RNA sequencing (RNA-seq) has been transforming the study of cellular functionality, which provides researchers with an unprecedented insight into the transcriptional landscape of cells. Employing the high-throughput and accurate next-generation sequencing technique (NGS), RNA-seq reveals gene expression profiles and describes the continuous variations in the transcriptome. In the RNA-seq technique, the single-stranded messenger RNAs (mRNAs) are selectively captured or enriched, and converted to complementary DNA (cDNA) for library preparation.
At Novogene, cDNA libraries are sequenced using the state-of-the-art Illumina NovaSeq platforms, which utilize a paired-end 150 bp sequencing strategy (short-reads). Along with our rich experience and strong sequencing capacity, Novogene offers services to meet a wide array of research objectives. Our services not only include eukaryotic mRNA sequencing (mRNA-seq) services, Novogene can also deliver data on prokaryotic transcripts, non-coding RNAs, full-length isoforms (long-reads), whole transcriptomes, and meta-transcriptomes.
Applications
mRNA-seq is a powerful tool to analyze the cell transcriptome profile. Novogene’s professional services help on research goals in a wide range of applications, including:
- Quantitative profiling of transcripts in different tissues or samples, under various conditions and treatments
- Discovery of novel transcripts, alternative splicing (AS), and transcript variations
- Research of developmental mechanisms and drug resistance through tissue-specific transcripts or time-course gene expression
- Biomarker discovery based on novel transcripts/isoforms, SNP/InDel identification, and fusion gene analysis
- Omics analysis in combination with the transcriptome
- Investigation of pathogenic mechanisms and clinical subtypes in clinical diagnosis
Benefits
- Novogene mRNA-seq offers high throughput and high accuracy (with Q30 score ≥ 85%) coupled with a low initial RNA input required. Novogene has extensive experience providing RNA-Seq services, having successfully completed thousands of projects to help multiple researchers to publish in high impact factor journals.
- Novogene offers inclusive solutions for quantification, differential gene expression, annotation of novel transcripts, alternative splicing, discovery of fusion gene, and other potential variations. Highly-qualified bioinformaticians deliver publication-ready data using personalized pipelines for species either with or without a reference genome.
Specifications: Sample Requirements
| Library Type | Sample Type | Amount | RNA Integrity Number (Agilent 2100) | Purity (NanoDrop) |
| Eukaryotic RNA-Seq (cDNA library) | Total RNA | ≥ 200 ng | ≥ 4.0, with smooth base line | A260/280 = 1.8-2.2 A260/230 ≥ 1.8 |
| Total RNA (Blood) | ≥ 400 ng | ≥ 5.8, with smooth base line | ||
| Amplified cDNA (double-stranded) | ≥ 100 ng | Fragments between 400bp and 5000bp with main peak at ~2000bp | A260/280 = 1.8-2.0 A260/230 ≥ 1.8 |
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| Eukaryotic RNA-Seq (strand specific library) | Total RNA | ≥ 400 ng | ≥ 5.8, with smooth base line | A260/280 = 1.8-2.2 A260/230 ≥ 1.8 |
Note: Sample amounts are listed for reference only. Download the Service Specifications or Sample Requirements to learn more. For detailed information, please contact us with your customized requests.
Specifications: Sequencing and Analysis
| Sequencing Platform | Illumina NovaSeq 6000 Sequencing System |
| Read Length | Paired-end 150 bp |
| Data Output |
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| Data Analysis Capability |
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Note: Recommended data outputs and analysis contents displayed are for reference only. Download the Service Specifications to learn more. For detailed information, please contact us with your customized requests.
Project Workflow
The project workflow starts with 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 application, and subsequently tested for its quality (Library QC). Next, a 150 bp paired-end sequencing strategy is used to sequence the samples and the quality of the resulting data is also checked for its quality (Data QC). Finally, bioinformatic analyses are performed and publication-ready results are provided. The following flowsheet describes the step-by-step protocol our mRNA-seq technique follows.
Preparation of sample is followed by the RNA library preparation. RNA library is formed by polyA capture (or rRNA removal) and reverse transcription of cDNA. Illumina PE150 technology is employed to sequence the sample and the final stage involves the bioinformatics analysis.
Featured Publications using Novogene’s RNA-seq service
RNA-seq (mRNA-seq) is the most frequently cited NGS method. Here we have summarized some outstanding academic publications that used Novogene RNA sequencing (mRNA Sequencing) services.
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Cell Death & DifferentiationIssue Date: 2021.2IF: 10.717DOI: 10.1038/s41418-021-00749-4
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Stem Cells Translational MedicineIssue Date: 2021.1IF: 11.5DOI: 10.1002/sctm.20-0468
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Journal of Hazardous MaterialsIssue Date: 2020.12IF: 9.038DOI: 10.1016/j.jhazmat.2020.124867
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Genome MedicineIssue Date: 2020.11IF: 10.675DOI: 10.1186/s13073-020-00796-5
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Advanced scienceIssue Date: 2020.3IF: 15.84DOI: 10.1002/advs.202000398
Error Rate Distribution
The x-axis shows the base position along each sequencing read and the y-axis shows the base error rate.
GC Content Distribution
The x-axis for reads position, the y-axis for single base percentage. Different color for different base type.
Classification of Raw Reads
Reads Distribution on Reference Genome
Gene Expression Quantification
The x-axis represents the name of sample, the y-axis indicates the log10(FPKM+1), parameters of box plots are indicated, including maximum, upper quartile, mid-value, lower quartile and minimum.
Volcano Plot of changes on Gene Expression
The x-axis shows the fold change of genes in different samples. The y-axis shows the statistically significant degree of changes in gene expression levels. The smaller the corrected pvalue, the bigger -log10(corrected pvalue), the more significant the difference. The points represent genes, blue dots indicate no significant difference in gene expression, red dots indicate upregulated differentially expressed genes, green dots indicate downregulated differentially expressed genes.
Hierarchical Clustering Heatmap of Differential Expression
The overall results of FPKM cluster analysis, clustered using the log10(FPKM+1) value. Red denotes genes with high expression levels, and blue denotes genes with low expression levels. The color ranging from red to blue indicates log10(FPKM+1) value from large to small.
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