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What is Bulk RNA Sequencing?

10’
Protocol and guide

The basics of bulk RNA sequencing

Bulk RNA sequencing (bulk RNA-seq) is a powerful transcriptomic tool that measures gene expression across a pooled population of cells or tissue. Unlike single-cell RNA sequencing (scRNA-seq), which captures individual cellular profiles, bulk RNA-seq provides an averaged snapshot of gene activity, making it ideal for studying homogeneous tissues or large-scale trends. This makes it particularly useful for identifying genes that are up- or downregulated under different biological conditions, such as disease vs. healthy states.

Cost and Practicality

Bulk RNA-seq is significantly more cost-effective than single-cell approaches. While scRNA-seq can cost hundreds to thousands of dollars per sample due to its complexity and data volume, bulk RNA-seq offers a more accessible entry point for many labs, especially when analysing large sample cohorts or conducting preliminary screens.

Why Choose Bulk RNA-seq?

Researchers opt for bulk RNA-seq when:

  • Investigating gene expression in homogeneous tissues or cell lines
  • Conducting differential expression analysis between conditions
  • Profiling transcriptomes in large-scale studies where single-cell resolution is unnecessary

How Does Bulk RNA-seq Work?

1. Sample Collection for RNA Extraction

Sample collection is a critical first step in bulk RNA sequencing, as it directly influences the quality and reliability of downstream analyses. 

Tissue or Cell Lysis

The first step in the bulk RNA sequencing workflow involves breaking open cells or tissues to release intracellular contents, including RNA, typically achieved through mechanical methods (e.g., bead beating, homogenisation, or sonication), chemical lysis (using detergents or chaotropic agents that solubilise cell membranes), or enzymatic digestion (such as with proteinase K or lysozyme to break down cellular components).

Often, a combination of these approaches is used to ensure efficient lysis across various sample types. Throughout this process, it is critical to preserve RNA integrity by minimising RNase activity. This is usually achieved through the addition of RNase inhibitors and by maintaining samples on ice or at low temperatures.

Total RNA Isolation

RNA is extracted using reagents like TRIzol or column-based kits. The goal is to isolate high-quality total RNA, including mRNA, rRNA, and non-coding RNAs.

Once cells are lysed, the next step in traditional workflows is to extract total RNA from the lysate. This is commonly achieved using phenol-chloroform-based reagents such as TRIzol, which separates RNA from DNA and proteins via phase separation, or silica column-based purification kits, which isolate RNA by binding it to a membrane for subsequent washing and elution. The objective is to obtain high-quality, intact total RNA, including various RNA species such as messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and non-coding RNAs (e.g., miRNA, lncRNA). High-quality RNA isolation is essential to minimise contaminants like genomic DNA and proteins that could interfere with downstream enzymatic reactions and sequencing accuracy.

Singleron’s bulk RNA sequencing platform, AccuraCode®, streamlines this process by eliminating the need for traditional RNA extraction. Instead, it employs cell barcoding technology to directly label and capture RNAs from lysed cells. This innovation significantly reduces hands-on time and simplifies the workflow, offering a faster and more efficient alternative to conventional extraction-based methods.

RNA Quality Control

Before proceeding to library preparation, the quality and quantity of isolated RNA must be assessed. RNA concentration and purity are typically measured using spectrophotometric methods (e.g., NanoDrop) or fluorometric assays (e.g., Qubit). More importantly, RNA integrity is evaluated using capillary electrophoresis systems such as the Agilent Bioanalyzer or TapeStation, which provide an RNA Integrity Number (RIN). A RIN value greater than 7 typically reflects high-quality, intact RNA suitable for high-throughput sequencing, ensuring reliable downstream results. Poor RNA quality can lead to biased or unreliable sequencing results, making this a critical quality control step.

2. Selecting mRNA for Analysis

Once high-quality total RNA is obtained, the next critical step is to enrich for transcripts of interest, most commonly messenger RNAs (mRNAs). This is achieved through two main strategies: poly(A) selection and ribosomal RNA (rRNA) depletion, each suited for different types of samples and experimental goals.

