High Throughput Sequencing (HTS): Principle, Steps, Uses microbiologystudy

High Throughput Sequencing (HTS) is a technology that allows the sequencing of multiple samples in a single run which increases the sequencing speed and efficiency compared to traditional sequencing methods.

It is another term for next-generation sequencing (NGS) or massively parallel sequencing. The ability to process large amounts of genetic information quickly helps to gain a better understanding of how our genes work and how diseases develop.

Earlier sequencing techniques such as Sanger sequencing were slower and could only process one sample at a time, making them low-throughput methods. In contrast, HTS techniques like Illumina and Oxford Nanopore sequencing platforms are highly advanced. They offer high throughput and are the preferred choice for sequencing projects at present. 

Different HTS platforms have been developed that generate millions of DNA or RNA sequences in a single reaction. Some HTS methods focus on sequencing targeted regions of specific genes known as targeted sequencing. Other methods include sequencing the entire genetic code or just the coding regions known as whole genome sequencing (WGS) and whole exome sequencing (WES). HTS is also used in transcriptome analysis and epigenome sequencing. 

Principle of High Throughput Sequencing (HTS)

HTS works on the principle of massively parallel sequencing which allows simultaneous processing of multiple DNA fragments and generates massive amounts of data in a short period. It involves breaking down large DNA/RNA molecules into smaller fragments and sequencing these fragments all at once.

The process begins by isolating and breaking down the genetic material of interest into smaller pieces. These fragments are then attached to short DNA sequences called adapters which help in identifying and attaching the sequences later during sequencing. Once these fragments are prepared, they are amplified and sequenced using several HTS platforms such as Illumina. The sequenced data is analyzed using different bioinformatics tools.

Process/Steps of High Throughput Sequencing (HTS)

1. Sample Preparation: The process starts with the preparation of the DNA or RNA sample for sequencing. This involves isolating the genetic material from biological samples of interest.
2. Library Preparation: The isolated nucleic acids are fragmented into small pieces. Special sequencing adapters are attached to these fragments. These adapters help to align and assemble the sequences. These fragments are then amplified to create a sequencing library with multiple copies of each fragment.
3. Sequencing: The prepared library is placed onto the sequencing platform. The sequencing platform reads the sequence by adding nucleotide bases one by one to form new DNA strands and each base added is recorded and identified. HTS platforms can generate vast amounts of raw sequencing data which is further processed to extract useful information.
4. Data Analysis: The final step is data analysis which involves processing the raw data, aligning it to reference genomes, and identifying genetic variation or expression patterns. The process starts with preprocessing and quality control to ensure the sequencing data is of high quality. This includes removing low-quality reads and trimming adapter sequences. The next step is to map and align the sequence reads with the reference genome or transcriptome. This is followed by the detection of genetic variants such as mutations or structural changes. Finally, functional annotation and pathway analysis are done to interpret the biological roles of these genes.

High Throughput Sequencing (HTS) Platforms

Some of the widely used commercially available HTS platforms are Illumina, Ion Torrent, Pacific Biosciences, and Oxford Nanopore Technologies.

1. Illumina is the most widely used HTS technology due to its high accuracy, scalability, and cost-effectiveness. It offers a range of sequencers designed for different purposes. For example, the MiSeq is used for targeted sequencing and small genomes. The HiSeq is ideal for high-throughput applications. There are more recent systems that offer faster sequencing speeds and are ideal for large-scale genome projects.
2. Ion Torrent offers a fast and more cost-effective alternative for certain applications, particularly in clinical diagnostics where speed is essential. Unlike other methods that rely on light detection, Ion Torrent measures pH changes as DNA bases are added during the sequencing reaction. This method reduces sequencing time and cost but has higher error rates. Despite its speed and versatility, the platform’s error rates, especially with insertions and deletions, limit its use in certain applications. It is used in targeted resequencing, small genome analysis, and some clinical applications.
3. PacBio sequencing monitors DNA synthesis in real time. It uses single-molecule real-time (SMRT) sequencing technology. Unlike other platforms, PacBio’s method does not require DNA amplification, allowing direct sequencing which reduces bias. This method is particularly useful for projects that need long reads such as de novo genome assembly and structural variation studies. While it provides long, unbiased reads, it has higher error rates.
4. Oxford Nanopore Technologies uses nanopores where DNA molecules pass through tiny channels and the changes in electrical current as each base passes through allow for sequencing. It is known for its portability, long-read capabilities, and real-time data generation. Though it has higher error rates, its unique features make it a promising technology especially in fieldwork and rapid sequencing projects. MinION is the first commercial nanopore sequencer released in 2014. It can produce long reads and has potential for rapid sequencing. 

Advantages of High Throughput Sequencing (HTS)

• HTS can process multiple samples in a single run making it faster than traditional sequencing methods. 
• It can generate large amounts of sequencing data in a short time. This is useful in rapid detection in clinical diagnostics and research settings.
• It is also more economical for large-scale projects. Running several samples together in one sequencing process lowers the overall cost per sample.
• It produces vast amounts of data in a single run and provides detailed information needed for comprehensive genetic analysis.
• It is used for a wide range of applications from whole-genome sequencing to targeted sequencing making it a flexible tool. 
• Modern HTS technologies offer high accuracy and reduce errors in sequencing results. It produces high-quality sequencing data with minimal errors.

Limitations of High Throughput Sequencing (HTS)

• Although HTS can reduce costs per sample, the initial setup costs can be high. The initial investment in equipment and necessary computational infrastructure can make it expensive for some laboratories to use this technology. 
• It can be challenging to store and manage the large volumes of data generated by HTS which requires advanced computational tools and expertise.
• Certain regions of the genome like GC-rich regions and long homopolymer sequences are not accurately sequenced.
• Most platforms produce short reads which limits the ability to accurately characterize large repeat regions and analyze complex structural variations.

Applications of High Throughput Sequencing (HTS)

• HTS has made whole genome sequencing (WGS) accessible which allows the sequencing of entire genomes at a single time. This is essential for studying the complete genetic makeup of an organism.
• It can also be used in whole exome sequencing (WES) to sequence protein-coding regions of the genome which represents about 1-2% of the total genome. 
• It is also used in medical research to understand genetic diseases, identify mutations, and develop personalized medicine. It can be used to understand the genetics of rare diseases and cancer.
• It has applications in denovo genome sequencing and the study of genetic variations. 
• It can also be used in mapping DNA methylation patterns across the genome which regulate gene expression.
• It also has applications in transcriptomics. Techniques like RNA Sequencing provide detailed information about gene expression and RNA transcripts including non-coding RNAs. 
• HTS methods like ChIP-seq can be used to map the binding sites of DNA-associated proteins like histones and transcription factors which helps to understand gene regulation and chromatin structure.
• HTS methods like metagenome sequencing and 16S rRNA gene sequencing provide detailed information about microbial communities in different environments.

References

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