Information content differentiates enhancers from silencers in mouse photoreceptors
Abstract
Enhancers and silencers often depend on the same transcription factors (TFs) and are conflated in genomic assays of TF binding or chromatin state. To identify sequence features that distinguish enhancers and silencers, we assayed massively parallel reporter libraries of genomic sequences targeted by the photoreceptor TF CRX in mouse retinas. Both enhancers and silencers contain more TF motifs than inactive sequences, but relative to silencers, enhancers contain motifs from a more diverse collection of TFs. We developed a measure of information content that describes the number and diversity of motifs in a sequence and found that, while both enhancers and silencers depend on CRX motifs, enhancers have higher information content. The ability of information content to distinguish enhancers and silencers targeted by the same TF illustrates how motif context determines the activity of cis-regulatory sequences.
Data availability
The pJK01 and pJK03 plasmids have been deposited with AddGene (IDs 173489, 173490). Raw sequencing data and barcode counts have been uploaded to the NCBI GEO database under accession GSE165812. All processed activity data, predicted occupancy, and information content values are available in the supplementary material. All code for data processing, analysis, and visualization is available on Github at https://github.com/barakcohenlab/CRX-Information-Content.
-
Information Content Differentiates Enhancers From Silencers in Mouse PhotoreceptorsNCBI Gene Expression Omnibus, GSE165812.
-
Deciphering the cis-regulatory architecture of mammalian photoreceptorsNCBI Gene Expression Omnibus, GSE20012.
-
ATAC-seq and RNA-seq of adult mouse rods and conesNCBI Gene Expression Omnibus, GSE83312.
-
Transcriptional Regulation of Rod Photoreceptor Homeostasis Revealed by In Vivo NRL Targetome AnalysisNEI Data Share, Hong PLoS-Genet-2012.
-
MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancersNCBI Gene Expression Omnibus, GSE61392.
Article and author information
Author details
Funding
National Institutes of Health (F31HG011431)
- Ryan Z Friedman
National Institutes of Health (R01GM121755)
- Michael A White
National Institutes of Health (R01EY027784)
- Barak A Cohen
National Institutes of Health (EY025196)
- Joseph C Corbo
National Institutes of Health (EY03075)
- Joseph C Corbo
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to protocol # A-3381-01 approved by the Institutional Animal Care and Use Committee of Washington University in St. Louis. Euthanasia of mice was performed according to the recommendations of the American Veterinary Medical Association Guidelines on Euthanasia. Appropriate measures are taken to minimize pain and discomfort to the animals during experimental procedures.
Copyright
© 2021, Friedman 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
-
- 3,325
- views
-
- 272
- downloads
-
- 20
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Computational and Systems Biology
The force developed by actively lengthened muscle depends on different structures across different scales of lengthening. For small perturbations, the active response of muscle is well captured by a linear-time-invariant (LTI) system: a stiff spring in parallel with a light damper. The force response of muscle to longer stretches is better represented by a compliant spring that can fix its end when activated. Experimental work has shown that the stiffness and damping (impedance) of muscle in response to small perturbations is of fundamental importance to motor learning and mechanical stability, while the huge forces developed during long active stretches are critical for simulating and predicting injury. Outside of motor learning and injury, muscle is actively lengthened as a part of nearly all terrestrial locomotion. Despite the functional importance of impedance and active lengthening, no single muscle model has all these mechanical properties. In this work, we present the viscoelastic-crossbridge active-titin (VEXAT) model that can replicate the response of muscle to length changes great and small. To evaluate the VEXAT model, we compare its response to biological muscle by simulating experiments that measure the impedance of muscle, and the forces developed during long active stretches. In addition, we have also compared the responses of the VEXAT model to a popular Hill-type muscle model. The VEXAT model more accurately captures the impedance of biological muscle and its responses to long active stretches than a Hill-type model and can still reproduce the force-velocity and force-length relations of muscle. While the comparison between the VEXAT model and biological muscle is favorable, there are some phenomena that can be improved: the low frequency phase response of the model, and a mechanism to support passive force enhancement.
-
- Computational and Systems Biology
- Evolutionary Biology
There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.