The incorporation of long-read sequencing into single-cell assays addresses this shortfall observed in traditional short-read sequencing methodologies. This integration offers insights into molecular mechanisms, enabling the identification of intricate structural variants, comprehensive exploration of whole transcript alternative splicing events, and the expression of cell-type-specific mRNA isoforms at the single-cell level.
Applications
- Isoform-level gene expression of RNA transcripts.
- Analyze different isoform, alternative splicing, fusion genes, etc.
- Characterization of transcript isoforms relevant to health, development, and disease in single cell level.
* : Only acceptable in AMEA (Asia pacific, Middle East and Africa)
Sample Requirement
| Sample Type | Sample Amount | Concentration | Others | Storage |
| Single cell suspension* | ≥ 1,000,000 | ≥500,000 cells/mL | Cell viability: >80% Cell size: <30 μm |
– |
| cDNA from 10x
GEM |
≥ 50 ng | ≥ 2 ng/ul | Peak Size: 1-1.8 kb | < 2 months under -20℃/-80℃ |
* For more information on the detailed sample requirements, please contact your local sales.
Specifications: Sequencing and Analysis
| Sequence platform | Nanopore PromethION | llumina NovaSeq PE150 |
| Comparison | Full length long reads
Get the full-length information of mRNA Analyze different mRNA isoform, alternative splicing, fusion genes, etc. |
3’ to 5’ short reads
Gene expression information only Impossible to analyze the differences in the isoform of transcripts between cells |
| Read length | Median read length: ~700-1000bp | Paired-end 150bp |
| Recommended Data Output |
1 PromethION cell ~ 100 M total reads/cell |
50,000 pair reads/cell 100 -120Gb |
| Data QC Standard Analysis |
Wf-single-cell
Data QC Identify the cell barcode and UMI sequences present in Nanopore sequencing reads Summary metrics (read quality, number of cells, genes and transcripts identified within each sample, median genes per cell, and sequence saturation) UMAP projections |
Cell Ranger
Demultiplex BCL files from a sequencer into FASTQs Summary metrics (sequencing quality, number of cells detected, the mean reads per cell, and the median genes detected per cell et al.) Alignment of reads to genome Gene expression quantification Clustering analysis Differentially expression analysis between clusters Visualization |
| Standard Analysis | Data QC
Mapping and Quantification Dimensionality reduction, clustering, and differential analysis Base on gene GO/KEGG/Reactome Enrichment Analysis Alternative Splicing |
Demultiplex BCL files from a sequencer into FASTQs
Alignment, UMI counting, Metrics summary Identification of highly variable gene (HVGs) Cell Subpopulation Identification Marker gene detection (Differentially expression analysis between clusters) GO/KEGG/Reactome Enrichment |
Project Workflow
From sample preparation, library preparation, sequencing and data quality control, to bioinformatics analysis, Novogene provides high-quality products and professional services. Each step is performed in agreement with a high scientific standard and meticulous design to ensure high-quality research results.
