What determines protein abundance in plants?

This project aims to understand how protein abundance is controlled in plants and to determine the phenotypic consequences of proteomic variation, together with genotypic, structural, epigenotypic and transcriptomic variation. We propose an integrated programme of quantitative trait loci (QTL) analysis of an Arabidopsis multiparental advanced generation intercross (MAGIC) population. Firstly, we will determine all variation in the 19 MAGIC founders, and interactions between different 'omic layers, via a comprehensive set of assays. Long-read sequencing of 18 founders' genomes will be performed for comparison of structural variation relative to the 19th founder, the Col-0 reference. We will measure epigenetic marks of cytosine DNA methylation and chromatin accessibility by ATAC-seq. Transcript abundance and regulatory RNA species will be analysed by RNA-seq and protein translation and abundance quantified by Ribo-seq and proteomics, respectively. Next, a holistic experimental and computational analysis of 400 Arabidopsis MAGIC RILs (recombinant inbred lines) will be used to understand the regulatory networks controlling protein expression and dissect the relative contributions of genotype (including small-scale variation and large-scale structural rearrangements), RNA transcription, protein synthesis and protein degradation. We will use statistical and machine learning (ML) approaches to construct different types of molecular networks and identify causal mediators. Co-expression analysis will also identify novel physical complexes and sets of proteins that participate in common processes. Selected networks and complexes will be tested experimentally. Whole plant phenotyping of the MAGIC lines will be performed and used together with the molecular data to interrogate the predictive ability of different 'omic layers across a range of phenotypes. Finally, data and knowledge generated will be shared with the community through a user-friendly web resource.