scTrends: A living review of commercial single-cell and spatial 'omic technologies DOI Creative Commons
Joachim De Jonghe, James W. Opzoomer, Amaia Vilas‐Zornoza

et al.

Cell Genomics, Journal Year: 2024, Volume and Issue: 4(12), P. 100723 - 100723

Published: Dec. 1, 2024

Understanding the rapidly evolving landscape of single-cell and spatial omic technologies is crucial for advancing biomedical research drug development. We provide a living review both mature emerging commercial platforms, highlighting key methodologies trends shaping field. This spans from foundational such as microfluidics plate-based methods to newer approaches like combinatorial indexing; on side, we consider next-generation sequencing imaging-based transcriptomics. Finally, highlight that may fundamentally expand scope data generation within pharmaceutical research, creating opportunities discover validate novel mechanisms. Overall, this serves critical resource navigating commercialization application in academic research.

Language: Английский

A practical guide to spatial transcriptomics DOI
Lukás Valihrach, Daniel Žucha, Pavel Abaffy

et al.

Molecular Aspects of Medicine, Journal Year: 2024, Volume and Issue: 97, P. 101276 - 101276

Published: May 21, 2024

Language: Английский

Citations

4
Gene count normalization in single-cell imaging-based spatially resolved transcriptomics DOI Creative Commons
Lyla Atta, Kalen Clifton, Manjari Anant

et al.

Genome biology, Journal Year: 2024, Volume and Issue: 25(1)

Published: June 12, 2024

Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations fixed tissues. Normalization gene expression data is often needed to account for technical factors that may confound underlying biological signals.

Language: Английский

Citations

4
Two distinct chromatin modules regulate proinflammatory gene expression DOI Creative Commons
Isabelle Seufert, Irene Gerosa, Vassiliki Varamogianni‐Mamatsi

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 6, 2024

Abstract Various mechanisms have been proposed to explain gene activation and co-regulation, including enhancer-promoter interactions via chromatin looping the enrichment of transcription factors into hubs or condensates. However, these conclusions often stem from analyses individual loci, genome-wide studies exploring mechanistic differences with coupled expression are lacking. In this study, we dissected proinflammatory program induced by TNFα in primary human endothelial cells using NGS- imaging-based techniques. Our findings, enabled our novel RWireX approach for single-cell ATAC-seq analysis, revealed two distinct regulatory modules: autonomous links co-accessibility (ACs) between separated sites, domains contiguous (DCs) increased local factor binding. Genes ACs DCs exhibited different transcriptional bursting kinetics, highlighting existence structurally functionally modules response. These findings provide a framework understanding how achieve rapid precise control. Graphical abstract Highlights Two distinct, non-mutually exclusive modules, DCs, that regulate were identified based on deep scATAC-seq. represent long-range genomic regulation occurring more burst frequency. regions binding can modulate size. The AC/DC model integrates sequencing-based evidence microscopy observations hubs/condensates unified model.

Language: Английский

Citations

4
Lessons learned from spatial transcriptomic analyses in clear-cell renal cell carcinoma DOI

J. H. Jespersen,

Cecilie Lindgaard,

Laura Iisager

et al.

Nature Reviews Urology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

Language: Английский

Citations

0
Systematic Benchmarking of High-Throughput Subcellular Spatial Transcriptomics Platforms DOI Creative Commons
Pengfei Ren, Rui Zhang, Yunfeng Wang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 25, 2024

Abstract Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. To address this, we collected clinical samples from three cancer types – colon adenocarcinoma, hepatocellular carcinoma, ovarian generated serial tissue sections evaluation. Using these uniformly processed samples, data across five high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, FF, CosMx 6K, Xenium 5K. establish ground truth datasets, profiled proteins adjacent corresponding to all using CODEX performed single-cell RNA sequencing on the same samples. Leveraging manual cell segmentation detailed annotations, systematically assessed each platform’s performance key metrics, including capture sensitivity, specificity, diffusion control, segmentation, annotation, clustering, transcript-protein alignment CODEX. The generated, processed, annotated multi-omics dataset is valuable advancing computational method development biological discoveries. accessible via SPATCH, a user-friendly web server visualization download ( http://spatch.pku-genomics.org/ ).

Language: Английский

Citations

2
Next‐generation spatial transcriptomics: unleashing the power to gear up translational oncology DOI Creative Commons
Nan Wang, Weifeng Hong,

Yixing Wu

et al.

MedComm, Journal Year: 2024, Volume and Issue: 5(10)

Published: Oct. 1, 2024

The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed last few years. However, harnessing power biology streamlining an array ST tools to achieve designated research goals are fundamental require real-world experiences. We present a review by updating technical scope across different principal basis timeline manner hinting on generally adopted techniques used within community. also current progress bioinformatic propose pipelined workflow toolbox available for data exploration. With particular interests tumor microenvironment where is broadly utilized, we summarize up-to-date made via ST-based technologies narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) multiple cancer types their ways deploying through ST. updated offers guidance forward-looking viewpoints endorsed many high-resolution utilized disentangle biological questions that may lead clinical significance future.

Language: Английский

Citations

1
autoFISH - a modular toolbox for sequential smFISH experiments DOI Creative Commons
Christian Weber, Thomas Defard,

Mickael Lelek

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 15, 2024

Abstract Fluorescence in situ hybridization (FISH) allows for spatial and quantitative profiling of gene expression by visualizing individual RNA molecules. Here, we introduce automated FISH (autoFISH), a comprehensive toolbox to conduct single molecule (smFISH) experiments that is both cost-effective versatile. This includes detailed plans constructing the necessary equipment, open-source software control, reliable experimental protocols, analysis workflows based on our FISH-quant package. Validation with cell lines tissue samples confirmed system’s robustness. We demonstrate standard amplified smFISH, along modified protocol clearing enhances nuclear retention while preserving background reduction efficiency.

Language: Английский

Citations

0
scTrends: A living review of commercial single-cell and spatial 'omic technologies DOI Creative Commons
Joachim De Jonghe, James W. Opzoomer, Amaia Vilas‐Zornoza

et al.

Cell Genomics, Journal Year: 2024, Volume and Issue: 4(12), P. 100723 - 100723

Published: Dec. 1, 2024

Understanding the rapidly evolving landscape of single-cell and spatial omic technologies is crucial for advancing biomedical research drug development. We provide a living review both mature emerging commercial platforms, highlighting key methodologies trends shaping field. This spans from foundational such as microfluidics plate-based methods to newer approaches like combinatorial indexing; on side, we consider next-generation sequencing imaging-based transcriptomics. Finally, highlight that may fundamentally expand scope data generation within pharmaceutical research, creating opportunities discover validate novel mechanisms. Overall, this serves critical resource navigating commercialization application in academic research.

Language: Английский

Citations

0