Methods and Challenges in Long Non-coding RNA Sequencing

Long non-coding RNA sequencing has become an essential tool for understanding the intricate roles of non-coding RNAs in gene regulation, cellular processes, and disease mechanisms. 

Unlike protein-coding genes, long non-coding RNAs (lncRNAs) do not translate into proteins but play critical roles in regulating gene expression, chromatin structure, and RNA processing. 

Despite their significance, the expression of most lncRNAs is significantly lower than protein-coding transcripts, which introduces challenges in transcriptome reconstruction.

This low abundance often results in incomplete or erroneous transcript assembly during RNA sequencing experiments, complicating downstream analyses.

This article explores the methods used in long non-coding RNA sequencing, as well as the challenges researchers face when studying these crucial molecules.

Methods in Long Non-coding RNA Sequencing

The complexity of long non-coding RNA (lncRNA) biology necessitates the application of highly specific sequencing techniques designed to capture their diverse characteristics.

Unlike protein-coding transcripts, lncRNAs typically exhibit low expression levels, variable polyadenylation, complex exon-intron structures, and distinct subcellular localization. 

This structural and functional diversity demands precision in sample preparation, RNA enrichment, library construction, and computational analysis. Below is a comprehensive and detailed exploration of the principal methods currently utilized in lncRNA sequencing.

1. Poly(A)-selected RNA Sequencing

Polyadenylated RNA selection remains one of the most widely used methods for sequencing poly(A)+ transcripts, which include a substantial portion of long non-coding RNAs (lncRNAs). The core principle of this approach is the selective enrichment of RNA species with poly(A) tails, which are predominantly found in many lncRNAs and protein-coding mRNAs. 

The method relies on the ability of oligo(dT) beads or magnetic particles to specifically capture poly(A) tails. This isolates polyadenylated RNAs while excluding the vast majority of rRNAs and non-polyadenylated RNAs. This results in the generation of a refined RNA pool that is more suitable for subsequent sequencing analysis.

Principle: Polyadenylated RNAs are captured by oligo(dT) beads that specifically bind the poly(A) tail present in most lncRNAs and mRNAs. This process allows for the exclusion of non-polyadenylated species, such as rRNAs, which dominate total RNA pools.

Workflow:

• RNA is extracted from cells or tissues, ensuring minimal degradation during collection.
• The poly(A) RNA is captured using oligo(dT) magnetic beads that selectively bind to the poly(A) tails of RNA transcripts.
• The enriched RNA is fragmented into smaller pieces to facilitate efficient cDNA synthesis.
• First-strand and second-strand cDNA synthesis is performed, utilizing reverse transcriptase and DNA polymerase.
• Adapters are ligated to the cDNA fragments, and PCR amplification is conducted to prepare the library.
• Sequencing is performed on high-throughput platforms such as Illumina NovaSeq, allowing for deep coverage of lncRNA expression levels.

This method is particularly effective for profiling lncRNAs that undergo canonical mRNA-like processing, which includes those with polyadenylation. However, poly(A)-selection does exclude non-polyadenylated and some tissue-specific lncRNAs from the analysis, which may require complementary techniques for comprehensive transcriptome profiling.

2. rRNA-depleted Total RNA Sequencing

Total RNA sequencing without poly(A) selection is critical for capturing a broader spectrum of lncRNAs, particularly those that lack polyadenylation. 

Ribosomal RNA (rRNA), which comprises more than 90% of total RNA, is efficiently removed using sequence-specific probes. This removal enables deeper insights into both coding and non-coding RNA populations.

This method ensures that a variety of lncRNAs—such as nuclear-retained, enhancer, and intergenic lncRNAs—are captured and sequenced, which is essential for comprehensive transcriptomic analysis.

Principle: Sequence-specific probes (e.g., Ribo-Zero, NEBNext) hybridize to rRNA, and enzymatic digestion removes it. This allows the enrichment of non-rRNA species, including lncRNAs, which are typically present at lower abundance.

Workflow:

1. Total RNA is isolated from the sample, ensuring minimal degradation.
2. rRNA depletion occurs by hybridizing probes to rRNA and performing enzymatic digestion to eliminate it.
3. The remaining RNA, enriched for non-coding and coding species, is fragmented into smaller pieces.
4. cDNA synthesis is performed using reverse transcriptase, followed by second-strand synthesis.
5. Sequencing adapters are ligated, and PCR amplification prepares the sequencing library.
6. Sequencing is performed using high-throughput platforms such as Illumina.

