RNA-Seq (Transcriptome)
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RNA-Seq (Transcriptome) is used for transcriptome quantification and structural analysis. The transcriptome analysis lays the foundation for gene structure and function research. RNA-Seq delivers unbiased transcriptome information for basic and medical research, pharmacogenomics research, and drug discovery and development.

Benefits:

  1. BGI’s extensive bioinformatics analysis expertise for RNA-Seq data
  2. Breadth of BGI’s experience in sequencing diverse species (de novo and with reference genome)
  3. BGI’s rapid turnaround time leads to faster publication and reduced R&D cost
  4. RNA-Seq, unlike microarrays, does not require prior knowledge of the genome and therefore offers the following advantages:
    1. Discover novel transcripts
    2. Identify alternative splicing
    3. Study transcriptome polymorphisms
    4. Examine gene fusion events

Customer Testimonials:

"As the principal investigator on two sequencing projects that are pushing the state-of-the-art (viral discovery using metagenomic sequencing and phylogenomic analysis of 1000 plant species) I cannot expect everything to work on the first iteration but I do expect my sequencing provider to work together with me to correct whatever went wrong regardless of whose fault it was. BGI-Shenzhen does that admirably." Dr. Gane Ka-Shu Wong, Professor and iCORE Chair in Biosystems Informatics Department of Biological Sciences - University of Alberta

The 1000 Plants de novo Transcriptomes Project

The 1000 plants de novo Transcriptomes Project plans to use new generation technology to de novo sequence and assemble the transcripts of 1,000 plants. This is an initiative project funded by the government of Alberta. BGI is one of the major participants of the 1000 Plants Initiative. BGI initially seeks to increase the number of plant species for which transcript sequence information is publicly available and to learn about their biology and evolutionary history. In later phases, the initiative might focus on commercial applications of the results. Fewer than 100 plant genomes have been characterized by sequencing so far, even at the EST level, judged by data submitted to GenBank. This project will greatly expand the knowledge of plant biodiversity.

Deep RNA Sequencing at Single Base-Pair Resolution Reveals High Complexity of the Rice Transcriptome. Genome Research 2010:646-654.

Deep RNA

RNA sequencing enabled the detection of transcripts expressed at an extremely low level. The results suggest that transcriptional regulation in rice is vastly more complex than previously believed.

Bioinformatics:

BGI Tech provides two types of bioinformatics analyses: de novo and transcriptome resequencing.

De novo Transcriptome Assembly

  1. Data filtering includes removing adaptors, contamination and low-quality reads from raw reads
  2. Statistical analysis and evaluation of data
  3. Assembly results
  4. Unigene function annotation
  5. Unigene GO classification
  6. Unigene differential expression analysis
  7. Protein coding region prediction (CDS)
  8. GO classification
  9. Pathway enrichment analysis

Transcriptome Resequencing

  1. Data filtering includes removing adaptors, contamination and low-quality reads from raw reads
  2. Assessment of Sequencing
  3. Differential gene expression analysis
  4. Refinement of gene structures (Eukaryotes only)
  5. Identification of alternative spliced transcripts (Eukaryotes only)
  6. Predication of novel transcripts
  7. SNP analysis

Strand-Specific Transcriptome Sequencing Bioinformatics Analysis

  1. Identification of sense and antisense strands
  2. Detection of antisense strand expression
  3. Other analysis content is the same as transcriptome resequencing with reference

Duplex-Specific Nuclease (DSN) Normalization Transcriptome Sequencing Bioinformatics Analysis

  1. The analysis content is the same as for de novo transcriptome sequencing.

Custom Bioinformatics Analysis

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

Sample Requirements:

  1. Sample condition: Integrate total RNA samples that have been treated with DNase. Avoid protein contamination during RNA isolation.
  2. Sample quantity (for library construction once):
    1. Pant and fungi: total RNA ≥ 20μg
    2. Bacteria: total RNA ≥ 5μg
    3. Mammal (human, rat and mouse): total RNA ≥ 5μg
    4. Other species: total RNA ≥ 10μg
  3. Sample concentration:
    1. Plant and fungi: ≥ 250ng/µl
    2. Bacteria: ≥ 65ng/µL
    3. Mammal (human, rat and mouse): ≥ 65ng/uL
    4. Other samples: concentration ≥ 150ng/µl
  4. Sample purity:OD260/280 = 1.8-2.2, OD260/230 ≥ 2.0
    1. Plant and fungi: RNA 28S:18S ≥ 1.0, RIN ≥ 6.5
    2. Bacteria: RNA 23S:16S ≥ 1.0, RIN ≥ 7.0
    3. Animal: RNA 28S:18S ≥ 1.0, RIN ≥ 7.0

Turnaround Time:

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

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