Spatial transcriptome of FFPE sample by DBiT-seq
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ABSTRACT:
PROVIDER: PRJNA659282 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12515582_1.fastq.gz | Fastqsanger.gz | |||
| SRR12515582_2.fastq.gz | Fastqsanger.gz | |||
| SRR12515583_1.fastq.gz | Fastqsanger.gz | |||
| SRR12515583_2.fastq.gz | Fastqsanger.gz | |||
| SRR12515584_1.fastq.gz | Fastqsanger.gz |
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Project description:Spatial transcriptome of FFPE sample by DBiT-seq
| PRJNA659282 | ENA
Project description:Here, we show that DBiT-seq (Deterministic barcoding in tissue) can be applied to FFPE samples, providing quality transcriptome information. We first studied the E10.5 mouse embryo tissue section with a 25 µm pixel size chip and identified all the major anatomical structures. Then, we analyzed the three major components of mouse heart and circulatory system: aorta, atrium, and ventricle. Results show that major cell types in all above tissue types can be identified after integration with published scRNA-seq reference data.
2020-10-30 | GSE156862 | GEO
Project description:FFPE tissue samples have long been considered challenging for sc-/sn-RNA sequencing assays. In this study, we developed a novel snRNA-seq workflow, snPATHO-seq, for FFPE tissue samples utilising isolated high-quality nuclei from FFPE samples and 10X Genomics FLEX chemistry. The snPATHO-seq demonstrated consistent performance with the established 10X Genomics 3' assay. In addition, it allows more accurate single-nucleus and spatial transcriptomics integration with the FFPE Visium dataset generated from the same FFPE block. We envision this new protocol can facilitate the transcriptomic interpretation of millions of FFPE archives generated and simplify the sample collection process and data generation.
2024-10-01 | GSE268426 | GEO
Project description:FFPE tissue samples have long been considered challenging for sc-/sn-RNA sequencing assays. In this study, we developed a novel snRNA-seq workflow, snPATHO-seq, for FFPE tissue samples utilising isolated high-quality nuclei from FFPE samples and 10X Genomics FLEX chemistry. The snPATHO-seq demonstrated consistent performance with the established 10X Genomics 3' assay. In addition, it allows more accurate single-nucleus and spatial transcriptomics integration with the FFPE Visium dataset generated from the same FFPE block. We envision this new protocol can facilitate the transcriptomic interpretation of millions of FFPE archives generated and simplify the sample collection process and data generation.
2024-10-01 | GSE268427 | GEO
Project description:Spatial transcriptomics facilitates the understanding of gene expression within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics’ Visium which provides whole tissue section profiling, enabling whole transcriptome spatial analysis. Our dataset comprises spleen tissue from mice infected with malaria, spanning multiple experiments and sample preparation protocols for tissue preservation, either as fresh frozen at optimal cutting temperature (OCT) or formalin-fixed paraffin-embedded (FFPE). Tissue placement was also considered, comparing direct tissue placement on the slide with the use of CytAssist (CA), which expands the Visium platform’s capabilities by allowing for the pre-selection of tissue sections and genes through a set of probes. We also include a matching scRNA-seq dataset that can be integrated with the spatial data.
2024-02-26 | GSE254652 | GEO
Project description:Current spatial transcriptomic methods have been widely used to resolve gene expression; however, these methods are limited to fresh or fresh-frozen samples due to unsuccess of oligo(dT) primers in degraded RNA samples. Here we develop a spatial random-sequencing (spRandom-seq) technology for Formalin-fixed paraffin-embedded (FFPE) tissues by capturing full-length total RNAs with random primers. This approach provides a powerful spatial platform for clinical FFPE specimens and promises enormous applications in biomedicine.
2023-12-31 | GSE247881 | GEO
Project description:Expression profiling in spatially defined regions is crucial for systematically understanding tissue complexity. Here, we report a method of photo-irradiation for in-situ barcoding hybridization and ligation sequencing, named PBHL-seq, which allows targeted expression profiling from the photo-irradiated region of interest in intact fresh frozen and FFPE tissue samples. PBHL-seq uses photo-caged oligodeoxynucleotides for in situ reverse transcription followed by spatially targeted barcoding of cDNAs to create spatially indexed transcriptomes of photo-illuminated regions. We recover thousands of differentially enriched transcripts from different regions by applying PBHL-seq to OCT-embedded tissue (E14.5 mouse embryo and mouse brain) and FFPE mouse embryo (E15.5). We also apply PBHL-seq to the subcellular microstructures (cytoplasm and nucleus, respectively) and detect thousands of differential expression genes. Thus, PBHL-seq provides an accessible workflow for expression profiles from the region of interest in frozen and FFPE tissue at subcellular resolution with areas expandable to centimeter scale, while preserving the sample intact for downstream analysis.
2024-06-30 | GSE268148 | GEO
Project description:The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.
2018-09-05 | GSE93337 | GEO