Total RNA Sequencing

Comprehensive transcriptome profiling of coding and noncoding RNAs to reveal gene expression patterns and transcriptomic complexity.

Total RNA sequencing (Total RNA-seq) provides a comprehensive view of the transcriptome by capturing both coding and non-coding RNAs, including lncRNAs, mRNAs, and other regulatory RNA species. Using an rRNA depletion strategy, this approach removes ribosomal RNA to enrich informative transcript types, enabling accurate detection of low-abundance and regulatory RNAs that are often missed by poly(A)-based methods.

Novogene’s Total RNA-seq workflow employs a refined library preparation process that enhances transcript diversity and delivers sensitive, strand-specific gene expression profiling. Through our integrated bioinformatics pipeline, researchers can explore transcript structure, quantify expression, and analyze regulatory relationships between lncRNAs and their target mRNAs—all within a single sequencing run. This enables in-depth investigation of RNA function, regulatory mechanisms, and transcriptome-wide activity.

Benefits of Novogene Total RNA Sequencing

high-performance, High-accuracy

Achieve high-throughput, high-accuracy transcriptome profiling with stringent quality standards (Q30 ≥ 85%) and low RNA input requirements—ideal for sensitive or precious samples.

Proven Expertise and Reliable Outcomes

Benefit from Novogene’s extensive experience in thousands of RNA-seq projects, supporting high-impact publications and providing dependable, well-validated transcriptomic datasets.

Comprehensive Total RNA Analysis

Access a complete suite of analyses, including transcript identification, quantification, differential expression, and regulatory characterization of both coding and non-coding RNAs, including lncRNAs.

Strand-specific, Regulatory Aware Insights

Enhanced library preparation and rRNA depletion enable sensitive detection of diverse transcripts. strand-specific data support accurate interpretation of lncRNA–mRNA regulatory relationships and functional RNA networks.

Publication Ready Bioinformatics Support

Receive high quality, expertly curated results from Novogene’s bioinformatics team, including visualization, annotation, and analysis outputs tailored for publication, grant submission, or downstream validation.

Benefits of Novogene Total RNA Sequencing

high-performance, High-accuracy

Achieve high-throughput, high-accuracy transcriptome profiling with stringent quality standards (Q30 ≥ 85%) and low RNA input requirements—ideal for sensitive or precious samples.

Proven Expertise and Reliable Outcomes

Benefit from Novogene’s extensive experience in thousands of RNA-seq projects, supporting high-impact publications and providing dependable, well-validated transcriptomic datasets.

Comprehensive Total RNA Analysis

Strand-specific, Regulatory Aware Insights

Publication Ready Bioinformatics Support

Applications of Total RNA‑seq

Total RNA sequencing (Total RNA‑seq) provides a broad, unbiased view of the transcriptome by capturing both coding and non‑coding RNAs, including lncRNAs, mRNAs, and other regulatory RNA species. This enables wide‑ranging applications in research, disease discovery, and functional genomics.

In‑Depth Transcriptome Exploration

Profile known and novel transcripts, quantify expression changes, and detect RNA variations across the entire transcriptome—supporting comprehensive discovery and characterization.

Novel Biological Insight & Biomarker Discovery

Reveal disease‑associated expression patterns and identify candidate biomarkers for cancer, neurological disorders, metabolic diseases, and other conditions through integrated mRNA and lncRNA analysis.

Target Prediction & Functional Interaction Analysis

Predict RNA–RNA and RNA–gene interactions to uncover regulatory targets, downstream pathways, and functional roles of coding and non‑coding RNAs.

Regulatory Network Characterization

Investigate lncRNA–mRNA regulatory relationships and broader gene expression networks to understand molecular mechanisms underlying development, stress response, and disease progression.

Applications of Total RNA‑seq

In‑Depth Transcriptome Exploration

Profile known and novel transcripts, quantify expression changes, and detect RNA variations across the entire transcriptome—supporting comprehensive discovery and characterization.

Novel Biological Insight & Biomarker Discovery

Target Prediction & Functional Interaction Analysis

Predict RNA–RNA and RNA–gene interactions to uncover regulatory targets, downstream pathways, and functional roles of coding and non‑coding RNAs.

Regulatory Network Characterization

Investigate lncRNA–mRNA regulatory relationships and broader gene expression networks to understand molecular mechanisms underlying development, stress response, and disease progression.

