Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
| Autor: | Kristof Wing, Quan Nguyen, Samuel W. Lukowski, Lynn Fink, Qianyu Shi, Lei Shi, Anne Senabouth, Anthony G Beckhouse, Feng Jiang, Alice Pébay, Stacey B. Andersen, Wenwei Zhang, Sandy S.C. Hung, Alex W. Hewitt, Maciej Daniszewski, Joseph E. Powell |
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| Rok vydání: | 2019 |
| Předmět: |
0303 health sciences
Computer science 0206 medical engineering Cell Read depth RNA Genomics 02 engineering and technology Computational biology Methart 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Data sequences medicine CRISPR Guide RNA Gene 020602 bioinformatics 030217 neurology & neurosurgery Illumina dye sequencing 030304 developmental biology |
| Zdroj: | NAR Genomics and Bioinformatics |
| ISSN: | 2631-9268 |
| Popis: | The libraries generated by high-throughput single cell RNA-sequencing (scRNA-seq) platforms such as the Chromium from 10× Genomics require considerable amounts of sequencing, typically due to the large number of cells. The ability to use these data to address biological questions is directly impacted by the quality of the sequence data. Here we have compared the performance of the Illumina NextSeq 500 and NovaSeq 6000 against the BGI MGISEQ-2000 platform using identical Single Cell 3′ libraries consisting of over 70 000 cells generated on the 10× Genomics Chromium platform. Our results demonstrate a highly comparable performance between the NovaSeq 6000 and MGISEQ-2000 in sequencing quality, and the detection of genes, cell barcodes, Unique Molecular Identifiers. The performance of the NextSeq 500 was also similarly comparable to the MGISEQ-2000 based on the same metrics. Data generated by both sequencing platforms yielded similar analytical outcomes for general single-cell analysis. The performance of the NextSeq 500 and MGISEQ-2000 were also comparable for the deconvolution of multiplexed cell pools via variant calling, and detection of guide RNA (gRNA) from a pooled CRISPR single-cell screen. Our study provides a benchmark for high-capacity sequencing platforms applied to high-throughput scRNA-seq libraries. |
| Databáze: | OpenAIRE |
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