RNA-Seq-based Glycogene Expression Profiling

RNA-Seq-based Glycogene Expression Profiling

The Principle of RNA sequencing (RNA-seq)

RNA-seq technology enables scientists to gain insight into the cell's transcriptome from a holistic perspective, explain disease states that were previously undiscovered, reveal responses to therapeutics, and explore changes in organisms under different environments. The working process of RNA-seq includes extracting all transcripts from the sample, segmenting the purified messenger RNA (mRNA), reversely transcribing mRNA into complementary DNA (cDNA), performing polymerase chain reaction (PCR) amplification and sequencing on the constructed cDNA library, obtaining the transcriptome data, and examining gene differential expression.

RNA-seq quickly completes sequencing with large scale, high accuracy, and greatly reduced cost compared with first-generation sequencing technology. It has high resolution, little background interference, and high sensitivity to low-expression genes. In addition, it enables the identification of transcripts undiscovered previously, disclosure of alternative splicing genes, and detection of allele-specific expression.

Fig.1 A typical RNA-seq workflow. (Wang, et al., 2009)Fig.1 A typical RNA-seq workflow. (Wang, et al., 2009)

RNA-seq-based Glycogene Expression Profiling at CD BioGlyco

CD BioGlyco provides you with powerful RNA-seq solutions that help you save time and effort while leading discoveries in transcriptomics and glycogene expression. Single-cell RNA-seq is used to detect mRNA levels in single cells, which provides an important technical means for the global pattern analysis of changes in gene expression. You apply the single-cell RNA-seq service in any field.

Fig.2 Some applications of RNA-seq technology. (CD BioGlyco)Fig.2 Some applications of RNA-seq technology. (CD BioGlyco)

  • Cancer research: RNA-seq provides new ideas for the study of tumor heterogeneity and cell subpopulation, tumor metastasis, tumor microenvironment, tumor resistance mechanism, and anti-tumor therapy development.
  • Microorganism research: RNA-seq is commonly used to discover disease-associated microbes, analyze the composition of microbial communities in specific environments, monitor microbial infections, and understand symbiotic interactions between bacteria and insects.
  • Virus research: RNAseq is used to detect the dynamic changes of viral infection, deeply understand the complex interaction between viruses and cells, and reveal the mechanism of viral infection to develop antiviral targets.
  • Immunology research: RNA-seq is a powerful tool for revealing the heterogeneity of immune cells, immune responses, and immune tolerance. It is used to discover novel cellular markers, identify immune cell subtypes, discover potential functions of immune cells, and reveal immunological differences between individuals.

Glycogenes play an indispensable role in organisms, especially in the malignant progression and molecular typing of cancer. Our RNA-seq-based glycogene expression profiling helps you quickly and efficiently obtain the differential expression of glycogenes at a low cost and supports your in-depth research in any field.

Applications

  • RNA-seq in cancer cells
  • RNA-seq in microorganisms
  • Study of RNA biomarkers related to drug response
  • Discovering new transcripts and alternative splicing genes

Highlights

  • Higher coverage and greater resolution for the dynamic nature of the transcriptome
  • Sensitive and accurate measurement of gene expression
  • Capturing known or unknown gene expression sequences
  • Generating quantitative or qualitative data based on specific customer needs
  • Applying with any species detection with no need for a reference sequence

At CD BioGlyco, we aim to apply innovative techniques to Glycogenomic Analysis. As a world-renowned biotechnology company, we are committed to supporting your scientific research with the best possible service. If you are interested in our services, please contact us for more detailed information.

Reference

  1. Wang, H.; et al. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics. 2009, 10: 57-63.
This service is for Research Use Only, not intended for any clinical use.

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