Novogene AMEA
  • Novogene AMEA
  • Genomics
    • Human Whole Genome Sequencing
    • Plant and Animal Whole Genome Sequencing
    • Microbial Whole Genome Sequencing
    • Plant and Animal De novo Sequencing
    • Microbial De novo Sequencing
    • Shotgun Metagenomics Sequencing
    • Amplicon Sequencing
    • Whole Exome Sequencing
    Transcriptomics
    • mRNA Sequencing
    • Total RNA Sequencing
    • Full-Length Transcriptome Sequencing
    • Whole Transcriptome Sequencing
    • Small RNA Sequencing
    • Circular RNA Sequencing
    • Metatranscriptome Sequencing
    • Prokaryotic RNA Sequencing
    Single Cell & Spatial Omics
    • Single Cell Gene Expression
    • Single Cell Immune Profiling Sequencing
    • Single Cell Long Read Transcriptome
    • Visium HD Spatial Gene Expression
    • Stereo-Seq Spatial Gene Expression
    • Xenium In Situ Spatial Transcriptome
    Epigenomics
    • Whole Genome Bisulfite Sequencing (WGBS)
    • Directed DNA Methylation Sequencing (DM-Seq) NEW
    • Reduced Representation Bisulfite Sequencing (RRBS)
    • Chromatin Immunoprecipitation Sequencing (ChIP-seq)
    • RNA Immunoprecipitation Sequencing (RIP-seq)
    • Assay for Transposase-Accessible Chromatin with Sequencing (ATAC-seq)

    Premade Library

    • Sequencing Only on Illumina Sequencer
    • Sequencing Only on PacBio Sequencer
    Proteomics and Metabolomics
    • Olink Proteomics
    • Quantitative Proteomics
    • Untargeted Metabolomics
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    • Cancer Research
    • Immuno-oncology
    • Agrigenomics
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    • Food Science
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    • Plant and Animal Microbiome
    • Drug Discovery and Development
    • Rare and Complex Diseases
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Whole Genome SequencingDe novo SequencingAmplicon SequencingShotgun Metagenomic SequencingDirected DNA Methylation Sequencing (DM-Seq)mRNA SequencingSingle Cell Gene ExpressionVisium HD Spatial Gene ExpressionXenium In Situ Spatial TranscriptomeOlink ProteomicsUntargeted Metabolomics
Support
NovoMagic Bioinformatics Analysis ToolCustomer Service SystemFalcon Intelligent Delivery Platform
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Copyright © 2026 Novogene Inc. All rights reserved.For Research Use Only. Not for Clinical Diagnostic Use.
Novogene AMEA
  • Novogene AMEA
  • Genomics
    • Human Whole Genome Sequencing
    • Plant and Animal Whole Genome Sequencing
    • Microbial Whole Genome Sequencing
    • Plant and Animal De novo Sequencing
    • Microbial De novo Sequencing
    • Shotgun Metagenomics Sequencing
    • Amplicon Sequencing
    • Whole Exome Sequencing
    Transcriptomics
    • mRNA Sequencing
    • Total RNA Sequencing
    • Full-Length Transcriptome Sequencing
    • Whole Transcriptome Sequencing
    • Small RNA Sequencing
    • Circular RNA Sequencing
    • Metatranscriptome Sequencing
    • Prokaryotic RNA Sequencing
    Single Cell & Spatial Omics
    • Single Cell Gene Expression
    • Single Cell Immune Profiling Sequencing
    • Single Cell Long Read Transcriptome
    • Visium HD Spatial Gene Expression
    • Stereo-Seq Spatial Gene Expression
    • Xenium In Situ Spatial Transcriptome
    Epigenomics
    • Whole Genome Bisulfite Sequencing (WGBS)
    • Directed DNA Methylation Sequencing (DM-Seq) NEW
    • Reduced Representation Bisulfite Sequencing (RRBS)
    • Chromatin Immunoprecipitation Sequencing (ChIP-seq)
    • RNA Immunoprecipitation Sequencing (RIP-seq)
    • Assay for Transposase-Accessible Chromatin with Sequencing (ATAC-seq)

