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 Concept Videos

Epistasis Analysis01:09

Epistasis Analysis

5.5K
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...
5.5K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.7K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

200
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
200
Epistasis01:39

Epistasis

49.4K
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...
49.4K
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

75.5K
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.
75.5K

You might also read

Related Articles

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

Sort by
Same author

Discovering putative novel stem rust resistance loci in wheat genetic resources.

The plant genome·2026
Same author

Epistatic interaction of the genes <i>Raw1</i> and <i>Raw7</i> controls barb size and frequency in barley awn roughness.

bioRxiv : the preprint server for biology·2026
Same author

Association mapping of hybrid seed set and heterosis in a central European multi-parental wheat population.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2026
Same author

Wheat historical phenotypic data from European genebanks as an important resource for research and breeding.

Scientific data·2026
Same author

Integrating genomic predictions into an applied Central European wheat breeding program.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2026
Same author

Large-scale multi-omics unveils host-microbiome interactions driving root development and nitrogen acquisition.

Nature plants·2026
Same journal

Inherited long telomeres induce a genome-wide transcriptional response in budding yeast.

Genetics·2026
Same journal

Adaptive Dynamics of Quantitative Traits in a Steadily Changing Environment.

Genetics·2026
Same journal

Functional Landscape of Zebrafish Gonadotropins and Receptors: A Comprehensive Genetic Analysis.

Genetics·2026
Same journal

Synergistic actions of Nup43 and Myosin VI drive actin cone assembly during Drosophila spermiogenesis.

Genetics·2026
Same journal

Identification of two Cryptococcus neoformans heme transporters involved in Fhb1-mediated nitrosative stress protection in a fission yeast model.

Genetics·2026
Same journal

Analysis of a hypomorphic mei-P26 mutation reveals coordination between developmental programming of germ cells and meiotic chromosome dynamics.

Genetics·2026
See all related articles

Related Experiment Video

Updated: Dec 7, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.6K

Efficient Algorithms for Calculating Epistatic Genomic Relationship Matrices.

Yong Jiang1, Jochen C Reif1

  • 1Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben 06466, Germany jiang@ipk-gatersleben.de.

Genetics
|September 25, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces precise iterative formulas and efficient algorithms for calculating the exact epistatic genomic relationship matrix, overcoming computational challenges in genetic diversity and prediction studies.

Keywords:
epistasisgenomic relationshiphigh-order interaction

More Related Videos

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.8K
Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

10.8K

Related Experiment Videos

Last Updated: Dec 7, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.6K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.8K
Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

10.8K

Area of Science:

  • Quantitative genetics
  • Bioinformatics
  • Statistical genomics

Background:

  • The genomic relationship matrix is crucial for genetic diversity analysis, genomic prediction, and genome-wide association studies.
  • The epistatic genomic relationship matrix generalizes the classic matrix by modeling marker epistasis, but exact calculation is computationally intensive.
  • Current approximations using the Hadamard product lack rigorous mathematical investigation.

Purpose of the Study:

  • To derive exact iterative formulas for the epistatic genomic relationship matrix of arbitrary epistasis degree.
  • To develop efficient recursive algorithms for calculating the exact epistatic genomic relationship matrix.
  • To provide a computationally feasible solution for precise epistatic relationship matrix calculation.

Main Methods:

  • Derived iterative formulas for the epistatic genomic relationship matrix using symmetric polynomial theory.
  • Implemented efficient recursive algorithms based on the derived iterative formulas.
  • Applied the new algorithms to alleviate computational burden in previous studies.

Main Results:

  • Developed precise iterative formulas for the epistatic genomic relationship matrix, encompassing additive and dominance interactions.
  • Created efficient recursive algorithms that accurately compute the exact epistatic genomic relationship matrix.
  • Demonstrated the computational advantage of the new algorithms over Hadamard product approximations.

Conclusions:

  • The developed algorithms offer a complete and computationally efficient solution for calculating the exact epistatic genomic relationship matrix.
  • This work facilitates more accurate genetic analyses by enabling precise modeling of epistatic effects.
  • The findings significantly reduce computational load in studies involving complex genetic interactions.