Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pedigree Analysis

Pedigree Analysis

Pedigree Analysis

Pedigree Analysis

Incomplete Dominance

Incomplete Dominance

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.

Hardy-Weinberg Principle

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...

Multiple Allele Traits

Multiple Allele Traits

The Concept of Multiple Allelism

Multiple Allele Traits

Multiple Allele Traits

The Concept of Multiple Allelism

You might also read

Related Articles

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

Sort by

Same author

Variation in cranial and caudal keel bone composition and its association with keel damage severity in laying hens.

Poultry science·2026

Same author

Deep learning can automate chicken tibia-breaking strength quantification to improve animal welfare.

Poultry science·2026

Same author

Genetics of digital phenotypes of keel bone in layer chickens and correlations with keel bone fractures and deviations.

Genetics, selection, evolution : GSE·2025

Same author

Improving genomic prediction accuracy for methane emission and feed efficiency in sheep: integrating rumen microbial PCA with host genomic variation using neural network GBLUP (NN-GBLUP).

Genetics, selection, evolution : GSE·2025

Same author

Genetic estimates and genome-wide association studies of antibody response in Tanzanian dairy cattle.

Frontiers in genetics·2025

Same author

Genetic markers associated with bone strength and density in Rhode Island Red laying hens.

Poultry science·2025

Search research articles

Related Experiment Video

Updated: Jun 29, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Detecting dominant QTL with variance component analysis in simulated pedigrees.

Suzanne J Rowe¹, Ricardo Pong-Wong, Christopher S Haley

¹Genetics and Genomics, Roslin Institute, Midlothian, Edinburgh EH25 9PS, UK. suzanne.rowe@bbsrc.ac.uk

Genetics Research

|October 9, 2008

Summary

Dominance effects in complex traits can be detected using quantitative trait locus (QTL) models. Accurate detection requires accounting for family structure and potential confounding factors like maternal effects.

More Related Videos

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

Related Experiment Videos

Last Updated: Jun 29, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

Area of Science:

Quantitative genetics
Statistical genomics
Complex trait analysis

Background:

Dominance variation significantly contributes to complex traits.
Previous quantitative trait locus (QTL) detection methods primarily focused on additive effects.

Purpose of the Study:

To investigate quantitative trait locus (QTL) detection using variance component (VC) models incorporating both additive and dominant effects.
To assess the accuracy, type 1 error, and statistical power of these models across different pedigree structures.

Main Methods:

Extensive simulations using two-generation human, poultry, and pig pedigrees.
Variance component (VC) models extended to include additive and dominant QTL effects.
Analysis of likelihood-ratio test statistic distribution and its dependence on family structure.

Main Results:

Empirical distribution of test statistics for dominant QTL effects varied with pedigree structure.
Statistical power for detecting dominance effects was high in pig and poultry pedigrees but lower in human pedigrees.
Maternal or common environment effects can confound dominance and must be included in QTL models.

Conclusions:

Dominance can be routinely included in QTL analysis for general pedigrees.
Optimal statistical power depends on selecting appropriate thresholds based on pedigree structure.
Accurate QTL detection necessitates accounting for dominance, additive, and maternal/environmental effects.