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

Methods for genetic linkage analysis using trisomies

E Feingold1, N E Lamb, S L Sherman

  • 1Division of Biostatistics, Emory University School of Public Health, Atlanta, GA 30322.

American Journal of Human Genetics
|February 1, 1995
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

Patricia A. Jacobs (1934-2026).

American journal of human genetics·2026
Same author

Pilot GWAS of caries in African-Americans shows genetic heterogeneity.

BMC oral health·2019
Same author

Systematic reanalysis of genomic data improves quality of variant interpretation.

Clinical genetics·2018
Same author

Genetic Association of <i>MMP10</i>, <i>MMP14</i>, and <i>MMP16</i> with Dental Caries.

International journal of dentistry·2017
Same author

Presence of inclusions positive for polyglycine containing protein, FMRpolyG, indicates that repeat-associated non-AUG translation plays a role in fragile X-associated primary ovarian insufficiency.

Human reproduction (Oxford, England)·2015
Same author

Association between telomere length and chromosome 21 nondisjunction in the oocyte.

Human genetics·2015
Same journal

Bi-allelic missense variants in human GPN2 result in Perrault syndrome.

American journal of human genetics·2026
Same journal

Integrative analysis of gastric tissue transcriptomes and gastric cancer GWAS implicates candidate susceptibility genes.

American journal of human genetics·2026
Same journal

A transparent and generalizable deep-learning framework for genomic ancestry prediction.

American journal of human genetics·2026
Same journal

Data-driven RNA phenotyping captures genetically regulated dimensions of the transcriptome.

American journal of human genetics·2026
Same journal

Linkage disequilibrium and allelic heterogeneity explain variation in coronary artery disease risk at 9p21 across populations and reduced effect in Africans.

American journal of human genetics·2026
Same journal

Genome-wide association study and predictors of neonatal blood cell traits in Hispanic newborns.

American journal of human genetics·2026
See all related articles

This study introduces a novel linkage analysis method to map genes for rare genetic disorders that are more common in individuals with trisomy. The method uses trisomic individuals to identify susceptibility genes by analyzing marker homozygosity inherited from the nondisjoining parent.

Area of Science:

  • Human Genetics
  • Statistical Genetics
  • Medical Genetics

Background:

  • Specific genetic disorders, such as leukemia and duodenal atresia, exhibit increased prevalence in individuals with trisomies, notably trisomy 21.
  • Understanding the genetic basis of these disorders can be challenging due to their rarity in the general population.

Purpose of the Study:

  • To develop and present a novel statistical method for gene mapping using individuals with trisomies.
  • To leverage trisomic individuals to identify genes associated with specific genetic disorders and susceptibility traits.

Main Methods:

  • A gene-specific dosage model is employed, positing that trait susceptibility is influenced by specific alleles at one or a few loci.
  • The method involves analyzing trisomic individuals for markers showing greater than expected homozygosity in chromosomes inherited from the nondisjoining parent.

Related Experiment Videos

  • Statistical techniques for linkage analysis, distance estimation, confidence intervals, power/sample size calculations, and handling partially informative markers are presented.

    • Main Results:

    • The proposed linkage analysis method provides a framework for mapping genes in trisomic populations.
    • Statistical tools are detailed for practical implementation, including testing linkage, estimating gene-marker distance, and assessing statistical power.
    • The approach is adaptable for candidate gene testing and utilizes partially informative markers.

    Conclusions:

    • Trisomic individuals offer a unique resource for mapping genes underlying specific genetic disorders.
    • The presented linkage analysis method provides a robust statistical approach to identify susceptibility genes in these populations.
    • This methodology can enhance our understanding of genotype-phenotype correlations in chromosomal abnormalities.