Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles

• DOI: 10.1038/s41588-024-01682-1
• Publication Date: 2024-04-09T10:02:06Z
• Authors: Saori Sakaue; Kathryn Weinand; Shakson Isaac; Kushal K. Dey; Karthik Jagadeesh; Masahiro Kanai; Gerald F. M. Watts; Zhu Zhu; ; Jennifer Albrecht; Jennifer H. Anolik; William Apruzzese; Nirmal Banda; Jennifer L. Barnas; Joan M. Bathon; Ami Ben-Artzi; Brendan F. Boyce; David L. Boyle; S. Louis Bridges; Vivian P. Bykerk; Debbie Campbell; Hayley L. Carr; Arnold Ceponis; Adam Chicoine; Andrew Cordle; Michelle Curtis; Kevin D. Deane; Edward DiCarlo; Patrick Dunn; Andrew Filer; Gary S. Firestein; Lindsy Forbess; Laura Geraldino-P...; Susan M. Goodman; Ellen M. Gravallese; Peter K. Gregersen; Joel M. Guthridge; Maria Gutierrez-A...; Siddarth Gurajala; V. Michael Holers; Diane Horowitz; Laura B. Hughes; Kazuyoshi Ishigaki; Lionel B. Ivashkiv; Judith A. James; Anna Helena Jonsson; Joyce B. Kang; Gregory Keras; Ilya Korsunsky; Amit Lakhanpal; James A. Lederer; Zhihan J. Li; Yuhong Li; Katherine P. Liao; Arthur M. Mandelin; Ian Mantel; Mark Maybury; Joseph Mears; Nida Meednu; Nghia Millard; Larry W. Moreland; Aparna Nathan; Alessandra Nerviani; Dana E. Orange; Harris Perlman; Costantino Pitzalis; Javier Rangel-Moreno; Deepak A. Rao; Karim Raza; Yakir Reshef; Christopher Ritchlin; Felice Rivellese; William H. Robinson; Laurie Rumker; Ilfita Sahbudin; Jennifer A. Seifert; Kamil Slowikowski; Melanie H. Smith; Darren Tabechian; Dagmar Scheel-Toe...; Paul J. Utz; Dana Weisenfeld; Michael H. Weisman; Qian Xiao; Fan Zhang; Michael B. Brenner; Andrew McDavid; Laura T. Donlin; Kevin Wei; Alkes L. Price; Soumya Raychaudhuri
• Keywords: 0303 health sciences; 03 medical and health sciences; Phenotype; 610; Humans; Chromosome Mapping; Genetic Predisposition to Disease; Regulatory Sequences, Nucleic Acid; Polymorphism, Single Nucleotide; Alleles; Chromatin; Genome-Wide Association Study

AbstractTranslating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. We developed a new non-parametric statistical method, SCENT (Single-Cell ENhancer Target gene mapping) which models association between enhancer chromatin accessibility and gene expression in single-cell multimodal RNA-seq and ATAC-seq data. We applied SCENT to 9 multimodal datasets including > 120,000 single cells and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in eQTLs and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases. In addition, we were able to link somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining non-coding variant function.