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Transcriptome sequencing (RNA‑Seq) refers to the use of next‑generation high‑throughput sequencing technologies to sequence cDNA, enabling the rapid and comprehensive identification of nearly all transcripts present in a specific organ or tissue of a given species under a particular physiological state. With the advent of the post‑genomic era, various omics technologies—such as transcriptomics, proteomics, and metabolomics—have emerged one after another, with transcriptomics being the earliest to develop and the most widely applied.
RNA-Seq has the following advantages:
(1) High throughput: Using next-generation sequencing platforms, it is possible to generate tens of millions to billions of base sequences, enabling complete coverage of the entire genome or transcriptome.
(2) High sensitivity, enabling the detection of as few as a few copies of rare transcripts in cells;
(3) High resolution: RNA‑Seq achieves single‑base resolution and excellent accuracy, while avoiding the cross‑reactivity and background noise inherent in traditional microarray hybridization due to fluorescent signal artifacts.
(4) Unrestricted: It enables whole-transcriptome analysis across any species without the need to design species-specific probes in advance, allowing direct transcriptomic profiling of any organism. Moreover, it can detect previously unknown genes, identify novel transcripts, and accurately pinpoint alternative splicing sites as well as SNPs and UTR regions.
RNA‑seq technology enables the detection of the global transcriptional activity of a given species at the single‑nucleotide level, thereby providing a comprehensive and rapid overview of nearly all transcriptome information under a specific condition. Because transcriptome sequencing can quantify the abundance of all RNA transcripts with high accuracy, it has a wide range of applications, primarily including:
(1) Detect novel transcripts, including unknown and rare transcripts;
(2) Studies at the gene transcription level, such as quantifying gene expression levels and identifying differentially expressed genes across samples;
(3) Functional studies of non-coding regions, such as microRNAs, long non-coding RNAs (lncRNAs), and RNA editing;
(4) Research on transcript structural variations, such as alternative splicing and gene fusions;
(5) Develop SNPs, SSRs, and other markers.
Original article link: HeYuan Bio – Transcriptomics
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