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

Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

1.5K
The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
1.5K
Epistasis Analysis01:09

Epistasis Analysis

6.0K
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...
6.0K
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

26.7K
Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
26.7K
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

4.1K
4.1K
Polygenic Traits01:18

Polygenic Traits

69.9K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
69.9K
Epistasis01:39

Epistasis

50.8K
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...
50.8K

You might also read

Related Articles

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

Sort by
Same author

Annotation-Based Gene-Peak Links Improve Regulatory Network Prediction of Gene Expression in Human Kidney Multi-Omics.

bioRxiv : the preprint server for biology·2026
Same author

ENPP1 blockade with a humanized monoclonal antibody enhances renal repair after acute kidney injury.

Cell stem cell·2026
Same author

A liver-heart endocrine axis revealed by systems genetics and mediated by hepatocyte growth factor activator.

medRxiv : the preprint server for health sciences·2026
Same author

Novel candidate genes for vestibular function identified through GWAS in the hybrid mouse diversity panel.

BMC genomics·2026
Same author

How epigenetic clocks tick: Unpacking the black box by deciphering biological pathways and transcriptomic signatures of accelerated aging.

Research square·2026
Same author

The liver regulates ectopic calcification in Abcc6-deficient models of pseudoxanthoma elasticum.

The Journal of clinical investigation·2026
Same journal

Abstracts from Specialized Centers of Research Excellence (SCORE) on Sex Differences 2025 annual meeting.

BMC proceedings·2026
Same journal

Conference abstracts the 1st UDOM scientific conference on health: healthy lives and well-being for all: opportunities and challenges.

BMC proceedings·2026
Same journal

Entrepreneurship beyond the lab: commercializing your creative outputs.

BMC proceedings·2026
Same journal

The need to strengthen laboratory leadership, systems, and networks to enhance outbreak detection and resilience in Africa: proceedings of a regional workshop.

BMC proceedings·2026
Same journal

Abstracts from the Globesync Community Research and Sustainability 2025 (GlobeCoReS 2025).

BMC proceedings·2026
Same journal

Bauru International Craniofacial Symposium: Comprehensive Care, Policy and Advocacy Proceedings.

BMC proceedings·2026
See all related articles

Related Experiment Video

Updated: Mar 10, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

23.4K

Genetic complexity at expression quantitative trait loci.

Rita M Cantor1, Calvin Pan1, Kimberly Siegmund2

  • 1Department of Human Genetics, David Geffen School of Medicine at UCLA, 695 Charles E. Young Dr, South, Los Angeles, CA 90024-7088 USA.

BMC Proceedings
|December 17, 2016
PubMed
Summary
This summary is machine-generated.

Expression quantitative trait loci (eQTL) show significant genetic complexity within families. Understanding this complexity is key to unraveling the genetic causes of complex diseases.

More Related Videos

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

4.9K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.6K

Related Experiment Videos

Last Updated: Mar 10, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

23.4K
Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

4.9K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.6K

Area of Science:

  • Genetics
  • Genomics
  • Complex Disease Etiology

Background:

  • Identifying gene expression regulatory variants and their genetic architecture is crucial for understanding complex diseases.
  • Genomic tools and analytical strategies are advancing for this research.

Purpose of the Study:

  • To investigate the genetic complexity of expression quantitative trait loci (eQTL).
  • To examine allelic heterogeneity as a contributor to genetic complexity at eQTL.

Main Methods:

  • Utilized Genetic Analysis Workshop (GAW) 19 data from 653 individuals across 20 pedigrees.
  • Analyzed lymphocyte expression profiles, single nucleotide polymorphism (SNP) genotyping, sequencing, and imputation.
  • Employed sequential SNP conditioning to assess allelic heterogeneity in eQTL.

Main Results:

  • SOLAR-MGA and FaST-LMM software were used for pedigree data analysis.
  • Both single and multiple SNP association testing showed consistent power and Type 1 error rates.
  • Analysis revealed substantial allelic heterogeneity at two examined eQTL, indicating genetic complexity.

Conclusions:

  • Expression quantitative trait loci (eQTL) demonstrate significant genetic complexity within and among pedigrees.