Poly(A) Selection vs. rRNA Depletion

– Poly(A) selection uses oligo(dT) primers that bind specifically to the polyadenylated tails found at the 3′ ends of mRNAs. This method effectively enriches for protein-coding transcripts while removing the majority of non-coding RNAs, such as rRNA and tRNA. It is best suited for high-quality RNA samples with intact poly(A) tails and is commonly used when the primary interest is gene expression profiling of coding transcripts.

– rRNA depletion removes abundant ribosomal RNA species (typically comprising over 80% of total RNA) through hybridisation-based capture and enzymatic digestion. This approach is advantageous for analysing degraded RNA samples (e.g., from formalin-fixed, paraffin-embedded tissues), as well as for detecting non-polyadenylated transcripts such as certain long non-coding RNAs (lncRNAs), histone mRNAs, and circular RNAs.

Total RNA Isolation

Following transcript selection, RNA samples may undergo additional purification steps to remove unwanted fragments and contaminants. These additional clean-up procedures help to improve the specificity and overall yield of the target RNA population, which is important for generating high-quality sequencing libraries.

RNA Quality Control

Post-selection and purification, RNA quality and concentration are re-evaluated using spectrophotometric or fluorometric methods (e.g., NanoDrop, Qubit), along with integrity assessment tools such as the Agilent Bioanalyzer or TapeStation. This step ensures that the RNA is of sufficient quality and quantity for successful library preparation and subsequent sequencing.

3. RNA Fragmentation

To prepare RNA for sequencing, it must first be broken down into smaller, manageable fragments—typically around 200 base pairs (bp) in length. This fragmentation step facilitates efficient cDNA synthesis and ensures even coverage across transcripts during sequencing. Fragmentation can be achieved through enzymatic digestion (using RNases) or chemical methods (e.g., using divalent cations at elevated temperatures). The method and extent of fragmentation are carefully controlled, as over-fragmentation can result in loss of information, while under-fragmentation may hinder library construction.

4. The Best cDNA Synthesis Protocol

Following fragmentation, the RNA fragments are reverse transcribed into cDNA. This step is catalysed by reverse transcriptase, often in combination with random hexamer primers or oligo(dT) primers, depending on the RNA selection strategy. Random primers are commonly used to ensure that the entire length of RNA fragments is captured, regardless of their polyadenylation status. This step is crucial for converting unstable RNA molecules into more stable DNA templates suitable for sequencing. High-fidelity reverse transcription is essential for preserving transcript diversity and preventing bias in downstream quantification.

5. cDNA Library Construction

Once cDNA is synthesised, sequencing libraries are prepared. This involves several steps:

  • End repair and A-tailing: The ends of cDNA fragments are blunted and adenylated to allow efficient adapter ligation.
  • Adapter ligation: Short, double-stranded DNA adapters containing sequencing platform-specific sequences and sample-specific barcodes (indexes) are ligated to both ends of each cDNA fragment.
  • PCR amplification: The adapter-ligated cDNA is amplified using polymerase chain reaction (PCR) to increase the amount of material available for sequencing.

The final cDNA libraries are quality-checked and quantified before being loaded onto high-throughput sequencing platforms such as Illumina’s NovaSeq or NextSeq. These platforms generate millions of short reads per sample, enabling comprehensive and quantitative analysis of the transcriptome.

The Workflow at a Glance

mRNA/Tissue/ Cells/TriZol Samples

mRNA Barcoding & One-step RT Amplification

Multiplexing

Library Generation

Sequencing

Bioinformatics Analysis

Workflow of bulk RNA sequencing (RNA-seq)

Here are the key steps in bulk RNA-seq, starting with sample collection and cell/tissue lysis to extract total RNA. This is followed by RNA purification, quality assessment, and fragmentation. The RNA is then converted to complementary DNA (cDNA), which undergoes library preparation, amplification, and high-throughput sequencing. The resulting sequencing data is processed through bioinformatic analysis pipelines to quantify gene expression and identify differentially expressed genes across experimental conditions.

Singleron’s Bulk RNA-seq service

Having a high number of samples that require quick, large-scale screening? 

