Single-cell RNA counting at allele and isoform resolution using Smart-seq3.
Nat Biotechnol
; 38(6): 708-714, 2020 06.
Article
en En
| MEDLINE
| ID: mdl-32518404
ABSTRACT
Large-scale sequencing of RNA from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states1. However, current short-read single-cell RNA-sequencing methods have limited ability to count RNAs at allele and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells2,3. Here we introduce Smart-seq3, which combines full-length transcriptome coverage with a 5' unique molecular identifier RNA counting strategy that enables in silico reconstruction of thousands of RNA molecules per cell. Of the counted and reconstructed molecules, 60% could be directly assigned to allelic origin and 30-50% to specific isoforms, and we identified substantial differences in isoform usage in different mouse strains and human cell types. Smart-seq3 greatly increased sensitivity compared to Smart-seq2, typically detecting thousands more transcripts per cell. We expect that Smart-seq3 will enable large-scale characterization of cell types and states across tissues and organisms.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
ARN
/
Análisis de Secuencia de ARN
/
Perfilación de la Expresión Génica
/
Análisis de la Célula Individual
Tipo de estudio:
Diagnostic_studies
Límite:
Animals
/
Humans
Idioma:
En
Revista:
Nat Biotechnol
Asunto de la revista:
BIOTECNOLOGIA
Año:
2020
Tipo del documento:
Article
País de afiliación:
Suecia