A new study from my lab uncovers the evolutionary origins of the cells that build our skeleton.
Hypertrophic chondrocytes evolved earlier than thought-in the common ancestor of Gnathostomes.
doi.org/10.1093/evle...
#Evolution #CellTypes #SkeletalBiology
Overview of HCNetlas. Top: Schematic representation of the workflow from single-cell transcriptomic data collection to the construction of the HCNetlas. Single-cell RNA sequencing data preannotated for cell type were used to build CGNs using the scHumanNet framework. HCNetlas is comprised of a comprehensive collection of these gene networks, representing various human tissues and cell types. Bottom left: UMAP visualization of CGNs based on gene profiles, highlighting the major cell lineages, with node size representing the number of genes in each network. Bottom right: UMAP plot displaying the interrelationship among the CGNs based on network gene profiles for major organs or tissue types. Each point represents a gene network associated with a specific organ or tissue type colored distinctly.
Alterations of gene regulatory networks (GRNs) in specific #CellTypes can cause disease. This study presents HCNetlas, a compilation of cell-type-specific #GRNs across healthy human tissues that can be used to uncover associations between #DiseaseGenes & cell types 🧪 @plosbiology.org plos.io/4jIwg7P
Overview of HCNetlas. Top: Schematic representation of the workflow from single-cell transcriptomic data collection to the construction of the HCNetlas. Single-cell RNA sequencing data preannotated for cell type were used to build CGNs using the scHumanNet framework. HCNetlas is comprised of a comprehensive collection of these gene networks, representing various human tissues and cell types. Bottom left: UMAP visualization of CGNs based on gene profiles, highlighting the major cell lineages, with node size representing the number of genes in each network. Bottom right: UMAP plot displaying the interrelationship among the CGNs based on network gene profiles for major organs or tissue types. Each point represents a gene network associated with a specific organ or tissue type colored distinctly.
Alterations of gene regulatory networks (GRNs) in specific #CellTypes can cause disease. This study presents HCNetlas, a compilation of cell-type-specific #GRNs across healthy human tissues that can be used to uncover associations between #DiseaseGenes & cell types 🧪 @plosbiology.org plos.io/4jIwg7P
Overview of HCNetlas. Top: Schematic representation of the workflow from single-cell transcriptomic data collection to the construction of the HCNetlas. Single-cell RNA sequencing data preannotated for cell type were used to build CGNs using the scHumanNet framework. HCNetlas is comprised of a comprehensive collection of these gene networks, representing various human tissues and cell types. Bottom left: UMAP visualization of CGNs based on gene profiles, highlighting the major cell lineages, with node size representing the number of genes in each network. Bottom right: UMAP plot displaying the interrelationship among the CGNs based on network gene profiles for major organs or tissue types. Each point represents a gene network associated with a specific organ or tissue type colored distinctly.
Alterations of gene regulatory networks (GRNs) in specific #CellTypes can cause disease. This study presents HCNetlas, a compilation of cell-type-specific #GRNs across healthy human tissues that can be used to uncover associations between #DiseaseGenes & cell types 🧪 @plosbiology.org plos.io/4jIwg7P
