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Created page with " === RNA Sequencing (RNA-seq) === '''RNA Sequencing (RNA-seq)''' is a powerful technology used to analyze the transcriptome of cells, tissues, or entire organisms. The transc..."
=== RNA Sequencing (RNA-seq) ===
'''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''':
#*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''':
#*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''':
#*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''':
#*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''':
#*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.
'''Applications''':
*'''Gene Expression Analysis''': Compare gene expression levels under different conditions or disease states.
*'''Discovery of New Transcripts''': Identify previously unknown RNA molecules.
*'''Splicing Variant Analysis''': Analyze different splicing forms and variants.
*'''Gene Fusion Detection''': Detect gene fusion events, often associated with cancers.
'''Advantages''':
*High sensitivity and accuracy: Can detect low-abundance RNA.
*Broad applicability: Suitable for various biological questions and sample types.
'''Limitations''':
*Complexity of data processing: Requires advanced computational biology skills to process and interpret large amounts of data.
*Cost: High-quality RNA-seq analysis can still be relatively expensive.
RNA-seq is an essential tool in biological and medical research, helping to understand disease mechanisms, discover biomarkers, develop new drugs, and more.
