Spatial transcriptome of FFPE sample by DBiT-seq
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ABSTRACT:
PROVIDER: PRJNA659282 | ENA |
REPOSITORIES: ENA
Similar Datasets
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: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: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
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 | GSE93336 | GEO
Project description:We present spatially resolved high-spatial-resolution genome-wide co-mapping of epigenome and transcriptome by simultaneously profiling of chromatin accessibility and gene expression (spatial-ATAC-RNA-seq), as well as histone modification and gene expression (spatial-CUT&Tag-RNA-seq) on the same tissue section at cellular level by combining the microfluidic deterministic barcoding strategy in DBiT-seq and the chemistry used in ATAC-seq/CUT&Tag.
2023-01-29 | GSE205054 | GEO
Project description:We present spatially resolved high-spatial-resolution genome-wide co-mapping of epigenome and transcriptome by simultaneously profiling of chromatin accessibility and gene expression (spatial-ATAC-RNA-seq), as well as histone modification and gene expression (spatial-CUT&Tag-RNA-seq) on the same tissue section at cellular level by combining the microfluidic deterministic barcoding strategy in DBiT-seq and the chemistry used in ATAC-seq/CUT&Tag.
2023-01-29 | GSE205052 | GEO
Project description:We present spatially resolved high-spatial-resolution genome-wide co-mapping of epigenome and transcriptome by simultaneously profiling of chromatin accessibility and gene expression (spatial-ATAC-RNA-seq), as well as histone modification and gene expression (spatial-CUT&Tag-RNA-seq) on the same tissue section at cellular level by combining the microfluidic deterministic barcoding strategy in DBiT-seq and the chemistry used in ATAC-seq/CUT&Tag.
2023-01-29 | GSE217091 | GEO
Project description:Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories as a cost-effective means of preserving invaluable specimens for subsequent study, including for clinical proteomics in translational medicine. With the rapid growth of spatial proteomics, FFPE tissue samples can serve as a more accessible alternative to commonly used fresh frozen tissues. However, extracting proteins from FFPE tissue for analysis by mass spectrometry has been challenging due to crosslinks formed between proteins and formalin, particularly when studying limited samples. We have previously demonstrated that nanoPOTS (Nanodroplet Processing in One Pot for Trace Samples) is an enabling technology for high-resolution and in-depth spatial and single-cell proteomics measurements, but only fresh frozen tissues had been previously analyzed. Here we have adapted the nanoPOTS sample processing workflows for proteome profiling of 10-µm-thick FFPE tissues with lateral dimensions as small as 50 µm. Following a comparison of extraction solvents, times, and temperatures, and under the most favorable conditions, we respectively identified an average of 1180 and 2990 proteins from FFPE preserved mouse liver tissues having dimensions of 50 µm and 200 µm. This was on average 87% of the coverage achieved for fresh frozen mouse liver samples analyzed with the same general procedure. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. These workflows provide the greatest depth of coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues.
2022-08-02 | PXD029729 | Pride