    Premade Library

    • Sequencing Only on Illumina Sequencer
    • Sequencing Only on PacBio Sequencer
    Proteomics and Metabolomics
    • Olink Proteomics
    • Quantitative Proteomics
    • Untargeted Metabolomics
  • PromotionsPromotions
    • Platforms
    • Automated Delivery Platform (Falcon)
    • Bioinformatics Analysis Tool (NovoMagic)
    • Customer Service System (CSS)
    • Brochures
    • Case Studies
    • Webinar
    • Blog
    • Sample Guidelines
    • Cancer Research
    • Immuno-oncology
    • Agrigenomics
    • Environment
    • Food Science
    • Human Microbiome
    • Plant and Animal Microbiome
    • Drug Discovery and Development
    • Rare and Complex Diseases
    • About Us
    • Our Locations
    • News
    • Careers
  • Contact UsContact Us

ServicesServices menu

SupportSupport menu

CompanyCompany menu

Services
Whole Genome SequencingDe novo SequencingAmplicon SequencingShotgun Metagenomic SequencingDirected DNA Methylation Sequencing (DM-Seq)mRNA SequencingSingle Cell Gene ExpressionVisium HD Spatial Gene ExpressionXenium In Situ Spatial TranscriptomeOlink ProteomicsUntargeted Metabolomics
Support
NovoMagic Bioinformatics Analysis ToolCustomer Service SystemFalcon Intelligent Delivery Platform
Company
About UsOur LocationsOur PlatformsNewsCareersContact Us
LinkedInLinkedIn hoverYouTubeYouTube hoverXX hover
Copyright © 2026 Novogene Inc. All rights reserved.For Research Use Only. Not for Clinical Diagnostic Use.
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Total RNA Sequencing

Comprehensive transcriptome profiling of coding and noncoding RNAs to reveal gene expression patterns and transcriptomic complexity.
Request a Quote
(Total RNA Sequencing)
Request a Quote
(Total RNA Sequencing)
OverviewOverview
BenefitsBenefits
ApplicationsApplications
SpecificationsSpecifications
ResourcesResources

Total RNA-seq captures the entire RNA landscape beyond mRNA — including regulatory molecules like lncRNA — to deliver a holistic view of gene expression and regulation. It empowers researchers to discover novel transcripts, investigate alternative splicing, analyze expression changes across conditions, and explore functional mechanisms in fields such as disease research, drug response, and developmental biology.


Novogene's Total RNA solution combines an optimized library preparation protocol for superior sensitivity with a complete bioinformatics pipeline. From precise strand-origin identification to lncRNA-mRNA regulatory network analysis, we deliver actionable insights through a streamlined, end-to-end workflow.

Why Choose Novogene for Total RNA Sequencing?

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Why Choose Novogene for Total RNA Sequencing?

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Applications of Total RNA-Seq

Total RNA-seq unlocks a deeper understanding of the transcriptome by capturing both coding and noncoding RNA, enabling broad research and clinical discovery.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Applications of Total RNA-Seq

Total RNA-seq unlocks a deeper understanding of the transcriptome by capturing both coding and noncoding RNA, enabling broad research and clinical discovery.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Specifications

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Specifications

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Demo Results

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

Demo Results

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

More Services

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(mRNA Sequencing)
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(mRNA Sequencing)

More Services

Small RNA Sequencing
(Small RNA Sequencing)
Small RNA Sequencing
(Small RNA Sequencing)
CircRNA Sequencing
(CircRNA Sequencing)
CircRNA Sequencing
(CircRNA Sequencing)
mRNA Sequencing
(mRNA Sequencing)
mRNA Sequencing
(mRNA Sequencing)
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Total RNA Sequencing

Comprehensive transcriptome profiling of coding and noncoding RNAs to reveal gene expression patterns and transcriptomic complexity.
Request a Quote
(Total RNA Sequencing)
Request a Quote
(Total RNA Sequencing)
OverviewOverview
BenefitsBenefits
ApplicationsApplications
SpecificationsSpecifications
ResourcesResources

Total RNA-seq captures the entire RNA landscape beyond mRNA — including regulatory molecules like lncRNA — to deliver a holistic view of gene expression and regulation. It empowers researchers to discover novel transcripts, investigate alternative splicing, analyze expression changes across conditions, and explore functional mechanisms in fields such as disease research, drug response, and developmental biology.


Novogene's Total RNA solution combines an optimized library preparation protocol for superior sensitivity with a complete bioinformatics pipeline. From precise strand-origin identification to lncRNA-mRNA regulatory network analysis, we deliver actionable insights through a streamlined, end-to-end workflow.

Why Choose Novogene for Total RNA Sequencing?

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Why Choose Novogene for Total RNA Sequencing?

