Description

Unsolved Mendelian cases often lack obvious pathogenic coding variants, suggesting potential non-coding etiologies. Here, we present a single cell multi-omic framework integrating embryonic mouse chromatin accessibility, histone modification, and gene expression assays to discover cranial motor neuron (cMN) cis-regulatory elements and subsequently nominate candidate non-coding variants in the congenital cranial dysinnervation disorders (CCDDs), a set of Mendelian disorders altering cMN development. We generate single cell epigenomic profiles for ~86,000 cMNs and related cell types, identifying ~250,000 accessible regulatory elements with cognate gene predictions for ~145,000 putative enhancers. We evaluate enhancer activity for 59 elements using an in vivo transgenic assay and validate 44 (75%), demonstrating that single cell accessibility can be a strong predictor of enhancer activity. Applying our cMN atlas to 899 whole genome sequences from 270 genetically unsolved CCDD pedigrees, we achieve significant reduction in our variant search space and nominate candidate variants predicted to regulate known CCDD disease genes MAFB, PHOX2A, CHN1, and EBF3 – as well as candidates in recurrently mutated enhancers through peak- and gene-centric allelic aggregation. This work delivers non-coding variant discoveries of relevance to CCDDs and a generalizable framework for nominating non-coding variants of potentially high functional impact in other Mendelian disorders.

Methods

The tracks represent single-cell ATAC-seq data for embryonic cranial motor neurons (cMNs) at stages e10.5 and e11.5. Data generation involved microdissection and fluorescence-activated cell sorting (FACS) of GFP-positive motor neurons marked by Isl1MN:GFP and Hb9:GFP reporters. Following FACS, droplet-based scATAC-seq was performed on GFP-positive primary cranial motor neurons (cMNs) (oculomotor (cMN3), trochlear (cMN4), abducens (cMN6), facial (cMN7), and hypoglossal (cMN12) neurons), spinal motor neurons (sMNs), and surrounding GFP-negative non-motor neuron cells (-neg). Fastq files were generated from bcl using 10x cellranger. Individual samples were aligned to the mm10 genome using Bowtie2.

Over 86,000 cells were profiled at an average coverage of 48,772 reads per cell. The dataset includes approximately 250,000 accessible regulatory elements, out of which around 145,000 are predicted enhancers. To validate this data, bulk ATAC-seq was used for cross-referencing single-cell peak representation. This dataset provides a detailed chromatin landscape for embryonic cranial motor neurons for identifying regulatory variants linked to congenital cranial dysinnervation disorders (CCDDs) and other cranial nerve developmental anomalies.

More information on the methods can be found in the referenced paper.

Track Descriptions

• track cMN34-R1-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN3/4 (oculomotor/ trochlear) cells, replicate 1.
• track cMN34-R2-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN3/4 (oculomotor/ trochlear) cells, replicate 2.
• track cMN34neg-R1-e10-5: ATAC-seq reads for e10.5 GFP-negative cMN3/4 (oculomotor/ trochlear) cells, replicate 1.
• track cMN34-R1-e11-5: ATAC-seq reads for e11.5 GFP-positive cMN3/4 (oculomotor/ trochlear) cells, replicate 1.
• track cMN34-R2-e11-5: ATAC-seq reads for e11.5 GFP-positive cMN3/4 (oculomotor/ trochlear) cells, replicate 2.
• track cMN34neg-R1-e11-5: ATAC-seq reads for e11.5 GFP-negative cMN3/4 (oculomotor/ trochlear) cells, replicate 1.
• track cMN6-R1-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN6 (abducens) cells, replicate 1.
• track cMN6-R2-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN6 (abducens) cells, replicate 2.
• track cMN6neg-R1-e10-5: ATAC-seq reads for e10.5 GFP-negative cMN6 (abducens) cells, replicate 1.
• track cMN6-R1-e11-5: ATAC-seq reads for e11.5 GFP-positive cMN6 (abducens) cells, replicate 1.
• track cMN6-R2-e11-5: ATAC-seq reads for e11.5 GFP-positive cMN6 (abducens) cells, replicate 2.
• track cMN6neg-R1-e11-5: ATAC-seq reads for e11.5 GFP-negative cMN6 (abducens) cells, replicate 1.
• track cMN7-R1-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN7 (facial) cells, replicate 1.
• track cMN7-R1T-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN7 (facial) cells, replicate 1T.
• track cMN7-R2-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN7 (facial) cells, replicate 2.
• track cMN7-R3-e10-5: ATAC-seq reads for e10.5 GFP-positive cMN7 (facial) cells, replicate 3.

Credits

Data were generated and processed by Engle Lab at Boston Children’s Hospital and collaborating institutions. For inquiries, please contact elizabeth.engle@childrens.harvard.edu.

References

Arthur S. Lee, Lauren J. Ayers, Michael Kosicki, Elizabeth Engle et al. (2024). A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders. Nature Communications, 15:8268.