Spatial Transcriptome Sequencing

Neither routine single-cell RNA sequencing nor tissue sample RNA sequencing can provide researchers with precise spatial information. The spatial transcriptome is a technology that analyzes RNA-Seq data at the spatial level to analyze all mRNA in a single tissue section and obtain transcription information at specific locations in the tissue, providing effective data support for research and diagnosis.

CD Genomics can help you generate all transcriptome data from complete tissue samples, so that you can locate and distinguish the active expression of functional genes in specific tissue regions, provide valuable insights for research and diagnosis, and allow scientists to detect gene expression of tissue samples. All gene activity, and map where the activity occurred. The technology has brought new discoveries that will help scientists better understand diseases and biological processes.

Overview

The workflow of spatial transcriptome sequencing is mainly divided into two parts: the histology part and the omics part. The histology part includes sample embedding, slicing, fixation, staining and imaging, and records the morphological information of the slice; the omics part includes cDNA synthesis, amplification, adaptor ligation and sequencing, and records the transcript information and spatial location information of the section. Using 10X Genomics spatial transcriptome sequencing technology, each slide used for library construction has four capture areas, where each capture area contains 5000 barcoded spots and each spot has a unique barcode sequence. The cells in the tissue section will release mRNA, and the mRNA that migrates to each spot will be marked with the corresponding barcode sequence, and then the library will be constructed and sequenced. Finally, analyze the data according to the barcode information of the data to determine which data comes from which location, so as to realize the visualization of spatial gene expression.

Features

Flexibility One-stop Service High Quality Data Analysis
Applicable to most tissue types, verified tissues include brain, tumor, kidney, skin, heart, etc. From tissue sectioning to library construction, to sequencing, and to data analysis. Rich experience in library construction and short-read NGS guarantee high quality. Data preprocessing, basic analysis, advanced analysis, and customized analysis.

Project Workflow

Sample Preparation

1. Sample Preparation

Tissue section; RNA purification; quality assessment and quantification

Library Preparation

2. Library Preparation

Ribosomal RNA Removal
250~300 bp Insert cDNA Library

Next-generation Sequencing

3. Sequencing

Illumina Novaseq, PE 150
≥ 80 million read pair per sample

Advanced Data Analysis

4. Data Analysis

Visualize and preprocess results, and perform custom bioinformatics analysis.

Spatial Transcriptome Sequencing

Bioinformatics Analysis Pipeline

In-depth data analysis:

  • Transcript assembly
  • Transcript expression profiling and differential expression
  • Manifold embedding and clustering based on transcriptional similarity
  • Composition and spatial architecture of transcriptome
  • Gene Identification: highlight expression of a specific gene with the spots from an individual cluster
  • Data visualization includes spatial Image and t-SNE
  • Statistical analysis of spatial expression patterns

Sample Requirements: Complete tissue section samples. Correct tissue processing and preparation can maintain the morphological quality of tissue sections and the integrity of mRNA transcription.

Sample storage: The prepared tissue section samples can be stored at -80°C for one week, and each slide is stored separately in a sealed container.

Shipping Method: When shipping histological samples, the sample should be stored in a sealed container. Shipments are generally recommended to contain 5-10 pounds of dry ice per 24 hours.

Deliverable: raw data as BAM files, coverage summary, QC report, custom bioinformatics analyses.

References:

  1. Liu Y, Enninful A, Deng Y, Fan R. Spatial transcriptome sequencing of FFPE tissues at the cellular level. bioRxiv. 2020;1.
  2. Liu S, Trapnell C. Single-cell transcriptome sequencing: recent advances and remaining challenges. F1000Research. 2016;5.
* For Research Use Only. Not for use in diagnostic procedures.


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