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

Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Trihybrid Crosses02:27

Trihybrid Crosses

Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal chance to...
Monohybrid Crosses01:20

Monohybrid Crosses

Overview
Monohybrid Crosses01:20

Monohybrid Crosses

Overview
Dihybrid Crosses01:18

Dihybrid Crosses

Overview
Test Cross01:39

Test Cross

Alleles are different forms of the same gene. Humans and other diploid organisms inherit two alleles of every gene, one from each parent.

You might also read

Related Articles

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

Sort by
Same author

Care Coordination and Hospitalization in Older Adults With or at Risk for Cardiovascular Disease: A Randomized Clinical Trial.

JAMA network open·2026
Same author

Remote Symptom Assessment in Ambulatory Palliative Care: User-Centered Development of an mHealth App.

Journal of palliative medicine·2026
Same author

BCGLMs: Bayesian modeling for disease prediction using compositional microbiome features.

Bioinformatics advances·2026
Same author

iMprovIng the meNtal hEalth of home healTh AiDeS: A study protocol for the MINDSET study.

Contemporary clinical trials·2025
Same author

Persistent poverty, glycemic control and adverse COVID-19 outcomes: a retrospective study using real-world data.

BMC public health·2025
Same author

Home Health Aides Caring for Adults With Heart Failure: A Pilot Randomized Clinical Trial.

JAMA network open·2025
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: May 22, 2026

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii
11:37

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

Identifying QTL for multiple complex traits in experimental crosses.

Samprit Banerjee1, Nengjun Yi

  • 1Division of Biostatistics and Epidemiology, Department of Public Health, Weill Cornell Medical College, New York, NY, USA. sab2028@med.cornell.edu

Methods in Molecular Biology (Clifton, N.J.)
|May 9, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a multivariate Bayesian model for joint quantitative trait loci (QTL) analysis. It enhances pleiotropy detection and estimation precision for complex traits using R/qtlbim software and Markov Chain Monte Carlo methods.

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

Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants
11:44

Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants

Published on: May 13, 2015

Related Experiment Videos

Last Updated: May 22, 2026

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii
11:37

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

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

Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants
11:44

Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants

Published on: May 13, 2015

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Joint analysis of multiple complex traits offers advantages over independent analysis, including detecting pleiotropy and improving estimation precision.
  • Quantitative trait loci (QTL) identification is crucial for understanding the genetic basis of complex traits.
  • Existing methods may not fully leverage the correlations between multiple traits.

Purpose of the Study:

  • To introduce and evaluate a multivariate Bayesian model for the joint analysis of multiple correlated complex traits.
  • To present a statistical software (R/qtlbim) implementing this model for QTL identification.
  • To demonstrate strategies for model selection, convergence checking, and pleiotropy testing.

Main Methods:

  • Development and application of a multivariate Bayesian model for joint QTL analysis.
  • Utilizing Markov Chain Monte Carlo (MCMC) methods for sampling from posterior distributions.
  • Implementation within the R/qtlbim statistical software package.

Main Results:

  • The multivariate model facilitates the identification of pleiotropy across multiple traits.
  • Joint analysis improves the precision of QTL effect estimates compared to independent analyses.
  • The R/qtlbim software provides a practical framework for implementing these advanced statistical methods.

Conclusions:

  • Joint analysis of correlated complex traits using a multivariate Bayesian framework is a powerful approach for QTL mapping.
  • The R/qtlbim software offers a comprehensive tool for researchers to perform such analyses, including model selection and pleiotropy testing.
  • This methodology enhances our ability to dissect the genetic architecture of complex traits and understand gene action across multiple biological functions.