Eberly College of Arts and Sciences
Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant’s sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes use of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. The resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.
Digital Commons Citation
Weighill, Deborah; Jones, Piet; Shah, Manesh; Ranjan, Priya; Muchero, Wellington; Schmutz, Jeremy; Sreedasyam, Avinash; Macaya-Sanz, David; Sykes, Robert; Zhao, Nan; Martin, Madhavi Z.; DiFazio, Stephen; Tschaplinski, Timothy J.; Tuskan, Gerald; and Jacobson, Daniel, "Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery" (2018). Faculty & Staff Scholarship. 1621.
Weighill D, Jones P, Shah M, Ranjan P, Muchero W, Schmutz J, Sreedasyam A, Macaya-Sanz D, Sykes R, Zhao N, Martin MZ, DiFazio S, Tschaplinski TJ, Tuskan G and Jacobson D (2018) Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery. Front. Energy Res. 6:30. doi: 10.3389/fenrg.2018.00030