Identifying Regulatory Genes in Gene Expression
Author Information
Author(s): Nora Franceschini, Mary K Wojczynski, Harald HH Göring, Juan Manuel Peralta, Thomas Dyer, Xia Li, Hao Li, Kari E North
Primary Institution: University of North Carolina Chapel Hill
Hypothesis
Can we identify regulatory quantitative trait loci (QTLs) for gene expression traits in non-diseased participants from CEPH Utah families?
Conclusion
The study identified several chromosomal regions of co-localized trans-regulatory genes with significant heritability, but linkage analysis did not improve the ability to identify these regions compared to univariate analysis.
Supporting Evidence
- 76% of transcripts had significant heritability.
- 54% of transcripts had LOD scores ≥ 1.8.
- Significant genetic correlation was found among some co-localized transcripts.
Takeaway
The researchers looked at genes that control how other genes work and found some important areas in the DNA, but their new methods didn't find more than the old methods.
Methodology
Linkage analysis of gene expression transcripts from 14 CEPH Utah families, heritability estimation, and principal-component analysis.
Potential Biases
Potential bias due to the small number of individuals and the adjustment for covariates.
Limitations
The small sample size may limit the power of the analyses, and the regions selected for analysis were arbitrarily chosen.
Participant Demographics
Non-diseased participants from 14 three-generation CEPH Utah families.
Statistical Information
P-Value
<0.001
Statistical Significance
p<0.05
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