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Related Concept Videos

DNA Replication02:40

DNA Replication

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DNA replication involves the separation of the two strands of the double helix, with each strand serving as a template from which the new complementary strand is copied.  After replication, each double-stranded DNA includes one parental or “old” strand and one “new” strand. This is known as semiconservative replication. The resulting DNA molecules have the same sequence and are divided equally into the two daughter cells.
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The DNA Replication Fork01:02

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An organism’s genome needs to be duplicated in an efficient and error-free manner for its growth and survival. The replication fork is a Y-shaped active region where two strands of DNA are separated and replicated continuously. The coupling of DNA unzipping and complementary strand synthesis is a characteristic feature of a replication fork.   Organisms with small circular DNA, such as E. coli, often have a single origin of replication; therefore, they have only two replication...
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S-Cdk Initiates DNA Replication02:38

S-Cdk Initiates DNA Replication

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The cell cycle is a series of events leading to DNA duplication followed by the division of cell content to form two daughter cells. The cell cycle progresses in four stages—the cell increases in size (gap 1 or G1-phase), duplicates its DNA (synthesis or S-phase), prepares to divide (gap 2 or G2-phase), and divides (mitosis or M-phase).
Two states at the origin of replication
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The Replisome03:01

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DNA replication is carried out by a large complex of proteins that act in a coordinated matter to achieve high-fidelity DNA replication. Together this complex is known as the DNA replication machinery or the replisome.
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DNA as a Genetic Template02:05

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Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
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Updated: Dec 24, 2025

Strand-Specific Analysis of Proteins at Replicating DNA Strands by Enrichment and Sequencing of Protein-Associated Nascent DNA Method
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Strand-Specific Analysis of Proteins at Replicating DNA Strands by Enrichment and Sequencing of Protein-Associated Nascent DNA Method

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Probabilistic model based on circular statistics for quantifying coverage depth dynamics originating from DNA

Shinya Suzuki1, Takuji Yamada1

  • 1School of Life Science and Technology, Tokyo Institute of Technology, Meguro, Tokyo, Japan.

Peerj
|April 8, 2020
PubMed
Summary
This summary is machine-generated.

We developed a novel probabilistic model to analyze DNA replication dynamics by quantifying coverage depth. This method reveals changes in replication origin activity, advancing microbial community analysis.

Keywords:
Coverage depthDNA replication modelGrowth rate estimation by metagenome sequenceMetagenomicsMicrobiomePeak to trough ratioVon mises generalized linear model

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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Advancements in DNA sequencing enable static omics profiling of microbial communities.
  • In situ growth rate estimation extends comparative metagenomics to dynamic profiling but has limitations.
  • Coverage depth characteristics during DNA replication remain under-investigated.

Purpose of the Study:

  • To develop a probabilistic model for quantifying DNA replication coverage depth dynamics.
  • To address biases in coverage depth due to replication and observation errors.
  • To enable broader application of statistical models for replication activity estimation.

Main Methods:

  • Developed a probabilistic model mimicking coverage depth dynamics during DNA replication.
  • Incorporated circular distribution to quantify coverage depth features around replication origins.
  • Validated the model using whole-genome sequence datasets and time-series culture samples.

Main Results:

  • The model explains coverage depth bias from DNA replication and observation errors.
  • It successfully reproduced previously observed microbial growth dynamics.
  • Analysis of time-series samples showed dynamic changes in replication origin peakedness and density, while skewness remained stable.
  • Demonstrated the ability to measure multiple replication origins within a single chromosome.

Conclusions:

  • A novel framework for quantifying coverage depth dynamics in microbial communities was developed.
  • The statistical model provides a basis for broader replication activity estimation.
  • This approach enhances the understanding of microbial DNA replication and dynamics.