Chimeric RNA and Sequencing Technologies: Advancing Detection and Research
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19 Oct 2023 05:22:15 am.
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Chimeric RNA, also known as fusion RNA, refers to RNA molecules that are formed as a result of the fusion of two or more different RNA transcripts. Chimeric RNA, a unique class of RNA molecules formed through various molecular mechanisms, such as trans-splicing, read-through transcription, and fusion genes. These hybrid transcripts play a significant role in diverse biological processes and have gained substantial attention in recent years.
Chimeric RNA Formation
Like mentioned earlier, the formation of chimeric RNAs involves multiple mechanisms. Chimeric RNA refers to a type of RNA molecule that is formed by the fusion of genetic material from two or more distinct genes. These chimeras can arise through different mechanisms, including chromosomal translocation, cis-splicing, or trans-splicing.
• Trans-splicing occurs when exons from different genes are spliced together, generating novel RNA molecules. Read-through transcription refers to the transcriptional read-through of adjacent genes, leading to the production of fusion transcripts. Fusion genes, resulting from chromosomal rearrangements, create chimeric RNA molecules by merging portions of two separate genes. These mechanisms give rise to unique transcripts that can have functional implications, such as altered protein-coding potential, regulatory effects, or generation of novel biomarkers.
• In chromosomal translocation, portions of two separate chromosomes break and rejoin, resulting in the fusion of two different genes. This rearrangement can occur within a single cell, leading to the production of chimeric RNA molecules.
• Cis splicing involves the abnormal joining of exons from two different genes located on the same chromosome. This can occur due to genetic mutations or errors in the splicing process. Trans-splicing, on the other hand, involves the joining of exons from different genes that are located on different chromosomes. This process requires the action of special trans-splicing machinery.
Chimeric RNAs have been observed in various organisms, including humans, and have been found to play a role in a variety of diseases, particularly cancer. They can contribute to tumorigenesis by generating abnormal proteins or disrupting normal cellular processes. Chimeric RNAs have also been implicated in other diseases, such as neurological disorders.
Sequencing Technologies for Chimeric RNA Detection
Chimeric RNA molecules, which arise from genomic rearrangements, alternative splicing, or fusion events, have emerged as crucial players in diverse biological processes and disease pathogenesis. Traditional sequencing methods, and next-generation sequencing (NGS) technologies as well as emerging long-read sequencing platforms, have traditionally been employed for chimeric RNA detection.
• Traditional sequencing methods, like Sanger sequencing and reverse transcription PCR (RT-PCR), have been historically employed for chimeric RNA detection. However, these techniques are limited in their ability to detect and characterize complex chimeric events and lack scalability.
• Next-generation sequencing technologies, particularly RNA-seq, have revolutionized chimeric RNA research. RNA-seq enables the high-throughput sequencing of transcriptomes, facilitating the discovery of novel chimeric events. It can efficiently identify multiple chimeric transcripts and DNA structural variants, especially when coupled with long RNA-seq reads and true chimeric mRNAs. RNA-seq provides valuable insights into transcriptome complexity and offers opportunities to study alternative splicing events and isoform diversity. Additionally, single-cell RNA-seq techniques enable the detection and analysis of chimeric RNA at the single-cell level, uncovering insights into cellular heterogeneity and disease processes.
• Emerging sequencing technologies, such as nanopore sequencing and PacBio sequencing, offer long-read sequencing capabilities. These technologies can provide valuable information about full-length chimeric transcripts, uncovering complex structural variations and alternative splicing events. But they have their own advantages and features. Nanopore sequencing offers the advantage of producing long reads, which are essential for capturing full-length chimeric transcripts, which provide information on the sequence and structural characteristics of chimeric RNA molecules, including complex structural variations and alternative splicing events. Furthermore, it enables the detection of base modifications and RNA modifications, contributing to the understanding of post-transcriptional RNA processing. PacBio sequencing, also known as Single Molecule, Real-Time (SMRT) sequencing, represents another long-read sequencing technology that holds promise for chimeric RNA analysis. This technology employs circular consensus sequencing (CCS) to generate highly accurate long reads. It offers high-resolution insights into RNA molecules and facilitates the investigation of intricate transcriptome landscapes.
Computational Analysis of Chimeric RNA Data
Chimeric RNA data analysis necessitates a multifaceted computational framework to unravel the intricacies inherent in these composite transcripts.
In general, analyzing chimeric RNA data involves several computational steps:
A. Preprocessing and quality control. Preprocessing chimeric RNA data mandates meticulous artifact filtering and curation of low-quality reads to ensure the integrity and reliability of subsequent analyses. By applying sophisticated techniques, such as noise reduction algorithms, sequence trimming, and adapter removal, spurious artifacts are mitigated, fostering robust downstream analysis.
B. Alignment and mapping. The alignment and mapping phase entails the meticulous alignment of sequencing reads to reference genomes or transcriptomes, thereby enabling the discernment of chimeric RNA junctions. This process necessitates the utilization of sophisticated alignment algorithms, including splice-aware aligners or de novo assembly methods, to accurately identify and characterize these fusion events.
C. Identification and quantification of chimeric RNA. It necessitates the deployment of specialized algorithms capable of deciphering the presence and relative abundance of chimeric transcripts. Advanced techniques, such as fusion gene detection algorithms, breakpoint analysis, or statistical modeling approaches, empower researchers to discern intricate patterns and uncover novel chimeric events lurking within the dataset.
D. Visualization and interpretation. Complex chimeric RNA structures present an intellectual challenge that demands state-of-the-art visualization and interpretation tools. These tools facilitate the comprehension of intricate chimeric RNA arrangements by offering visual representations, such as circular plots, heatmaps, or interactive networks. Integration with complementary datasets, such as gene expression profiles or functional annotations, enriches the interpretative capacity, unraveling potential functional roles and underlying mechanisms of chimeric RNA molecules.
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