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| − | | + | [[RNA sequencing]] |
| − | === RNA Sequencing (RNA-seq) ===
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| − | '''RNA Sequencing (RNA-seq)''' is a powerful technology used to analyze the transcriptome of cells, tissues, or entire organisms. The transcriptome includes all RNA molecules expressed within a cell at a specific time and under specific conditions. RNA-seq determines the quantity and sequences of RNA molecules, generating gene expression profiles. The process involves the following steps:
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| − | '''RNA Extraction''':
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| − | #*Total RNA is extracted from the cells or tissues of interest. Total RNA typically includes mRNA, tRNA, rRNA, etc., but RNA-seq mainly focuses on mRNA.
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| − | '''cDNA Synthesis''':
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| − | #*The extracted RNA is converted into complementary DNA (cDNA) using reverse transcriptase. cDNA is stable and suitable for sequencing.
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| − | '''Library Preparation''':
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| − | #*Adapter sequences are attached to the cDNA fragments to prepare a sequencing library. Adapter sequences enable the sequencing machine to recognize and read the DNA fragments.
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| − | '''Sequencing''':
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| − | #*The prepared cDNA library is sequenced using next-generation sequencing (NGS) technology. This process generates millions of short DNA sequence reads.
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| − | '''Data Analysis''':
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| − | #*The generated sequence data are aligned to a reference genome. This step quantifies gene expression levels, detects novel transcripts, splicing variants, gene fusions, and more.
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| − | '''Applications''':
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| − | *'''Gene Expression Analysis''': Compare gene expression levels under different conditions or disease states.
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| − | *'''Discovery of New Transcripts''': Identify previously unknown RNA molecules.
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| − | *'''Splicing Variant Analysis''': Analyze different splicing forms and variants.
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| − | *'''Gene Fusion Detection''': Detect gene fusion events, often associated with cancers.
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| − | '''Advantages''':
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| − | *High sensitivity and accuracy: Can detect low-abundance RNA.
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| − | *Broad applicability: Suitable for various biological questions and sample types.
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| − | '''Limitations''':
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| − | *Complexity of data processing: Requires advanced computational biology skills to process and interpret large amounts of data.
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| − | *Cost: High-quality RNA-seq analysis can still be relatively expensive.
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| − | RNA-seq is an essential tool in biological and medical research, helping to understand disease mechanisms, discover biomarkers, develop new drugs, and more.
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