Analysis of zebrafish periderm enhancers facilitates identification of a regulatory variant near human KRT8/18
- Wuhan University, China
- University of Iowa, United States
- University of Pittsburgh, United States
- Lawrence Berkeley Laboratories, United States
- DOE Joint Genome Institute, United States
- Emory University School of Medicine, United States
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.
-
Zebrafish periderm at 4-somite stageNCBI Gene Expression Omnibus, GSE140241.
-
ATAC-seq profile of mouse palatal epithelium at E14.5NCBI Gene Expression Omnibus, GSE139945.
-
Human oral epithelial cell line HIOECNCBI Gene Expression Omnibus, GSE139809.
-
ChIP-seq from embryonic facial prominence (ENCSR481SGM)NCBI Gene Expression Omnibus, GSE82727.
-
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
Jenna Colavincenzo Carlson
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.
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.
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.
Metrics
-
- 3,291
- views
-
- 406
- downloads
-
- 26
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
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)
Analysis of zebrafish periderm enhancers facilitates identification of a regulatory variant near human KRT8/18
eLife 9:e51325.
https://doi.org/10.7554/eLife.51325
Further reading
-
- Computational and Systems Biology
The RAS-MAPK system plays an important role in regulating various cellular processes, including growth, differentiation, apoptosis, and transformation. Dysregulation of this system has been implicated in genetic diseases and cancers affecting diverse tissues. To better understand the regulation of this system, we employed information flow analysis based on transfer entropy (TE) between the activation dynamics of two key elements in cells stimulated with EGF: SOS, a guanine nucleotide exchanger for the small GTPase RAS, and RAF, a RAS effector serine/threonine kinase. TE analysis allows for model-free assessment of the timing, direction, and strength of the information flow regulating the system response. We detected significant amounts of TE in both directions between SOS and RAF, indicating feedback regulation. Importantly, the amount of TE did not simply follow the input dose or the intensity of the causal reaction, demonstrating the uniqueness of TE. TE analysis proposed regulatory networks containing multiple tracks and feedback loops and revealed temporal switching in the reaction pathway primarily responsible for reaction control. This proposal was confirmed by the effects of an MEK inhibitor on TE. Furthermore, TE analysis identified the functional disorder of a SOS mutation associated with Noonan syndrome, a human genetic disease, of which the pathogenic mechanism has not been precisely known yet. TE assessment holds significant promise as a model-free analysis method of reaction networks in molecular pharmacology and pathology.
-
- Computational and Systems Biology
- Genetics and Genomics
Root causal gene expression levels – or root causal genes for short – correspond to the initial changes to gene expression that generate patient symptoms as a downstream effect. Identifying root causal genes is critical towards developing treatments that modify disease near its onset, but no existing algorithms attempt to identify root causal genes from data. RNA-sequencing (RNA-seq) data introduces challenges such as measurement error, high dimensionality and non-linearity that compromise accurate estimation of root causal effects even with state-of-the-art approaches. We therefore instead leverage Perturb-seq, or high-throughput perturbations with single-cell RNA-seq readout, to learn the causal order between the genes. We then transfer the causal order to bulk RNA-seq and identify root causal genes specific to a given patient for the first time using a novel statistic. Experiments demonstrate large improvements in performance. Applications to macular degeneration and multiple sclerosis also reveal root causal genes that lie on known pathogenic pathways, delineate patient subgroups and implicate a newly defined omnigenic root causal model.
