RNA sequencing (RNA-Seq) has revolutionized transcriptome analysis, providing valuable insights into gene expression, transcript structure, and variation. However, the detection of rare or low-abundance expressed genes remains a challenge due to the vast size and complexity of the transcriptome. To overcome these limitations, targeted RNA sequencing has emerged as a powerful approach that focuses on specific genes or transcripts of interest. By employing target enrichment strategies and capture baits, this technique enables sensitive and cost-effective detection of fusion genes, thereby unlocking their potential as crucial molecular markers in cancer research and clinical applications. This article delves into the intricacies of targeted RNA sequencing, emphasizing the role of target enrichment and bait-based strategies in fusion gene detection.
Fusion Genes in Cancer
Fusion genes play a pivotal role as indispensable molecular markers that possess significant clinical implications in terms of cancer diagnosis, prognosis, and targeted therapeutic interventions. The precise identification of fusion genes assumes paramount importance in comprehending the intricate process of tumor development and facilitating personalized treatment decisions.
You may be interested in our article Unveiling Gene Isoforms by RNA Sequencing: Detection Methods and Applications.
Challenges in Fusion Gene Detection
- The need for lengthy probes to cover intron regions containing numerous repetitive sequences.
- High GC content hinders effective capture of target region fragments by the probes.
- Similar repetitive sequences in introns of different genes hinder accurate sequence comparisons and impact detection accuracy.
- Complex transcriptional or post-transcriptional splicing processes can influence gene fusion.
In contrast, fusion genes at the RNA level demonstrate a distinct advantage as they exhibit a fixed articulation between the exons of the two genes before and after fusion. This characteristic provides an excellent opportunity for precise probe design. Consequently, owing to the distinctive sequence characteristics of fusion genes, detecting them at the RNA level is comparatively more feasible than at the DNA level.
Please refer to Chimeric RNA and Sequencing Technologies: Advancing Detection and Research for more information about RNA cis splicing.
Targeted RNA Sequencing: A Paradigm Shift in Fusion Gene Detection
Principle and Workflow: Targeted RNA sequencing represents a groundbreaking approach that harnesses the power of target enrichment strategies to selectively capture and sequence specific genes or transcripts of interest. The workflow encompasses several key stages, including probe or bait design, target capture, library preparation, and high-throughput sequencing.
Designing Capture Probes and Baits: To ensure utmost precision, customized capture probes or baits are meticulously designed to exclusively target the fusion junctions and the surrounding exonic regions. These sophisticated probes play a pivotal role in the accurate capture of fusion transcripts, resulting in heightened sensitivity and reduced sequencing depth requirements.
Targeted RNA Sequencing. (Hardwick et al., 2019)
Advanced Target Enrichment Strategies: In the pursuit of robust fusion gene detection, targeted RNA sequencing employs a repertoire of advanced techniques, such as hybridization-based enrichment and PCR amplification. These innovative strategies effectively enrich the captured fusion transcripts while minimizing background noise, thereby optimizing the signal-to-noise ratio and facilitating the reliable identification of fusion genes.
Unveiling the Advantages of Targeted RNA Sequencing: This cutting-edge approach offers an array of remarkable advantages. By enhancing sensitivity, targeted RNA sequencing significantly elevates the chances of detecting even the rarest fusion transcripts, alternative splicing events, and novel genetic variants. Moreover, it remarkably reduces sequencing costs by enabling focused analysis of specific genes or pathways, eliminating the need for extensive sequencing efforts and conserving valuable resources. Consequently, targeted RNA sequencing emerges as a transformative paradigm in fusion gene detection, propelling scientific research and clinical diagnostics to unprecedented heights.
Bait-Based Strategies for Fusion Gene Detection
Bait Design: The design of bait sequences involves a meticulous process to specifically target fusion junctions, exonic regions, and potential alternative splicing isoforms. Several criteria, including specificity, coverage, and uniformity across the intended regions, are considered during the selection of suitable bait sequences.
Overview of targeted RNAseq. (Heyer et al., 2019)
Hybridization Capture: The selected bait sequences are employed in a hybridization process with complementary RNA molecules, resulting in the formation of stable complexes. This critical step enables the selective capture of fusion transcripts and their associated exonic regions, thereby facilitating subsequent analysis.
Sequencing Analysis: Following the hybridization capture, the captured RNA fragments are transformed into a sequencing library and subjected to high-throughput sequencing. Advanced bioinformatics analysis tools are subsequently employed to map the obtained reads, detect fusion junctions, and characterize the breakpoints of fusion genes.
Bioinformatics Analysis and Interpretation for Targeted RNA Sequencing
Alignment and Fusion Detection: Bioinformatics pipelines facilitate the alignment of sequencing reads to the reference genome, enabling the identification of fusion junctions and breakpoints. Specialized fusion detection algorithms such as FusionCatcher, STAR-Fusion, or deFuse contribute to accurate identification and classification of fusion genes.
Quantification and Differential Expression: By quantifying the expression levels of fusion genes and their parental genes, valuable insights can be gained into their relative abundance and differential expression patterns across samples or conditions.
Alternative Splicing Analysis: Targeted RNA sequencing data empowers the characterization of alternative splicing events associated with fusion genes, augmenting our understanding of their regulatory mechanisms.
Structural Variant Analysis: Fusion gene detection can uncover structural variants, such as gene rearrangements and deletions, providing valuable information on genomic alterations linked to cancer development.
Integration with Genomic Data: The integration of targeted RNA sequencing data with other genomic data, such as DNA sequencing or epigenetic profiling, enhances the comprehensive characterization of fusion genes and their genomic context.
Applications and Beyond of Fusion Gene Detection by Targeted RNA Sequencing
Cancer Diagnosis and Prognosis: The precise detection and characterization of fusion genes through targeted RNA sequencing assist in cancer diagnosis, prognosis, and therapeutic decision-making, thereby facilitating the implementation of precision medicine approaches.
Biomarker Discovery: Fusion genes hold promise as potential biomarkers for disease monitoring, treatment response assessment, and early detection of cancer recurrence. Targeted RNA sequencing allows for the identification and validation of fusion gene biomarkers.
Drug Target Identification: Fusion genes represent actionable targets for therapeutic intervention. Targeted RNA sequencing plays a vital role in identifying fusion genes amenable to targeted therapies, thus enabling the development of novel treatment strategies.
Beyond Cancer Research: Targeted RNA sequencing demonstrates broad applications beyond cancer research, encompassing the study of gene fusions in other diseases, transcriptome analysis in developmental biology, and exploration of gene expression patterns in diverse biological processes.
Conclusion
Targeted RNA sequencing has ushered in a paradigm shift in fusion gene detection by overcoming the limitations associated with traditional RNA-Seq approaches. Leveraging target enrichment strategies and capture baits, this technique enables sensitive and cost-effective detection of fusion genes, thereby enhancing our understanding of their significance in cancer biology and opening new avenues for personalized therapeutic approaches. As advancements in probe design, target enrichment methods, and bioinformatics analysis persist, targeted RNA sequencing will undoubtedly assume a pivotal role in unraveling the intricate landscape of fusion genes and their clinical implications across diverse research fields.
References:
- Hardwick, Simon A., et al. "Targeted, high-resolution RNA sequencing of non-coding genomic regions associated with neuropsychiatric functions." Frontiers in Genetics 10 (2019): 309.
- Heyer, Erin E., et al. "Diagnosis of fusion genes using targeted RNA sequencing." Nature communications 10.1 (2019): 1388.
