Synthetic Analyses of Single-Cell Transcriptomes from Multiple Brain Organoids and Fetal Brain

Summary: Human brain organoid systems offer unprecedented opportunities to investigate both neurodevelopmental and neurological disease. Single-cell-based transcriptomics or epigenomics have dissected the cellular and molecular heterogeneity in the brain organoids, revealing a complex organization. Similar but distinct protocols from different labs have been applied to generate brain organoids, providing a large resource to perform a comparative analysis of brain developmental processes. Here, we take a systematic approach to compare the single-cell transcriptomes of various human cortical brain organoids together with fetal brain to define the identity of specific cell types and differentiation routes in each method. Importantly, we identify unique developmental programs in each protocol compared to fetal brain, which will be a critical benchmark for the utility of human brain organoids in the future.: Tanaka et al. report integrative analyses of single-cell RNA-seq for human brain organoids derived from different protocols. They find a unique preference of cell differentiation routes across protocols and provide a benchmark for the use and the improvement of human brain organoids. Keywords: hESC, stem cells, scRNA-seq, brain organoid, hCOs, cortical spheroids, brain development, developmental trajectory, protocol comparison

Abstract licence: CC BY-NC

• Microglia-containing human brain organoids for the study of brain development and pathology · 2022

• Expression of the transcription factor PU.1 induces the generation of microglia-like cells in human cortical organoids · 2022

• SOX Transcription Factors as Important Regulators of Neuronal and Glial Differentiation During Nervous System Development and Adult Neurogenesis · 2021

• Human ALS/FTD brain organoid slice cultures display distinct early astrocyte and targetable neuronal pathology · 2021

• Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution · 2020

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.