A combinatorial transcription factor signature defines the HSN serotonergic neuron regulatory landscape
Abstract
Cell differentiation is controlled by individual transcription factors (TFs) that together activate a selection of enhancers in specific cell types. How these combinations of TFs identify and activate their target sequences remains poorly understood. Here, we identify the cis-regulatory transcriptional code that controls the differentiation of serotonergic HSN neurons in C. elegans. Activation of the HSN transcriptome is directly orchestrated by a collective of six TFs. Binding site clusters for this TF collective form a regulatory signature that is sufficient for de novo identification of HSN neuron functional enhancers. Among C. elegans neurons, the HSN transcriptome most closely resembles that of mouse serotonergic neurons. Mouse orthologs of the HSN TF collective also regulate serotonergic differentiation and can functionally substitute for their worm counterparts which suggests deep homology. Our results identify rules governing the regulatory landscape of a critically important neuronal type in two species separated by over 700 million years.
Article and author information
Author details
Funding
Ministerio de Economía y Competitividad (SAF2014-56877-R)
- Carla Lloret-Fernández
- Miren Maicas
- Carlos Mora-Martínez
- Angela Jimeno-Martín
- Laura Chirivella
- Nuria Flames
European Research Council (ERC Stg 2011-281920)
- Carla Lloret-Fernández
- Miren Maicas
- Carlos Mora-Martínez
- Angela Jimeno-Martín
- Laura Chirivella
- Nuria Flames
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experiments were performed according to the animal care guidelines of the European Community Council (86 ⁄ 609 ⁄ EEC) and to Spanish regulations (RD1201 ⁄ 2005), following protocols approved by the ethics committees of the Consejo Superior Investigaciones Científicas (CSIC).
Copyright
© 2018, Lloret-Fernández et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 3,661
- views
-
- 490
- downloads
-
- 50
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 50
- citations for umbrella DOI https://doi.org/10.7554/eLife.32785