Biology subjects

Curtis, S. W.

Publications and source records attributed to Curtis, S. W..

4 recordsLinked to original sources

bioRxiv2026

Conservation of transcriptional regulatory networks in zebrafish and human periderm facilitates identification of GRHL1 as an orofacial cleft risk gene

Most heritable risk for orofacial clefts (OFC) remains unassigned to specific genes or loci. IRF6 and GRHL3, two established OFC risk genes, encode transcription factors (TFs) essential for the differentiation of the periderm, a transient embryonic tissue required for secondary palate fusion. To identify novel risk candidates, we modeled the zebrafish periderm transcriptional regulatory network (TRN). Using single-cell multiome sequencing (RNA-seq and ATAC-seq) from shield-stage embryos, we inferred TF-to-target gene connections by integrating correlated gene expression with TF binding site predictions within chromatin elements open in periderm cells. We generated sets of gold-standard edges by conducting RNA-seq on TF-depleted embryos and ChIP-seq/CUT&RUN on wild-type embryos and used them to benchmark model performance. Within the top-performing model, zebrafish periderm modules are strongly preserved in human embryonic periderm and orthologs of human OFC-associated genes have higher centrality and edge-sum scores than non-associated genes. Functional validation confirmed the networks predictive power: depleting high-centrality TFs, including grhl1, klf6a, tead3b, and klf17, disrupted periderm differentiation in sensitized embryos. Moreover, analysis of whole-genome sequencing data from 2,415 OFC trios identified 15 individuals with rare or de novo GRHL1 variants, four of which introduced premature stop codons. This study establishes GRHL1 as a novel OFC risk gene and highlights the power of cross-species gene regulatory network analysis to prioritize candidates for rare variants in complex structural birth defects.

developmental biology↗

bioRxiv2025

Gene expression patterns of the developing human face at single cell resolution reveal cell type contributions to normal facial variation and disease risk

Craniofacial development gives rise to the complex structures of the face and involves the interplay of diverse cell types. Despite its importance, our understanding of human-specific craniofacial developmental mechanisms and their genetic underpinnings remains limited. Here, we present a comprehensive single-nucleus RNA sequencing (snRNA-seq) atlas of human craniofacial development from craniofacial tissues of 24 embryos that span six key time points during the embryonic period (4-8 post-conception weeks). This resource resolves the transcriptional dynamics of seven major cell types and uncovers distinct major cell types, including muscle progenitors and cranial neural crest cells (CNCCs), as well as dozens of subtypes of ectoderm and mesenchyme. Comparative analyses reveal substantial conservation of major cell types, alongside human biased differences in gene expression programs. CNCCs, which play a crucial role in craniofacial morphogenesis, exhibit the lowest marker gene conservation, underscoring their evolutionary plasticity. Spatial transcriptomics further localizes cell populations, providing a detailed view of their developmental roles and anatomical context. We also link these developmental processes to genetic variation, identifying cell type-specific enrichments for common variants associated with facial morphology and rare variants linked to orofacial clefts. Intriguingly, Neanderthal-introgressed sequences are enriched near genes with biased expression in cartilage and specialized ectodermal subtypes, suggesting their contribution to modern human craniofacial features. This atlas offers unprecedented insights into the cellular and genetic mechanisms shaping the human face, highlighting conserved and distinctly human aspects of craniofacial biology. Our findings illuminate the developmental origins of craniofacial disorders, the genetic basis of facial variation, and the evolutionary legacy of ancient hominins. This work provides a foundational resource for exploring craniofacial biology, with implications for developmental genetics, evolutionary biology, and clinical research into congenital anomalies.

developmental biology↗

bioRxiv2024

Functional analysis of ESRP1/2 gene variants and CTNND1 isoforms in orofacial cleft pathogenesis

Orofacial cleft (OFC) is a common human congenital anomaly. Epithelial-specific RNA splicing regulators ESRP1 and ESRP2 regulate craniofacial morphogenesis and their disruption result in OFC in zebrafish, mouse and humans. Using esrp1/2 mutant zebrafish and murine Py2T cell line models, we functionally tested the pathogenicity of human ESRP1/2 gene variants. We found that many variants predicted by in silico methods to be pathogenic were functionally benign. Esrp1 also regulates the alternative splicing of Ctnnd1 and these genes are co-expressed in the embryonic and oral epithelium. In fact, over-expression of ctnnd1 is sufficient to rescue morphogenesis of epithelial-derived structures in esrp1/2 zebrafish mutants. Additionally, we identified 13 CTNND1 variants from genome sequencing of OFC cohorts, confirming CTNND1 as a key gene in human OFC. This work highlights the importance of functional assessment of human gene variants and demonstrates the critical requirement of Esrp-Ctnnd1 acting in the embryonic epithelium to regulate palatogenesis.

genetics↗

bioRxiv2021

Efficient Estimation of Indirect Effects in Case-Control Studies Using a Unified Likelihood Framework

Mediation models are a set of statistical techniques that investigate the mechanisms that produce an observed relationship between an exposure variable and an outcome variable in order to deduce the extent to which the relationship is influenced by intermediate mediator variables. For a case-control study, the most common mediation analysis strategy employs a counterfactual framework that permits estimation of indirect and direct effects on the odds ratio scale for dichotomous outcomes, assuming either binary or continuous mediators. While this framework has become an important tool for mediation analysis, we demonstrate that we can embed this approach in a unified likelihood framework for mediation analysis in case-control studies that leverages more features of the data (in particular, the relationship between exposure and mediator) to improve efficiency of indirect effect estimates. One important feature of our likelihood approach is that it naturally incorporates cases within the exposure-mediator model to improve efficiency. Our approach does not require knowledge of disease prevalence and can model confounders and exposure-mediator interactions, and is straightforward to implement in standard statistical software. We illustrate our approach using both simulated data and real data from a case-control genetic study of lung cancer.

genetics↗