Josh Tycko

Systematic discovery of protein functions in human cells to understand gene regulation and enable gene therapy



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Josh Tycko

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Department of Neurobiology

Harvard Medical School




Josh Tycko

Systematic discovery of protein functions in human cells to understand gene regulation and enable gene therapy



Department of Neurobiology

Harvard Medical School



Development of compact transcriptional effectors using high-throughput measurements in diverse contexts


Journal article


Josh Tycko, Mike V. Van, Aradhana, Nicole DelRosso, David Yao, Xiaoshu Xu, Connor Ludwig, Kaitlyn K. Spees, Kathy Liu, Gaelen T. Hess, Mingxin Gu, Aditya Mukund, Peter H. Suzuki, Roarke A. Kamber, Lei S. Qi, Lacramioara Bintu, M. Bassik
bioRxiv, 2023

Semantic Scholar DOI
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APA   Click to copy
Tycko, J., Van, M. V., Aradhana, DelRosso, N., Yao, D., Xu, X., … Bassik, M. (2023). Development of compact transcriptional effectors using high-throughput measurements in diverse contexts. BioRxiv.


Chicago/Turabian   Click to copy
Tycko, Josh, Mike V. Van, Aradhana, Nicole DelRosso, David Yao, Xiaoshu Xu, Connor Ludwig, et al. “Development of Compact Transcriptional Effectors Using High-Throughput Measurements in Diverse Contexts.” bioRxiv (2023).


MLA   Click to copy
Tycko, Josh, et al. “Development of Compact Transcriptional Effectors Using High-Throughput Measurements in Diverse Contexts.” BioRxiv, 2023.


BibTeX   Click to copy

@article{josh2023a,
  title = {Development of compact transcriptional effectors using high-throughput measurements in diverse contexts},
  year = {2023},
  journal = {bioRxiv},
  author = {Tycko, Josh and Van, Mike V. and Aradhana and DelRosso, Nicole and Yao, David and Xu, Xiaoshu and Ludwig, Connor and Spees, Kaitlyn K. and Liu, Kathy and Hess, Gaelen T. and Gu, Mingxin and Mukund, Aditya and Suzuki, Peter H. and Kamber, Roarke A. and Qi, Lei S. and Bintu, Lacramioara and Bassik, M.}
}

Abstract

Human nuclear proteins contain >1000 transcriptional effector domains that can activate or repress transcription of target genes. We lack a systematic understanding of which effector domains regulate transcription robustly across genomic, cell-type, and DNA-binding domain (DBD) contexts. Here, we developed dCas9-mediated high-throughput recruitment (HT-recruit), a pooled screening method for quantifying effector function at endogenous targets, and tested effector function for a library containing 5092 nuclear protein Pfam domains across varied contexts. We find many effectors depend on target and DBD contexts, such as HLH domains that can act as either activators or repressors. We then confirm these findings and further map context dependencies of effectors drawn from unannotated protein regions using a larger library containing 114,288 sequences tiling chromatin regulators and transcription factors. To enable efficient perturbations, we select effectors that are potent in diverse contexts, and engineer (1) improved ZNF705 KRAB CRISPRi tools to silence promoters and enhancers, and (2) a compact human activator combination NFZ for better CRISPRa and inducible circuit delivery. Together, this effector-by-context functional map reveals context-dependence across human effectors and guides effector selection for robustly manipulating transcription.


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