Overview
Messenger RNA (mRNA) is one type of the transcripts that carries information from DNA to ribosomes, instructing the protein synthesis (translation) in cells. Eukaryotic mRNA sequencing (mRNA-Seq), utilizing the technology of next-generation sequencing (NGS), reveals the expression profiles of mRNA in a biological sample and illustrates the continuous variations in the cellular transcriptome. Novogene’s mRNA-Seq, based on state-of-the-art Illumina NovaSeq platforms with paired-end 150 bp sequencing strategy, offers comprehensive solutions for analysis of gene expression quantification and differential gene expression among sample groups, as well as for identification of novel transcripts, alternative splicing, gene fusion events, and etc.. Our experienced bioinformaticians work closely with customers to provide standard and customized data analysis and publication-ready results for species with or without a reference genome.
With multiple research needs, please find more services of Prokaryotic RNAs, Non-coding RNAs, Full-length RNAs, Whole Transcriptome and Metatranscriptome for your study.
Service Specifications demo reportApplications
For medical research:
- Pathological mechanism
- Tumor-subtypes classification
- Molecular markers
- Human evolution
- Drug target
- Clinical diagnostics
- Personal health care
For agricultural research:
- Development
- Adaptability
- Agronomic traits
- Crop evolution
Advantages
- Extensive experience with thousands of projects successfully completed and multiple articles published in journals of high Impact Factors.
- Unsurpassed data quality with a guaranteed Q30 score ≥ 80% that exceeds Illumina’s official benchmarks.
- Comprehensive data analysis using widely accepted industry standard software and mature in-house pipeline to detect differential expressions, to discover novel transcripts and to make functional annotations.
- Easily visualize data analysis results with Novogene’s user-friendly in-house software.
Sample Requirements
| Library Type | Sample Type | Amount | RNA Integrity Number (Agilent 2100) |
Purity （NanoDrop） |
|
Eukaryotic RNA-Seq
（cDNA library) |
Total RNA | ≥ 0.4 μg |
≥ 6.8 (Animal), with smooth base line
≥ 6.3 (Plant and Fungus), with smooth base line |
OD260/280 = 1.8-2.2;
OD260/230 ≥ 1.8; |
| Total RNA (Blood) | ≥ 0.8 μg | |||
| Total RNA (Single Cell) | ≥ 100 ng | |||
| Amplified cDNA (double-stranded) | ≥ 100 ng | Fragments between 400bp and 5000bp with main peak at ~2000bp | OD260/280 = 1.8-2.0; OD260/230 ≥ 1.8; |
|
| Eukaryotic RNA-Seq （strand specific library) |
Total RNA | ≥ 0.8 μg | ≥ 6.8 (Animal), with smooth base line ≥ 6.3 (Plant and Fungus), with smooth base line |
OD260/280 = 1.8-2.2; OD260/230 ≥ 1.8; |
Sequencing Parameters and Analysis Contents
| Sequencing Platform | Illumina NovaSeq 6000 |
| Read Length | Paired-end 150 |
| Recommended Data Output | ≥ 20 million read pair per sample for species with reference genome； ≥ 50 million read pairs per sample for species without reference genome (de novo transcriptome assembly projects) |
| Standard Data Analysis |
|
Note: For detailed information, please refer to the Service Specifications & Demo Reports and contact us for customized requests.
Project Workflow
Sampling & Sequencing Strategy:
Sample Preparation
• Tumor cells with/ without MYCN amplification
Sequencing Strategy
• Library preparation: RNA-seq library
• Sequencing: Illumina HiSeq Platform
Results:
A Volcano plots (left panel), Venn diagram (middle panel), and heatmap (right panel) revealing the alteration of gene expression (fold change > 2.0, FDR < 0.05) in SH-SY5Y cells stably transfected with empty vector (mock) or ARMC12. Red indicates high expression, and blue indicates low expression in heatmap.
