Comparison of strategies for identification of regulatory quantitative trait loci of transcript expression traits Public Deposited

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Creator
  • Peralta, Juan M
    • Other Affiliation: Southwest Foundation for Biomedical Research, PO Box 760459, San Antonio, Texas 78245-0549, USA
  • Franceschini, Nora
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Göring, Harald HH
    • Other Affiliation: Southwest Foundation for Biomedical Research, PO Box 760459, San Antonio, Texas 78245-0549, USA
  • Li, Hao
    • Other Affiliation: Glaxo-Smith-Kline, 17.2136A Sanders Building, 5 Moore Drive, Research Triangle Park, North Carolina 27709, USA
  • Wojczynski, Mary K
    • Other Affiliation: Department of Biostatistics, University of Alabama-Birmingham, 1665 University Boulevard, Ryals Public Health Building 414, Birmingham, Alabama 35294, USA
  • North, Kari
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Li, Xia
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Dyer, Thomas D
    • Other Affiliation: Southwest Foundation for Biomedical Research, PO Box 760459, San Antonio, Texas 78245-0549, USA
Abstract
  • Abstract In order to identify regulatory genes, we determined the heritability of gene transcripts, performed linkage analysis to identify quantitative trait loci (QTLs), and evaluated the evidence for shared genetic effects among transcripts with co-localized QTLs in non-diseased participants from 14 CEPH (Centre d'Etude du Polymorphisme Humain) Utah families. Seventy-six percent of transcripts had a significant heritability and 54% of them had LOD score ≥ 1.8. Bivariate genetic analysis of 15 transcripts that had co-localized QTLs on 4q28.2-q31.1 identified significant genetic correlation among some transcripts although no improvement in the magnitude of LOD scores in this region was noted. Similar results were found in analysis of 12 transcripts, that had co-localized QTLs in the 13q34 region. Principal-component analyses did not improve the ability to identify chromosomal regions of co-localized gene expressions.
Date of publication
Identifier
  • doi:10.1186/1753-6561-1-S1-S85
Resource type
  • Article
Rights statement
  • In Copyright
Rights holder
  • Nora Franceschini et al.; licensee BioMed Central Ltd.
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Language
  • English
Is the article or chapter peer-reviewed?
  • Yes
Bibliographic citation
  • BMC Proceedings. 2007 Dec 18;1(Suppl 1):S85
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  • Open Access
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  • BioMed Central Ltd
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