Compared with microarray analysis, mRNA sequencing (RNA-Seq) provides a more precise and complete snapshot of the transcriptome and enables the identification of novel transcripts, alternative splicing, and gene fusion events. RNA-Seq also provides an alternative and affordable approach for gene expression quantification and differential gene expression analysis among groups of samples. It is widely used in disease research, drug response research, pharmacokinetics, and personalized healthcare research.
Novogene offers complete solutions for transcriptome sequencing and RNA-Seq quantification using state-of-the-art Illumina NovaSeq and HiSeq platforms with paired-end 150 bp (PE 150) sequencing strategy. The longer read length ensures superior data quality and accurate sequence assembly. Our experienced bioinformaticians work closely with customers to provide standard and customized data analysis and publication ready results for species with and without a reference genome.
The Novogene Advantage
- Extensive experience with thousands of samples successfully sequenced.
- Unsurpassed data quality with a guaranteed Q30 score ≥80% that exceeds Illumina’s official guarantee.
- Comprehensive data analysis using widely accepted mainstream software and mature in-house pipeline to discover novel transcripts, differential expressions, and function annotations.
- Free, powerful Novofinder software that enables Novogene customers to easily access and visualize data analysis results and annotations through a user-friendly interface.
- 250-300 bp insert cDNA library
- HiSeq platform, paired-end 150 bp
- NovaSeq 6000 platform, paired-end 150 bp
Data Quality Guarantee
- Our data quality guarantee, as measured by the percentage of bases with a sequencing quality score above Q30 (PE 150, ≥80%; SE 50, ≥90%), exceeds Illumina’s official guarantee (PE 150, ≥75%; SE 50, ≥80%). See examples of our high quality data.
- For extracted RNA: Total RNA ≥ 1 μg; RNA concentration (quantified by Qubit) ≥ 20 ng/μl; Volume ≥ 20 μl; RIN value (analyzed by Agilent 2100) ≥ 6.8; Purity: without degradation or contamination.
- For low input RNA: Total cDNA ≥ 10 ng; Peak range: 400 – 9000 bp, main peak: 1200 – 2500 bp; Purity: without degradation or contamination.
- Within 20 working days from verification of sample quality without data analysis
- The turnaround for data analysis is project dependent
Recommended Sequencing Depth
- ≥ 20 M reads
Pipeline for transcriptome analysis
Pipeline for RNA-Seq quantification
Table. Representative data quality results of Novogene’s mRNA sequencing service (PE150)
|Platform||Sample Name||# Of Raw reads||# Of Clean reads||Clean bases||Error Rate (%)||Q 20 (%)||Q 30(%)||GC Content (%)|
The following study utilized Novogene’s expert mRNA-Seq services.
JNK1 negatively controls antifungal innate immunity by suppressing CD23 expression
Nature Medicine, 23(3): 337-346 (2017)
Fungal infections pose a severe threat to immunocompromised patients, and improved understanding of the mechanisms that negatively regulate host immune responses could lead to better treatments for these infections. In this research, the role of the kinase JNK1 in host antifungal responses was explored.
This study first showed that mice deficient in JNK1 had a significantly higher survival rate than wild-type (WT) mice following infection with the opportunistic pathogen Candida albicans. Next, Novogene’s RNA sequencing service was employed to identify genes that might be responsible for resistance to fungal infection. The gene Fcer2a, which encodes CD23, a novel lectin receptor that plays a major role in the induction of host antifungal immune responses, was found to be significantly upregulated in stimulated JNK1-knockout cells when compared with WT control cells. The role of CD23 was validated by showing that suppression of CD23 gene expression eliminated the enhanced antifungal response found in JNK1-deficient mice. This study indicated that JNK1 may be a therapeutic target for treating fungal infection and confirmed the value of RNA-Seq for identifying novel gene expression patterns during host immune responses.
Figure. WT and JNK1-knockout (KO) bone marrow-derived macrophages were stimulated with yeast-form C. albicans for 24 hours or exposed to medium as a control. Heat maps of selected gene panels are shown. The red arrow indicates the Fcer2a gene.