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The future beyond DNA sequencing: How will NGS technology revolutionize genomics?
Since the mid-1990s, the rise of next-generation sequencing (NGS) technology has transformed the biotechnology field. NGS technology has successfully promoted the revolution of genomics with its high throughput, rapidity and relatively low cost. This technology not only enables researchers to obtain massive amounts of genomic data in a short period of time, but also makes the analysis and application of this data possible. Whether in disease diagnosis, personalized medicine or gene therapy, the potential of NGS is unlimited.
In the past, although the traditional Sanger sequencing method was reliable, its speed and efficiency were relatively low, which limited the progress of genomics. NGS technology uses millions of parallel sequencing reactions to generate billions of sequencing data in each experiment. According to the report, each NGS run can obtain up to 4.3 billion short sequences. This amount of data allows genomic research to break through previous bottlenecks.
"The development of next-generation sequencing technology has enabled genomics to move from theoretical exploration in the laboratory to the era of practical application."
NGS operations rely on several key steps: first, generating a DNA sequencing library, and then sequencing by synthesis. This method involves huge amounts of data and can analyze multiple gene sequences simultaneously, thus significantly improving work efficiency. Unlike Sanger sequencing, NGS avoids the physical separation step, which means researchers can obtain a wide range of data in a single process.
Evolution of NGS Platforms and Template Preparation Methods
Among the multiple NGS platforms, some use amplified single-molecule templates, while others rely on independent DNA molecule templates. Common amplification methods include emulsion PCR, rolling circle amplification and solid phase amplification. Each amplification technology has its own unique advantages, especially in improving the accuracy and reliability of sequencing.
Among them, the emulsion PCR method ensures that there is only one DNA template in each PCR microreactor, thus avoiding cross-contamination and sequencing errors. This improves data accuracy throughout the process. The rolling circle amplification algorithm allows researchers to solve screening problems while maintaining high-throughput output."Effective template preparation is the key to ensuring the success of NGS sequencing."
Diverse sequencing methods
NGS technology has not only made great progress in data output, but its sequencing methods are also constantly evolving. Currently, mainstream sequencing methods include synthesis sequencing, pulse sequencing, and ligation-based sequencing. Each method has its own uniqueness, both in terms of the balance between data processing speed and accuracy.
For example, the core of synthesis sequencing is the synthesis of DNA by DNA polymerase, while ligation-mediated sequencing uses DNA ligase to connect probes to obtain sequencing data. These advances have not only improved data throughput but also facilitated various applications of gene sequencing, especially in pathology and genetic research.
"The revolutionary progress of NGS technology lies not only in technological breakthroughs, but also in the new ideas it provides for early diagnosis and treatment of diseases."
Future challenges and opportunities
Although NGS technology has great potential, it still faces a series of challenges. The first is that the explosive growth of data volume makes data analysis a tedious and complicated process. Researchers need efficient computing resources and advanced algorithms to process and interpret this data. In addition, how to ensure data sharing and protect personal privacy is also an issue that needs to be paid attention to in the future.
However, these challenges also open up new opportunities in related fields with advances in AI, automation and other biotechnologies. The future of genomics will rely more on interdisciplinary collaboration, combining biology, data science, and healthcare to achieve a comprehensive transition from gene sequences to health predictions.
In this era of constant change, how will next-generation sequencing technology lead us into a new era of genomics?