Conclusion:
ARMC12 plays a crucial role in tumor progression and could be a potential therapeutic approach for NB. Mechanistically, ARMC12 physically interacts with retinoblastoma binding protein 4 (RBBP4) to facilitate the formation and activity of polycomb repressive complex 2, resulting in transcriptional repression of tumor suppressive genes.
Targeting epigenetic crosstalk as a therapeutic strategy for ezh2-aberrant solid tumors
Background:
Mutations or aberrant upregulation of EZH2 occur frequently in human cancers, yet clinical benefits of EZH2 inhibitor (EZH2i) remain unsatisfactory and limited to certain hematological malignancies. Addressing how EZH2i modulates global epigenetic signatures and, more importantly, how the new insights can be translated into a better therapeutic strategy using EZH2is in a variety of solid tumors is quite meaningful.
Sampling & Sequencing Strategy:
Sample Preparation
• U2932, SMMC-7721 and Pfeiffer cells
Sequencing Strategy
• Library Preparation: mRNA library, NEBNext UltraTM RNA Library Prep it for Illumina
• Sequencing: Illumina platform
Results:
A) GSEA analysis of H3K27ac ChIP-seq data, RNA-seq data, and proteome data affected by EPZ-6438. The global heatmap showing the enriched pathways in the oncogenic signatures from the Molecular Signatures Database (MSigDB) with EPZ-6438 compared to DMSO treated in U2932, SMMC-7721, and Pfeiffer cell lines. The color is according to FDR q value, and the darkest blue represents q R 0.1 or N/A. (B and C) Venn diagram showing the overlap of the statistically (FDR q < 0.05) enriched pathways among the insensitive cell lines (U2932, SMMC-7721) based on RNA-seq data (B) and proteome data (C), respectively.
Conclusion:
Together, the epigenetic interplay revealed in this study enabled us to expand the therapeutic potential of EZH2is from hematological malignances to solid tumors. The insights reveal that EZH2i caused the crosstalk between H3K27me and H3K27ac and leads to oncogene activation. This may suggest that targeting this crosstalk could provide therapeutic promise.
mRNA and Small RNA Transcriptomes Reveal Insights into Dynamic Homoeolog Regulation of Allopolyploid Heterosis in Nascent Hexaploid Wheat
Background:
Nascent allohexaploid wheat may represent the initial genetic state of common wheat (Triticumaestivum), which arose as a hybrid between Triticum turgidum (AABB) and Aegilops tauschii (DD) and by chromosome doubling and outcompeted its parents in growth vigor and adaptability. The molecular basis for this success remains unclear.
Sampling & Sequencing Strategy:
Sample Preparation
• Tissues of Hexaploid Wheat, Chinese spring, Triticum Turgidum, Aegilops Tauschii
Sequencing Strategy
• Library preparation: mRNA-seq and sRNA-seq libraries
• Sequencing: Illumina HiSeq 2000
Results:
(A) Genes differentially expressed in S3 progeny and their tetraploid (AABB) and diploid (DD) progenitors. Numbers close to the species (colored) represent upregulated genes compared with the neighboring species. Percentages indicate those among all expressed genes in young spikes. The total number of genes differentially expressed between two species is given (black).
(B) GO enrichment analysis of nonadditively expressed genes. Shown are significantly enriched GO terms (Fisher test FDR < 0.05). BP, biological process; MF, molecular function; CC, cellular component.
Conclusion:
Allohexaploid wheat combines the AB genomes from tetraploid wheat with the D genome from Ae. tauschii, resulting in the union of genomes from varieties previously adapted to different environments and thus providing the potential for further adaptation to a wider range of growth environments. Overall, the molecular underpinnings established during the early allopolyploidization events laid the groundwork for the successful advent of common wheat.
Error Rate Distribution
GC Content Distribution
Classification of Raw Reads
Reads Distribution on Reference Genome
Gene Expression Quantification
Volcano Plot of changes on Gene Expression
Hierarchical Clustering Heatmap of Differential Expression
