Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis.
Nat Genet
; 56(4): 627-636, 2024 Apr.
Article
en En
| MEDLINE
| ID: mdl-38514783
ABSTRACT
We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Cromatina
/
Estudio de Asociación del Genoma Completo
Idioma:
En
Revista:
Nat Genet
Asunto de la revista:
GENETICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos