Nature Communications (Sep 2024)

A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders

  • Arthur S. Lee,
  • Lauren J. Ayers,
  • Michael Kosicki,
  • Wai-Man Chan,
  • Lydia N. Fozo,
  • Brandon M. Pratt,
  • Thomas E. Collins,
  • Boxun Zhao,
  • Matthew F. Rose,
  • Alba Sanchis-Juan,
  • Jack M. Fu,
  • Isaac Wong,
  • Xuefang Zhao,
  • Alan P. Tenney,
  • Cassia Lee,
  • Kristen M. Laricchia,
  • Brenda J. Barry,
  • Victoria R. Bradford,
  • Julie A. Jurgens,
  • Eleina M. England,
  • Monkol Lek,
  • Daniel G. MacArthur,
  • Eunjung Alice Lee,
  • Michael E. Talkowski,
  • Harrison Brand,
  • Len A. Pennacchio,
  • Elizabeth C. Engle

DOI
https://doi.org/10.1038/s41467-024-52463-7
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 26

Abstract

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Abstract 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.