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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

102.1K
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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Sanger Sequencing01:57

Sanger Sequencing

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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: Apr 16, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Inference for one-step beneficial mutations using next generation sequencing.

Andrzej J Wojtowicz, Craig R Miller, Paul Joyce

    Statistical Applications in Genetics and Molecular Biology
    |February 27, 2015
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    Summary
    This summary is machine-generated.

    This study introduces a new experimental evolution method using next-generation sequencing to track multiple beneficial mutations. This approach enables robust statistical inference for understanding microbial evolution and mutation dynamics.

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    Area of Science:

    • Microbiology
    • Evolutionary Biology
    • Genomics

    Background:

    • Experimental evolution is crucial for studying microbial evolution.
    • Existing methods have limitations in tracking multiple concurrent mutations.
    • Next-generation sequencing offers high-throughput data for evolutionary studies.

    Purpose of the Study:

    • To develop a novel experimental evolution approach utilizing next-generation sequencing.
    • To enable the concurrent tracking of multiple beneficial mutations within evolving microbial populations.
    • To establish statistical inference methods for analyzing this complex evolutionary data.

    Main Methods:

    • Application of population-level sequencing in experimental evolution.
    • Development of statistical inference methods for analyzing mutation frequencies.
    • Imputation of selection coefficients for first-step beneficial mutations.

    Main Results:

    • Observed frequencies of multiple beneficial mutations in each experimental replicate.
    • Developed a method for imputing selection coefficients of beneficial mutations.
    • Enabled testing of mutation distribution and estimation of mean selection coefficients.

    Conclusions:

    • The novel approach provides a powerful tool for studying evolutionary processes.
    • Statistical inference methods allow for robust analysis of complex mutation data.
    • This method can be used to estimate the total number of available beneficial mutations under uniform selection.