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

Combined expression trait correlations and expression quantitative trait locus mapping.

Hong Lan1, Meng Chen, Jessica B Flowers

  • 1Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, USA.

Plos Genetics
|January 21, 2006
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

AutoZyme: An Autonomous Agentic Framework to Optimize Bioinformatics Software.

bioRxiv : the preprint server for biology·2026
Same author

Pancreatic islet α cell function and proliferation require the arginine transporter SLC7A2.

The Journal of clinical investigation·2026
Same author

Cost-effectiveness analysis of encorafenib in untreated BRAF V600E-mutant metastatic colorectal cancer in China.

The pharmacogenomics journal·2026
Same author

Human neural organoid modeling of diffuse midline glioma captures the complexity of patient tumors.

Journal of neuro-oncology·2026
Same author

Proinsulin regulators identified with CRISPR screen and in vivo mouse QTL mapping.

Nature communications·2026
Same author

Distinct genetic architecture of gene and isoform level QTL in the Diversity Outbred (DO) mouse population.

bioRxiv : the preprint server for biology·2026
Same journal

Genetic survey of biomarkers at early and mid-pregnancy identifies pregnancy-specialized immune regulation.

PLoS genetics·2026
Same journal

Argonaute proteins orchestrate Meiotic Sex Chromosome Inactivation and timing of the spermatogenic transcriptional program.

PLoS genetics·2026
Same journal

Genome wide association study meta-analysis of neuropathologic lesions of Alzheimer's disease and related dementias in a multi-site autopsy cohort.

PLoS genetics·2026
Same journal

Microtubule stiffening by the doublecortin-domain protein ZYG-8 contributes to mitotic spindle orientation during zygote division in Caenorhabditis elegans.

PLoS genetics·2026
Same journal

Multiple instance fine-mapping: Predicting causal regulatory variants with a deep sequence model.

PLoS genetics·2026
Same journal

Nuclear ubiquitin-conjugating enzyme TrUbc4 and F-box protein TrFwd1-mediated modification of Cre1 in Trichoderma reesei establishes a regulatory mechanism for carbon catabolite repression.

PLoS genetics·2026
See all related articles

Analyzing gene expression correlations across genetic variations reveals regulatory networks. This approach identifies gene functions and novel pathway members, offering greater sensitivity than traditional linkage mapping alone.

Area of Science:

  • Genomics
  • Systems Biology
  • Gene Expression Analysis

Background:

  • Gene expression correlation analysis across time or tissues aids in predicting gene function.
  • Exploring correlations across a genetic dimension offers insights into coregulated genes and regulatory loci.
  • Understanding gene regulatory networks is crucial for deciphering complex biological processes.

Purpose of the Study:

  • To investigate gene expression correlations across a genetic dimension to identify regulatory networks.
  • To predict functions of uncharacterized genes and characterize novel pathway members.
  • To assess the sensitivity of combined trait correlation and linkage mapping analysis.

Main Methods:

  • Calculated correlations among approximately 45,000 expression traits from 60 F2 individuals.

Related Experiment Videos

  • Integrated correlation data with linkage mapping information.
  • Performed experimental validation for identified gene candidates.

    • Main Results:

    • Identified regulatory networks and made functional predictions for uncharacterized genes.
    • Found coordinate regulation of 174 G protein-coupled receptor protein signaling pathway expression traits.
    • Characterized a Riken cDNA clone involved in lipid metabolism regulation, validated experimentally.

    Conclusions:

    • Trait correlation combined with linkage mapping effectively reveals regulatory networks missed by studying individual mRNA traits.
    • This integrated approach is more sensitive than linkage mapping alone for detecting gene regulatory relationships.
    • The study highlights the power of genetic dimension correlation in uncovering complex gene interactions and functions.