Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development

• DOI: 10.1371/journal.pgen.1008367
• Publication Date: 2019-09-12T18:38:35Z
• Authors: Robert L. Baker; Wen Fung Leong; Marcus T. Brock; Matthew J. Rubin; R. J. Cody Markelz; Stephen Welch; Julin N. Maloof; Cynthia Weinig
• Keywords: Genetic architecture; Gene regulatory network; Brassica rapa; Pleiotropy

Plant developmental dynamics can be heritable, genetically correlated with fitness and yield, undergo selection. Therefore, characterizing the mechanistic connections between genetic architecture governing plant development resulting ontogenetic of plants in field settings is critically important for agricultural production evolutionary ecology. We use hierarchical Bayesian Function-Valued Trait (FVT) models to estimate Brassica rapa growth curves throughout ontogeny, across two treatments, growing seasons. find variation plasticity rates final sizes, but not inflection point (transition from accelerating decelerating growth) curves. There are trade-offs rate duration, indicating that selection maximum yields at early harvest dates may come expense late vice versa. generate eigengene modules determine which co-expressed FVT traits using a Weighted Gene Co-expression Analysis. Independently, we seed Mutual Rank co-expression network model identify specific genes gene networks related FVT. GO-analyses indicate roles actin/cytoskeletal genes, herbivore resistance/wounding responses, cell division, while MR demonstrate close association metabolic regulation growth. combining Quantitative Loci (QTL) genes/WGCNA expression profiles better characterizes phenotypic than any single data type (i.e. QTL, gene, or alone). Our analysis allows us employ targeted eQTL analysis, regulatory hotspots examine cis vs. trans mechanistically link QTL structural trait variation. Colocalization FVT, provide strong evidence candidate influencing height. The study first explore specifically do so agroecologically relevant settings.