From cc962172fb535bacf1069895e19e37c22beebba7 Mon Sep 17 00:00:00 2001 From: Fran McDade Date: Fri, 3 Jan 2025 10:46:06 +1000 Subject: [PATCH] feat: update organoid description (#2646) --- .../organoid-endoderm/v1.0/description.mdx | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/content/organoid/atlases/organoid-endoderm/v1.0/description.mdx b/content/organoid/atlases/organoid-endoderm/v1.0/description.mdx index be080d722..cf7ceff7d 100644 --- a/content/organoid/atlases/organoid-endoderm/v1.0/description.mdx +++ b/content/organoid/atlases/organoid-endoderm/v1.0/description.mdx @@ -1,3 +1,13 @@ +### Highlights + +- The Endoderm Organoid Atlas brings together **all currently available single-cell transcriptome datasets from diverse organoids** derived from the endoderm (54 data sets, 806k cells). +- Here, we integrate single-cell transcriptomes from 218 samples covering organoids of diverse endoderm-derived tissues including lung, pancreas, intestine, liver, biliary system, stomach, and prostate to establish an initial version of a human endoderm organoid cell atlas (HEOCA). +- The integration includes nearly one million cells across diverse conditions, data sources and protocols. We align and compare cell types and states between organoid models, and harmonize cell type annotations by mapping the atlas to primary tissue counterparts. +- To demonstrate utility of the atlas, we focus on intestine and lung, and clarify ontogenic cell states that can be modeled _in vitro_. We further provide examples of mapping novel data from new organoid protocols to expand the atlas, and showcase how integrating organoid models of disease into the HEOCA identifies altered cell proportions and states between healthy and disease conditions. +- The atlas makes diverse datasets centrally available, and will be valuable to assess organoid fidelity, characterize perturbed and diseased states, and streamline protocol development. + +### Overview + Human stem cell derived organoids provide extraordinary opportunities to study human physiology in health and disease. The atlas **describes cellular heterogeneity** in these systems, as well as uses comparison to primary reference atlases in order to benchmark organoid protocols. @@ -6,9 +16,3 @@ The atlas **describes cellular heterogeneity** in these systems, as well as uses **The atlas makes diverse datasets centrally available, and will be valuable to assess organoid fidelity, characterize perturbed and diseased states, and streamline protocol development.** Many members of the bionetwork were involved in contributing datasets (published and unpublished) and providing metadata. **Bionetwork members were also consulted for biological questions.** The progress of the atlas was presented and discussed at the HCA General meetings and at organoid-specific meetings (e.g. CSHL meeting on Development and 3D modeling of the human brain). - -- The Endoderm Organoid Atlas brings together **all currently available single-cell transcriptome datasets from diverse organoids** derived from the endoderm (54 data sets, 806k cells). -- Here, we integrate single-cell transcriptomes from 218 samples covering organoids of diverse endoderm-derived tissues including lung, pancreas, intestine, liver, biliary system, stomach, and prostate to establish an initial version of a human endoderm organoid cell atlas (HEOCA). -- The integration includes nearly one million cells across diverse conditions, data sources and protocols. We align and compare cell types and states between organoid models, and harmonize cell type annotations by mapping the atlas to primary tissue counterparts. -- To demonstrate utility of the atlas, we focus on intestine and lung, and clarify ontogenic cell states that can be modeled _in vitro_. We further provide examples of mapping novel data from new organoid protocols to expand the atlas, and showcase how integrating organoid models of disease into the HEOCA identifies altered cell proportions and states between healthy and disease conditions. -- The atlas makes diverse datasets centrally available, and will be valuable to assess organoid fidelity, characterize perturbed and diseased states, and streamline protocol development.