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Whole Transcriptome Sequencing

What is Whole Transcriptome Sequencing?

Novogene’s Whole Transcriptome Sequencing service equips the researcher with cutting-edge NGS solutions that provide in-depth bioinformatic analysis on all transcripts including mRNAs and non-coding RNAs. This competitive approach investigates and explores potential transcriptional and regulatory network mechanisms, while providing key insights into interaction and intersection functionality from a comprehensive transcriptomic perspective.

Service Specifications

Whole Transcriptome Sequencing finds its applications in:

  • Profiling mRNA and ncRNA in a single run
  • Exploring miRNA sponge and target regulatory elements
  • Investigating regulatory networks among lncRNA/circRNA-miRNA-gene pairs

Benefits of Whole Transcriptome Sequencing

  • Whole Transcriptome Sequencing provides a more comprehensive analysis of transcriptional regulation network, compared to mRNA-seq, lncRNA-seq, sRNA-seq, and circRNA-seq, respectively.
  • Whole transcriptome sequencing help researchers in identifying biomarkers across a wide transcript range.
  • WTS allows the capture of both known and new features
  • It enables the whole transcriptome profiling across a broad dynamic scale

Sample Requirements

Library Type Sample Type Amount RNA Integrity Number
(Agilent 2100)
Purity
(NanoPore)
lncRNA Library & small RNA Library Total RNA ≥ 3 μg Animal ≥ 7.5, Plant ≥ 7, with smooth baseline OD260/280 = 1.8-2.2;
OD260/230 ≥ 1.8;
lncRNA library & small RNA library & circRNA library ≥ 5 μg

Sequencing Parameter and Analysis

Platform Illumina Novaseq 6000
Read length Paired-end 150bp for lncRNA/circRNA library
Single-end 50bp for small RNA library
Recommended Data Amount ≥ 40 million read pair per sample (lncRNA library);
≥ 20 million read pair per sample (small RNA library);
Content of Data Analysis
  • Individual ncRNA analysis package
  • Network analysis between lncRNA vs miRNA, mRNA vs miRNA, circRNA vs miRNA, lncRNA-miRNA-mRNA, and circRNA-miRNA-mRNA

Note: For detailed information, please refer to the Service Specifications and contact us for customized requests.

Project Workflow

The first step of the project workflow includes the sample quality control (Sample QC) to ensure that your samples meet the criteria of the RNA-Seq technique. Then, the appropriate library is prepared according to your target organism and subsequently tested for its quality (Library QC). Next, a paired-end 150 bp sequencing strategy is used to sequence the lncRNA and circRNA library and single-end 50bp is used to sequence the small RNA library. The resulting data go through quality data control (Data QC) to guarantee the quality of the resulting data. Finally, bioinformatic analyses are performed and publication-ready results are provided. The following flowsheet describes the step-by-step protocol.

Sampling:

Total RNA was extracted from the spinal cord dorsal horn tissue

Sequencing Strategy:

1. lncRNA library: NEBNext UltraTM Directional RNA Library Prep Kit for Illumina
2. small RNA library: NEBNext Multiplex Small RNA Library Prep Set for Illumina
3. sequenced on Illumina HiSeq 2500 platform, 125 bp paired-end and 50-bp single-end reads, respectively.

Figure 1. The expression profiling changes of lncRNAs in spinal cord of SNI rats Vocalno Plot indicate up and down regulated lncRNAs of rats in group SNI compared with group CON (A)

Figure 2. The expression profiling changes of circRNAs in spinal cord of SNI rats Vocalno Plot indicate up and down regulated circRNAs of rats in group SNI compared with group CON (A)

Figure 3. The expression profiling changes of miRNAs in spinal cord of SNI rats Vocalno Plot indicate up and down regulated miRNAs of rats in group SNI compared with group CON (A)

Figure 4. The expression profiling changes of mRNAs in spinal cord of SNI rats Vocalno Plot indicate up and down regulated mRNAs of rats in group SNI compared with group CON (A)

Figure 5. Counts of relatived ncRNAs and mRNAs in spinal cord of SNI rats.

Figure 6. lncRNA-micRNA-mRNAs regulatory network analysis of ncRNAs in spinal cord of SNI rats.

Figure 7. cirRNA-micRNA-mRNAs regulatory network analysis of ncRNAs in spinal cord of SNI rats.
Conclusion:

This study comprehensively identifies regulated ncRNAs of the spinal cord and to demonstrate the involvement of different ncRNA expression patterns in the spinal cord of NP pathogenesis by sequence analysis. This information will enable further research on the pathogenesis of NP and facilitate the development of novel NP therapeutics targeting ncRNAs.


Correlation analysis of circRNA and miRNA and mRNA

The circRNA-miRNA-gene triplets in which circRNA, miRNA, and genes are all differentially expressed were selected, and their numbers were counted in each comparison.

Figure 1 circRNA-miRNA-gene counting and networks

Note:
The histogram graph shows the number of differentially expressed genes, circRNA, miRNA in lncRNA-miRNA-gene triplets in each comparison


circRNA harbors miRNA

binding sites and acts as a molecular sponge for a miRNA to competitively keep miRNA from suppressing its downstream target genes of the corresponding miRNA family. Based on the competitive endogenous RNA (ceRNA) hypothesis, we filter out circRNA and genes targeted by the same miRNA and construct ceRNA regulation networks to reveal the expression regulation mechanisms of circRNA at the whole transcriptome level.

Figure 2 Interaction network of circRNA-miRNA-gene

Note:
In the figure, different shapes represent different RNA types, and different colors represent the up-and down-regulation of


the RNA genes

The size of a node is proportional to its degree. If more lines are connected to a node, its degree will be greater, and correspondingly the size will also be larger. These nodes are more likely to be in a core position in the network.

*Please contact us to get the full demo report.