Organoid Transcriptomics Reveals Potential Autism Drivers

June 15, 2022

Organoid Research: A New Frontier

Organoids are becoming an increasingly sophisticated and valuable tool for in vitro studies, capturing more elements of real tissue complexity than cultures of individual cell types. Improvements to organoid engineering and culture have allowed for robust studies to emerge using these models.

The brain is of particular research interest to be recapitulated as an organoid grown in culture, as in vivo brain tissue studies are extremely limited, and post-mortem brain tissue cannot provide adequate insight into the dynamic processes of gene expression changes during development or disease.

Combining Single Cell and Bulk RNA Seq

In a new paper published in Nature Communications last week, Lim et. al. from the Church Lab at Harvard combined transcriptomics with organoid research to investigate potential drivers for autism. They describe a framework called “Orgo-Seq” that integrates bulk and single-cell RNA sequence data from 71 samples comprising 1,420 cerebral organoids from 25 donors.

Their pipeline represents a quantitative way to phenotype organoids based on genetics and transcriptomics. Their analysis revealed that immature neurons and intermediate progenitor cells are the specific cell types that may drive autism associated with 16p11.2 deletions, as well as other, novel driver genes that are also cell-type specific.

Outsourcing Bioinformatics Analysis

This unique approach illustrates the power of bulk scRNA-seq for research, but interpreting single cell RNA-seq data is a challenging computational and bioinformatic task. Outsourcing your bioinformatic analysis to experts like our team at Bridge Informatics helps eliminate common challenges with these projects. If you’re interested, book a free discovery call with us today to discuss your project needs.

Jane Cook, Journalist & Content Writer, Bridge Informatics

Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email or


illustration of lab tools for bioinformatics and genomic analyses

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