ArticleBMC genomics2025
Plate-based 10X Genomics-compatible single-cell RNA-sequencing based on Smart-seq3xpress.
Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
background10X Genomics (10X) is a leading single-cell RNA-sequencing (scRNA-seq) technology that permits gene expression and T-cell receptor (TCR) repertoire profiling. However, its microfluidics-based approach restricts direct pairing of upstream indexed single-cell sorting with downstream scRNA-seq data and poses challenges for cost-effective profiling of small-scale cell populations.
resultsTo address these limitations, we developed a plate-based, 10X-compatible (PB10X) scRNA-seq strategy built on the Smart-seq3xpress (SS3X) principle. PB10X supports indexed sorting using Fluorescence Activated Cell Sorting (FACS) directly into 384-well plates and generates cDNA compatible with any standardized 10X Single Cell 5' library construction kit including the 5' V(D)J and 5' Gene Expression kits. PB10X offers the flexibility of plate-based scRNA-seq with the robustness of the 10X sequencing library preparation, while retaining full compatibility with downstream Cell Ranger data processing. We demonstrated PB10X's performance on Jurkat lymphoblasts by generating V(D)J and gene expression sequencing libraries, and benchmarking these against 10X and SS3X. PB10X proved particularly effective for TCR repertoire sequencing, yielding paired TCRαβ chains for 81.71% of the cells at a limited sequencing depth. PB10X further detected a mean of 4,343 genes and 16,137 UMIs per cell, while achieving the highest proportion of uniquely mapped reads and protein-coding genes among the compared methods. Notably, PB10X resolves the strand invasion artifact observed in SS3X.
conclusionsThe novel cost-effective PB10X method offers unprecedented 10X-compatibility in a plate-based format, both for immune receptor repertoire sequencing and gene expression profiling, representing a promising single-cell transcriptomics strategy, especially in immunological settings with limited cell populations.
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