RNA Sequencing

  • DNA Reading
  • Hybridoma Antibody Sequencing
    Immune Repertoire Sequencing
    DNA Sequencing & Gene Analysis
    NGS High Throughput Sequencing
    16S rDNA Sequencing
    Metagenome Sequencing
    RNA Sequencing
    CRISPR Amplicon Sequencing

    A transcriptome refers to the sets of all transcription products in a cell under a certain physiological condition, including mRNA, rRNA, tRNA, and non-coding RNA. In short, it means the set of all mRNAs. The research scope of transcriptomes is all mRNA of a particular cell in certain state. Based on Synbio Technologies’s high-throughput sequencing technology, almost all RNA information of a tissue or organ can be sequenced comprehensively. Eukaryotic and prokaryotic RNA sequencing is used to discover expressed genes in cells, tissues, or individuals under different physiological or pathological conditions. A transcriptome bonds a genome’s genetic information and biological functions. Nowadays, RNA sequencing is widely applied to a wide variety of biological research as well as clinical diagnosis and drug development.


    • Medical Research: Disease markers, disease diagnosis and classification, disease recurrence diagnosis, disease mechanism, clinical efficacy evaluation, drug toxicology evaluation, personalized therapy.
    • Life Science Research: Abiotic environmental relationships, plants and microorganisms, phenotypic identification, metabolic pathway and functional genomic studies, medicinal plants.

    Competitive Advantages

    • High Data Quality: Rich experience in library construction for prokaryotic RNA sequencing to reach good rRNA removal efficiency.
    • High Coverage: High or low abundances can be identified and quantified simultaneously.
    • Strand-specific RNA-seq Library: The dUTP strand-specific RNA-seq library is used to ensure the directivity of transcripts and accurate quantitative results.
    • Comprehensive Analysis: Specific probes and reference genomic information are not necessary to detect genes but also to discover new transcripts.
    • Integrative Analysis of Multiomics: Full spectrum & comprehensive analysis of biomolecule function and regulatory mechanisms.

    RNA Sequencing Technical Strategy


    Service Specifications

    ServiceSample TypeSequencing ModelSampling Requirements
    Prokaryotic RNA Sequencing
    Microorganism (≥ 5 ×107), tissue, environmental samples, total RNA, etc.
    HiSeq 4000, PE150Total RNA ≥3μg, Concentration ≥70 ng/μL
    Eukaryotic RNA SequencingCell, tissue, serum, plasma, total RNA, etc.
    Total RNA ≥ 2μg (minimum 1μg), concentration ≥ 50 ng/μL

    Project Design

    The design idea of a transcriptome experiment is to compare different genes, and the common type is to compare the experimental group and the control group. With time and space factors considered, multiple comparative analyses can be implemented according to different growth stages or the occurrence and development of diseases. At least 3 biological replicates are required for each group.

    Analysis Items

    1. Prokaryotic transcriptome sequencing
    NumberAnalysis ItemNumberAnalysis Item
    1Raw data processing and data quality control7Differential gene cluster analysis
    2Reference genome alignment8KEGG enrichment analysis of differential genes
    3Quality assessment of RNA-Seq9Antisense transcript prediction
    4Gene expression level analysis10Operon analysis
    5Differential gene expression analysis11sRNA analysis
    6GO enrichment analysis of differential genes12Mutation analysis
    2. Eukaryotic transcriptome sequencing with reference genome
    NumberAnalysis ItemNumberAnalysis Item
    1Raw data output statistics7KEGG annotation of Unigene
    2Reference genome comparison and statistics8GO enrichment analysis of differential genes
    3Analysis of gene expression abundance9KEGG enrichment analysis of differential genes
    4SNP and InDel anslysis10Prediction of new transcripts
    5GO enrichment analysis11Differential splicing analysis
    6GO annotation for Unigene12DEU analysis (Differential Exon Usage)
    3. Eukaryotic transcriptome sequencing without reference genome
    NumberAnalysis ItemNumberAnalysis Item
    1Raw data output statistics and quality control8KOG annotation for Unigene
    2Transcript splicing9SNV/SNP analysis
    3Length distribution statistics and GC content statistics of Unigene and Transcript10SSR analysis of Unigene
    4Predict coding protein frame according to splicing sequence11Analysis of gene expression abundance
    5Unigene functional annotation12Differential gene expression analysis
    6KEGG enrichment analysis13GO enrichment analysis of differential genes
    7Profile analysis of differential gene expression14KEGG enrichment analysis of differential genes

    Data Analysis


    Box Diagram of Gene Expression Distribution

    PCA Analysis

    Differential Gene Volcano Plot

    Differential Gene Venn Diagram

    Cluster Heatmap

    KEGG Pathway Enrichment Plot

    Differential Gene Trend Analysis

    Variation Locus Region Statistics