High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue
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Abstract
We present deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq) for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via next-generation sequencing (NGS). Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide, and crossflow of two sets of barcodes, A1-50 and B1-50, followed by ligation in situ, yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10-μm pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology.
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DBiT-seq enables simultaneous detection of the whole transcriptome and 22 proteins.
“developing the first spatial multi-omics technology, deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq), enabling simultaneous detection of the whole transcriptome and 22 proteins [85].”
From Single-cell sequencing to multi-omics: technologies and applications (2024) · cites this paper as [85]
DBiT-seq is an unbiased multiomic approach that allows for spatial barcoding of the transcriptome in tissues.
“DBiT-seq is an unbiased multiomic approach that allows for spatial barcoding of the transcriptome in tissues57.”
From Spatial mapping of cellular senescence: emerging challenges and opportunities (2023) · cites this paper as [57]
KRT17 functions as a tumor promoter and regulates proliferation in pancreatic cancer, and MMP11 has been found to be a prognostic biomarker for pancreatic cancer.
“KRT17 functions as a tumor promoter and regulates proliferation in pancreatic cancer 21 , and MMP11 has been found to be a prognostic biomarker for pancreatic cancer 22 .”
From SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network (2021) · cites this paper as [21]
The Results sections on whole mouse embryos and internal-organ development discuss spatial gene-expression mapping, not pancreatic cancer. Searches for KRT17 as a tumor promoter and MMP11 as a prognostic biomarker found no passage addressing either claim in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredDBiT-seq was the first reported spatial multi-omics technology to co-map tens of proteins and whole transcriptome.
“DBiT-seq was the first reported spatial multi-omics technology that demonstrated co-mapping of tens of proteins and with a whole transcriptome, and this method has further expanded to spatial epigenomics profiling of chromatin accessibility124 and histone modification125.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [123]
Paired experimental methods are easier computationally because modalities can be tethered to a single cell or spot, but sequencing capacity of each modality decreases overall sample size.
“By contrast, paired experimental methods (10x Multiome, SHARE-seq60, DBiT-seq123, SNARE-seq57, CITE-seq68 and others) are easier to work with computationally as different modalities can be tethered to a single cell or a single spot; however, the sequencing capacity of each modality causes the overall sample size to decrease.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [123]
Current spatial technologies capture only one layer of omics information at a time, precluding examination of mechanistic relationships across the central dogma.
“However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology.”
From Spatial epigenome–transcriptome co-profiling of mammalian tissues (2023) · cites this paper as [1]
Previously, deterministic barcoding in tissue for spatial omics sequencing was developed for spatially resolved comeasurement of the transcriptome and a panel of proteins, and recently realized in the 10X Visium platform.
“Previously we developed deterministic barcoding in tissue for spatial omics sequencing for spatially resolved comeasurement of the transcriptome and a panel of proteins1, and recently it was also realized in the 10X Visium platform11.”
From Spatial epigenome–transcriptome co-profiling of mammalian tissues (2023) · cites this paper as [1]
Spatial epigenomics, transcriptomics and proteomics emerged recently but most capture only one layer of omics information.
“Spatial epigenomics, transcriptomics and proteomics emerged recently1–5 but most of these can capture only one layer of the omics information.”
From Spatial epigenome–transcriptome co-profiling of mammalian tissues (2023) · cites this paper as [1]
For 50-μm pixel size, an average of 25 cells was obtained for E10 mouse embryo and between one and nine cells for human hippocampus.
“For the 50-μm pixel size we obtained an average of 25 cells for E10 mouse embryo1 and between one and nine cells for human hippocampus3.”
From Spatial epigenome–transcriptome co-profiling of mammalian tissues (2023) · cites this paper as [1]
Early mouse embryos, specific late-stage-embryonic tissues such as the cerebral cortex, and whole midgestation embryos have been analyzed using spatially resolved transcriptomic approaches.
“Early mouse embryos (Lohoff et al., 2022; Peng et al., 2019), specific late-stage-embryonic tissues such as the cerebral cortex (Di Bella et al., 2021; Stickels et al., 2021), and whole midgestation embryos (Liu et al., 2020; Srivatsan et al., 2021; Yao et al., 2020) have been analyzed using these approaches.”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Liu et al., 2020
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“…equipped with parallel microfluidic channels to deliver DNA barcodes to tissue sections, developing the first spatial multi-omics technology, deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq), enabling simultaneous detection of the whole transcriptome and 22 proteins [85].”
BackgroundSuper-resolved spatial transcriptomics by deep data fusion
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- Authors
- Liu, Y., Yang, M., Deng, Y., Su, G., Enninful, A., Guo, C. C., Tebaldi, T., Zhang, D., Kim, D., Bai, Z., Norris, E., Pan, A., Li, J., Xiao, Y., Halene, S., & Fan, R.
- Affiliations
- Yale Cancer Center (US)
- Yale University (US)
- Corresponding author
- Fan, Rong
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 183
- Issue
- 6
- Pages
- 1665-1681.e18
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC7736559
- OpenAlex
- W3100967665
- Cited by
- 966
- References
- 51
- Citations by year
- 2026: 208 · 2025: 200 · 2024: 181 · 2023: 154 · 2022: 133 · 2021: 76 · 2020: 10 · 2019: 3
- FWCI
- 30.26
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- Funders
- Stand Up To Cancer
- National Institutes of Health
- David and Lucile Packard Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- spatial omics, mouse embryo development, organogenesis, microcirculation, pigmented epithelium, cell type annotation, spatial gene expression
- MeSH terms
- Animals, Automation, Brain, Embryo, Mammalian, Eye, Female, Humans, Mice, Inbred C57BL, Organ Specificity, RNA, Messenger, Reproducibility of Results, Cluster Analysis, DNA, Complementary, Gene Expression Regulation, Developmental, Genomics, Microfluidics, DNA Barcoding, Taxonomic, Single-Cell Analysis, Transcriptome, Human Umbilical Vein Endothelial Cells
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