This method is essential for the unbiased detection of non-polyadenylated lncRNAs, especially those involved in chromatin remodeling and other regulatory processes. It also captures lncRNAs associated with complex regulatory regions, such as enhancer RNAs (eRNAs), which are often missed in poly(A)-selected RNA sequencing.

Biostate AI enhances this process by making RNA sequencing more accessible and cost-effective. The platform offers Total RNA-Seq services for various sample types—FFPE tissue, blood, and cell cultures—covering everything from RNA extraction to sequencing and comprehensive data analysis. 

This end-to-end service ensures that researchers can gain valuable insights into complex transcriptomes and study multi-organ impacts, making it an invaluable tool for longitudinal research.

3. Strand-specific RNA Sequencing

Strand-specific RNA sequencing is essential when dealing with complex loci where both protein-coding genes and lncRNAs are transcribed from opposite strands or share overlapping regions. 

This method preserves the orientation of the RNA strand, ensuring that the directionality of transcription is maintained. Understanding the transcriptional orientation is especially crucial for differentiating sense and antisense lncRNAs, which often arise from bidirectional promoters or overlapping genomic regions.

Principle: Directional RNA sequencing preserves strand identity, enabling the accurate assignment of reads to either the sense or antisense strand. This is crucial for lncRNAs, which frequently overlap with protein-coding genes or are transcribed antisense to coding regions.

Chemistries Employed:

• dUTP-based strand specificity: During second-strand synthesis, dUTP is incorporated in place of dTTP, causing DNA polymerase to stall at uracil residues. The strand containing dUTP is degraded during amplification, thus preserving the directionality of the RNA.
• Adapter-ligation methods: Specific adapters are ligated to the 5′ ends of RNA transcripts before reverse transcription. The directionality of the RNA is preserved through ligation and reverse transcription, which ensures accurate strand assignment during sequencing.

Strand-specific methods are compatible with both poly(A)-selected and rRNA-depleted RNA sequencing, offering high-resolution profiling of antisense lncRNAs and other regulatory elements.

These protocols are essential for accurate annotation of lncRNAs, especially those involved in antisense regulation, enhancer activities, and gene silencing. They are indispensable for studies involving transcriptional overlaps, such as bidirectional promoters and sense-antisense pairs.

4. Cap Analysis Gene Expression (CAGE) and 5′ RACE

CAGE and 5′ RACE are both specialized techniques aimed at accurately identifying and mapping transcription start sites (TSS) of lncRNAs. These methods are critical when studying the initiation of transcription, especially for lncRNAs involved in gene regulation and enhancer activities.

• CAGE (Cap Analysis of Gene Expression): CAGE captures the 5′ ends of capped RNA molecules using a cap-trapping technique, which is followed by linker ligation and reverse transcription. This method provides high-resolution mapping of active TSSs and promoter usage across the genome, allowing for the identification of novel transcription initiation sites.
• 5′ RACE (Rapid Amplification of cDNA Ends): This method focuses on identifying unknown 5′ ends of RNA transcripts. After reverse transcription, nested PCR amplifies the 5′ ends, enabling the discovery of novel TSSs and verification of lncRNAs involved in enhancer-promoter interactions and other regulatory functions.

CAGE is particularly useful for generating a high-resolution map of the transcriptome’s start sites, which is vital for understanding promoter regulation. While 5′ RACE is an excellent complementary tool for verifying TSSs and determining the boundaries of lncRNAs associated with regulatory regions.

A study demonstrated the utility of CAGE in mapping TSSs of lncRNAs and its role in identifying transcriptional regulatory elements in human and mouse genomes, which highlighted its importance in studying non-coding RNA biology.

In understanding the role of lncRNAs in disease, BC200 has emerged as a key player in cancer progression. For example, studies have shown that in colorectal and esophageal cancers, BC200 lncRNA is overexpressed, contributing to increased cell migration and invasion. These findings underscore the importance of lncRNA sequencing in identifying biomarkers with potential therapeutic applications, particularly in oncology.

5. Long-read Sequencing (Third-generation Sequencing)

Long-read sequencing platforms, such as PacBio and Oxford Nanopore, have revolutionized the field of lncRNA sequencing by enabling the capture of entire transcripts without the need for assembly.

These technologies offer significant advancements in resolving isoforms, splicing events, and complex transcript structures—challenges that short-read platforms have historically struggled to address.

