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Related Concept Videos

Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
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Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis
10:05

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Published on: December 12, 2017

Predicting nucleosome positions in yeast: using the absolute frequency.

Zhiqian Zhang1, Yusen Zhang, Ivan Gutman

  • 1School of Mathematics and Statistics, Shandong University at Weihai, Weihai 264209, China.

Journal of Biomolecular Structure & Dynamics
|February 2, 2012
PubMed
Summary

This study introduces a new model to distinguish nucleosome DNA from linker DNA. The model accurately predicts nucleosome positioning, crucial for understanding gene transcription regulation in eukaryotic cells.

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Nucleosomes are fundamental units of chromatin in eukaryotic cells, essential for DNA packaging.
  • Nucleosome positioning plays a critical role in regulating gene transcription.
  • Differentiating between nucleosome-forming and nucleosome-inhibiting DNA sequences is key to understanding this regulation.

Purpose of the Study:

  • To develop a novel computational model for distinguishing nucleosome DNA from linker DNA.
  • To leverage nucleotide frequency patterns for improved prediction of nucleosome formation.

Main Methods:

  • Analysis of the absolute frequency of nucleotide 2-mers (dinucleotides) in genomic sequences.
  • Construction of a predictive model based on these frequency differences.
  • Validation of the model using data from Saccharomyces cerevisiae (S. cerevisiae).

Main Results:

  • The model effectively differentiates between DNA sequences that form nucleosomes and those that do not.
  • Achieved a high prediction accuracy of 96.05% for nucleosome formation in S. cerevisiae.
  • Demonstrated the utility of 2-mer nucleotide frequencies in predicting nucleosome positioning.

Conclusions:

  • The developed model offers a robust method for predicting nucleosome positioning.
  • This approach can significantly aid research in gene transcription regulation.
  • The findings highlight the importance of local nucleotide composition in chromatin structure.