Sequence-based Transcript Analysis Service

Achieve Precision in Glycoprotein Research with CD BioGlyco's Advanced Sequence-based Glyco-Transcriptomics Analysis Services

Using advanced single-molecule sequencing technologies, such as Pacific Biosciences and Oxford Nanopore sequencing, CD BioGlyco provides the sequence-based transcript analysis service and other Glyco-transcriptomics Transcript Analysis Services. Our service delivers accurate and comprehensive annotation of glycoprotein and glycan-related transcript sequences. This service identifies transcription start and end sites (TSS and TES), alternative splicing (AS), and alternative polyadenylation (APA), offering detailed insights into glycosylation processes and glycan-related gene expression and regulation. By eliminating common sequencing errors and mapping inaccuracies, this approach improves the accuracy of glycoprotein transcript quantitation and all subsequent analysis steps, enabling an array of glycoinformatics research applications, such as identifying glycan responses to various environmental conditions and enhancing glycome annotations. Moreover, clients can search out our Glycoinformatics-assisted Glycan-related Transcriptomics Analysis Service for more services and information.

Fig.1 The transcription initiation complex structure.Fig.1 Schematic of the transcription initiation complex structure. (Basu, et al., 2014)

The workflow of our sequence-based transcript analysis service is given a detailed and sophisticated structure. We start with biological samples containing glycoproteins or antibody transcripts. We follow the extraction with standardized RNA isolation protocols to ensure purity and integrity. In the library preparation, isolated RNA is reverse transcribed by using the enzymes of reverse transcriptase and subsequently amplified to generate enough material for sequencing.

The process of data processing typically involves base calling transformation from raw sequencing data to nucleotide sequences, and quality control/filtering. Following assembly, transcripts are annotated and analyzed, including mapping to reference genomes or known glycoprotein databases, quantification of AS events, and detection of APA sites that can serve as regulatory mechanisms.

The next stage, interpretation, and validation, focuses on elucidating the biological significance of the identified transcripts and their variations. Finally, the reporting phase includes compiling the results into comprehensive reports that feature detailed annotations and visualizations. If you would like a more comprehensive analysis of your projects, please go to our Glycomics Analysis Service Section for more choices!

The workflow of our sequence-based transcript analysis. (CD BioGlyco)

Publication

DOI: 10.1371/journal.ppat.1002342

Technology: RNA sequencing, sRNAs, Non-coding RNAs

Journal: PLoS pathogens

Published: 2011

IF: 5.5

Results: In this study, the whole transcriptome of Mycobacterium tuberculosis was analyzed using RNA sequencing, and a large number of non-coding RNAs were found, including long non-coding regions, antisense transcripts, and spacer RNAs (sRNAs). Non-coding RNAs accounted for more than a quarter of the total transcriptome, and the density of reads in non-coding regions was more than twice as high as in coding regions. Some of the sRNAs were more abundant in stationary phase cultures and accumulated to very high levels in the lungs of chronically infected mice, suggesting that they may play a role in pathogenicity. The results suggest that non-coding RNAs may be involved in the adaptation of Mycobacterium tuberculosis to the changing environment within the host and may play an important role in its pathogenicity and drug resistance.

Applications

  • The sequence-based transcript analysis can be used to identify differentially expressed genes (DEGs) and mutations in cancerous tissues compared to normal tissues, aiding in the discovery of biomarkers and targets.
  • The sequence-based transcript analysis can be used to analyze gene expression profiles associated with genetic disorders to understand disease mechanisms and identify potential interventions.
  • It is used to identify novel drug targets by analyzing gene expression changes in disease versus healthy states.
  • This technology can be used to study transcriptomic changes in plants under various conditions to identify genes involved in stress responses, disease resistance, and yield improvement.

Advantages

  • Sequence-based transcript analysis can detect and quantify a wide range of RNA species, including mRNA, non-coding RNA, and microRNA, providing a comprehensive view of the transcriptome.
  • We provide precise quantification of gene expression levels, enabling accurate comparisons between different samples or conditions.
  • Our experts integrate transcriptomic data with other omics data (e.g., genomics, proteomics, metabolomics) to gain a holistic understanding of biological systems.

Frequently Asked Questions (FAQs)

  • What is sequence-based transcript analysis can offer?
    • This service offers an unbiased view of differential gene expression to detect and quantify hundreds to thousands of RNA species, including mRNA, non-coding, and microRNA.
  • What types of samples can be analyzed?
    • The samples we can analyze are as diverse as human, animal, plant, and microbial tissues/cells. The samples can be either fresh, frozen, or stabilized in RNA stabilization reagents.

By the advantages of sequence-based transcript analysis, CD BioGlyco provides researchers with powerful tools to explore gene expression landscapes, uncover molecular mechanisms, and drive innovation across various fields of study. Please do not hesitate to contact us for more information if you are interested in our services.

References

  1. Basu, R.S.; et al. Structural basis of transcription initiation by bacterial RNA polymerase holoenzyme. The Journal of Biological Chemistry. 2014, 289(35): 24549-59.
  2. Arnvig, K.B.; et al. Sequence-based analysis uncovers an abundance of non-coding RNA in the total transcriptome of Mycobacterium tuberculosis. PLoS pathogens. 2011, 7(11):e1002342.
For research use only. Not intended for any diagnostic use.
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