ArticleBMC genomics2017
Massively parallel nanowell-based single-cell gene expression profiling.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.
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Who cites it
74 citing papers in PubMed.
- Single-cell transcriptomics uncovers endothelial progenitor-like remodelling driving human coronary atherosclerosis progression.Nature cell biology · 2026Article
- Decoding Cardiac Development and Maturation at Single-Cell and Spatial Transcriptomic Resolution.Circulation research · 2026Review
- An expanded role for single-cell chemical genomics profiling in drug discovery.The Biochemical journal · 2026Review
- A hitchhiker's guide to single-cell epigenomics: Methods and applications for cancer research.International journal of cancer · 2026Review
- Advances in scCUT&Tag and computational analysis for single-cell gene regulatory element mapping.Briefings in bioinformatics · 2026Review
- Single-cell RNA sequencing of platelets: challenges and potential.Journal of thrombosis and thrombolysis · 2026Article
- Integration of hyperspectral imaging and transcriptomics from individual cells with SpectralSeq.Genome research · 2025Article
- Integrated analysis of miRNAs and mRNAs in thousands of single cells.Scientific reports · 2025Article
- Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research.Acta biochimica Polonica · 2025Review
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- From Cell to Gene: Deciphering the Mechanism of Heart Failure With Single-Cell Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Emerging toolkits for decoding the co-occurrence of modified histones and chromatin proteins.EMBO reports · 2024Review
- Transcriptomic Approaches to Cardiomyocyte-Biomaterial Interactions: A Review.ACS biomaterials science & engineering · 2024Review
- Revisiting Cardiac Biology in the Era of Single Cell and Spatial Omics.Circulation research · 2024Review
- Characteristics of peripheral blood mononuclear cells and potential related molecular mechanisms in patients with autoimmune hepatitis: a single-cell RNA sequencing analysis.Medical molecular morphology · 2024Article
- Mapping Cell Atlases at the Single-Cell Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Cardiac Development at a Single-Cell Resolution.Advances in experimental medicine and biology · 2024Article
- Single-cell sequencing technology applied to epigenetics for the study of tumor heterogeneity.Clinical epigenetics · 2023Review
- Article
- Transitioning single-cell genomics into the clinic.Nature reviews. Genetics · 2023Review
14 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTechnological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable.
resultsHere we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells.
conclusionsOverall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.
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