Platforms:

• PacBio SMRT (Single Molecule, Real-Time): This platform produces high-accuracy circular consensus sequencing (CCS) reads, ideal for capturing the full-length structure of lncRNAs, including complex splicing events and isoform variations. This advancement has been pivotal in overcoming previous limitations related to read lengths and isoform resolution, ensuring better transcript accuracy and coverage.
• Oxford Nanopore Technologies (ONT): ONT offers portable, real-time sequencing, allowing direct sequencing of RNA molecules. This platform produces long reads, offering a more accurate picture of full-length lncRNA sequences without requiring reverse transcription. ONT’s capability to preserve RNA base modifications like m6A provides crucial insights into RNA regulation, enabling functional annotation of lncRNAs.

Advantages:

• Long-read sequencing allows for the resolution of complex isoform structures and transcript boundaries, which are often masked in short-read data.
• These platforms also enable the detection of non-canonical splicing events, alternative transcription start sites, and 3′ ends that are challenging to capture with traditional methods.
• Direct RNA sequencing, especially with ONT, preserves base modifications such as m6A, which can provide valuable insights into RNA regulation.

These technologies are invaluable for characterizing the structural complexity of lncRNAs. They enable researchers to resolve full-length isoforms and accurately map alternative splicing events, which is crucial for understanding the functional diversity of lncRNAs.

However, long-read sequencing often presents challenges in terms of cost and technical expertise. Biostate AI’s affordable, end-to-end service streamlines the entire RNA-Seq process, making it more accessible and efficient for researchers working on both large-scale studies and more targeted research applications. 

6. Targeted RNA Capture and Sequencing

Targeted RNA sequencing provides an efficient and focused approach to sequencing specific lncRNAs, particularly when dealing with low-abundance transcripts or limited sample quantities. 

By using biotinylated oligonucleotide probes that specifically bind to known lncRNAs, researchers can enrich the RNA pool for target lncRNAs, improving sensitivity and detection.

Principle: This method involves the hybridization of biotinylated probes to complementary sequences of lncRNAs, which are then captured using streptavidin-coated magnetic beads. This process ensures that only the target lncRNAs are sequenced, thus increasing the sensitivity and specificity of the assay.

Workflow:

1. RNA is fragmented, and hybridization with specific probes is performed.
2. The probe-bound RNA is captured using magnetic beads and then washed to remove non-target RNAs.
3. The captured RNA is converted into cDNA, ligated with sequencing adapters, and amplified.
4. The enriched library is sequenced using standard platforms such as Illumina.

This method is ideal for highly sensitive quantification of low-abundance lncRNAs, especially in clinical settings or with small sample sizes. It is often preferred when conventional RNA-Seq may not be feasible due to RNA degradation or limited amounts of material.

Challenges in Long Non-coding RNA Sequencing

Despite advances in sequencing technologies, several persistent challenges continue to hinder comprehensive and reproducible lncRNA characterization.

1. Low Expression Levels

lncRNAs are generally expressed at lower levels than protein-coding genes, often near the threshold of detection. Their abundance is also highly cell-type- and condition-specific. This necessitates ultra-deep sequencing or RNA enrichment techniques to achieve sufficient read coverage.

This low expression profile increases vulnerability to technical noise, reduces reproducibility across biological replicates, and can lead to erroneous conclusions in differential expression analysis. In many cases, lncRNAs may not surpass the expression cutoffs used in transcript quantification algorithms, leading to underrepresentation in downstream analyses.

2. Incomplete Annotations

Although databases like GENCODE, NONCODE, and LNCipedia have expanded lncRNA annotations, they remain incomplete, especially for tissue-specific or low-abundance transcripts. Furthermore, annotations often lack isoform resolution and functional context. Incomplete references hinder read alignment and transcript assembly. 

Many tools rely heavily on annotation-guided mapping, which may overlook novel transcripts or inaccurately assign reads to existing loci. De novo assembly methods (e.g., StringTie, Scallop) can help, but are limited by read coverage and assembly errors.

An interesting example of how lncRNA sequencing has uncovered clinically significant targets is the study of ultraconserved elements (UCEs). These sequences are highly conserved across species, and their transcribed forms, known as ultraconserved region lncRNAs (T-UCRs), have been associated with diseases like leukemia and prostate cancer. 

For instance, the T-UCR uc.160 is linked to leukemia, emphasizing the importance of sequencing in identifying disease-relevant lncRNAs that could serve as both biomarkers and therapeutic targets.

