Abstract
Quantitative trait loci (QTL) studies of common diseases have been spectacularly successful in the last few years and became routine in medical genetics. These studies typically identify genetic variants (QTLs) that are associated with organismal phenotypes, such as susceptibility to disease. Genetic variants can underlie the abundance of gene transcripts, forming ‘expression QTLs’ (eQTLs; [1]). Despite the biomedical importance of understanding how such loci truly affect quantitative traits, several questions remain unsolved: What is the particular mechanism by which a genomic locus affects a quantitative trait? Which specific signaling pathways are responsible for propagating the inherited variation from an eQTL to the gene expression or physiological trait? On which component within such a pathway does the genetic variant act? While it is clear that genetic variants play a critical role in quantitative traits, it is still not fully understood how such variants lead to the inherited variation.
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References
Mackay, T.F., Stone, E.A., Ayroles, J.F.: The genetics of quantitative traits: challenges and prospects. Nat. Rev. Genet. 10(8), 565–577 (2009)
Kim, Y.A., Przytycka, T.M.: Bridging the Gap between Genotype and Phenotype via Network Approaches. Frontiers in Genetics 3, 227 (2012)
Tu, Z., Wang, L., Arbeitman, M.N., Chen, T., Sun, F.: An integrative approach for causal gene identification and gene regulatory pathway inference. Bioinformatics 22(14), e489–e496 (2006)
Suthram, S., Beyer, A., Karp, R.M., Eldar, Y., Ideker, T.: eQED: an efficient method for interpreting eQTL associations using protein networks. Mol. Syst. Biol. 4, 162 (2008)
Gagneur, J., Stegle, O., Zhu, C., Jakob, P., Tekkedil, M.M., Aiyar, R.S., Schuon, A.K., Pe’er, D., Steinmetz, L.M.: Genotype-environment interactions reveal causal pathways that mediate genetic effects on phenotype. PLoS Genetics 9(9), e1003803 (2013)
Gat-Viks, I., Chevrier, N., Wilentzik, R., Eisenhaure, T., Raychowdhury, R., Steuerman, Y., Shalek, A.K., Hacohen, N., Amit, I., Regev, A.: Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli. Nat. Biotechnol. 31(4), 342–349 (2013)
Peirce, J.L., Lu, L., Gu, J., Silver, L.M., Williams, R.W.: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet. 5, 7 (2004)
Kawai, T., Akira, S.: The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nat. Immunol. 11(5), 373–384 (2010)
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Wilentzik, R., Gat-Viks, I. (2015). A Novel Probabilistic Methodology for eQTL Analysis of Signaling Networks. In: Przytycka, T. (eds) Research in Computational Molecular Biology. RECOMB 2015. Lecture Notes in Computer Science(), vol 9029. Springer, Cham. https://doi.org/10.1007/978-3-319-16706-0_34
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DOI: https://doi.org/10.1007/978-3-319-16706-0_34
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