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Related Concept Videos

Epistasis Analysis01:09

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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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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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Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
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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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Incomplete Dominance01:43

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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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Related Experiment Video

Updated: Aug 27, 2025

In Vivo Modeling of the Morbid Human Genome using Danio rerio
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Epistasis and evolutionary dependencies in human cancers.

Marco Mina1, Arvind Iyer1, Giovanni Ciriello1

  • 1Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.

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Cancer evolution involves molecular alterations with dependencies influenced by tumor context. Understanding these evolutionary dependencies (EDs) is key for cancer biology and precision oncology.

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Area of Science:

  • Oncology
  • Genomics
  • Computational Biology

Background:

  • Cancer progression is driven by multiple molecular alterations.
  • The selective advantage of an alteration depends on tumor lineage, epigenetic state, and other alterations.
  • Epistatic interactions between genes create evolutionary dependencies (EDs).

Purpose of the Study:

  • To review algorithmic approaches for inferring evolutionary dependencies (EDs) from cancer genomics data.
  • To discuss the challenges and unmet needs in inferring EDs.
  • To explore the implications of EDs in cancer biology and precision oncology.

Main Methods:

  • Review of algorithmic approaches for inferring EDs.
  • Conceptualization of EDs in cancer evolution.
  • Analysis of large-scale cancer genomics datasets.

Main Results:

  • EDs influence tumor progression, disease phenotypes, and therapeutic response.
  • Algorithmic methods have been developed to infer EDs, addressing various challenges.
  • These methods provide insights into cancer evolutionary trajectories.

Conclusions:

  • Evolutionary dependencies are crucial for understanding cancer.
  • Inference of EDs aids in cancer biology and precision oncology.
  • Further research is needed to address unmet challenges in ED inference.