HReg-CNCC reconstructs a regulatory network in human cranial neural crest cells and annotates variants in a developmental context

Zhanying Feng,Yong Wang,Fan Liu,Zhana Duren,Ziyi Xiong,Sijia Wang,Wing Hung Wong

doi:10.1038/s42003-021-01970-0

Abstract

Cranial Neural Crest Cells (CNCC) originate at the cephalic region from forebrain, midbrain and hindbrain, migrate into the developing craniofacial region, and subsequently differentiate into multiple cell types. The entire specification, delamination, migration, and differentiation process is highly regulated and abnormalities during this craniofacial development cause birth defects. To better understand the molecular networks underlying CNCC, we integrate paired gene expression & chromatin accessibility data and reconstruct the genome-wide human Regulatory network of CNCC (hReg-CNCC). Consensus optimization predicts high-quality regulations and reveals the architecture of upstream, core, and downstream transcription factors that are associated with functions of neural plate border, specification, and migration. hReg-CNCC allows us to annotate genetic variants of human facial GWAS and disease traits with associated cis-regulatory modules, transcription factors, and target genes. For example, we reveal the distal and combinatorial regulation of multiple SNPs to core TF ALX1 and associations to facial distances and cranial rare disease. In addition, hReg-CNCC connects the DNA sequence differences in evolution, such as ultra-conserved elements and human accelerated regions, with gene expression and phenotype. hReg-CNCC provides a valuable resource to interpret genetic variants as early as gastrulation during embryonic development. The network resources are available at https://github.com/AMSSwanglab/hReg-CNCC.

Highlights

Cranial Neural Crest Cells (CNCC) originate at the cephalic region from forebrain, midbrain and hindbrain, migrate into the developing craniofacial region, and subsequently differentiate into multiple cell types
We collected paired RNA-seq and ATAC-seq data from (Prescott, et al.)[21] and applied PECA226 to R replicates (R 1⁄4 6, samples were matched at the cell type level, Supplementary Data 1) to obtain R context-specific regulatory networks (Methods)
We proposed to construct a regulatory network in a developmental context to understand the genetic variants and complex phenotypes

Summary

Introduction

Cranial Neural Crest Cells (CNCC) originate at the cephalic region from forebrain, midbrain and hindbrain, migrate into the developing craniofacial region, and subsequently differentiate into multiple cell types. Genome-wide association studies (GWAS) have identified many genetic changes for human facial variations and craniofacial defects[1,2,3,4,5,6,7] These genetic variants are enriched in enhancers preferentially active in cranial neural crest cells (CNCC) and embryonic craniofacial tissue[2,4]. For a better understanding of how genetic variants affect human craniofacial traits and diseases, a genome-wide regulatory network with non-coding REs for the human neural crest is in pressing need. Wilderman et al.[22] profiled multiple histone markers of chromatin activity as comprehensive functional genomics data and predicted chromatin states for 4.5–8 postconception weeks of early human craniofacial development These multi-omics data make inferring a comprehensive human regulatory network of cranial crest cell computationally a possible task. We started from PECA2 to integrate paired RNA-seq and ATAC-seq data and constructed a human Regulatory network of Cranial Neural Crest Cell

Methods

Results

Conclusion