Specifications

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

Project Workflow

Novogene’s Total RNA sequencing (Total RNA‑seq) workflow begins with sample preparation and quality control, followed by ribosomal RNA (rRNA) depletion to enrich informative transcripts. The remaining RNA is fragmented and converted into cDNA, after which strand‑specific (directional) libraries are prepared. Sequencing is carried out using a paired‑end 150 bp strategy on the Illumina platform. All data are processed through Novogene’s established bioinformatics pipeline, with custom analysis options available upon request.

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

Project Workflow

Specifications

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

Project Workflow

Resources

1/1

Coding Potential Filtering

Coding potential analysis is used to determine whether a transcript is likely to encode a protein. Tools such as CPC, CNCI, and PFAM are applied to evaluate coding likelihood, and transcripts predicted as non-coding across multiple methods are classified as lncRNAs.

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Feature Comparison of lncRNA and mRNA

Transcript features—including transcript length, exon count, and open reading frame (ORF) length—are compared between lncRNAs and mRNAs to highlight characteristic differences between the two RNA classes.

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Distribution of Expression Levels

Expression distributions are visualized using log10(FPKM + 1). The x-axis represents sample names, and the y-axis displays the transformed expression values.

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Volcano Plot of Differential Genes

The volcano plot illustrates differential gene expression, with the x-axis showing fold change between groups and the y-axis indicating statistical significance (e.g., –log10 p-value).

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Heatmap of Differentially Expressed Genes

Hierarchical clustering is performed on normalized FPKM values to group genes or samples with similar expression patterns. The resulting heatmap visually clusters expression profiles into biologically meaningful groups.

Resources

1/1

Coding Potential Filtering

1/1

Feature Comparison of lncRNA and mRNA

1/1

Distribution of Expression Levels

Expression distributions are visualized using log10(FPKM + 1). The x-axis represents sample names, and the y-axis displays the transformed expression values.

1/1

Volcano Plot of Differential Genes

The volcano plot illustrates differential gene expression, with the x-axis showing fold change between groups and the y-axis indicating statistical significance (e.g., –log10 p-value).

1/1

Heatmap of Differentially Expressed Genes

Frequently Asked Questions

What types of RNA are captured in Total RNA-seq?

Total RNA-seq profiles both coding and non-coding RNA, including mRNAs, lncRNAs, and other regulatory transcripts. Because the workflow uses rRNA depletion, it enriches all transcript types—not just polyadenylated RNAs—providing a more complete view of the transcriptome.

What sample types are accepted?

How much RNA is required?

What sequencing strategy does Novogene use?

Why use rRNA depletion instead of poly(A) selection?

Can Total RNA-seq identify novel lncRNAs?

What downstream analyses are included?

Does Total RNA-seq support regulatory network analysis?

How is data delivered?

Can Total RNA-seq analyze low-input or degraded samples?

More Services

Full-Length Transcriptome Sequencing

Metatranscriptome Sequencing

mRNA Sequencing

Prokaryotic RNA Sequencing

Small RNA Sequencing

Whole Transcriptome Sequencing

Ready to start your project?

Our platform offers tailored solutions for your unique experimental needs, ensuring a seamless experience from project design to data delivery.

Total RNA Sequencing

Comprehensive transcriptome profiling of coding and noncoding RNAs to reveal gene expression patterns and transcriptomic complexity.

Benefits of Novogene Total RNA Sequencing

high-performance, High-accuracy

Achieve high-throughput, high-accuracy transcriptome profiling with stringent quality standards (Q30 ≥ 85%) and low RNA input requirements—ideal for sensitive or precious samples.

Proven Expertise and Reliable Outcomes

Benefit from Novogene’s extensive experience in thousands of RNA-seq projects, supporting high-impact publications and providing dependable, well-validated transcriptomic datasets.

Comprehensive Total RNA Analysis

Strand-specific, Regulatory Aware Insights

Publication Ready Bioinformatics Support

Benefits of Novogene Total RNA Sequencing

high-performance, High-accuracy

Achieve high-throughput, high-accuracy transcriptome profiling with stringent quality standards (Q30 ≥ 85%) and low RNA input requirements—ideal for sensitive or precious samples.

Proven Expertise and Reliable Outcomes

Benefit from Novogene’s extensive experience in thousands of RNA-seq projects, supporting high-impact publications and providing dependable, well-validated transcriptomic datasets.

Comprehensive Total RNA Analysis

Strand-specific, Regulatory Aware Insights

Publication Ready Bioinformatics Support

Applications of Total RNA‑seq

In‑Depth Transcriptome Exploration

Profile known and novel transcripts, quantify expression changes, and detect RNA variations across the entire transcriptome—supporting comprehensive discovery and characterization.

