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Identification of plant transcriptional activation domains.
- Source :
-
Nature [Nature] 2024 Aug; Vol. 632 (8023), pp. 166-173. Date of Electronic Publication: 2024 Jul 17. - Publication Year :
- 2024
-
Abstract
- Gene expression in Arabidopsis is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA-binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for nearly all Arabidopsis TFs, we lack knowledge about the presence, location and transcriptional strength of their ADs <superscript>1</superscript> . To address this gap, here we use a yeast library approach to experimentally identify Arabidopsis ADs on a proteome-wide scale, and find that more than half of the Arabidopsis TFs contain an AD. We annotate 1,553 ADs, the vast majority of which are, to our knowledge, previously unknown. Using the dataset generated, we develop a neural network to accurately predict ADs and to identify sequence features that are necessary to recruit coactivator complexes. We uncover six distinct combinations of sequence features that result in activation activity, providing a framework to interrogate the subfunctionalization of ADs. Furthermore, we identify ADs in the ancient AUXIN RESPONSE FACTOR family of TFs, revealing that AD positioning is conserved in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examining function in intrinsically disordered regions and a predictive model of ADs.<br /> (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)
- Subjects :
- Conserved Sequence genetics
Datasets as Topic
Indoleacetic Acids metabolism
Intrinsically Disordered Proteins
Molecular Sequence Annotation
Neural Networks, Computer
Proteome chemistry
Proteome metabolism
Arabidopsis chemistry
Arabidopsis genetics
Arabidopsis metabolism
Arabidopsis Proteins chemistry
Arabidopsis Proteins classification
Arabidopsis Proteins metabolism
Gene Expression Regulation, Plant genetics
Protein Domains
Transcription Factors chemistry
Transcription Factors classification
Transcription Factors metabolism
Transcriptional Activation genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1476-4687
- Volume :
- 632
- Issue :
- 8023
- Database :
- MEDLINE
- Journal :
- Nature
- Publication Type :
- Academic Journal
- Accession number :
- 39020176
- Full Text :
- https://doi.org/10.1038/s41586-024-07707-3