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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

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

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Published on: February 24, 2015

Screening for SNPs with Allele-Specific Methylation based on Next-Generation Sequencing Data.

Bo Hu1, Yuan Ji, Yaomin Xu

  • 1Department of Quantitative Health Sciences, Cleveland Clinic.

Statistics in Biosciences
|May 28, 2013
PubMed
Summary

This study identifies 269 candidate single nucleotide polymorphisms (SNPs) with allele-specific methylation (ASM) in prostate cells using a novel Bayesian approach and next-generation sequencing. The findings advance understanding of epigenetic regulation in prostate cancer.

Keywords:
ASMDNA MethylationNext-generation SequencingSNP

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Area of Science:

  • Epigenetics
  • Genomics
  • Bioinformatics

Background:

  • Allele-specific methylation (ASM) is traditionally studied in genomic imprinting and X chromosome inactivation.
  • Next-generation sequencing (NGS) enables genome-wide ASM analysis.

Purpose of the Study:

  • To develop and apply a Bayesian method for identifying single nucleotide polymorphisms (SNPs) with ASM across the genome.
  • To identify novel candidate SNPs exhibiting ASM in prostate cell lines.

Main Methods:

  • High-throughput sequencing of four prostate cell lines.
  • A Bayesian model to analyze SNP read counts and genotype data.
  • Posterior false discovery rates for multiple comparison correction.

Main Results:

  • Identified 269 candidate SNPs with ASM in prostate cell lines.
  • The Bayesian approach provides posterior probabilities for ASM.
  • A simulation study validated the method's performance.

Conclusions:

  • The proposed Bayesian method effectively identifies genome-wide ASM.
  • This approach expands the study of epigenetic variations in prostate cells.
  • The identified SNPs are potential candidates for further functional studies in prostate cancer.