Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications DOI Open Access
Qianwen Wang,

Hong-Yuan Zhu,

Linhong Deng

et al.

Small Methods, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 6, 2025

Spatial transcriptomics (ST) represents a revolutionary approach in molecular biology, providing unprecedented insights into the spatial organization of gene expression within tissues. This review aims to elucidate advancements ST technologies, their computational tools, and pivotal applications neuroscience. It is begun with historical overview, tracing evolution from early image-based techniques contemporary sequence-based methods. Subsequently, methods essential for data analysis, including preprocessing, cell type annotation, clustering, detection spatially variable genes, cell-cell interaction 3D multi-slices integration are discussed. The central focus this application neuroscience, where it has significantly contributed understanding brain's complexity. Through ST, researchers advance brain atlas projects, gain development, explore neuroimmune dysfunctions, particularly tumors. Additionally, enhances neuronal vulnerability neurodegenerative diseases like Alzheimer's neuropsychiatric disorders such as schizophrenia. In conclusion, while already profoundly impacted challenges remain issues enhancing sequencing technologies developing robust tools. underscores transformative potential paving way new therapeutic research.

Language: Английский

Spatially resolved transcriptomics: a comprehensive review of their technological advances, applications, and challenges DOI Creative Commons

Mengnan Cheng,

Yujia Jiang, Jiangshan Xu

et al.

Journal of genetics and genomics/Journal of Genetics and Genomics, Journal Year: 2023, Volume and Issue: 50(9), P. 625 - 640

Published: March 27, 2023

The ability to explore life kingdoms is largely driven by innovations and breakthroughs in technology, from the invention of microscope 350 years ago recent emergence single-cell sequencing, which scientific community has been able visualize at an unprecedented resolution. Most recently, Spatially Resolved Transcriptomics (SRT) technologies have filled gap probing spatial or even three-dimensional organization molecular foundation behind mysteries life, including origin different cellular populations developed totipotent cells human diseases. In this review, we introduce progress challenges on SRT perspectives bioinformatic tools, as well representative applications. With currently fast-moving promising results early adopted research projects, can foresee bright future such new tools understanding most profound analytical level.

Language: Английский

Citations

74
Spatiotemporal omics for biology and medicine DOI
Longqi Liu, Ao Chen, Yuxiang Li

et al.

Cell, Journal Year: 2024, Volume and Issue: 187(17), P. 4488 - 4519

Published: Aug. 1, 2024

Language: Английский

Citations

24
The covariance environment defines cellular niches for spatial inference DOI Creative Commons

Doron Haviv,

Ján Remšík, Mohamed I. Gatie

et al.

Nature Biotechnology, Journal Year: 2024, Volume and Issue: unknown

Published: April 2, 2024

A key challenge of analyzing data from high-resolution spatial profiling technologies is to suitably represent the features cellular neighborhoods or niches. Here we introduce covariance environment (COVET), a representation that leverages gene-gene covariate structure across cells in niche capture multivariate nature interactions within it. We define principled optimal transport-based distance metric between COVET niches scales millions cells. Using encode context, developed environmental variational inference (ENVI), conditional autoencoder jointly embeds and single-cell RNA sequencing into latent space. ENVI includes two decoders: one impute gene expression modality second project information onto data. can confer context genomics single dissociated outperforms alternatives for imputing on diverse datasets.

Language: Английский

Citations

23
TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data DOI Creative Commons
Nicolas Pielawski, Axel Andersson, Christophe Avenel

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(5), P. e15306 - e15306

Published: April 18, 2023

Spatially resolved techniques for exploring the molecular landscape of tissue samples, such as spatial transcriptomics, often result in millions data points and images too large to view on a regular desktop computer, limiting possibilities visual interactive exploration. TissUUmaps is free, open-source browser-based tool GPU-accelerated visualization exploration 10

Language: Английский

Citations

28
Spatial Transcriptomics: Emerging Technologies in Tissue Gene Expression Profiling DOI Creative Commons
Agustín Robles-Remacho, Rosario M. Sánchez‐Martín, Juan J. Díaz‐Mochón

et al.

Analytical Chemistry, Journal Year: 2023, Volume and Issue: 95(42), P. 15450 - 15460

Published: Oct. 10, 2023

In this Perspective, we discuss the current status and advances in spatial transcriptomics technologies, which allow high-resolution mapping of gene expression intact cell tissue samples. Spatial enables creation maps patterns within their native context, adding an extra layer information to bulk sequencing data. has expanded significantly recent years is making a notable impact on range fields, including architecture, developmental biology, cancer, neurodegenerative infectious diseases. The latest advancements have resulted development highly multiplexed methods, transcriptomic-wide analysis, single-cell resolution utilizing diverse technological approaches. provide detailed analysis molecular foundations behind main methods based microdissection, situ sequencing, single-molecule FISH, capturing, selection regions interest, or nuclei dissociation. We contextualize detection capturing efficiency, strengths, limitations, compatibility, applications these techniques as well data analysis. addition, Perspective discusses future directions potential transcriptomics, highlighting importance continued promote widespread adoption research community.