3. Short-reads vs. Long-reads

Short-read sequencing technologies, like Illumina, offer high-throughput capabilities but often face difficulties in resolving isoform diversity and complex transcript structures due to their limited read lengths. The short length of the reads makes it challenging to assemble isoforms, particularly for lncRNAs, which can have complex splicing patterns and overlapping exonic structures.

Long-read sequencing platforms, such as PacBio and Oxford Nanopore, provide significant advantages by offering full-length reads that can better resolve isoforms, alternative splicing events, and transcript boundaries. These technologies enable the capture of complex transcriptomes, which is crucial for understanding the full diversity of lncRNAs. 

However, despite these improvements, long-read data often comes with challenges like higher error rates and lower throughput compared to short-reads.

4. Isoform Diversity and Structural Complexity

lncRNAs often exhibit complex splicing patterns, multiple transcription start and end sites, and overlapping exonic structures. This structural complexity challenges short-read alignment algorithms, particularly in repetitive or GC-rich regions.

Distinguishing between true alternative splicing and sequencing artifacts requires high read depth and full-length transcript sequencing. Tools such as FLAIR, TALON, and IsoQuant are being developed to improve isoform quantification from long-read data but still require standardization and benchmarking.

5. Strand Ambiguity and Overlapping Transcripts

A significant proportion of lncRNAs are transcribed antisense to protein-coding genes or share exonic sequences with coding transcripts. Without strand-specific protocols, it is impossible to accurately assign reads to the correct gene locus.

This ambiguity not only distorts expression estimates but also complicates functional interpretations. Moreover, bidirectional promoters and enhancer RNAs further confound strand assignment in non-stranded datasets.

6. Subcellular Localization and RNA Stability

lncRNAs localized in the nucleus may escape detection due to inefficient RNA extraction, especially if they are tightly bound to chromatin or exist in structured ribonucleoprotein complexes. Conversely, cytoplasmic lncRNAs may degrade rapidly during RNA isolation.

RNA stability varies widely among lncRNAs, influenced by secondary structure, binding partners, and sequence motifs. Differential stability introduces sample-to-sample variability and complicates normalization. Specialized extraction protocols and crosslinking strategies are sometimes necessary but are not universally adopted.

Conclusion

Long non-coding RNA sequencing has significantly advanced our understanding of gene regulation and cellular processes. Despite this, capturing the full diversity of lncRNAs presents ongoing challenges due to low expression levels, complex isoform diversity, and subcellular localization. 

Techniques like poly(A)-selection, rRNA depletion, strand-specific RNA sequencing, and long-read sequencing continue to evolve, improving the accuracy and depth of lncRNA studies. Overcoming these challenges will enhance our understanding of lncRNA functions and their potential therapeutic applications.

Biostate AI provides unmatched RNA sequencing services, offering an end-to-end and affordable solution that ensures high-quality results and valuable insights for research and clinical applications.

Disclaimer

The information present in this article is provided only for informational purposes and should not be interpreted as medical advice. Treatment strategies, including those related to gene expression and regulatory mechanisms, should only be pursued under the guidance of a qualified healthcare professional. Always consult a healthcare provider or genetic counselor before making decisions about your research or any treatments based on gene expression analysis.

Frequently Asked Questions

1. What is a long intervening non-coding RNA? 

Long intervening non-coding RNAs (lincRNAs) are a type of long non-coding RNA that typically reside between protein-coding genes. They are involved in regulating gene expression, chromatin remodeling, and cellular processes without being translated into proteins.

2. How to detect long non-coding RNA? 

Long non-coding RNAs (lncRNAs) can be detected using RNA sequencing (RNA-Seq), which provides comprehensive data on RNA transcripts. Additional methods include qRT-PCR for targeted quantification and Northern blotting for larger, more specific RNA molecules.

3. How to isolate long non-coding RNA? 

Isolation of long non-coding RNA involves total RNA extraction followed by methods like rRNA depletion or poly(A) selection to enrich lncRNA. Specific kits such as Ribo-Zero can be used to remove ribosomal RNA and isolate non-coding RNA.

4. How is transcription regulated by long non-coding RNAs? 

Long non-coding RNAs regulate transcription by interacting with transcription factors, chromatin-modifying proteins, and RNA polymerase complexes. They can modulate gene expression by either enhancing or repressing the transcription of nearby genes or distant loci.