We offer a comprehensive, end-to-end bulk RNA-seq service that includes:

  • Project consultation to tailor experimental design
  • Flexible sample input (tissue, cells, TRIzol, or mRNA)
  • High-quality library prep and sequencing
  • Advanced bioinformatics analysis with publication-ready reports
  • Dedicated project management for seamless communication

What sets Singleron apart?

  • Integration with our single-cell and multi-omics platforms
  • Use of proprietary reagents and protocols for superior data quality
  • Global service labs trusted by academia, biotech and pharma alike

Book a Free Consultation!

Bulk RNA-seq vs. Single-Cell RNA-seq

How Does Single-Cell RNA-seq Work?

Single-cell RNA sequencing (scRNA-seq) allows researchers to study gene expression at the resolution of individual cells. The process begins by isolating single cells from a complex tissue or sample, often using microfluidics, droplet-based systems, fluorescence-activated cell sorting (FACS), or microwell-based methods. Once isolated, the RNA within each cell is captured and reverse-transcribed into cDNA. This cDNA is then amplified and sequenced, producing a detailed transcriptome profile for each individual cell. By analysing these profiles, we can uncover cellular heterogeneity, identify rare or previously unknown cell types, and track dynamic changes in gene expression that occur during development, disease progression, or in response to treatments. This single-cell approach provides a much more nuanced understanding of biological systems compared to traditional methods.

Bulk or Single-Cell RNA-seq: Which Method Fits Your Study?

Choosing between bulk RNA-seq and scRNA-seq depends largely on your research goals and the level of detail you need. Bulk RNA-seq analyses RNA from a mixed population of cells, providing an average gene expression profile that reflects the overall sample. This approach is efficient, cost-effective, and ideal if you’re interested in broad gene expression trends across tissues or cell populations. However, it does not reveal differences between individual cells or detect rare cell types.

On the other hand, scRNA-seq examines gene expression at the level of individual cells, uncovering cellular diversity and revealing subtle differences that bulk methods miss. This makes it the preferred choice when studying complex tissues, developmental processes, or diseases like cancer, where heterogeneity and rare populations are important. Although scRNA-seq can be more expensive and technically demanding, it provides richer data that can lead to deeper biological insights.

In summary, if your focus is on understanding differential gene expression across many cells, regardless of the specific cell type, or you have limited resources, bulk RNA-seq may be the best fit. But if you need to explore cellular heterogeneity or identify unique cell types, investing in scRNA-seq will give you a much more detailed and informative picture.

Comparative overview of bulk RNA sequencing and single-cell RNA sequencing

Comparative overview of bulk RNA sequencing and single-cell RNA sequencing

Illustration of the key differences between bulk RNA-seq and scRNA-seq in terms of sample input, data resolution, and analytical outputs. Bulk RNA-seq captures an average gene expression profile from a pooled cell population, while scRNA-seq enables transcriptomic analysis at the individual cell level, uncovering cellular heterogeneity.

Read more: Exploring Single-Cell RNA Seq with Singleron Solutions

Conclusion

Bulk RNA sequencing remains a cornerstone of transcriptomics, offering a balance of depth, affordability, and scalability. Singleron Biotechnologies enhances this approach with personalised support, high-quality data generation, and seamless integration into a broader suite of genomic solutions. Whether you’re exploring gene expression in tissues or laying the groundwork for single-cell follow-up, Singleron’s bulk RNA-seq service is a smart, reliable, and strategic choice.

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A post by Marisa Amato

Dr. Marisa Amato is a scientist-turned-strategic leader, serving as Business Development Manager for Singleron Biotechnologies across the UK and Ireland. With a PhD in Clinical Neuroscience and Molecular Biology, Marisa brings a rare combination of deep scientific knowledge and commercial insight to help researchers and industry partners unlock the full potential of single-cell and multi-omics technologies.

At Singleron, she works at the intersection of science and innovation, supporting academic institutions, biotech companies, and pharma companies with tailored solutions for tissue dissociation, single-cell sequencing, and multi-omics applications. Her role bridges basic scientific discovery and clinical applications, ensuring researchers have the tools they need to accelerate breakthroughs.

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