Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
Project description:Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is still an unsolved issue. Moreover, due to the rapid development of RNA-Seq technology, a vast number of DE analysis methods are created. Applying these newly developed RNA-Seq-oriented tools to proteomics data is still a question that needs to be addressed. In order to benchmark these analysis methods, a proteomics dataset constituted the proteins derived from human, yeast, and drosophila with different ratios were generated. Based on this dataset, DE analysis tools (including array-based and RNA-Seq based), imputation algorithms, and protein quantification methods were compared and benchmarked. This study provided useful information on analyzing quantitative proteomics datasets. All the methods used in this study were integrated into Perseus which are available at https://www.maxquant.org/perseus.
Project description:We performed RNA-seq and Ribo-seq analyses to elucidate the translation in seeds at 85 and 115 DAF. We also completed a data-independent acquisition (DIA)-based proteomic analysis, while also examining relevant lipid metabolites.
Project description:RNA-binding proteins (RPBs) are deeply involved in many fundamental cellular processes in bacteria and are vital for their survival. Despite this, few studies have so far been dedicated to globally identifying bacterial RBPs. We have adapted the RNA interactome capture (RIC) technique, originally developed for eukaryotic systems, to globally identify RBPs in bacteria. RIC takes advantage of the base pairing potential of poly(A) tails to pull-down mRNA-protein complexes. By overexpressing the poly(A) polymerase I, we drastically increase the frequency of polyadenylated RNA in E. coli, allowing us to pull down RNA-protein complexes using immobilized oligo-d(T) as bait. With this approach, we identified 167 putative RBPs, roughly half of which are already annotated as RNA-binding. We experimentally verified the RNA-binding ability of several proteins previously unknown to interact with RNA, including the uncharacterized protein YhgF. YhgF is exceptionally well conserved not only in bacteria, but also in archaea and eukaryotes. We identified YhgF in vivo RNA targets using CLIP-seq, two of which were verified using electromobility shift assays. Our findings present a simple and robust strategy for RBP identification in bacteria, provide a resource of new bacterial RBPs, and lays the foundation for further studies of the strongly conserved RBP Yhg