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

 High-Performance Sequencing
High-Performance Sequencing

Achieve high-throughput, high-accuracy data (Q30 ≥ 85%) with minimal starting material.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

Proven Service Track Record
Proven Service Track Record

Benefit from our extensive experience, supporting thousands of projects and high-impact publications.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

 Comprehensive Total RNA Analysis
Comprehensive Total RNA Analysis

Access all-inclusive solutions for identification, quantification, and differential expression analysis.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Publication-Ready Bioinformatics Support
Publication-Ready Bioinformatics Support

Obtain customized, publication-quality results backed by our expert bioinformatics team.

Applications of Total RNA-Seq

Total RNA-seq unlocks a deeper understanding of the transcriptome by capturing both coding and noncoding RNA, enabling broad research and clinical discovery.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Applications of Total RNA-Seq

Total RNA-seq unlocks a deeper understanding of the transcriptome by capturing both coding and noncoding RNA, enabling broad research and clinical discovery.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

In-Depth Exploration

Profile both known and novel transcripts, identify expression changes, and detect sequence variations across the whole transcriptome.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Uncover Novel Insights

Discover biomarkers for disease diagnosis, classification, and therapeutic response through comprehensive RNA expression and lncRNA analysis.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Target Prediction

Predict RNA–RNA and RNA–gene interactions to reveal regulatory targets and functional pathways.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Comprehensive Analysis

Investigate regulatory relationships between coding and noncoding RNAs to understand gene expression networks and molecular mechanisms.

Specifications

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Specifications

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sample Requirements

Sample amounts are listed for reference only. Download the Sample Requirements to learn more. For detailed information, please contact us with your customized requests.

Library TypeSample TypeAmountRNA Integrity NumberPurity (NanoDrop)
lncRNA LibraryTotal RNA≥ 300 ng≥ 5.5, with flat baselineOD260/280 ≥ 2.0;
OD260/230 ≥ 2.0;
no degradation,
no genomic contamination
Exosomal lncRNA LibraryExosomal RNA≥ 10 ngFragments between 80-200 nt, no peaks > 2000 nt, FU*>10, with flat baseline
Dual RNA libraryTotal RNA≥ 400 ng≥ 6.5, with flat base line
*FU: Fluorescent unit

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Sequencing and Analysis

Recommended data outputs and analysis contents displayed are for reference only. For detailed information, please contact us with your customized requests.

Sequencing PlatformIllumina NovaSeq System
Recommended Sequencing Depth≥ 40 million read pairs per sample for species with reference genome
Standard Data Analysis•Data quality control
•Structural analysis (alternative splicing & variation calling)
•lncRNA identification & annotation
•Expression quantification & differential expression profiling
•Functional enrichment analysis
•Protein-protein interaction (PPI) analysis
•lncRNA target gene prediction

Project Workflow

The workflow of the Total RNA-seq starts with sample preparation and quality control. The ribosomal RNA (rRNA) is depleted for target transcript enrichment. The fragmented RNA undergoes reverse transcription into cDNA. Strand-specific libraries (also known as stranded libraries, directional libraries) are prepared, and the sequencing is performed using a paired-end 150bp strategy on the Illumina platform. The downstream processing follows the well-established Novogene pipeline, which guarantees the highest quality results. Customized bioinformatics solutions are available upon request.

Project Workflow

Demo Results

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Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
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1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
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1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
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1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

Demo Results

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

Image
Image
1/1
Coding Potential Prediction

Coding potential analysis is a key step to distinguish lncRNAs from other transcripts. We integrate predictions from multiple established algorithms — including CPC, CNCI, and Pfam — using a consensus approach for reliable classification.

Image
Image
1/1
Structural Comparison: lncRNA vs. mRNA

We compare key structural features — such as transcript length, exon count, and ORF length — to reveal the characteristic differences between lncRNAs and mRNAs.

Image
Image
1/1
Expression Level Distribution

This chart displays expression levels across samples, with the x-axis showing sample names and the y-axis representing log₁₀(FPKM+1) values.

Image
Image
1/1
Volcano Plot of Differentially Expressed Genes (DEGs)

The volcano plot visualizes differential expression, where the x-axis indicates log₂ fold change and the y-axis represents statistical significance (--log₁₀ p-value).

Image
Image
1/1
Clustering Heatmap of DEGs

Differentially expressed genes are clustered via hierarchical clustering based on their expression patterns (row-normalized). The heatmap groups genes or samples with similar profiles for intuitive visualization.

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