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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
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RNA-seq03:21

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Updated: Aug 11, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
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Methods to improve the accuracy of next-generation sequencing.

Chu Cheng1, Zhongjie Fei1, Pengfeng Xiao1

  • 1State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.

Frontiers in Bioengineering and Biotechnology
|February 6, 2023
PubMed
Summary

Next-generation sequencing (NGS) offers cost and throughput benefits but struggles with accuracy, hindering clinical applications like SNP detection. This study reviews NGS error reduction strategies for improved clinical utility.

Keywords:
clinical applicationfuture developmenthigh accuracyimprovementnext-generation sequencing

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Area of Science:

  • Genomics
  • Molecular Biology
  • Clinical Diagnostics

Background:

  • Next-generation sequencing (NGS) is widely used in life sciences and clinical diagnostics.
  • NGS offers advantages in cost and throughput but has limitations in read length and accuracy.
  • High error rates in NGS impede the detection of single nucleotide polymorphisms (SNPs) and low-abundance mutations, crucial for pharmacogenomics and early diagnosis.

Purpose of the Study:

  • To summarize NGS procedures and highlight error reduction improvements.
  • To discuss challenges and future directions for NGS in clinical applications.
  • To provide insights into enhancing NGS data quality for clinical settings.

Main Methods:

  • Review of general procedures across various NGS platforms.
  • Identification and summarization of error-mitigation strategies at different stages (template preparation, sequencing, data processing).
  • Analysis of current limitations and future prospects of NGS in clinical diagnostics.

Main Results:

  • NGS platforms have undergone significant improvements to enhance data accuracy.
  • Specific strategies targeting template preparation, sequencing methods, and data analysis have been developed to minimize errors.
  • Despite advancements, Sanger sequencing remains the gold standard for high-accuracy verification in clinical practice.

Conclusions:

  • Continuous improvements in NGS technologies are crucial for overcoming accuracy limitations.
  • Addressing error rates is key to unlocking the full potential of NGS in clinical applications, including SNP analysis and mutation detection.
  • Further research and development are needed to optimize NGS for reliable clinical diagnosis and pharmacogenomics.