Identifying Genes Controlling Complex Traits in Forest Trees via Network Construction and Decomposition

Abstract:  We report that we have developed two cost-efficient approaches to identify genes that control complex traits in forest trees.  One is to construct co-expression network of all regulatory genes and then decompose it to identify coordinated regulators that collectively govern a complex trait.  The other approach is to build multi-layered hierarchical gene regulatory network (ML-hGRN) using small- or medium-size of gene expression data sets (> 9 microarrays or RNA-seq libraries).  Based on the network topology, we can identify pleiotropic regulators that exert control over complex traits.  Both approaches were validated with experimental approaches and data, and proven to be highly efficient in identifying important high hierarchical regulators that regulate complex traits.