April 11, 2025
For decades, scientists have been dependent on complementary DNA (cDNA) synthesis for research on RNA. However, this approach has significant drawbacks because converting RNA to cDNA introduces biases, artifacts, and loss of transcript diversity, limiting our ability to capture the true complexity of the transcriptome.
This raises a critical question: Can you sequence RNA directly without altering its natural structure? Yes! You can use direct RNA sequencing (DRS). Unlike traditional methods, DRS bypasses cDNA synthesis and amplification steps, allowing RNA molecules to be sequenced in their native form. Nanopore-based Direct RNA Sequencing (DRS) is an advanced technology that enables real-time sequencing of full-length RNA molecules without requiring amplification or fragmentation.
One of the most promising advancements in DRS is its application on nanopore arrays. By passing RNA molecules through nanopores, this approach enables real-time sequencing with minimal preparation. Let’s explore these concepts in depth below and try to understand direct DNA sequencing on nanopore arrays, features, advantages, applications, and more.
Source: NIH
Exploring the comparison between direct RNA sequencing (DRS) and traditional RNA sequencing will help us better understand how DRS can offer an advantage by overcoming limitations.
Traditional RNA-seq methods rely on cDNA synthesis, which introduces several biases and artifacts that can affect transcript identification and quantification. One major issue is the generation of spurious second-strand cDNA, which complicates strand-specific RNA-seq.
Template switching during reverse transcription can create chimeric cDNAs, leading to errors in identifying exon-intron boundaries and true chimeric transcripts. Additionally, reverse transcriptases have poor fidelity due to the lack of proofreading mechanisms, resulting in sequencing errors.
Other limitations include non-uniform transcript coverage caused by priming and amplification biases, transcript-length bias due to multiple fragmentation steps, and challenges in accurately quantifying transcripts due to mapping uncertainties. Short read length is also a significant problem in traditional RNA sequencing (RNA-seq).
DRS eliminates many of these issues by bypassing cDNA synthesis and sequencing RNA molecules in their native form. This removes template switching errors, reduces biases from amplification, and allows for more accurate detection of transcript boundaries, polyadenylation sites, and modifications.
DRS also requires significantly less RNA input, making it ideal for analyzing small RNA quantities or degraded samples. Furthermore, it provides a more straightforward approach to studying both short and long RNA species without separate protocols.
While DRS still faces challenges, such as generating high read quantities and reducing error rates, its ability to sequence RNA directly offers a more comprehensive and less biased view of transcriptomes compared to cDNA-based methods. Also, DRS can offer long reads, especially with nanopore-based technologies.
Now that you have explored how DRS overcomes the limitations of traditional RNA sequencing (RNA-seq), you’ll explore direct RNA sequencing using a nanopore array below.
Characterizing viral transcriptomes with high gene density, overlapping reading frames, and intricate splicing patterns is complex. Nanopore-based direct RNA sequencing (DRS) presents a good alternative by allowing the sequencing of individual polyadenylated RNAs in their native form, eliminating recording and amplification biases.
This technology is particularly useful for studying viruses like herpes simplex virus type 1 (HSV-1), whose transcriptome consists of numerous polyadenylated RNAs, including both coding and noncoding elements. DRS using nanopore technology allows for the real-time sequencing of native RNA molecules without the need for reverse transcription or amplification. Below, you’ll explore the procedure of direct RNA sequencing on nanopore arrays.
Below is a comprehensive procedure of the DRS using nanopore technology:
Cells are cultured in appropriate media with necessary supplements. After this, RNA is extracted using tools like TRIzol reagent (Invitrogen) following the manufacturer’s protocol. The RNA integrity or quality is checked using an Agilent Bioanalyzer 2100 with an RNA 6000 nanochip. Then poly(A)+ RNA is isolated from total RNA using the Dynabeads™ mRNA Purification Kit (Invitrogen).
After the cell culture and RNA extraction step, the library preparation is generated from poly(A)+ RNA. A synthetic calibration strand (Enolase 2 RNA) is spiked into the sample. Libraries are prepared for sequencing using the Oxford Nanopore Technologies (ONT) protocol. Standard protocols recommend starting with 500 ng to 1 µg of total RNA or 25–500 ng of mRNA. The inclusion of a synthetic calibration strand, such as Enolase 2 RNA, is optional and can serve as a control for sequencing performance.
