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Related Concept Videos

Epigenetic Regulation01:37

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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.
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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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Epigenetics is the study of inherited changes in a cell's phenotype without changing the DNA sequences. It provides a form of memory for the differential gene expression pattern to maintain cell lineage, position-effect variegation, dosage compensation, and maintenance of chromatin structures such as telomeres and centromeres. For example, the structure and location of the centromere on chromosomes are epigenetically inherited. Its functionality is not dictated or ensured by the underlying...
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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
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A Recursive Model Approach to Include Epigenetic Effects in Genetic Evaluations Using Simulated DNA Methylation

Adrián López-Catalina1,2,3, Mohamed Ragab1, Antonio Reverter3

  • 1Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), CSIC, Madrid, Spain.

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|January 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a multiomic model (GOBLUP) to integrate DNA methylation data into animal breeding. GOBLUP improves breeding decisions by separating additive genetic and epigenetic variances for enhanced accuracy.

Keywords:
GOBLUPbreeding programmesdairy cattle methylationepigenetics in linear mixed models

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Area of Science:

  • Animal genetics and genomics
  • Epigenetics and quantitative genetics
  • Bioinformatics and statistical modeling

Background:

  • DNA methylation is a key epigenetic mechanism influencing gene regulation and animal traits.
  • Advances in high-throughput sequencing enable large-scale, affordable capture of methylation data.
  • Integrating multiomic data into genetic evaluation models is crucial for improving animal breeding.

Purpose of the Study:

  • To adapt and evaluate a multiomic model (GOBLUP) for incorporating DNA methylation data into genetic evaluations.
  • To assess the model's ability to separate additive genetic and epigenetic variances.
  • To develop and validate an Estimated Epigenetic Value (EEV) for improved breeding decisions.

Main Methods:

  • Simulated methylation profiles for 13,183 genotyped animals based on data from six dairy cows.
  • Treated liability to methylation as an additive trait and simulated a methylation-moderated trait.
  • Adapted the GOBLUP multiomic model and compared it with the traditional BLUP method.

Main Results:

  • GOBLUP accurately estimated heritability for methylation liability and epigenetics-moderated traits.
  • The model effectively separated additive genetic and epigenetic variances.
  • The novel Estimated Epigenetic Value (EEV) showed higher correlations with true breeding values than traditional EBVs.

Conclusions:

  • The GOBLUP multiomic model effectively integrates DNA methylation data for improved genetic evaluations in animal breeding.
  • Accounting for genetic liability to DNA methylation enhances breeding decisions and selection accuracy.
  • Cost-effective simultaneous acquisition of genetic and epigenetic data will further boost breeding accuracy.