Whole transcriptome sequencing
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Technical Information
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Long non-coding RNA (lncRNA) is longer than 200 nucleotides in length. Although lncRNAs do not encode proteins, these RNA sequences are important for epigenetic inheritance, transcription, post-transcription, and other multi-level regulatory processes. In addition to mRNA and microRNA, lncRNA is a major hotspot in functional genomics research. BGI’s whole transcriptome sequencing enables researchers to simultaneously obtain information on mRNAs and lncRNAs. Our approach not only quantifies the amounts of lncRNAs and mRNAs, but also predicts the identities of the novel lncRNAs and mRNAs present in research materials.

Benefits:

  1. High correlation between mRNA expression and technical reproducibility (Pearson value ≥ 0.993)
  2. Access to almost all lncRNA and mRNA information in a single sequencing run
  3. Both known and novel lncRNAs can be analyzed
  4. Applied to all eukaryotic species (lncRNA-seq for species other than human and mouse can be customized)

RNA-seq Analysis of Prostate Cancer in the Chinese Population Identifies Recurrent Gene Fusions, Cancer-associated Long Non-coding RNAs and Aberrant Alternative Splicings. Cell research. 22:806-821 (2012).

There are remarkable disparities among patients of different races with prostate cancer; however, the mechanism underlying this difference remains unclear. Here, we present a comprehensive landscape of the transcriptome profiles of 14 primary prostate cancers and their paired normal counterparts from the Chinese population using RNA-seq, revealing tremendous diversity across prostate cancer transcriptomes with respect to gene fusions, long noncoding RNAs (long ncRNA), alternative splicing and somatic mutations.Further systematic transcriptional profiling identified numerous long ncRNAs that were differentially expressed in the tumors. An analysis of the correlation between expression of long ncRNA and genes suggested that long ncRNAs may have functions beyond transcriptional regulation.

Bioinformatics:

The bioinformatics analyses on mRNA are the same as RNA-Seq(transcriptome). Here we mainly list the analyses on lncRNA.

Standard Bioinformatics Analysis

  1. Data filtering and statistics
    1. Removal of adapters, contaminated reads and low quality reads from raw reads
    2. Removal of the remaining rRNA reads by alignment/mapping to rRNA database
  2. LncRNA identification
    1. Transcripts assembly
    2. Identification of known (including known lncRNA) and novel transcripts
    3. Prediction of novel lncRNA
  3. Quantification and differential expression analysis
    1. Quantification and differential expression analysis of lncRNA (at least 2 samples)
    2. Group differentially expressed lncRNA screening (two or more groups (three or more samples in each group) should be provided)
    3. Expression pattern analysis of lncRNA
  4. LncRNA function prediction
    1. Interaction analysis of complementary lncRNA-mRNA
    2. Investigation of up- and downstream lncRNA for genes of interest
    3. Pre-miRNA prediction
  5. LncRNA family prediction and classification

Customized Bioinformatics Analysis

  1. Coding-non-coding (CNC) co-expression annotation (at least 5 pairs of case and control samples)
  2. Pathway enrichment analysis

We can also perform other customized analyses to meet the requirements of specific projects.

Sample Requirements:

  1. Sample condition:Integrated total RNA samples (no mRNA isolation). Avoid protein contamination during RNA isolation.
  2. Sample quantity (for library construction once): total RNA ≥ 5 μg
  3. Sample concentration: ≥ 300 ng/μL
  4. Sample purity: for eukaryotes, except insects RIN ≥ 7.0, 28S:18S ≥ 1.0

Turnaround time:

The standard turnaround time for the workflow (above) is 50 business days.

Completion indicator:

Completion is indicated by the number of clean reads. Goals are individualized for each project.

Technologies

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