Analysis of zebrafish periderm enhancers facilitates identification of a regulatory variant near human KRT8/18
Abstract
Genome wide association studies for non-syndromic orofacial cleft (OFC) have identified single nucleotide polymorphisms (SNPs) at loci where the presumed risk-relevant gene is expressed in oral periderm. The functional subsets of such SNPs are difficult to predict because the sequence underpinnings of periderm enhancers are unknown. We applied ATAC-seq to models of human palate periderm, including zebrafish periderm, mouse embryonic palate epithelia, and a human oral epithelium cell line, and to complementary mesenchymal cell types. We identified sets of enhancers specific to the epithelial cells and trained gapped-kmer support-vector-machine classifiers on these sets. We used the classifiers to predict the effect of 14 OFC-associated SNPs at 12q13 near KRT18. All the classifiers picked the same SNP as having the strongest effect, but the significance was highest with the classifier trained on zebrafish periderm. Reporter and deletion analyses support this SNP as lying within a periderm enhancer regulating KRT18/KRT8 expression.
Data availability
1 Raw and processed sequencing data were deposited in GEO repository (GSE140241, GSE139945 and GSE139809).2 Custom scripts and piplines we deployed for sequencing data analysis and visualization are available at https://github.com/Badgerliu/periderm_ATACSeq.3 All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures.
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Zebrafish periderm at 4-somite stageNCBI Gene Expression Omnibus, GSE140241.
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ATAC-seq profile of mouse palatal epithelium at E14.5NCBI Gene Expression Omnibus, GSE139945.
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Human oral epithelial cell line HIOECNCBI Gene Expression Omnibus, GSE139809.
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ChIP-seq from embryonic facial prominence (ENCSR481SGM)NCBI Gene Expression Omnibus, GSE82727.
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127-reference epigenome/25-state Imputation Based Chromatin State Model127-reference epigenome/25-state Imputation Based Chromatin State Model.
Article and author information
Author details
Funding
National Institutes of Health (DE023575)
- Robert A Cornell
National Institute for Health Research (DE027362)
- Robert A Cornell
National Institute of Dental and Craniofacial Research (DE025060)
- Elizabeth Leslie
National Institute of Dental and Craniofacial Research (DE024427)
- Axel Visel
National Institute of Dental and Craniofacial Research (DE028599)
- Axel Visel
National Natural Science Foundation of China (81771057)
- Huan Liu
National Natural Science Foundation of China (81400477)
- Huan Liu
Natural Science Foundation of Hubei Province (2017CFB515)
- Huan Liu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Marianne E Bronner, California Institute of Technology, United States
Ethics
Animal experimentation: D. rerio were maintained in the University of Iowa Animal Care Facility according to a standard protocol (protocol no. 6011616). All mouse experiments were performed in accordance with approval of the Institutional Animal Care and Use Committees at the School and Hospital of Stomatology of Wuhan University (protocol no. 00271454).Mouse experiments for LacZ reporter transgenic animal work performed at the Lawrence Berkeley National Laboratory (LBNL) were reviewed and approved by the LBNL Animal Welfare and Research Committee.
Version history
- Received: August 25, 2019
- Accepted: February 6, 2020
- Accepted Manuscript published: February 7, 2020 (version 1)
- Version of Record published: February 24, 2020 (version 2)
Copyright
© 2020, Liu 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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Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here, I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors, and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode Caenorhabditis elegans. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.