Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing

Basic information
Technology
10X Genomics
Omics
scRNA-seq
Source
PBMCs

Dataset ID
36109685
Platform
454 GS,NovaSeq 6000,NextSeq 500
Species
Human
Disease
Healthy
Age range
0 - 0
Update date
2022-09-15
Summary

Here we introduce a mostly natural sequencing-by-synthesis (mnSBS) method for single-cell RNA sequencing (scRNA-seq), adapted to the Ultima genomics platform, and systematically benchmark it against current scRNA-seq technology. mnSBS uses mostly natural, unmodified nucleotides and only a low fraction of fluorescently labeled nucleotides, which allows for high polymerase processivity and lower costs. 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. Benchmarking shows that results from mnSBS-based scRNA-seq are very similar to those using Illumina sequencing, with minor differences in results related to the position of reads relative to annotated gene boundaries, owing to single-end reads of Ultima being closer to gene ends than reads from Illumina. The method is thus compatible with state-of-the-art scRNA-seq libraries independent of the sequencing technology. We expect mnSBS to be of particular utility for cost-effective large-scale scRNA-seq projects.

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.

Contributors

Sean K. Simmons†, Gila Lithwick-Yanai†, Xian Adiconis†, Joshua Z. Levin✉️

Contact

jlevin@broadinstitute.org(Joshua Z. Levin)

snRNA-Seq
Sample nameSample titleDiseaseGenderAgeSourceTreatmentTechnologyPlatformOmicsSample IDDataset IDAction
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