Evidence map›Paper›PMID 41353535›Full record

ArticleBMC genomics2025

Plate-based 10X Genomics-compatible single-cell RNA-sequencing based on Smart-seq3xpress.

Koen Deserranno, Elise Callens, Danique Berrevoet, Aaron Verplancke, Tamara De Vos, Tom Taghon, Dieter Deforce, Filip Van Nieuwerburgh

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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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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Koen Deserranno *Laboratory of Pharmaceutical Biotechnology - NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, BLOK A, FLOOR3, Ghent, 9000, Belgium.
Elise Callens *Laboratory of Pharmaceutical Biotechnology - NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, BLOK A, FLOOR3, Ghent, 9000, Belgium.
Danique BerrevoetLaboratory of Pharmaceutical Biotechnology - NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, BLOK A, FLOOR3, Ghent, 9000, Belgium.
Aaron VerplanckeLaboratory of Pharmaceutical Biotechnology - NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, BLOK A, FLOOR3, Ghent, 9000, Belgium.
Tamara De VosDepartment of Diagnostic Sciences, Ghent University, Ghent, Belgium.
Tom TaghonDepartment of Diagnostic Sciences, Ghent University, Ghent, Belgium.
Dieter DeforceLaboratory of Pharmaceutical Biotechnology - NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, BLOK A, FLOOR3, Ghent, 9000, Belgium.
Filip Van NieuwerburghLaboratory of Pharmaceutical Biotechnology - NXTGNT, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, BLOK A, FLOOR3, Ghent, 9000, Belgium. Filip.VanNieuwerburgh@Ugent.be.

Funding

Bijzonder Onderzoeksfonds UGent BOF21/DOC/042
6 · The paper itself

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.

Indexed as

GenomicsSequence Analysis, RNASingle-Cell AnalysisFlow CytometryGene Expression ProfilingGene LibraryHigh-Throughput Nucleotide SequencingHumans10X GenomicsBenchmarkingIndexed sortingPlate-based scRNA-seqSmart-seq

Identifiers

PMID41353535
PMCPMC12797766

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.