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Related Concept Videos

Epistasis Analysis01:09

Epistasis Analysis

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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Epistasis

In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
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Gregor Mendel's pioneering work on the principles of inheritance fundamentally transformed our understanding of how traits are transmitted from generation to generation. His experiments with pea plants laid the groundwork for the discovery of genes, discrete units within organisms that control heredity.
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Position-effect Variegation02:32

Position-effect Variegation

In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
Background and Environment Affect Phenotype02:27

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Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
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Epigenetic Regulation

Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.

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Related Experiment Video

Updated: May 23, 2026

Analysis of Cell Differentiation, Morphogenesis, and Patterning During Chicken Embryogenesis Using the Soaked-Bead Assay
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Analysis of Cell Differentiation, Morphogenesis, and Patterning During Chicken Embryogenesis Using the Soaked-Bead Assay

Published on: January 12, 2022

Geometry, epistasis, and developmental patterning.

Francis Corson1, Eric Dean Siggia

  • 1Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021, USA.

Proceedings of the National Academy of Sciences of the United States of America
|March 22, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a geometric model to quantify complex developmental signaling networks, successfully predicting cell fate probabilities in Caenorhabditis elegans vulval development and explaining noise in mutant phenotypes.

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Published on: December 14, 2015

Area of Science:

  • Developmental biology
  • Systems biology
  • Computational biology

Background:

  • Developmental signaling networks involve numerous components, making in vivo quantification challenging.
  • Vulval development in Caenorhabditis elegans integrates Epidermal Growth Factor (EGF) and Notch signaling pathways.

Purpose of the Study:

  • To develop a quantitative geometric model for analyzing complex developmental signaling.
  • To predict cell fate probabilities and understand noise in developmental processes.

Main Methods:

  • Utilized geometric reasoning to create a discrete hierarchy of phenotypic models.
  • Employed existing data on cell type probabilities and signal ablation in C. elegans.
  • Developed a dynamic model encompassing signaling and cell commitment.

Main Results:

  • A single geometric model was favored and parameterized using in vivo data.
  • The model dynamically integrates EGF and Notch signaling additively.
  • It accurately predicts correlated cell fate probabilities and quantifies noise contributions.

Conclusions:

  • The geometric model provides a quantitative framework for understanding developmental signaling integration.
  • The model explains epistasis and noise in mutant phenotypes without additional parameters.
  • It successfully fits genetic experiments and quantifies signaling pathway contributions.