Published February 10, 2022 | Version v1
Journal article Open

Human embryoid bodies as a novel system for genomic studies of functionally diverse cell types

  • 1. University of Chicago
  • 2. Johns Hopkins University

Description

Practically all studies of gene expression in humans to date have been performed in a relatively small number of adult tissues. Gene regulation is highly dynamic and context-dependent. In order to better understand the connection between gene regulation and complex phenotypes, including disease, we need to be able to study gene expression in more cell types, tissues, and states that are relevant to human phenotypes. In particular, we need to characterize gene expression in early development cell types, as mutations that affect developmental processes may be of particular relevance to complex traits. To address this challenge, we propose to use embryoid bodies (EBs), which are organoids that contain a multitude of cell types in dynamic states. EBs provide a system in which one can study dynamic regulatory processes at an unprecedentedly high resolution. To explore the utility of EBs, we systematically explored cellular and gene expression heterogeneity in EBs from multiple individuals. We characterized the various cell types that arise from EBs, the extent to which they recapitulate gene expression in vivo, and the relative contribution of technical and biological factors to variability in gene expression, cell composition, and differentiation effi-ciency. Our results highlight the utility of EBs as a new model system for mapping dynamic inter-individual regulatory differences in a large variety of cell types.

Data availability

Sequencing Data have been deposited in GEO under accession code GSE178274. Code used in this project is available on GitHub: Workflowr site: Workflowr site: https://klrhodes.github.io/Embryoid_Body_Pilot_Workflowr/index.html, Preprocessing: https://github.com/kennethabarr/HumanChimp, (copy archived at swh:1:rev:1722b3484d1120384c910bef13bffd6a6cd6179a), Additional Preprocessing, Integration, Differential Expression, Topic Modelling, Variance Partitioning, Hierarchical Clustering, and Reference Annotation: https://github.com/KLRhodes/Embryoid_Body_Pilot_Workflowr, (copy archived at swh:1:rev:3d3fa9b4e0a96ea840009b62107d47e464e08c11) Trajectory Inference, Identification of dynamic gene modules: https://github.com/jmp448/ebpilot, (copy archived at swh:1:rev:8b9b9700063610b4f9f2406131b646542bfa7af2).

The following data sets were generated:

Rhodes K Barr KA Popp JM Strober BJ Battle A Gilad Y (2021) NCBI Gene Expression Omnibus ID GSE178274. Human embryoid bodies as a novel system for genomic studies of functionally diverse cell types. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178274

The following previously published data sets were used:

Han X Guo G Zhou Z Fei L Sun H Wang R Wang J Chen H (2020) NCBI Gene Expression Omnibus ID GSE134355. Construction of a human cell landscape at single-cell level. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE134355

Cao J O'Day DR Pliner HA Kingsley P Deng M Daza RM Zager MA Kimberly A Blecher R Zhang F Spielmann M Palis J Doherty D Steemers FJ Glass IA Trapnell C Shendure J (2020) NCBI Gene Expression Omnibus ID GSE156793. A human cell atlas of fetal gene expression. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156793

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Additional details

Identifiers

DOI
10.7554/eLife.71361
Other
oai:uchicago.tind.io:9943

Funding

National Heart, Lung, and Blood Institute
Ruth L. Kirschstein National Research Service Award Individual Predoctoral Fellowship
National Institute of General Medical Sciences
R35GM131726
National Institute of General Medical Sciences
R35GM139580

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Medicine