High-throughput discovery and characterization of human transcriptional effectors
release_3lazhg4ut5dz5fnmqgmcqs66o4
by
Josh Tycko,
Nicole DelRosso,
Gaelen T. Hess,
Aradhana,
Abhimanyu Banerjee,
Aditya Mukund,
Mike V. Van,
Braeden K. Ego,
David Yao,
Kaitlyn Spees,
Peter Suzuki,
Georgi K Marinov
(+3 others)
2020
Abstract
Thousands of proteins localize to the nucleus; however, it remains unclear which contain transcriptional effectors. Here, we develop HT-recruit - a pooled assay where protein libraries are recruited to a reporter, and their transcriptional effects are measured by sequencing. Using this approach, we measure gene silencing and activation for thousands of domains. We find a relationship between repressor function and evolutionary age for the KRAB domains, discover Homeodomain repressor strength is collinear with Hox genetic organization, and identify activities for several Domains of Unknown Function. Deep mutational scanning of the CRISPRi KRAB maps the co-repressor binding surface and identifies substitutions that improve stability/silencing. By tiling 238 proteins, we find repressors as short as 10 amino acids. Finally, we report new activator domains, including a divergent KRAB. Together, these results provide a resource of 600 human proteins containing effectors and demonstrate a scalable strategy for assigning functions to protein domains.
In application/xml+jats
format
Archived Files and Locations
application/pdf
10.0 MB
file_ipeiaj2iifbc7ffmdjcov7eoby
|
www.biorxiv.org (repository) web.archive.org (webarchive) |
application/pdf
10.0 MB
file_gmi4rnguzbalpkz7ry7ahj47t4
|
www.biorxiv.org (repository) web.archive.org (webarchive) |
post
Stage
unknown
Date 2020-09-10
access all versions, variants, and formats of this works (eg, pre-prints)
Crossref Metadata (via API)
Worldcat
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar