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 Experiment Videos

Mapping binary trait loci in the F(2:3) design.

Chengsong Zhu1, Ju Huang, Yuan-Ming Zhang

  • 1Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement/National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China.

The Journal of Heredity
|July 12, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

[1,3-dicaffeoylquinic acid mitigates dextran sulfate sodium-induced colitis in mice by alleviating oxidative stress <i>via</i> inhibiting the PI3K/Akt pathway].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University·2026
Same author

Defining an Optimal Boron-Doping Window to Navigate the Trade-Off between Li-Ion Kinetics and Interfacial Stability in LiMn<sub>0.6</sub>Fe<sub>0.4</sub>PO<sub>4</sub>@C Cathodes.

ACS applied materials & interfaces·2026
Same author

A novel therapeutic monoclonal antibody targeting PZR demonstrates potent anti-metastatic efficacy in triple-negative breast cancer.

Journal of translational medicine·2026
Same author

A nurse-led bundled care intervention for preventing deep vein thrombosis in immobilized neurosurgical patients: a quasi-experimental study.

Frontiers in neurology·2026
Same author

Genomics meets metabolomics: decoding <i>Arnebia tschimganica</i> and the shikonin biosynthesis pathway.

Horticulture research·2026
Same author

Deciphering small sequence differences in T cell receptor-antigen pairing.

Nature communications·2026
Same journal

Chromosome-scale genome assembly of the rice stink bug (Hemiptera: Oebalus pugnax) illuminates genome structure and gene family evolution in Pentatomidae.

The Journal of heredity·2026
Same journal

Rapid Derivation of Cloning-Competent Cells from Peripheral Blood Advances Conservation Biobanking.

The Journal of heredity·2026
Same journal

Genomic vulnerability to climate change of a poorly dispersing and threatened fish, the southern pygmy perch (Nannoperca australis).

The Journal of heredity·2026
Same journal

The complete genomes of two hybridizing field crickets, Gryllus pennsylvanicus and Gryllus firmus.

The Journal of heredity·2026
Same journal

Chromosome-level genome assembly and annotation of the transverse lady beetle Coccinella transversoguttata.

The Journal of heredity·2026
Same journal

A Chromosome-Level Assembly of the Pine Processionary Moth (Thaumetopoea pityocampa) genome.

The Journal of heredity·2026
See all related articles

This study introduces a new method for mapping binary trait loci (BTL) using an F(2:3) design, improving precision for low heritability traits. The approach enhances the power of quantitative trait loci (QTL) detection in genetic analysis.

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Quantitative trait loci (QTL) detection with low heritability presents precision challenges.
  • An F(2:3) design improves precision by genotyping F(2) plants and phenotyping F(2:3) progeny, reducing residual variance.
  • Previous work demonstrated mixture distribution enhances QTL detection power in F(2:3) designs for continuous traits.

Purpose of the Study:

  • Extend the mixture distribution method to binary traits within the F(2:3) design.
  • Develop a novel framework for mapping binary trait loci (BTL) that integrates penetrance and liability models.
  • Enhance the statistical power and accuracy of BTL detection, especially for traits with low heritability.

Main Methods:

  • Integrated penetrance and liability models for binary trait loci mapping.

Related Experiment Videos

  • Utilized the sum of phenotypic values of F(2:3) progeny (following binomial distribution) for analysis.
  • Implemented the Expectation-Maximization algorithm within a single BTL model framework.
  • Estimated the threshold within the liability model.

    • Main Results:

    • The proposed method accurately estimates BTL effects and locations.
    • Demonstrated high statistical power for BTL detection, even with low heritability.
    • Simulated studies confirmed the method's effectiveness and accuracy.

    Conclusions:

    • A robust framework for mapping binary trait loci (BTL) using the F(2:3) design is established.
    • The new method offers improved precision and power for genetic analysis of binary traits.
    • The developed computational tool is available for real-world genetic mapping applications.