After library preparation, samples are sequenced using tools like Oxford Nanopore MinION MkIb with R9.4 flow cells. The sequencing is performed for 18 hours and can be adjusted based on experimental needs. Basecalling software, such as Albacore or its successors, processes raw data to generate readable sequences.
It is also important to involve the procedure of error correction that can be done using Illumina data. Illumina sequencing is performed using a HiSeq 4000 with paired-end reads (2 × 76 bp). FLASh software can be used to merge overlapping reads before correction. Nanopore reads are corrected using Proovread, leveraging subsampled Illumina RNA-Seq reads (250,000–5,000,000 reads).
Here comes the alignment, and the analysis of the basecalled reads is aligned using Minimap2 with splice-aware settings. Transcripts are mapped to the reference genome and analyzed for splice junctions, transcript boundaries, and fusion transcripts. Then, BAM files are processed and visualized using tools like SAMtools, BEDtools, and IGV.
This is the step of data processing that is done by performing PCR and RT-qPCR to validate splice-site usage. Protein expression is analyzed using Western blotting and immunoprecipitation. Data visualization is done using GViz and GenomicFeatures in RStudio.
Lastly, depositing processed sequencing data in public repositories, such as the European Nucleotide Archive (ENA), is a common practice to ensure data accessibility for further analysis.
Above, you explore the steps or procedure of the DRS using nanopore technology; now, below, you’ll examine the application for nanopore-based direct RNA sequencing (DRS) in different fields.
Do you know? Nanopore sequencing originated in the 1980s, but it wasn’t until the 1990s that researchers detected recognizable ionic current blockades from RNA and DNA homopolymers. Two major advancements accelerated its development: the engineering of wild-type α-hemolysin protein, which allowed the differentiation of DNA bases on oligonucleotides, and the use of specific processive enzymes to slow DNA movement through the nanopore, improving sequencing accuracy.
Nanopore-based direct RNA sequencing (DRS) has been gaining popularity for its affordability, straightforward library preparation, and ability to detect single-molecule RNA modifications. It offers ample applications, ranging from viral genome sequencing and RNA modification detection to full-length transcriptome analysis in both model and non-model organisms. Below, you explore some of these applications.
Nanopore-based direct RNA sequencing (DRS) is useful for capturing the complexity of viral transcriptomes, including subgenomic RNA (sg mRNA) populations and splicing events that are difficult to reconstruct using short-read sequencing platforms. DRS can also be applied to characterize the generated recombined RNA molecules.
For example, DRS was applied to characterize the recombined RNA molecules generated during the infection of porcine reproductive and respiratory syndrome virus (PRRSV) in porcine alveolar macrophages. By using two PRRSV isolates, XM-2020 and GD, the sequencing data revealed an intricate transcriptional landscape, highlighting differences in subgenomic recombination patterns and previously unobserved TRS-independent subpopulations.
RNA modifications, particularly N6-methyladenosine (m6A), play a crucial role in gene regulation, yet traditional sequencing methods struggle to detect them at single-nucleotide resolution. To overcome these challenges, researchers developed m6Anet, a machine-learning model designed to identify m6A sites.
For example, nanopore technology, specifically Nanopore Direct RNA Sequencing (DRS), was applied to detect and analyze N6-methyladenosine (m6A) modifications in RNA. Unlike previous approaches that require m6A-free control samples or rely on short-read sequencing, m6Anet, EpiNano and Tombo leverage neural networks to analyze signal intensity variations in long-read Nanopore data.
N6-methyladenosine (m6A) is a key modification in messenger and circular RNAs, influencing various aspects of RNA metabolism. While m6A modifications have been widely studied in linear RNAs, their presence in plant circular RNAs remained unverified due to the limitations of existing methods. To address the traditional approach's challenges, researchers developed a novel approach that enables precise identification of m6A modifications in plant circular RNAs using Nanopore-based Direct RNA Sequencing (DRS).
