Microscopic examination of spatial transcriptome using Seq-Scope

Cho, Chun‐Seok; Xi, Jingyue; Si, Yichen; Park, Sung-Rye; Hsu, Jer-En; Kim, Myung-Jin; Jun, Goo; Kang, Hyun Min; Lee, Jun H.

doi:10.1016/j.cell.2021.05.010

Cited by 344 publications

(342 citation statements)

References 51 publications

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“…Stereo-seq captured numbers ranging on average 69 UMI per 2 µm (diameter) bin (bin 3, 3 × 3 DNB), 1,450 UMI per 10 µm (diameter) bin (bin 14, 14 × 14 DNB, equivalent to ~1 medium size cell) and 133,776 UMI per 100 µm (diameter) bin (bin 140, 140 × 140 DNB) (Figure 1C and S1B). This is superior to other available technologies including Seq-Scope (848 UMI on average per 10 µm diameter bin) (Cho et al, 2021a) when compared at the same bin resolution.…”

Section: Dnb Patterned Arrays Enable Large Field-of-view Spatially Resolved Transcriptomics With High Definitionmentioning

confidence: 92%

“…HDST data (Vickovic et al, 2019) were taken from GSE130682, SLIDE-seqV2 data (Stickels et al, 2021) from the Single Cell Portal of the Broad Institute, DBiT-seq data (Yao et al, 2020) from GSE137986, and Visium data (Lebrigand et al, 2020b) from GSE153859, Seq-Scope data were taken from GSE169706 (Cho et al, 2021a). For Fig.…”

Section: Comparison Of Stereo-seq With Other Published Methodsmentioning

confidence: 99%

“…Several remarkable methodologies have been recently developed that allow spatially resolved transcriptomic profiling of tissue sections. They can be divided in three main classes based on their detection method: physical segmentation using microdissection coupled to sequencing (Nichterwitz et al, 2016;Peng et al, 2019), pre-designed probes for either single-molecule hybridization (Eng et al, 2019;Zhuang, 2021) or amplification and in situ decoding (Alon et al, 2021;Lee et al, 2014;Wang et al, 2018), and barcoded probes (Cho et al, 2021a;Rodriques et al, 2019;Srivatsan et al, 2021;Stahl et al, 2016;Vickovic et al, 2019;Yao et al, 2020). These techniques all have specific advantages and disadvantages in resolution and applicability but share a major caveat in the limited field of view.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

Chen¹,

Liao²,

Cheng³

et al. 2021

Preprint

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High-throughput profiling of in situ gene expression represents a major advance towards the systematic understanding of tissue complexity. Applied with enough capture area and high sample throughput it will help to define the spatio-temporal dynamics of gene expression in tissues and organisms. Yet, current technologies have considerable bottlenecks that limit widespread application. Here, we have combined DNA nanoball (DNB) patterned array chips and in situ RNA capture to develop Stereo-seq (Spatio-Temporal Enhanced REsolution Omics-sequencing). This approach allows high sample throughput transcriptomic profiling of histological sections at unprecedented (nanoscale) resolution with areas expandable to centimeter scale, high sensitivity and homogenous capture rate. As proof of principle, we applied Stereo-seq to the adult mouse brain and sagittal sections of E11.5 and E16.5 mouse embryos. Thanks to its unique features and amenability to additional modifications, Stereo-seq can pave the way for the systematic spatially resolved-omics characterization of tissues and organisms.

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Section: Dnb Patterned Arrays Enable Large Field-of-view Spatially Resolved Transcriptomics With High Definitionmentioning

confidence: 92%

Section: Comparison Of Stereo-seq With Other Published Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

Chen¹,

Liao²,

Cheng³

et al. 2021

Preprint

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show abstract

“…Seq-Scope is another tool for high resolution spatial transcriptomics, enabling the visualization of transcriptomic heterogeneity at the cellular/subcellular level. In contrast to Slide-seq V2, which is based on barcoded beads, seq-scope depends on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides spotted on a Illumina flow cell [ 31 ]. Deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq) is another method that uses a microfluidic chip with parallel channels on top of a tissue section [ 32 ].…”

Section: Spatial Sequencingmentioning

confidence: 99%

The Potential of OMICs Technologies for the Treatment of Immune-Mediated Inflammatory Diseases

Anchang

Raimondo

et al. 2021

IJMS

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Immune-mediated inflammatory diseases (IMIDs), such as inflammatory bowel diseases and inflammatory arthritis (e.g., rheumatoid arthritis, psoriatic arthritis), are marked by increasing worldwide incidence rates. Apart from irreversible damage of the affected tissue, the systemic nature of these diseases heightens the incidence of cardiovascular insults and colitis-associated neoplasia. Only 40–60% of patients respond to currently used standard-of-care immunotherapies. In addition to this limited long-term effectiveness, all current therapies have to be given on a lifelong basis as they are unable to specifically reprogram the inflammatory process and thus achieve a true cure of the disease. On the other hand, the development of various OMICs technologies is considered as “the great hope” for improving the treatment of IMIDs. This review sheds light on the progressive development and the numerous approaches from basic science that gradually lead to the transfer from “bench to bedside” and the implementation into general patient care procedures.

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“…Second, spatial labeling technologies use ingenious ways to link all transcripts within a spatial unit with known coordinates. This in situ capturing step is subsequently followed by an unbiased standard sequencing approach (Ståhl et al 2016;Rodriques et al 2019;Vickovic et al 2019;Liu et al 2020;Merritt et al 2020;Chen et al 2021;Cho et al 2021;Stickels et al 2021). Third, select genes can be targeted for in situ sequencing (ISS), with the synthesized cDNA products labeled by fluorescent nucleotides and detected by imaging (Lee et al 2014;Wang et al 2018;Qian et al 2020;Hu et al 2020b;Alon et al 2021;Fu et al 2021).…”

mentioning

confidence: 99%

Advances in spatial transcriptomic data analysis

et al. 2021

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Spatial transcriptomics is a rapidly growing field that promises to comprehensively characterize tissue organization and architecture at the single-cell or subcellular resolution. Such information provides a solid foundation for mechanistic understanding of many biological processes in both health and disease that cannot be obtained by using traditional technologies. The development of computational methods plays important roles in extracting biological signals from raw data. Various approaches have been developed to overcome technology-specific limitations such as spatial resolution, gene coverage, sensitivity, and technical biases. Downstream analysis tools formulate spatial organization and cell–cell communications as quantifiable properties, and provide algorithms to derive such properties. Integrative pipelines further assemble multiple tools in one package, allowing biologists to conveniently analyze data from beginning to end. In this review, we summarize the state of the art of spatial transcriptomic data analysis methods and pipelines, and discuss how they operate on different technological platforms.

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Microscopic examination of spatial transcriptome using Seq-Scope

Cited by 344 publications

References 51 publications

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

The Potential of OMICs Technologies for the Treatment of Immune-Mediated Inflammatory Diseases

Advances in spatial transcriptomic data analysis

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