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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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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.
Sanger Sequencing01:57

Sanger Sequencing

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...
Next-generation Sequencing03:00

Next-generation Sequencing

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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Proofreading01:31

Proofreading

Synthesis of new DNA molecules is carried out by the enzyme DNA polymerase, which adds nucleotides on the daughter strand complementary to the template DNA strand. DNA polymerase has a higher affinity to add the correct base and ensures fidelity during DNA replication. Furthermore,  it exhibits proofreading activity during replication, using an exonuclease domain that cuts off incorrect nucleotides from the nascent DNA strand.
Errors During Replication are Corrected by the DNA Polymerase Enzyme
Proofreading01:43

Proofreading

Synthesis of new DNA molecules starts when DNA polymerase links nucleotides together in a sequence that is complementary to the template DNA strand. DNA polymerase has a higher affinity for the correct base to ensure fidelity in DNA replication. The DNA polymerase furthermore proofreads during replication, using an exonuclease domain that cuts off incorrect nucleotides from the nascent DNA strand.Errors during Replication Are Corrected by the DNA Polymerase EnzymeGenomic DNA is synthesized in...

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Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Incorporating sequence quality data into alignment improves DNA read mapping.

Martin C Frith1, Raymond Wan, Paul Horton

  • 1Computational Biology Research Center, Institute for Advanced Industrial Science and Technology, Koto-ku, Tokyo 135-0064, Japan. martin@cbrc.jp

Nucleic Acids Research
|January 30, 2010
PubMed
Summary
This summary is machine-generated.

New DNA sequencing methods produce more data but have higher error rates. This study introduces a new alignment method that accounts for sequencing errors, improving DNA read mapping accuracy for diverse genomic applications.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) technologies offer high throughput but introduce higher error rates.
  • Traditional sequence alignment algorithms assume error-free reads, limiting their accuracy with modern sequencing data.
  • Accurate DNA read mapping is crucial for genomic analysis, especially for non-model organisms.

Purpose of the Study:

  • To develop a novel DNA read mapping method that incorporates per-base error probabilities from sequencers.
  • To improve the accuracy of sequence alignment by modeling both sequencing errors and biological sequence variations.
  • To enhance the utility of DNA sequencing data for organisms lacking high-quality reference genomes.

Main Methods:

  • Developed a probabilistic alignment approach that integrates per-base error rates.
  • Modeled both technical sequencing errors and biological sequence differences (e.g., SNPs, indels).
  • Evaluated the method's performance on simulated and real sequencing data, including cross-species mapping.

Main Results:

  • The new method consistently improved mapping accuracy compared to standard alignment tools.
  • Mapping accuracy increased even with low rates of biological sequence variation (0.2%).
  • Successfully mapped 66% of Drosophila melanogaster reads to the Drosophila simulans genome, a significant improvement from 49%.

Conclusions:

  • Incorporating per-base error probabilities into alignment significantly enhances DNA read mapping accuracy.
  • This approach is particularly valuable for analyzing genomic data from highly polymorphic, extinct, or reference-poor organisms.
  • Enables more effective utilization of sequencing data in challenging genomic research areas.