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Related Concept Videos

RNA-seq03:21

RNA-seq

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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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.
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Related Experiment Video

Updated: Jun 23, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

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Published on: October 18, 2013

DNA Sudoku--harnessing high-throughput sequencing for multiplexed specimen analysis.

Yaniv Erlich1, Kenneth Chang, Assaf Gordon

  • 1Watson School of Biological Sciences, Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA.

Genome Research
|May 19, 2009
PubMed
Summary

Researchers developed a new method for analyzing tens of thousands of specimens simultaneously using combinatorial pooling and barcode assignment. This strategy decodes specimen identity from pooling patterns, achieving over 97% accuracy in large-scale trials.

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Last Updated: Jun 23, 2026

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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • High-Throughput Sequencing

Background:

  • Next-generation sequencing enables multiplexing, analyzing multiple DNA specimens simultaneously.
  • Current multiplexing methods use molecular barcodes, practical for dozens of samples.
  • Scaling multiplexing to tens of thousands of specimens requires innovative approaches.

Purpose of the Study:

  • To develop and validate a strategy for simultaneous analysis of tens of thousands of specimens.
  • To enable high-confidence inference of individual specimen identity through combinatorial pooling.
  • To apply this method to diverse biological problems, including population genetics.

Main Methods:

  • Implemented combinatorial pooling strategies where pools, not individual specimens, are barcoded.
  • Encoded specimen identity within the pooling pattern rather than specific sequence tags.
  • Developed decoding algorithms to infer original specimen sequences from pooling patterns.

Main Results:

  • Achieved greater than 97% accuracy in decoding specimen identities in large-scale trials.
  • Successfully simulated and validated the method using clone libraries and human population data.
  • Demonstrated efficacy with 40,000 bacterial clones targeting microRNAs in real-world pooling experiments.

Conclusions:

  • The combinatorial pooling strategy significantly enhances the scale of multiplexed sequencing.
  • This method accurately identifies individual specimens within massive pooled sets.
  • The approach is broadly applicable to large-scale genotypic variation studies and other biological problems.