Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex

Johansen, Nelson J, Kempynck, Niklas, Zemke, Nathan R, Somasundaram, Saroja, Winter, Seppe De, Hooper, Marcus, Dwivedi, Deepanjali, Lohia, Ruchi, Wehbe, Fabien, Li, Bocheng, Abaffyová, Darina, Armand, Ethan J, Man, Julie De, Eksi, Eren Can, Hecker, Nikolai, Hulselmans, Gert, Konstantakos, Vasilis, Mauduit, David, Mich, John K, Partel, Gabriele, Daigle, Tanya L, Levi, Boaz P, Zhang, Kai, Tanaka, Yoshiaki, Gillis, Jesse, Ting, Jonathan T, Ben-Simon, Yoav, Miller, Jeremy, Ecker, Joseph R, Ren, Bing, Aerts, Stein, Lein, Ed S, Tasic, Bosiljka, Bakken, Trygve E (August 2024) Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex. bioRxiv. (Submitted)

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Abstract

Identifying cell type-specific enhancers in the brain is critical to building genetic tools for investigating the mammalian brain. Computational methods for functional enhancer prediction have been proposed and validated in the fruit fly and not yet the mammalian brain. We organized the ‘Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics’ to assess machine learning and feature-based methods designed to nominate enhancer DNA sequences to target cell types in the mouse cortex. Methods were evaluated based on in vivo validation data from hundreds of cortical cell type-specific enhancers that were previously packaged into individual AAV vectors and retro-orbitally injected into mice. We find that open chromatin was a key predictor of functional enhancers, and sequence models improved prediction of non-functional enhancers that can be deprioritized as opposed to pursued for in vivo testing. Sequence models also identified cell type-specific transcription factor codes that can guide designs of in silico enhancers. This community challenge establishes a benchmark for enhancer prioritization algorithms and reveals computational approaches and molecular information that are crucial for the identification of functional enhancers for mammalian cortical cell types. The results of this challenge bring us closer to understanding the complex gene regulatory landscape of the mammalian brain and help us design more efficient genetic tools and potential gene therapies for human neurological diseases.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
organism description > animal
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene regulation
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene regulation
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function
organism description > animal > mammal
CSHL Authors:
Communities: CSHL labs > Gillis Lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 21 August 2024
Date Deposited: 09 Sep 2024 17:11
Last Modified: 09 Sep 2024 17:11
Related URLs:
URI: https://repository.cshl.edu/id/eprint/41655

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