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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

101.9K
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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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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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.
Challenges of the Maxam-Gilbert Method
The...
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Sanger Sequencing01:57

Sanger Sequencing

780.0K
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...
780.0K
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

7.6K
Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
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Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

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SeedsGraph: an efficient assembler for next-generation sequencing data.

Chunyu Wang, Maozu Guo, Xiaoyan Liu

    BMC Medical Genomics
    |June 6, 2015
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    Summary
    This summary is machine-generated.

    This study presents an efficient whole genome shotgun assembly algorithm for DNA sequencing. The cloud-based method clusters short reads, builds graphs, and uses Euler paths to assemble sequences, proving effective for next-generation sequencing data.

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • DNA sequencing technologies generate vast amounts of short reads.
    • Efficient assembly algorithms are crucial for analyzing large-scale genomic data.

    Purpose of the Study:

    • To develop an efficient and feasible whole genome shotgun assembly algorithm.
    • To address the challenges posed by the increasing volume of short reads from next-generation sequencing.

    Main Methods:

    • Clustering short DNA reads within a cloud computing framework.
    • Condensing clustered reads into seed chains and constructing a graph.
    • Analyzing the graph for Euler paths to assemble reads into contigs and scaffolds.

    Main Results:

    • The developed algorithm demonstrates efficiency in handling large datasets of short reads.
    • The method successfully assembles reads into contigs and scaffolds using mate-pair information.
    • The approach is feasible for next-generation sequencing data volumes.

    Conclusions:

    • The proposed whole genome shotgun assembly algorithm is effective for large-scale DNA sequencing data.
    • Cloud computing enhances the scalability and efficiency of the assembly process.
    • This method provides a viable solution for modern genomic data analysis.