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 >or= 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.
Highlights
There is a breadth of information being generated by the Human Genome Project and the interpretation of these data has been a major area of research
In an effort to dissect some of these complexities, we performed linkage analysis of gene expression transcripts of members of Centre d'Etude du Polymorphisme Humain (CEPH) Utah families to determine the heritability of transcripts and the evidence for regulatory quantitative trait loci (QTLs) and we performed pairwise bivariate linkage analysis and principal-component analysis (PCA) for data-reduction to evaluate the evidence for shared genetic effects
Fifteen transcripts co-localized in this region in the univariate linkage analysis, and the LOD scores ranged from 1.17 to 3.72
Summary
There is a breadth of information being generated by the Human Genome Project and the interpretation of these data has been a major area of research. For complex oligogenic or polygenic disorders, understanding all the interconnections between genes influencing a trait is a difficult task because the understanding of the biology of many of these disorders is still evolving. Multiple gene × gene and gene × environment interactions can influence the expression of phenotypes. Genes can interact by modifying the expression of other genes and function as regulatory genes [1]. In an effort to dissect some of these complexities, we performed linkage analysis of gene expression transcripts of members of Centre d'Etude du Polymorphisme Humain (CEPH) Utah families to determine the heritability of transcripts and the evidence for regulatory quantitative trait loci (QTLs) and we performed pairwise bivariate linkage analysis and principal-component analysis (PCA) for data-reduction to evaluate the evidence for shared genetic effects. The ability to assess gene expression traits simultaneously and to link them to QTLs offers the possibility of identifying previously unknown underlying molecular processes for future investigation
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