High-density spatial transcriptomics arrays for in situ tissue profiling
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ABSTRACT:
PROVIDER: PRJNA540976 | ENA |
REPOSITORIES: ENA
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Project description:Tissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures molecular profiles but not spatial organization. Conversely, spatial profiling assays to date have lacked global transcriptome information, throughput or single-cell resolution. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-Seq at high spatial resolution. Spatially barcoded reverse transcription oligonucleotides are coupled to beads that are randomly deposited into tightly packed individual microsized wells on a slide. The position of each bead is decoded with sequential hybridization using complementary oligonucleotides providing a unique bead-specific spatial address. We then capture, and spatially in situ barcode, RNA from the histological tissue sections placed on the HDST array. HDST recovers hundreds of thousands of transcript-coupled spatial barcodes per experiment at 2 μm resolution. We demonstrate HDST in the mouse brain, use it to resolve spatial expression patterns and cell types, and show how to combine it with histological stains to relate expression patterns to tissue architecture and anatomy. HDST opens the way to spatial analysis of tissues at high resolution.
2019-09-09 | GSE130682 | GEO
Project description:Spatial Transcriptomics and In Situ Sequencing to Study Alzheimer’s Disease
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Project description:While complex inflammatory-like alterations are observed around the amyloid plaques of Alzheimer disease (AD), little is known about the molecular changes and cellular interactions that characterize this response. We investigate here in an AD mouse model the transcriptional changes occurring in tissue domains of 100 μm diameter around the amyloid plaques using spatial transcriptomics. We demonstrate early alterations in a gene co-expression network enriched for myelin and oligodendrocyte genes (OLIG), while a multicellular gene co- expression network of Plaque-Induced Genes (PIGs) involving the complement system, oxidative stress, lysosomes and inflammation is prominent in the later phase of the disease. We confirm the majority of the observed alterations at the cellular level using in situ sequencing on mouse and human brain sections. Genome-wide spatial transcriptomic analysis provides an unprecedented approach to untangle the dysregulated cellular network in the vicinity of pathogenic hallmarks of AD and other brain diseases.
2020-07-22 | GSE152506 | GEO
Project description:Identification of cell types in the interphase between muscle and tendon by Visium Spatial Transcriptomics of four human semitendinous muscle-tendon biopsies. Cell types identified by single nuclei RNA seq on similar tissue were localized in situ with the use of Spatial Transcriptomics.
2023-03-02 | E-MTAB-12530 | biostudies-arrayexpress
Project description:The integration of genomic and epigenomic data is becoming increasingly popular as we try to gain better understanding of the complex mechanisms driving the development and progression of cancer. However, this results in increased cost and sample depletion, the latter being particularly important when considering intra-tumour heterogeneity. We therefore sought to investigate the possible utility of high-density DNA methylation arrays to assess both aberrant methylation as well as changes in gene copy number. Comparing CN (Copy Number) data derived from the Infinium Human Methylation 450K arrays with that generated on SNP arrays, we demonstrate the utility of the Infinium arrays to detect single copy alterations as well as homozygous deletions and high level amplification with the reliability of current gold standard platforms. Furthermore, we show that the gene centric design of the Infinium methylation arrays allows identification of small single gene alterations, which would not be detected using standard SNP array analysis. These results show that Infinium 450K methylation arrays provide a robust and economic platform for detecting copy number and methylation changes in a single experiment. The ability to integrate such data from the same sample is critical for cancer research and will improve our understanding of how complex genomic and epigenomic interactions are driving the development and progression of a malignant phenotype.
2016-05-31 | GSE48941 | GEO
Project description:Global comparisons of gene expression profiles between species provide significant insight into gene regulation, evolutionary processes, and disease mechanisms. In this work, we describe a flexible and intuitive approach for global expression profiling of closely related species, using high-density exon arrays designed for a single reference genome. The high-density probe coverage of exon arrays allows us to select the identical set of perfect-match probes for measuring expression levels of orthologous genes. This eliminates a serious confounding factor in probe affinity effects of species-specific microarray probes, and enables direct comparisons of estimated expression indexes across species. Keywords: analysis of gene expression in tissues
2009-05-05 | GSE15665 | GEO
Project description:We applied Illumina’s 317K high-density SNP-arrays to profile chromosomal aberrations in clear cell renal cell carcinoma (ccRCC) from 80 patients and analyzed the association of LOH/amplification events with clinicopathological characteristics
2009-05-09 | GSE16019 | GEO
Project description:Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.
2024-02-22 | GSE256319 | GEO
Project description:Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.
2024-02-22 | GSE256318 | GEO
Project description:Global comparisons of gene expression profiles between species provide significant insight into gene regulation, evolutionary processes, and disease mechanisms. In this work, we describe a flexible and intuitive approach for global expression profiling of closely related species, using high-density exon arrays designed for a single reference genome. The high-density probe coverage of exon arrays allows us to select the identical set of perfect-match probes for measuring expression levels of orthologous genes. This eliminates a serious confounding factor in probe affinity effects of species-specific microarray probes, and enables direct comparisons of estimated expression indexes across species. Keywords: analysis of gene expression in tissues
2009-05-05 | GSE15626 | GEO