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| Status |
Public on Dec 01, 2019 |
| Title |
An optimization system for isolating and sequencing of single human colon cancer cells |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Single cell sequencing (SCS) is a promising approach for precisely digging into the genetic heterogeneity at single cells level. Single cell whole genome/exome sequencing (scWGS/scWES) and single cell whole transcriptome sequencing (scRNA-seq) are methods of SCS and have been applied in various studies of solid tumors, e.g. liver cancer, breast cancer. However, no scRNA-seq-related studies of human colon-cancer tissue-samples have been conducted. In this study, we developed a modified and efficient colon-cancer-tissue SCSs system (named CCTSs-SCSs system) by combining four optimization technologies: tissue digestion, live and intact single-cells capture, single-cell RNA or genome amplification and sequencing, and bioinformatics analysis. This advanced system is applicable to both scRNA-seq and scWGS/scWES. Using this system, we successfully completed several single cells scRNA-seq and scWES, and found three key points of this system: an improved digestion system, FACS-based dead-cell-removal method for scRNA-seq, 20 cycles for scRNA amplification. Our CCTSs-SCSs system provides a reliable and efficient method of scRNA-seq or scWGS/scWES for human colon cancer tissue and contributes to single-cell level and precise studies for colon cancer.
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| Overall design |
5 cells for beads-based DCR kit, and 5 cells for FACS-based DCR kit
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| Contributor(s) |
Zhang X, Yang L |
| Citation missing |
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| Submission date |
Dec 15, 2016 |
| Last update date |
Dec 01, 2019 |
| Contact name |
Ling Yang |
| E-mail(s) |
kaji331@hotmail.com
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| Organization name |
Hangzhou cancer institute
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| Street address |
34th, Yanguan alley
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| City |
Hangzhou |
| ZIP/Postal code |
310002 |
| Country |
China |
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| Platforms (1) |
| GPL20301 |
Illumina HiSeq 4000 (Homo sapiens) |
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| Samples (10)
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| Relations |
| BioProject |
PRJNA357555 |
| SRA |
SRP095161 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE92432_gene_count_matrix.csv.gz |
721.7 Kb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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