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

Gene Flow02:39

Gene Flow

38.1K
Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
38.1K
Gene-Environment Interactions01:20

Gene-Environment Interactions

1.2K
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
1.2K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

8.2K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
8.2K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

9.2K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
9.2K
What is Gene Expression?01:42

What is Gene Expression?

197.1K
Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
197.1K
Gene Families01:57

Gene Families

10.0K
Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
10.0K

You might also read

Related Articles

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

Sort by
Same author

Parametric hypothesis testing for pathway based hierarchical structural component models.

Genes & genomics·2026
Same author

Analysis of severity in COVID-19 patients by using longitudinal immune profiles.

iScience·2026
Same author

Enhancing polygenic risk prediction by modeling quantile-specific genetic effects.

Scientific reports·2026
Same author

Periorbital skin index as a biomarker for biological aging and health status.

Frontiers in aging·2026
Same author

Optoelectronic Synaptic Transistors Based on Colloidal CdSe Nanowires for Energy-Efficient Neuromorphic Computing.

ACS applied materials & interfaces·2026
Same author

Impact of ACEI/ARB use on COVID-19 mortality in patients with ischaemic heart disease: insights from South Korean National health insurance service data.

BMC infectious diseases·2025

Related Experiment Video

Updated: Feb 13, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.8K

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

Minseok Kwon1, Sangseob Leem2, Joon Yoon3

  • 1Department of Biomedical Informatics, Harvard Medical School, Boston, 02115, MA, USA.

BMC Systems Biology
|March 22, 2018
PubMed
Summary

We introduce GxGrare, a novel method for detecting gene-gene interactions among rare genetic variants. This approach addresses the "missing heritability" in complex diseases by analyzing rare variants, crucial for understanding genetic contributions to conditions like type 2 diabetes.

Keywords:
Gene-gene interactionMultifactor dimensionality reductionRare variant

More Related Videos

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
08:46

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis

Published on: August 26, 2020

5.4K
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

19.5K

Related Experiment Videos

Last Updated: Feb 13, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.8K
Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
08:46

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis

Published on: August 26, 2020

5.4K
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

19.5K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) identify common variants but explain limited disease heritability.
  • Missing heritability in complex diseases may stem from gene-gene interactions (epistasis) and rare variants.
  • Existing methods for gene-gene interaction analysis primarily focus on common variants, with limited progress for rare variants.

Purpose of the Study:

  • To propose GxGrare, a new method for detecting gene-gene interactions specifically for rare variants.
  • To address the limitations in analyzing rare variant interactions within the context of complex diseases.
  • To identify causal gene-gene interactions for type 2 diabetes using rare variants.

Main Methods:

  • GxGrare employs a three-step framework based on multifactor dimensionality reduction (MDR) analysis.
  • Step 1: Collapsing rare variants to simplify analysis.
  • Step 2: Applying MDR to collapsed rare variants for interaction detection.
  • Step 3: Identifying top candidate gene-gene interaction pairs.

Main Results:

  • The proposed GxGrare method effectively detects gene-gene interactions involving rare variants.
  • The method was illustrated using whole exome sequencing data from 1080 Korean individuals for type 2 diabetes analysis.
  • GxGrare can identify interactions between different genes as well as within a single gene.

Conclusions:

  • GxGrare demonstrates robust performance in detecting gene-gene interactions through rare variant collapsing.
  • The GxGrare software is publicly available with simulation data and documentation.
  • The method is supported on Linux and OS X operating systems.