- de novo Sequencing
- Whole Genome Resequencing
- Exome Sequencing
- Target Region Sequencing
- Genotyping by Sequencing
- Whole Genome Mapping
- Sanger Sequencing
- Single-Cell DNA Sequencing
- Human MHC-Seq
- Single-Cell Sequencing
- Immune Repertoire Sequencing
- FFPE Samples
- High correlation between mRNA expression and technical reproducibility (Pearson value ≥ 0.993)
- Access to almost all lncRNA and mRNA information in a single sequencing run
- Both known and novel lncRNAs can be analyzed
- 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
- Data filtering and statistics
- Removal of adapters, contaminated reads and low quality reads from raw reads
- Removal of the remaining rRNA reads by alignment/mapping to rRNA database
- LncRNA identification
- Transcripts assembly
- Identification of known (including known lncRNA) and novel transcripts
- Prediction of novel lncRNA
- Quantification and differential expression analysis
- Quantification and differential expression analysis of lncRNA (at least 2 samples)
- Group differentially expressed lncRNA screening (two or more groups (three or more samples in each group) should be provided)
- Expression pattern analysis of lncRNA
- LncRNA function prediction
- Interaction analysis of complementary lncRNA-mRNA
- Investigation of up- and downstream lncRNA for genes of interest
- Pre-miRNA prediction
- LncRNA family prediction and classification
Customized Bioinformatics Analysis
- Coding-non-coding (CNC) co-expression annotation (at least 5 pairs of case and control samples)
- Pathway enrichment analysis
We can also perform other customized analyses to meet the requirements of specific projects.
- Sample condition:Integrated total RNA samples (no mRNA isolation). Avoid protein contamination during RNA isolation.
- Sample quantity (for library construction once): total RNA ≥ 5 μg
- Sample concentration: ≥ 300 ng/μL
- Sample purity: for eukaryotes, except insects RIN ≥ 7.0, 28S:18S ≥ 1.0
The standard turnaround time for the workflow (above) is 50 business days.
Completion is indicated by the number of clean reads. Goals are individualized for each project.