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| Status |
Public on May 31, 2022 |
| Title |
Single cell RNA-seq by mostly-natural sequencing by synthesis |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
Other
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| Summary |
Massively parallel single cell RNA-seq (scRNA-seq) for diverse applications, from cell atlases to functional screens, is increasingly limited by sequencing costs, and large-scale low-cost sequencing can open many additional applications, including patient diagnostics and drug screens. Here, we adapted and systematically benchmarked a newly developed, mostly-natural sequencing by synthesis method for scRNA-seq. We demonstrate successful application in four scRNA-seq case studies of different technical and biological types, including 5’ and 3’ scRNA-seq, human peripheral blood mononuclear cells from a single individual and in multiplex, as well as Perturb-Seq. Our data show comparable results to existing technology, including compatibility with state of the art scRNA-seq libraries independent of the sequencing technology used – thus providing an enhanced cost-effective path for large scale scRNA-seq.
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| Overall design |
We generated and analysed single cell RNA-seq (10x Chromium) data for 4 samples. 1) PBMC sample with 3' technology, 2) PBMC sample (same as 1) with 5' single cell technology, 3) a mixture of PBMCs from 8 individuals with 5' technology, and 4) a mixture of 8 Perturb-seq samples (mixed using cell hashing) with 3' technology. For each we sequenced with both Illumina and Ultima sequencing.
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| Contributor(s) |
Simmons SK, Levin JZ, Lithwick-Yanai G, Adiconis X, Oberstrass F, Iremadze N, Geiger-Schuller K, Thakore PI, Frangieh CJ, Barad O, Almogy G, Rozenblatt-Rosen O, Regev A, Lipson D |
| Citation(s) |
36109685 |
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| Submission date |
Feb 25, 2022 |
| Last update date |
Jun 01, 2023 |
| Contact name |
Joshua Levin |
| E-mail(s) |
jlevin@broadinstitute.org
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| Organization name |
Broad Institute
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| Department |
Stanley Center
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| Street address |
75 Ames St
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| City |
Cambridge |
| State/province |
MA |
| ZIP/Postal code |
02142 |
| Country |
USA |
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| Platforms (4)
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| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (16)
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| Relations |
| BioProject |
PRJNA810422 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE197452_RAW.tar |
890.2 Mb |
(http)(custom) |
TAR (of CSV, H5, TXT) |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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