Pathway_eQTL_online - A systems biology approach for...

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A systems biology approach for identifying novel pathway regulators in eQTL mapping Shaoyu Li 1 , Qing Lu 2 and Yuehua Cui 1* 1 Department of Statistics & Probability, 2 Department of Epidemiology, Michigan State University, East Lansing, Michigan 48824 Running head : Identify pathway regulators in eQTL mapping Abstract Expression quantitative trait loci (eQTL) mapping holds great promise in elucidating gene regulations and predicting gene networks associated with complex phenotypes. We propose a systems biology approach by incorporating prior pathway information into an eQTL mapping framework, to identify novel pathway regulators that mediate pathway expression changes. We model gene expressions in a pre-defined biological pathway as a multivariate response to test the joint variation changes among different genotype categories at a locus. The method is motivated and applied to a yeast dataset. Significant pathway regulators and regulation hotspots are detected. The proposed method provides a powerful tool for understanding gene regulations in a pathway level. Key words: Expression quantitative trait loci, Hotelling’s 2 T test, pathway enrichment analysis, Pathway regulator, Pathway regulation hotspot *To whom correspondence should be addressed: Dr. Yuehua Cui, [email protected] 1
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1 Introduction Traditional quantitative trait loci (QTL) mapping has been focused on identifying genetic loci responsible for the phenotypic changes of a trait. Such studies are designed to detect linkage or association between genetic markers and the functional (causal) variants responsible for the phenotypic changes, and fail to disentangle the functional mechanisms of variants due to the regulation of other genes. In addition, the number and effect size for the detected alleles for most complex traits are very limited, leaving a large faction unaccounted for from a systems biology perspective. Recent advances on microarray technology open an alternative front for multiple gene discoveries by studying thousands of gene expression profiles simultaneously under certain conditions or treatments. As an intermediate process that associates transcriptional profiles with an organism’s trait variation, analysis of gene expression holds great promise to infer genetic regulatory changes accompanying a disease trait, and serves as an alternative to identify novel relationships among genes. A number of studies have shown that gene expressions are inheritable traits, thus can be used for genetic mapping (e.g., Brem et al., 2002; Cheung et al. 2003; Schadt et al. 2003). The two endeavors, genetic mapping and gene expression analysis, were recently merged together through a procedure called expression QTL (eQTL) mapping in which each gene expression is considered as one trait for QTL identification (Schadt et al., 2003). Most current eQTL mapping studies treat each gene expression as one single trait. The so
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This note was uploaded on 04/06/2010 for the course COMPUTER S COSC1520 taught by Professor Paul during the Spring '09 term at York University.

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Pathway_eQTL_online - A systems biology approach for...

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