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Related Concept Videos

Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
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Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
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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.
Pharmacogenomics: Identification of New Drug Targets01:29

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
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Bridging the genotype-phenotype gap: what does it take?

Arne B Gjuvsland1, Jon Olav Vik, Daniel A Beard

  • 1Centre for Integrative Genetics, Department of Mathematical and Technological Sciences, Norwegian University of Life Sciences, Norway.

The Journal of Physiology
|February 13, 2013
PubMed
Summary
This summary is machine-generated.

Understanding the genotype-phenotype map requires mathematical models integrating genetic and phenotypic data. This approach is crucial for advancing computational physiology and developing new phenomics technologies.

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Published on: May 12, 2016

Area of Science:

  • Physiology
  • Genetics
  • Computational Biology

Background:

  • The genotype-phenotype map (GP map) describes the relationship between an organism's genes and its observable traits.
  • Understanding the GP map is complex, involving environmental effects and intricate biological dynamics.
  • Current physiological research necessitates bridging the gap between genetic information and phenotypic expression.

Purpose of the Study:

  • To advocate for the use of mathematical models to causally link genetic and phenotypic data.
  • To emphasize the integration of large-scale biological ('omics') data with computational physiology.
  • To call for advancements in phenomics technology and the establishment of a Human Phenome Programme.

Main Methods:

  • Developing causally cohesive mathematical models that integrate genetic and phenotypic data.
  • Illustrating these models with phenotypes ranging from gene expression to organ development.
  • Highlighting the necessity of integrating 'omics' data and bioinformatics with computational physiology.

Main Results:

  • Demonstrated the utility of mathematical models in understanding genotype-phenotype dynamics.
  • Showcased how these models can span diverse phenotypic levels.
  • Identified key areas for improvement in data integration and technological development.

Conclusions:

  • Mathematical modeling is essential for bridging the genotype-phenotype gap.
  • Effective integration of 'omics' data and computational physiology is critical.
  • Advancing phenomics technology and establishing a Human Phenome Programme are vital for future research.