Background: Interest in studying the spatial distribution of gene expression in tissues is rapidly increasing. Spatial Transcriptomics is a novel sequencing-based technology that generates high-throughput information on the distribution, heterogeneity and co-expression of cells in tissues. Unfortunately, manual preparation of high-quality sequencing libraries is time-consuming and subject to technical variability due to human error during manual pipetting, which results in sample swapping and the accidental introduction of batch effects. All these factors complicate the production and interpretation of biological datasets.
Results: We have integrated an Agilent Bravo Automated Liquid Handling Platform into the Spatial Transcriptomics workflow. Compared to the previously reported Magnatrix 8000+ automated protocol, this approach increases the number of samples processed per run, reduces sample preparation time by 35%, and minimizes batch effects between samples. The new approach is also shown to be highly accurate and almost completely free from technical variability between prepared samples.
Conclusions: The new automated Spatial Transcriptomics protocol using the Agilent Bravo Automated Liquid Handling Platform rapidly generates high-quality Spatial Transcriptomics libraries. Given the wide use of the Agilent Bravo Automated Liquid Handling Platform in research laboratories and facilities, this will allow many researchers to quickly create robust Spatial Transcriptomics libraries.
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http://dx.doi.org/10.1186/s12864-020-6631-z | DOI Listing |
Brief Bioinform
November 2024
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, 2 Sipailou, Xuanwu District, Nanjing 210096, China.
Spatial transcriptomics technologies have been extensively applied in biological research, enabling the study of transcriptome while preserving the spatial context of tissues. Paired with spatial transcriptomics data, platforms often provide histology and (or) chromatin images, which capture cellular morphology and chromatin organization. Additionally, single-cell RNA sequencing (scRNA-seq) data from matching tissues often accompany spatial data, offering a transcriptome-wide gene expression profile of individual cells.
View Article and Find Full Text PDFJ Transl Med
January 2025
Division of Spine, Department of Orthopedics, Tongji Hospital affiliated to Tongji University, Tongji University School of Medicine, Shanghai, 200065, China.
Background: Ferroptosis and immune responses are critical pathological events in spinal cord injury (SCI), whereas relative molecular and cellular mechanisms remain unclear.
Methods: Micro-array datasets (GSE45006, GSE69334), RNA sequencing (RNA-seq) dataset (GSE151371), spatial transcriptome datasets (GSE214349, GSE184369), and single cell RNA sequencing (scRNA-seq) datasets (GSE162610, GSE226286) were available from the Gene Expression Omnibus (GEO) database. Through weighted gene co-expression network analysis and differential expression analysis in GSE45006, we identified differentially expressed time- and immune-related genes (DETIRGs) associated with chronic SCI and differentially expressed ferroptosis- and immune-related genes (DEFIRGs), which were validated in GSE151371.
Brief Bioinform
November 2024
Cancer Institute, Suzhou Medical College, Soochow University, NO. 199 Ren-ai Road, SIP, Suzhou 215000, China.
Alternative polyadenylation (APA) is an important driver of transcriptome diversity that generates messenger RNA isoforms with distinct 3' ends. The rapid development of single-cell and spatial transcriptomic technologies opened up new opportunities for exploring APA data to discover hidden cell subpopulations invisible in conventional gene expression analysis. However, conventional gene-level analysis tools are not fully applicable to APA data, and commonly used unsupervised dimensionality reduction methods often disregard experimentally derived annotations such as cell type identities.
View Article and Find Full Text PDFDev Cell
January 2025
Program in Epithelial Biology and Center for Definitive and Curative Medicine, Stanford University, Stanford, CA, USA. Electronic address:
Human pluripotent stem cell-derived tissue engineering offers great promise for designer cell-based personalized therapeutics, but harnessing such potential requires a deeper understanding of tissue-level interactions. We previously developed a cell replacement manufacturing method for ectoderm-derived skin epithelium. However, it remains challenging to manufacture the endoderm-derived esophageal epithelium despite possessing a similar stratified epithelial structure.
View Article and Find Full Text PDFCancers (Basel)
December 2024
Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis School of Medicine, University of California Davis Comprehensive Cancer Center, Sacramento, CA 95817, USA.
Patient-centered precision oncology strives to deliver individualized cancer care. In lung cancer, preclinical models and technological innovations have become critical in advancing this approach. Preclinical models enable deeper insights into tumor biology and enhance the selection of appropriate systemic therapies across chemotherapy, targeted therapies, immunotherapies, antibody-drug conjugates, and emerging investigational treatments.
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