Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 34
Published: Jan. 1, 2025
Language: Английский
Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 52(D1), P. D1053 - D1061
Published: Nov. 11, 2023
Abstract Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their locations at the single-cell level, generating detailed biological insight into processes. A comprehensive database could facilitate sharing transcriptomic data streamline acquisition process for researchers. Here, we present Spatial TranscriptOmics DataBase (STOmicsDB), a that serves as one-stop hub transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified regions genes, performed cell-cell interaction analysis these datasets. features user-friendly interface rapid visualization millions cells. To further reusability interoperability data, developed standards archiving constructed system. Additionally, offer distinctive capability customizing dedicated sub-databases researchers, assisting them visualizing analyses. believe contribute research insights field, including archiving, sharing, analysis. is freely accessible https://db.cngb.org/stomics/.
Language: Английский
Citations
58
Cell, Journal Year: 2024, Volume and Issue: 187(17), P. 4488 - 4519
Published: Aug. 1, 2024
Language: Английский
Citations
24
Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 51(15), P. 7798 - 7819
Published: June 23, 2023
Seeds are a vital source of calories for humans and unique stage in the life cycle flowering plants. During seed germination, embryo undergoes major developmental transitions to become seedling. Studying gene expression individual cell types has been challenging due lack spatial information or low throughput existing methods. To overcome these limitations, transcriptomics workflow was developed germinating barley grain. This approach enabled high-throughput analysis expression, revealing specific patterns various functional categories at sub-tissue level. study revealed over 14 000 genes differentially regulated during first 24 h after imbibition. Individual genes, such as aquaporin family, starch degradation, wall modification, transport processes, ribosomal proteins transcription factors, were found have time. Using autocorrelation algorithms, we identified auxin that had increasingly focused within subdomains time, suggesting their role establishing axis. Overall, our provides an unprecedented spatially resolved cellular map germination identifies genomics targets better understand restricted processes germination. The data can be viewed https://spatial.latrobe.edu.au/.
Language: Английский
Citations
25
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
Blood, Journal Year: 2024, Volume and Issue: 143(12), P. 1069 - 1079
Published: Jan. 9, 2024
Language: Английский
Citations
9
The Neuroscientist, Journal Year: 2024, Volume and Issue: unknown
Published: May 17, 2024
The existence of neurogenesis in the adult human hippocampus has been under considerable debate within past three decades due to diverging conclusions originating mostly from immunohistochemistry studies. While some these reports conclude that hippocampal humans occurs throughout physiologic aging, others indicate this phenomenon ends by early childhood. More recently, groups have adopted next-generation sequencing technologies characterize with more acuity extent humans. Here, we review current state research on brain an emphasis challenges and limitations using for its study.
Language: Английский
Citations
9
Wiley Interdisciplinary Reviews - RNA, Journal Year: 2024, Volume and Issue: 15(2)
Published: March 1, 2024
Abstract Spatially resolved transcriptomics has been dramatically transforming biological and medical research in various fields. It enables transcriptome profiling at single‐cell, multi‐cellular, or sub‐cellular resolution, while retaining the information of geometric localizations cells complex tissues. The coupling cell spatial its molecular characteristics generates a novel multi‐modal high‐throughput data source, which poses new challenges for development analytical methods data‐mining. Spatial transcriptomic are often highly complex, noisy, biased, presenting series difficulties, many unresolved, analysis generation insights. In addition, to keep pace with ever‐evolving experimental technologies, existing theories tools need be updated reformed accordingly. this review, we provide an overview discussion current computational approaches mining data. Future directions perspectives methodology design proposed stimulate further discussions advances models algorithms. This article is categorized under: RNA Methods > Analyses Cells Evolution Genomics Computational Export Localization
Language: Английский
Citations
8
Nature Reviews Methods Primers, Journal Year: 2024, Volume and Issue: 4(1)
Published: Aug. 1, 2024
Language: Английский
Citations
8
Small Methods, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 28, 2025
Abstract Accurately defining cell boundaries for spatial transcriptomics is technically challenging. The current major approaches are nuclear staining or mathematical inference, which either exclude the cytoplasm determine a hypothetical boundary. Here, new method introduced boundaries: labeling membranes using genetically coded fluorescent proteins, allows precise indexing of sequencing spots and transcripts within cells on sections. Use this membrane‐based greatly increases number genes captured in compared to nucleus‐based methods; numbers increased by 67% 119% mouse axolotl livers, respectively. obtained expression profiles more consistent with single‐cell RNA‐seq data, demonstrating rational clustering apparent type‐specific markers. Furthermore, improved resolution achieved better identify rare types elaborate domains brain intestine. In addition regular cells, accurate recognition multinucleated lacking nuclei liver achieved, its ability analyze complex tissues organs, not achievable previous methods. This study provides powerful tool improving that has broad potential applications biological medical sciences.
Language: Английский
Citations
1
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