Author_Institution :
JM Rendel Lab., CSIRO Livestock Ind., Rockhampton, QLD
Abstract :
Genetical systems biology or systems genetics treats the genome as the central reference point for all omics variations and is an emerging new branch of systems biology. Quantitative genetic principles were developed for high-throughput genomic, transcriptomic and metabolomic data observed in large populations. New statistical genetic models were developed for expression quantitative trait loci (eQTL), namely, marker regression eQTL mapping and marker-expression co-factor mapping. Evaluations of power to detect eQTL showed that sample size requirements are higher for detecting trans-acting genes than cis-acting genes. Power is higher for eQTL with high heritability than for eQTL with low heritability. These results will be valuable for systems genetic investigations. Gonadotrophin releasing hormone (GnRH) and its receptor gene (GnRH-R) are crucial for mammalian reproduction. Whole genome scan of eQTLs for GnRH-R gene expression in mouse showed three possible trans-eQTL regions on chr 13 and 19, harbouring regulatory genes. Applications of genetical genomics in systems biology were identified as: (1) detection and validation of causal gene for complex traits; (2) development of genetic interaction networks; (3) prediction of transcription factor binding sites and (4) in data-driven systems biology. These applications were illustrated using data on eQTL, protein network and signalling pathways for GnRH. Gpr54 (G protein-coupled receptor kinase 54), Prl (prolactin), Ins1 (insulin) and Fos (viral oncogenes) were found to be major regulators of GnRH and GnRH-R; thus validating their important role in reproduction, mammary gland development and sexual (im)maturity. These results will be useful for further study of mammalian reproductive biology.
Keywords :
biochemistry; biology computing; enzymes; genetics; proteins; G protein-coupled receptor kinase; data-driven systems biology; gene expression; genetic interaction networks; genetical systems biology; genomic data; gonadotrophin releasing hormone; mammary gland development; marker regression mapping; marker-expression co-factor mapping; metabolomic data; protein network; quantitative trait loci; receptor gene; reproductive biology; sexual maturity; signalling pathways; statistical genetic model; trans-acting genes; transcription factor binding sites; transcriptomic data;