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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
Although all next-generation methods use different technologies, they all share a set of standard features....
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RNA-seq03:21

RNA-seq

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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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Maxam-Gilbert Sequencing01:05

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
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Sanger Sequencing01:57

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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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Related Experiment Video

Updated: Jul 24, 2025

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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Efficient real-time selective genome sequencing on resource-constrained devices.

Po Jui Shih1, Hassaan Saadat2, Sri Parameswaran3

  • 1School of Computer Science and Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.

Gigascience
|July 3, 2023
PubMed
Summary
This summary is machine-generated.

Hardware Accelerated Read Until (HARU) enables efficient nanopore selective sequencing on resource-constrained devices. This method significantly speeds up real-time genomic analysis, making rapid genetic tests more accessible and energy-efficient.

Keywords:
FPGAadaptive samplingedge computinghardware accelerationnanoporeselective sequencingsubsequence dynamic time warping

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Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Third-generation nanopore sequencers enable selective sequencing (Read Until) for real-time analysis.
  • This technology is crucial for applications like rapid, low-cost genetic testing.
  • Current subsequence dynamic time warping (sDTW) methods are computationally intensive, hindering real-time analysis on portable sequencers.

Purpose of the Study:

  • To develop a resource-efficient method for accelerating the sDTW algorithm for nanopore selective sequencing.
  • To enable real-time genomic analysis on portable and resource-constrained devices.

Main Methods:

  • Introduced Hardware Accelerated Read Until (HARU), a hardware-software codesign approach.
  • Utilized a heterogeneous multiprocessor system-on-chip (SoC) with on-chip field-programmable gate arrays (FPGA).
  • Accelerated the sDTW algorithm for real-time read analysis.

Main Results:

  • HARU achieved 2.5x speedup compared to optimized software on a 36-core server using a Xilinx FPGA with a 4-core ARM processor.
  • Demonstrated an 85x speedup over unoptimized software.
  • Reduced energy consumption by two orders of magnitude compared to server-based execution.

Conclusions:

  • HARU successfully enables nanopore selective sequencing on resource-constrained devices.
  • The approach highlights the potential of hardware-software optimizations for portable genomic analysis.
  • Open-source code for HARU is available for further development and application.