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

Target SNP selection in complex disease association studies.

Matthias Wjst1

  • 1Gruppe Molekulare Epidemiologie, Institut für Epidemiologie, GSF - Forschungszentrum für Umwelt und Gesundheit, Ingolstädter Landstrasse 1, D-85758 Neuherberg/Munich, Germany. wjst@gsf.de

BMC Bioinformatics
|July 14, 2004
PubMed
Summary

Researchers developed a computational method to identify functional Single Nucleotide Polymorphisms (SNPs) for disease association studies. This approach prioritizes SNPs within critical genomic regions, improving genetic variation analysis.

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

INSPECT-SR: a tool for assessing trustworthiness of randomised controlled trials.

medRxiv : the preprint server for health sciences·2025
Same author

Exploring Detection Methods for Synthetic Medical Datasets Created With a Large Language Model.

JAMA ophthalmology·2025
Same author

Neonatal Vitamin D and Associations with Longitudinal Changes of Eczema up to 25 Years of Age.

Nutrients·2024
Same author

Prenatal vitamin D supplementation mitigates inflammation-related alveolar remodeling in neonatal mice.

American journal of physiology. Lung cellular and molecular physiology·2023
Same author

High variability of COVID-19 case fatality rate in Germany.

BMC public health·2023
Same author

Exome variants associated with asthma and allergy.

Scientific reports·2022

Area of Science:

  • Genomics
  • Bioinformatics
  • Human Genetic Variation

Background:

  • Publicly available Single Nucleotide Polymorphism (SNP) data offers extensive insights into human genetic variation.
  • Current methods for selecting SNPs in disease-gene association studies are largely random due to a lack of decision rules for functional relevance.

Purpose of the Study:

  • To develop and implement a computational pipeline for identifying functionally relevant SNPs.
  • To establish decision rules for selecting SNPs with potential impact on gene function and disease association.

Main Methods:

  • A computational pipeline was developed to retrieve gene sequences, analyze variation, and identify SNPs within functional motifs.
  • Considered motifs include promoters, exon-intron structures, mRNA elements, transcription factor binding sites, and splice sites.

Related Experiment Videos

  • A case study focused on 396 genes in the HLA region on chromosome 6p21, analyzing nearly 20,000 SNPs.

    • Main Results:

    • Approximately 2,500 SNPs were identified within functional motifs through computer annotation.
    • Most identified SNPs disrupt transcription factor binding sites; however, only those creating new sites significantly affected SNP allele frequency.
    • Additional criteria for SNP selection include motif position, database entry validity, genomic uniqueness, and cross-mammalian sequence conservation.

    Conclusions:

    • Only 10% of all gene-based SNPs demonstrate sequence-predicted functional relevance.
    • These functionally relevant SNPs are prime candidates for genotyping in association studies.