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Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...
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Genome-wide methylation data mirror ancestry information.

Elior Rahmani1, Liat Shenhav2, Regev Schweiger1

  • 1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.

Epigenetics & Chromatin
|February 3, 2017
PubMed
Summary

DNA methylation data can reveal human ancestry, similar to genetic data. A new method, EPISTRUCTURE, infers population structure from methylation patterns without needing genotype information.

Keywords:
AncestryDNA methylationEpigeneticsEpigenome-wide association study (EWAS)Illumina 450KPopulation structure

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Area of Science:

  • Epigenetics
  • Population Genetics
  • Bioinformatics

Background:

  • Genetic data are widely used to infer human demographics and ancestry.
  • The extent to which DNA methylation data capture population structure remains unclear.

Purpose of the Study:

  • To investigate if genome-wide DNA methylation data contain discernible ancestry information.
  • To develop a method for inferring ancestry from methylation data without genetic data.

Main Methods:

  • Analysis of three large-cohort 450K methylation array datasets.
  • Leveraging correlations between CpGs and cis-located SNPs.
  • Development of the EPISTRUCTURE method for ancestry inference.

Main Results:

  • Genome-wide DNA methylation data mirror ancestry information.
  • Ancestry signals in methylation data can be effectively isolated.
  • EPISTRUCTURE successfully infers ancestry from methylation data alone.

Conclusions:

  • EPISTRUCTURE enables ancestry inference using only DNA methylation data, crucial for studies with limited genetic data access.
  • The method is particularly valuable for analyzing publicly available epigenetic datasets.
  • EPISTRUCTURE is implemented within the GLINT toolset for DNA methylation analysis.