Multilayered Genetic and Omics Dissection − A new age for biomedical researches
The manner by which genotype and environment coordinately influence complex traits is one of the fundamental questions in biology. On the one hand, the proteome is more than a mere translation of a genome. DNA sequence is not an accurate proxy for its transcript and protein product, and transcript levels generally have modest correlation with the levels of their corresponding proteins (Ghazalpour et al., 2011; Gygi et al., 1999). On the other hand, genome-wide association analysis (GWAS) and quantitative trait locus (QTL) analysis have been successfully applied to identify genes driving phenotypic variations and have provided valuable evidence on disease-driven SNPs on gene expression. However, it has become evident that regulation of complex traits cannot be fully explained by reductive gene-by-gene or protein-by-protein theory, and genotype-phenotype association will become apparent only with system-scale measurement and multilayered dissection of gene products in the form of dynamic networks.
In the previous study, we combined transcriptomics, targeted proteomics and metabolomics strategies, and applied it to investigate mitochondrial activity in a mammalian genetic reference population (Wu et al., 2014). We have identified dozens of transcript and protein QTLs, several of which were linked to phenotypes. Most significantly, we identified Dhtkd1 as a diabetic gene shared in mice and human. Furthermore, these multilayered data sets allowed further characterization of the mitochondrial unfolded protein reponse (UPRmt), which shows significantly variant responses at the transcript and protein level. Currently, we expanded this integrated omics approach to a more system-wide scale using Sequential Window Acquisition of all THeoretical Mass Spectra (SWATH-MS) and obtained complete coverage of 2,622 proteins in the livers of 80 distinct BXD mice, providing an unprecedentedly comprehensive view of cellular processes in a population study. These findings indicate that the integrated multilayered omics approach is ready to tackle complex traits from an entirely new angle, and a new age for biomedical researches has just begun.
Ghazalpour, A., Bennett, B., Petyuk, V.A., Orozco, L., Hagopian, R., Mungrue, I.N., Farber, C.R., Sinsheimer, J., Kang, H.M., Furlotte, N., et al. (2011). Comparative analysis of proteome and transcriptome variation in mouse. PLoS genetics 7, e1001393.
Gygi, S.P., Rochon, Y., Franza, B.R., and Aebersold, R. (1999). Correlation between protein and mRNA abundance in yeast. Molecular and cellular biology 19, 1720-1730.
Wu, Y., Williams, E.G., Dubuis, S., Mottis, A., Jovaisaite, V., Houten, S.M., Argmann, C.A., Faridi, P., Wolski, W., Kutalik, Z., et al. (2014). Multilayered genetic and omics dissection of mitochondrial activity in a mouse reference population. Cell 158, 1415-1430.