For example. A study found that about 10% of exonic circular RNAs contained m6A sites, primarily near acceptor and donor splice sites, offering new insights into RNA modifications in non-polyadenylated transcripts. This antibody-independent method demonstrates the power of nanopore sequencing in detecting RNA modifications with high accuracy, expanding the possibilities for studying epitranscriptomics in plant systems.
Enteroviruses are RNA viruses responsible for a range of diseases affecting millions worldwide. Traditional PCR-based diagnostic methods, often combined with partial sequencing, are commonly used for enterovirus identification but do not provide full-genome sequencing directly from clinical samples. In this study, researchers tested nanopore-based direct RNA sequencing (DRS) as a rapid approach to whole-genome sequencing of enteroviruses directly from patient stool samples.
For instance, the nanopore DRS method successfully generated long RNA fragments, covering 59% to 99.6% of the reference enterovirus genomes, confirming its ability to identify viral genotypes. Comparisons between DRS and Illumina MiSeq sequences showed 94% to 97% identity, validating the approach's accuracy. Additionally, Nanopore DRS provided rich metatranscriptomic data, offering insights into other RNA molecules present in the samples.
These are some of the examples that display the capabilities of nanopore-based direct RNA sequencing (DRS); below, you’ll explore some limitations of this technology to better understand this concept.
While nanopore-based direct RNA sequencing (DRS) offers several advantages, it also has certain limitations:
These limitations are essential for you to consider, as they represent areas where nanopore DRS still faces challenges. Understanding these points will help in managing expectations regarding the technology’s current capabilities and the ongoing research aimed at overcoming these limitations.
Nanopore-based Direct RNA Sequencing (DRS) enables real-time sequencing of full-length RNA molecules without the need for cDNA conversion or amplification, reducing biases in transcriptome analysis. Its application on nanopore arrays enhances throughput and efficiency, making it valuable for studying viral transcriptomes, RNA modifications like m6A, and whole-genome sequencing in clinical and plant research. Despite its advantages, DRS faces challenges such as higher error rates, RNA degradation sensitivity, and difficulties in reading non-polyadenylated RNAs.
However, ongoing improvements in nanopore technology and machine learning-based error correction are addressing these limitations. DNA sequencing has long been the standard in genomics, compared to RNA sequencing, which offers advantages by directly sequencing RNA molecules, providing a clearer view of gene expression and modifications. While DNA sequencing focuses on the genome itself, RNA sequencing, especially DRS, reveals the dynamic nature of gene activity, such as alternative splicing and RNA modifications.
As you explored the DRS in depth above, platforms like Biostate.ai contribute to research on RNA and genes by offering complete RNA sequencing and comprehensive insight into any sample at an affordable rate. The team handles all the procedures and offers high-quality and reliable results. Get Your Quote Now!
Nanopore RNA sequencing is a method that allows the direct sequencing of full-length RNA molecules without the need for reverse transcription or amplification. It works by passing native RNA strands through a biological nanopore, where changes in electrical current are measured to determine the sequence, including RNA modifications and poly(A) tail lengths.
Nanopore sequencing operates on the principle of detecting electrical current changes as nucleotides pass through a nanopore embedded in a membrane. Each nucleotide or modification causes a unique disruption in the current, allowing for real-time sequencing. This method enables long-read sequencing, capturing full-length RNA molecules and preserving native modifications.
Nanopore sequencing has a higher error rate than Illumina, which restricts its use in high-resolution epidemiological surveillance. However, advances in base-calling algorithms and error-correction tools, such as Dorado and Guppy, have significantly improved their accuracy. For most organisms, median read accuracy ranges between 88% and 92%, with mouse and zebrafish datasets showing the lowest accuracy at 87.8% and 86.7%, respectively.
Both PacBio and Nanopore have strengths depending on the application. PacBio HiFi sequencing offers higher accuracy (~99%), making it ideal for genome assembly and error-sensitive applications. Nanopore sequencing, on the other hand, provides real-time sequencing, ultra-long reads, and direct RNA sequencing capabilities, making it more suitable for transcriptomics and epitranscriptomics.