Language: Английский

Citations

25
Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications DOI Creative Commons

Xiaojie Liu,

Ting Peng,

Miaochun Xu

et al.

Journal of Hematology & Oncology, Journal Year: 2024, Volume and Issue: 17(1)

Published: Aug. 24, 2024

The emergence of spatial multi-omics has helped address the limitations single-cell sequencing, which often leads to loss context among cell populations. Integrated analysis genome, transcriptome, proteome, metabolome, and epigenome enhanced our understanding biology molecular basis human diseases. Moreover, this approach offers profound insights into interactions between intracellular intercellular mechanisms involved in development, physiology, pathogenesis In comprehensive review, we examine current advancements technologies, focusing on their evolution refinement over past decade, including improvements throughput resolution, modality integration, accuracy. We also discuss pivotal contributions revealing heterogeneity, constructing detailed atlases, deciphering crosstalk tumor immunology, advancing translational research cancer therapy through precise mapping.

Language: Английский

Citations

14
Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025 DOI Creative Commons
Yīmíng Bào, Xue Bai, Congfan Bu

et al.

Nucleic Acids Research, Journal Year: 2024, Volume and Issue: 53(D1), P. D30 - D44

Published: Nov. 11, 2024

The National Genomics Data Center (NGDC), which is a part of the China for Bioinformation (CNCB), offers comprehensive suite database resources to support global scientific community. Amidst unprecedented accumulation multi-omics data, CNCB-NGDC committed continually evolving and updating its core through big data archiving, integrative analysis value-added curation. Over past year, has expanded collaborations with international databases established new subcenters focusing on biodiversity, traditional Chinese medicine tumor genetics. Substantial efforts have been made toward encompassing broad spectrum developing innovative enhancing existing resources. Notably, developed single-cell omics (scTWAS Atlas), genome variation (VDGE), health disease (CVD Atlas, CPMKG, Immunosenescence Inventory, HemAtlas, Cyclicpepedia, IDeAS), biodiversity biosynthesis (RefMetaPlant, MASH-Ocean) research tools (CCLHunter). All services are publicly accessible at https://ngdc.cncb.ac.cn.

Language: Английский

Citations

13
Benchmarking clustering, alignment, and integration methods for spatial transcriptomics DOI Creative Commons
Yunfei Hu,

Manfei Xie,

Yikang Li

et al.

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

Published: Aug. 9, 2024

Spatial transcriptomics (ST) is advancing our understanding of complex tissues and organisms. However, building a robust clustering algorithm to define spatially coherent regions in single tissue slice aligning or integrating multiple slices originating from diverse sources for essential downstream analyses remains challenging. Numerous clustering, alignment, integration methods have been specifically designed ST data by leveraging its spatial information. The absence comprehensive benchmark studies complicates the selection future method development.

Language: Английский

Citations

12
Spatial transcriptomics data and analytical methods: An updated perspective DOI

Mohd Danishuddin,

Shawez Khan, Jong-Joo Kim

et al.

Drug Discovery Today, Journal Year: 2024, Volume and Issue: 29(3), P. 103889 - 103889

Published: Jan. 18, 2024

Language: Английский

Citations

8
Points to Consider From the ESTP Pathology 2.0 Working Group: Overview on Spatial Omics Technologies Supporting Drug Discovery and Development DOI
Kerstin Hahn, Bettina Amberg, Josep M. Monné Rodríguez

et al.

Toxicologic Pathology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

Recent advances in bioanalytical and imaging technologies have revolutionized our ability to assess complex biological pathological changes within tissue samples. Spatial omics, a rapidly evolving technology, enables the simultaneous detection of multiple biomolecules sections, allowing for high-dimensional molecular profiling microanatomical contexts. This offers powerful opportunity precise, multidimensional exploration disease pathophysiology. The Pathology 2.0 working group European Society Toxicologic (ESTP) includes subgroup dedicated spatial omics technologies. Their primary goal is raise awareness about these emerging their potential applications discovery toxicologic pathology. review provides an overview commonly used, commercially available platforms transcriptomic, proteomic, multiomic analysis, discussing technical aspects illustrative examples applications. To harness power translational drug human safety risk assessment, we emphasize important role pathologists at every stage workflow—from hypothesis generation sample preparation, data interpretation. offer novel opportunities target discovery, lead selection, preclinical clinical development compound development.

Language: Английский

Citations

1