Please use this identifier to cite or link to this item: https://doi.org/10.1038/ng1522
Title: Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease
Authors: Hubner N.
Wallace C.A.
Zimdahl H.
Petretto E.
Schulz H.
Maciver F.
Mueller M.
Hummel O.
Monti J.
Zidek V.
Musilova A.
Kren V.
Causton H.
Game L.
Born G.
Schmidt S.
M�ller A.
Cook S.A. 
Kurtz T.W.
Whittaker J.
Pravenec M.
Aitman T.J.
Issue Date: 2005
Publisher: Nature Research
Citation: Hubner N., Wallace C.A., Zimdahl H., Petretto E., Schulz H., Maciver F., Mueller M., Hummel O., Monti J., Zidek V., Musilova A., Kren V., Causton H., Game L., Born G., Schmidt S., M�ller A., Cook S.A., Kurtz T.W., Whittaker J., Pravenec M., Aitman T.J. (2005). Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nature Genetics 37 (3) : 243-253. ScholarBank@NUS Repository. https://doi.org/10.1038/ng1522
Abstract: Integration of genome-wide expression profiling with linkage analysis is a new approach to identifying genes underlying complex traits. We applied this approach to the regulation of gene expression in the BXH/HXB panel of rat recombinant inbred strains, one of the largest available rodent recombinant inbred panels and a leading resource for genetic analysis of the highly prevalent metabolic syndrome. In two tissues important to the pathogenesis of the metabolic syndrome, we mapped cis- and transregulatory control elements for expression of thousands of genes across the genome. Many of the most highly linked expression quantitative trait loci are regulated in cis, are inherited essentially as monogenic traits and are good candidate genes for previously mapped physiological quantitative trait loci in the rat. By comparative mapping we generated a data set of 73 candidate genes for hypertension that merit testing in human populations. Mining of this publicly available data set is expected to lead to new insights into the genes and regulatory pathways underlying the extensive range of metabolic and cardiovascular disease phenotypes that segregate in these recombinant inbred strains.
Source Title: Nature Genetics
URI: http://scholarbank.nus.edu.sg/handle/10635/149998
ISSN: 10614036
DOI: 10.1038/ng1522
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