Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Variance component analysis of polymorphic metabolic systems.

Joseph L McClay1, Edwin J C G van den Oord

  • 1Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia, Virginia Commonwealth University, Biotech 1, 800 East Leigh Street, Richmond, VA 23298-0126, USA. jlmcclay@vcu.edu

Journal of Theoretical Biology
|November 29, 2005
PubMed
Summary

Understanding how gene variants affect population variance is key. Our study shows that the impact of genetic changes depends on both the effect size and the biological system

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Methylome-wide association study in blood suggests cell type-specific relationships between DNA methylation and lifetime anxiety.

Nature communications·2026
Same author

Striatal Dysregulation of Angpt2 and Circadian Gene Expression in a Rotenone Rat Model of Parkinson's Disease.

Journal of molecular neuroscience : MN·2026
Same author

Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches.

Bioinformatics (Oxford, England)·2026
Same author

A large-scale DNA methylation study of alcohol use identified robust associations and cell-type specific insights.

Molecular psychiatry·2026
Same author

Cell type-specific methylome-wide association studies of childhood ADHD symptoms.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology·2025
Same author

DNA Methylation Signatures of Alcohol Use Disorder - A large-scale Meta-Analysis in the Psychiatric Genomics Consortium.

medRxiv : the preprint server for health sciences·2025

Area of Science:

  • Systems biology
  • Quantitative genetics
  • Molecular genetics

Background:

  • The interplay between mechanistic allelic interactions in multi-gene systems and genetic contribution to population variance is not well understood.
  • Reconciling dynamic cellular processes with individual differences in a population is crucial for understanding genotype-phenotype relationships.

Purpose of the Study:

  • To develop and demonstrate an approach for calculating steady-state biomarker concentrations in individual systems with different alleles.
  • To investigate the genetic components of variance in biomarker concentration for metabolic systems with varying allelic interactions.

Main Methods:

  • Simulated two versions of a three-enzyme linear synthesis pathway: a Standard model with conventional kinetics and a model with competitive inhibition (CI).

Related Experiment Videos

  • Incorporated alleles conferring different transcription rates into multi-level simulations from transcription to enzyme action.
  • Calculated genetic components of variance (additivity, dominance, epistasis) for biomarker concentrations in simulated populations.

    • Main Results:

    • Both Standard and CI models showed substantial genetic additivity and some dominance with high and low expression alleles.
    • The Standard model exhibited equal gene contribution, while CI significantly altered individual gene importance.
    • Epistasis was generally low (<5%), but increased substantially as allelic effects approached null, particularly in the CI model.

    Conclusions:

    • The contribution of alleles to population variance is contingent on the magnitude of their effect and the system's structure.
    • This modeling approach offers a promising framework for understanding the genotype-to-phenotype transition, especially for integrating small allelic effects.