map representing the correlation between the expression of every gene and the top 10 principal components' scores bins described in Figure 2D-E. Low correlations are labeled in blue while high correlations are shown in white, as shown in the color bar found in the right of the heat map.
Quality control and principal component analysis of bins in the mouse section. A. Distribution of... more Quality control and principal component analysis of bins in the mouse section. A. Distribution of the number of reads found on each bin. Dashed red line indicates the minimum number of reads/cell required and dashed green line indicates the maximum number of reads accepted. B. Distribution of the number reads found for each gene in the sample analyzed. The dashed red line indicates the minimum number of reads required for a gene to be included in further analysis. C. Percentage of variable explained by each principal component found when performing PCA on the bins accomplishing the QC requirements from Additional file 2A and Additional file 2B. D. Score of each of the bins for the top 10 principal components found in the binned dataset. Red indicates high score in a specific bin and blue indicates low score. Differentially expressed regions are found when exploring each of the 10 principal components.
Coronal brain region selected for analysis and KDE plots. A. Regions of interest (ROI) analyzed i... more Coronal brain region selected for analysis and KDE plots. A. Regions of interest (ROI) analyzed in Figure 2A (blue) and Figure 2.B-C/Additional file 1.D (yellow) displayed over the DAPI staining from the mouse coronal section explored in Gyllborg et al30. B. Regional localization of mouse brain coronal section, indicating the approximate location of the regions of interest (ROI) analyzed in Figure 2A (blue) and Figure 2B-C/Additional file 1.D (yellow). Image credit: Allen Brain Institute. C. Main gradient found de novo in the mouse coronal cortex ROI (blue square in Additional file 1A), which indicates the different gene expression found between the different layers of the mouse cortex. D. KDE plots of 14 of the genes studied in detail in yellow ROI defined in Additional File 1. A grayscale color map is used to represent the level of expression of the different genes, where white represents high expression while black represents lack of expression.
Background A range of spatially resolved transcriptomic methods has recently emerged as a way to ... more Background A range of spatially resolved transcriptomic methods has recently emerged as a way to spatially characterize the molecular and cellular diversity of a tissue. As a consequence, an increasing number of computational techniques are developed to facilitate data analysis. There is also a need for versatile user friendly tools that can be used for a de novo exploration of datasets. Results Here we present MATLAB-based Analysis toolbox for in situ sequencing (ISS) expression maps (Matisse). We demonstrate Matisse by characterizing the 2-dimensional spatial expression of 119 genes profiled in a mouse coronal section, exploring different levels of complexity. Additionally, in a comprehensive analysis, we further analyzed expression maps from a second technology, osmFISH, targeting a similar mouse brain region. Conclusion Matisse proves to be a valuable tool for initial exploration of in situ sequencing datasets. The wide set of tools integrated allows for simple analysis, using t...
With the emergence of high throughput single cell techniques, the understanding of cellular diver... more With the emergence of high throughput single cell techniques, the understanding of cellular diversity in biologically complex processes has rapidly increased. The next step towards comprehension of e.g. key organs in the mammal development is to obtain spatiotemporal atlases of the cellular diversity. However, targeted cell typing approaches relying on existing single cell data achieve incomplete and biased maps that could mask the molecular and cellular heterogeneity present in a tissue slide. Here we applied spage2vec, a de novo approach to spatially resolve and characterize cellular diversity during human heart development. We obtained well defined spatial maps of tissue samples from 4.5 to 9 post conception weeks, not biased by probabilistic cell typing approaches. We found previously unreported molecular diversity within cardiomyocytes and epicardial cells and identified their characteristic expression signatures by matching them with specific subpopulations found in single cel...
Highly multiplexed spatial mapping of multiple transcripts within tissues allows for investigatio... more Highly multiplexed spatial mapping of multiple transcripts within tissues allows for investigation of the transcriptomic and cellular diversity of mammalian organs previously unseen. Here we explore the possibilities of a direct RNA (dRNA) detection approach incorporating the use of padlock probes and rolling circle amplification in combination with hybridization-based in situ sequencing (HybISS) chemistry. We benchmark a dRNA targeting kit that circumvents the standard reverse transcription limiting, cDNA-based in situ sequencing (ISS). We found a five-fold increase in transcript detection efficiency when compared to cDNA-based ISS and also validated its multiplexing capability by targeting a curated panel of 50 genes from previous publications on mouse brain sections, leading to additional data interpretation such as de novo cell typing. With this increased efficiency, we maintain specificity, multiplexing capabilities and ease of implementation. Overall, the dRNA chemistry shows ...
Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-c... more Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-cell RNA-sequencing data, providing an additional dimension to investigate spatial cell typing and cell atlases, disease architecture or even data driven discoveries. The field of spatially resolved transcriptomic technologies is emerging as a vital tool to profile gene-expression, continuously pushing current methods to accommodate larger gene panels and larger areas without compromising throughput efficiency. Here, we describe a new version of the in situ sequencing (ISS) method based on padlock probes and rolling circle amplification. Modifications in probe design allows for a new barcoding system via sequence-by-hybridization chemistry for improved spatial detection of RNA transcripts. Due to the amplification of probes, amplicons can be visualized with standard epifluorescence microscopes with high-throughput efficiency and the new sequencing chemistry removes limitations bound by se...
SummaryThe lung contains numerous specialized cell-types with distinct roles in tissue function a... more SummaryThe lung contains numerous specialized cell-types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a first comprehensive topographic atlas of early human lung development. We report 83 cell states, several spatially-resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated scRNA-Seq and spatial transcriptomics into a web-based, open platform for interactive exploration. To illustrate the utility of our approach we show distinct states of secretory and neuroendocrine cells, largely overlapping with the programs activated either during lung fibrosis or small cell lung cancer progression. We define the origin of uncharacterized airway fibroblasts associated with airway smooth muscle in bronchovascular bundles, and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas pr...
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Papers by Sergio Marco Salas