Next-generation sequencing (NGS) technologies have revolutionized genomics by enabling rapid and cost-effective DNA sequencing. These methods, like Illumina and PacBio, provide diverse applications, from whole genome sequencing to RNA analysis, driving advancements in computational genomics.
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Illumina sequencing (sequencing by synthesis)
- Utilizes reversible dye terminators to identify nucleotides as they are incorporated into growing DNA strands.
- High throughput capability allows for sequencing millions of fragments simultaneously.
- Generates short reads (typically 50-300 bp), which are useful for a variety of applications including whole genome sequencing and targeted resequencing.
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Ion Torrent semiconductor sequencing
- Measures changes in pH as nucleotides are added to a growing DNA strand, allowing for real-time sequencing.
- Offers a faster and more cost-effective alternative to optical methods, with a focus on smaller-scale projects.
- Produces shorter reads (up to 400 bp) and is particularly useful for targeted sequencing and small genomes.
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454 pyrosequencing
- Based on the detection of pyrophosphate release during nucleotide incorporation, generating light signals proportional to the number of nucleotides added.
- Capable of producing longer reads (up to 1,000 bp) compared to other NGS technologies.
- Primarily used for applications such as metagenomics and de novo sequencing, though it has largely been phased out in favor of other technologies.
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SOLiD sequencing
- Employs ligation-based methods to sequence DNA, using fluorescently labeled oligonucleotides.
- Provides high accuracy and the ability to generate short reads (50-75 bp), making it suitable for applications requiring precise variant detection.
- Often used in targeted resequencing and transcriptome analysis.
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Pacific Biosciences (PacBio) SMRT sequencing
- Utilizes single-molecule real-time (SMRT) technology to sequence long DNA fragments (up to 15,000 bp or more).
- Offers high accuracy with circular consensus sequencing (CCS) and is particularly useful for complex genomes and structural variant detection.
- Enables comprehensive transcriptome analysis and epigenetic studies due to its long-read capabilities.
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Oxford Nanopore sequencing
- Employs nanopore technology to sequence DNA by measuring changes in ionic current as nucleotides pass through a nanopore.
- Capable of producing ultra-long reads (up to several megabases), which is advantageous for resolving repetitive regions and structural variants.
- Portable devices allow for real-time sequencing and field applications, making it versatile for various genomic studies.
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Paired-end and mate-pair sequencing
- Paired-end sequencing involves sequencing both ends of a DNA fragment, providing information about the distance between reads, which aids in genome assembly.
- Mate-pair sequencing uses longer fragments to link distant regions of the genome, improving assembly and structural variant detection.
- Both methods enhance the accuracy of genome mapping and facilitate the identification of complex genomic rearrangements.
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RNA-Seq
- A technique for sequencing RNA to analyze gene expression levels, alternative splicing, and non-coding RNA.
- Provides a comprehensive view of the transcriptome, allowing for the identification of novel transcripts and isoforms.
- Utilizes various NGS platforms, with data analysis requiring specialized computational tools for quantification and differential expression analysis.
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ChIP-Seq
- Combines chromatin immunoprecipitation (ChIP) with sequencing to identify binding sites of proteins (e.g., transcription factors) on DNA.
- Provides insights into gene regulation and epigenetic modifications by mapping protein-DNA interactions across the genome.
- Data analysis involves peak calling and integration with other genomic datasets to understand regulatory networks.
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Whole genome sequencing (WGS)
- Involves sequencing the entire genome of an organism, providing a comprehensive view of genetic variation.
- Useful for applications such as population genomics, evolutionary studies, and personalized medicine.
- Requires substantial computational resources for data storage, processing, and analysis, including variant calling and annotation.