Novel Biological Insight & Biomarker Discovery

Target Prediction & Functional Interaction Analysis

Predict RNA–RNA and RNA–gene interactions to uncover regulatory targets, downstream pathways, and functional roles of coding and non‑coding RNAs.

Regulatory Network Characterization

Investigate lncRNA–mRNA regulatory relationships and broader gene expression networks to understand molecular mechanisms underlying development, stress response, and disease progression.

Applications of Total RNA‑seq

In‑Depth Transcriptome Exploration

Profile known and novel transcripts, quantify expression changes, and detect RNA variations across the entire transcriptome—supporting comprehensive discovery and characterization.

Novel Biological Insight & Biomarker Discovery

Target Prediction & Functional Interaction Analysis

Predict RNA–RNA and RNA–gene interactions to uncover regulatory targets, downstream pathways, and functional roles of coding and non‑coding RNAs.

Regulatory Network Characterization

Investigate lncRNA–mRNA regulatory relationships and broader gene expression networks to understand molecular mechanisms underlying development, stress response, and disease progression.

Specifications

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

Project Workflow

Specifications

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

Sample Requirements

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

Library Type (All workflows use rRNA‑depletion)	Sample Type	Amount	RNA Integrity Number	Purity (NanoDrop)
lncRNA Library	Total RNA	≥ 300 ng	RIN ≥ 5.5, smooth baseline	OD260/280≥ 2.0; 0D260/230≥ 2.0; no degradation, no contamination
	Total RNA (human, mouse, rat)	≥ 25 ng	RIN ≥ 5.5, flat baseline
	Total RNA (blood; human, mouse, rat)	≥ 120 ng	RIN ≥ 5.5, flat baseline
Exosomal lncRNA Library	Exosomal RNA	≥ 5 ng	Fragment size 25–200 nt, FU* > 10
Dual RNA Library	Total RNA	≥ 1 µg	RIN ≥ 6.5, flat baseline

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

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 Platform	Illumina NovaSeq Plus
Recommended Data Output	≥ 40 million read pairs per sample
Recommended Sequencing Depth	≥ 40 million read pairs per sample for species with reference genome
Data quality	Guaranteed ≥ 85% bases with Q30 or higher
Standard Data Analysis	• Data QC (adapter, ambiguous, and low‑quality read filtering) • Read mapping & transcript prediction • Alternative splicing quantification & differential AS (comparison groups) • Structural transcript analysis • lncRNA prediction • Transcript expression quantification • SNP/InDel detection & annotation • Transcript assembly • Correlation analysis (requires biological replicates) • Differential expression analysis (comparison groups) • lncRNA target prediction • Candidate lncRNA filtering • Co‑location & co‑expression analysis of lncRNA–mRNA pairs • KEGG pathway enrichment • Functional analysis of differentially expressed mRNAs/lncRNA targets • Transcription factor annotation • Protein–protein interaction (PPI) analysis • Fusion gene detection (tumor/cancer samples only)

Project Workflow

Resources

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Coding Potential Filtering

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Feature Comparison of lncRNA and mRNA

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Distribution of Expression Levels

Expression distributions are visualized using log10(FPKM + 1). The x-axis represents sample names, and the y-axis displays the transformed expression values.

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Volcano Plot of Differential Genes

The volcano plot illustrates differential gene expression, with the x-axis showing fold change between groups and the y-axis indicating statistical significance (e.g., –log10 p-value).

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Heatmap of Differentially Expressed Genes

Resources

1/1

Coding Potential Filtering

1/1

Feature Comparison of lncRNA and mRNA

1/1

Distribution of Expression Levels

Expression distributions are visualized using log10(FPKM + 1). The x-axis represents sample names, and the y-axis displays the transformed expression values.

1/1

Volcano Plot of Differential Genes

The volcano plot illustrates differential gene expression, with the x-axis showing fold change between groups and the y-axis indicating statistical significance (e.g., –log10 p-value).

1/1

Heatmap of Differentially Expressed Genes

Frequently Asked Questions

What types of RNA are captured in Total RNA-seq?

What sample types are accepted?

How much RNA is required?

What sequencing strategy does Novogene use?

Why use rRNA depletion instead of poly(A) selection?

Can Total RNA-seq identify novel lncRNAs?

What downstream analyses are included?

Does Total RNA-seq support regulatory network analysis?

How is data delivered?

Can Total RNA-seq analyze low-input or degraded samples?

More Services

Full-Length Transcriptome Sequencing

Metatranscriptome Sequencing

mRNA Sequencing

Prokaryotic RNA Sequencing

Small RNA Sequencing

Whole Transcriptome Sequencing

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