CD Genomics's mRNA-Seq service, powered by the state-of-the-art Illumina NovaSeq platforms, offers comprehensive solutions for gene expression quantification, differential gene expression analysis, identification of novel transcript isoforms, alternative splicing, and gene fusions, etc. Our expert team works closely with you to provide standard and customized high-throughput sequencing and bioinformatics analyses based on project-specific needs, as well as exquisite results for publication.
Messenger RNA (mRNA) is one type of RNA transcripts that corresponds to the genetic sequence of a gene, instructing the protein synthesis in cells. Eukaryotic mRNA sequencing (mRNA-Seq), by leveraging the technology of next-generation sequencing (NGS), reveals the expression profiles of mRNA in a given biological sample, as well as differential gene expression among sample groups. The mRNA-seq provides a clear, complete, high-resolution view of the coding transcriptome, including detection of known and novel transcript isoforms, identification of gene fusion events and other features, as well as gene expression analysis by measuring transcript abundance. In contrast with whole transcriptome sequencing that sequences all coding and non-coding transcripts, mRNA-seq focuses on the coding RNAs, which are around 2% of the whole transcriptome and contain a poly-A tail. The mRNA-seq delivers a comprehensive picture of the coding transcriptome without the need of prior knowledge and is advantageous over gene expression arrays and other approaches. mRNA-seq has been widely used for identification and comparison of gene expression levels between groups, perfect for drug treatment, behavioral selection, identification of cellular responses to viruses, and disease related research.
De novo sequencing directly sequences the genome or transcriptome without any sequence information as a reference. Our eukaryotic de novo sequencing utilizes the Illumina platform to sequence all mRNAs transcribed by a specific eukaryotic tissue or cell in a specific state, and spliced out the longest transcript as unigene for subsequent analysis.
Eukaryotic mRNA sequencing based on reference sequences can comprehensively obtain transcript information of species-specific cells, tissues, or organs, so as to conduct eukaryotic transcript structure analysis, variation analysis, gene expression level analysis, novel transcript discovery, and more.
Our comprehensive blood RNA sequencing services to characterize total RNA in blood samples, including, circle RNA, mRNA and small RNA. Our advanced whole blood transcriptional profiling solution ensures reproducible, specific, sensitive and accurate results to aid disease research and biomarker discovery.
|Flexibility to prepare libraries and analyze data according to your needs.||Enables sensitive and accurate isoform detection and quantification.||ptimized workflows to maximize output and accuracy.||Especially useful for medical research and agricultural research|
RNA purification; quality assessment and quantification
cDNA library or strand-specific library
Illumina NovaSeq, PE 150
Visualize and preprocess results, and perform custom bioinformatics analysis.
Sample storage: RNA can be dissolved in ethanol or RNA-free ultra-pure water and stored at -80°C. RNA should avoid repeated freezing and thawing.
Shipping Method: When shipping RNA samples, the RNA sample is stored in a 1.5 mL Eppendorf tube, sealed with sealing film. Shipments are generally recommended to contain 5-10 pounds of dry ice per 24 hours.
Deliverable: raw data as BAM files, coverage summary, QC report, custom bioinformatics analyses.
Transcriptome Alignment Analysis Results
Differential expression of known genes
Differential expression profiling
Blood samples for RNA extraction require the removal of white blood cells. The concentration of RNA in the blood is low and requires 2mL of sample and about 3uL of total RNA extracted.
Sequencing mode: 2×100 (150) bp, data volume: 20~30M reads/sample.
Transcriptome measures complete transcript information, while expression profiling measures partial cDNA sequences; compared with gene expression microarray, transcriptome not only compares differential expression, but also predicts new transcripts and variable splicing; transcript sequencing can be done without a reference genome, while microarrays must rely on a reference genome.
FPKM and RPKM are used to calculate gene expression levels. FPKM is indicating the number of fragments from a particular gene per Kilobase of transcript sequence per Millions base pairs sequenced. RPKM is indicating the number of reads per Kilobase of transcript sequence per Millions base pairs sequenced from a particular gene. It can be seen that FPKM is in terms of fragment (read pair), while RPKM is in terms of read (single read). In addition, we used FPKM to quantify the transcripts of genes.