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

Background and Environment Affect Phenotype

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...

Genetic Lingo

Genetic Lingo

Reliability and Validity

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.

Punnett Squares

Punnett Squares

Monohybrid Crosses

Monohybrid Crosses

Position-effect Variegation

Position-effect Variegation

In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.

You might also read

Related Articles

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

Sort by

Same author

Selphi, a tool for improving genotype imputation accuracy.

Scientific reports·2026

Same author

A novel simulation tool for low-coverage whole-genome sequencing using multivariate Gaussian mixture models.

BMC bioinformatics·2026

Same author

Development and validation of a two-stage machine learning model for personalised type 2 diabetes screening in the All of Us Research Program and UK Biobank.

BMJ open·2026

Same author

Improved Identification of Large-effect Rare Genetic Variants using Haplotype Aggregated Allele-specific Expression Data.

medRxiv : the preprint server for health sciences·2025

Same author

Apolipoprotein B outperforms low density lipoprotein particle number as a marker of cardiovascular risk in the UK Biobank.

European journal of preventive cardiology·2025

Same author

Author Correction: Meta-prediction of coronary artery disease risk.

Nature medicine·2025

Same journal

Genetic suppressors as new therapeutic targets for Mendelian diseases.

Trends in genetics : TIG·2026

Same journal

Beyond housekeeping: snRNA diversity, regulation, and human disease.

Trends in genetics : TIG·2026

Same journal

Rethinking mitochondrial metabolism: Intraindividual variability meets population constraints.

Trends in genetics : TIG·2026

Same journal

A role for epigenetics in rapid adaptation.

Trends in genetics : TIG·2026

Same journal

The myth of asexual fungi.

Trends in genetics : TIG·2026

Same journal

Rethinking molecular evolution through protein language model embeddings.

Trends in genetics : TIG·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 5, 2026

Genotyping of Sea Anemone during Early Development

Genotyping of Sea Anemone during Early Development

Published on: May 13, 2019

Drilling for Insight: Forecasting Phenotype from Genotype.

Ali Torkamani¹

¹Scripps Research Translational Institute, La Jolla, California, 92037, USA; Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA 92037, USA; mygenerank.scripps.edu.

Trends in Genetics : TIG

|September 18, 2018

Summary

This summary is machine-generated.

Genomic medicine can now predict detailed disease traits from genetic variants. This advances individualized medicine beyond broad disease categories by focusing on specific phenotypic information.

Keywords:

expressivity genome sequencing individualized medicine penetrance phenotypes precision medicine

More Related Videos

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

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

Published on: December 7, 2021

Author Spotlight: A Reproducible and Efficient Method for Accessing Porcine Brain via Craniectomy

Author Spotlight: A Reproducible and Efficient Method for Accessing Porcine Brain via Craniectomy

Published on: July 5, 2024

Related Experiment Videos

Last Updated: Feb 5, 2026

Genotyping of Sea Anemone during Early Development

Genotyping of Sea Anemone during Early Development

Published on: May 13, 2019

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

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

Published on: December 7, 2021

Author Spotlight: A Reproducible and Efficient Method for Accessing Porcine Brain via Craniectomy

Author Spotlight: A Reproducible and Efficient Method for Accessing Porcine Brain via Craniectomy

Published on: July 5, 2024

Area of Science:

Genomics
Individualized Medicine
Computational Biology

Background:

Disease presentation varies significantly between individuals.
Current genomics in personalized medicine often links genetic variants to general disease classifications.
A gap exists in predicting specific phenotypic details from genetic data.

Purpose of the Study:

To develop a novel approach for predicting detailed phenotypic information from disease-causing genetic variants.
To move beyond broad disease categorization in genomic medicine.
To enhance the precision of individualized medicine through variant-phenotype prediction.

Main Methods:

Utilized a dataset of disease-causing genetic variants.
Developed a predictive model linking variants to detailed phenotypic outcomes.
Employed computational methods for variant-phenotype association.

Main Results:

Demonstrated the feasibility of predicting detailed phenotypic information from genetic variants.
Showcased a predictive capability that surpasses linking variants to broad disease categories.
Identified specific variant-phenotype relationships.

Conclusions:

This new approach represents a significant step towards highly personalized disease prediction.
The findings support a future where detailed phenotypic outcomes can be forecasted from an individual's genome.
Advances in genomics can refine individualized medicine by predicting specific disease manifestations.