CRC/TRR 175/1: Leveraging Deep Sequenzing Data to Move From Predictive to Mechanistic Models of Plastid Gene Expression (SP D01)

Deep sequencing and other –omics approaches contribute significant data towards our understanding of how acclimation processes play out at different levels of gene regulation. To integrate these data, we will develop a hierarchical model for translation that accounts for different levels of gene expression across time and quantifies the contributions of each level. To better characterize the impact of acclimation at the RNA level, we will furthermore apply long-read single-molecule direct RNA sequencing (Oxford Nanopore) to gain insights on chloroplast RNA processing, RNA modifications, and translation dynamics.
Deep sequencing and other –omics approaches contribute significant data towards our understanding of how acclimation processes play out at different levels of gene regulation. To integrate these data, we will develop a hierarchical model for translation that accounts for different levels of gene expression across time and quantifies the contributions of each level. To better characterize the impact of acclimation at the RNA level, we will furthermore apply long-read single-molecule direct RNA sequencing (Oxford Nanopore) to gain insights on chloroplast RNA processing, RNA modifications, and translation dynamics.