Gene regulation gravitates towards either addition or multiplication when combining the effects of two signals
Abstract
Two different cell signals often affect transcription of the same gene. In such cases, it is natural to ask how the combined transcriptional response compares to the individual responses. The most commonly used mechanistic models predict additive or multiplicative combined responses, but a systematic genome-wide evaluation of these predictions is not available. Here, we analyzed the transcriptional response of human MCF-7 cells to retinoic acid and TGF-β, applied individually and in combination. The combined transcriptional responses of induced genes exhibited a range of behaviors, but clearly favored both additive and multiplicative outcomes. We performed paired chromatin accessibility measurements and found that increases in accessibility were largely additive. There was some association between super-additivity of accessibility and multiplicative or super-multiplicative combined transcriptional responses, while sub-additivity of accessibility associated with additive transcriptional responses. Our findings suggest that mechanistic models of combined transcriptional regulation must be able to reproduce a range of behaviors.
Data availability
We have uploading our data to NIH GEO. We are committed to sharing this manuscript's data openly and will happily upload it to any additional databases if requested.All of our raw and processed data (RNA-seq and ATAC-seq data sets) are also available on Dropbox and Github:Data:https://www.dropbox.com/sh/fhx7huyhhtf8fux/AACKW5Bd7k34uy6Rrk3k0WZ4a?dl=0&lst=Analysis Code:https://github.com/emsanford/combined_responses_paperhttps://github.com/arjunrajlaboratory/atac-seq_pipeline_paired-endhttps://github.com/arjunrajlaboratory/RajLabSeqTools
Article and author information
Author details
Funding
National Institutes of Health (R01 CA238237)
- Arjun Raj
National Institutes of Health (T32 GM007170)
- Benjamin L Emert
National Institutes of Health (T32 HG000046)
- Benjamin L Emert
National Institutes of Health (T32 GM- 07229)
- Allison Coté
Tara Miller Foundation
- Arjun Raj
National Institutes of Health (SPORE P50 CA174523)
- Arjun Raj
National Institutes of Health (F30 HG010986)
- Eric M Sanford
National Institutes of Health (Transformative Research Award R01 GM137425)
- Arjun Raj
National Institutes of Health (R01 CA232256)
- Arjun Raj
National Science Foundation (CAREER 1350601)
- Arjun Raj
National Institutes of Health (U01 CA227550)
- Arjun Raj
National Institutes of Health (U01 HL129998)
- Arjun Raj
National Institutes of Health (RM1 HG007743)
- Arjun Raj
National Institutes of Health (P30 CA016520)
- Arjun Raj
National Institutes of Health (F30 CA236129)
- Benjamin L Emert
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Sanford 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.
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