Boosting complex traits analyses in maize through the integration of pan-genomics and transcriptomics in a multiparental population

Maize is characterized by great genetic diversity, whose potential has yet to be fully exploited by plant breeding. In this work we aim at identifying genetic variants and evaluating their impact on the phenotypic expression of complex traits. To achieve our purposes we use a segregant population derived by crossing eight genetically diverse inbred lines, the Multi-parent Advanced Generation InterCrosses (MAGIC) maize population. We created a new platform for the detection of Structural Variants (SVs) on the MAGIC population: the pan-genome of the founders. This is done by performing long reads sequencing with Oxford Nanopore Technologies and de novo assembly of the 8 parental lines. The combination of the founders’ pan-genome with phenotypic data produced on the population, allows the detection of SVs controlling traits of interest. Complex traits are regulated by the combined action of multiple genes’ products, whose expression can depend on specific genetic makeup. We developed a systemic approach to reconstruct the network of interactions underlying gene expression, by combining genotyping and transcriptomics data produced on the Recombinant Inbred Lines (RILs) of the MAGIC population. The resulting network is weighted for the impact of genetic diversity in regulating gene expression. Our work shows how the integration of genome-scale data can inform the reconstruction of allelic diversity in maize and support the identification of genetic targets valuable for crop improvement.