Proteomics and Genomics in Rice Research

Professor Andy Jones
University of Liverpool
Integration of proteomics and genomics to support next-generation rice research.


Large scale dynamic integration of proteomics and genomics to support next-generation rice research.
Participating Institutions: University of Liverpool; BGI Shenzhen, China

There is extensive omics data for rice, including canonical genomes and gene models for the two major rice varieties Japonica and Indica, variant information for >3000 varieties, RNA-Sequencing data for various conditions, and data profiling protein expression and post-translational modifications (PTMs) on rice proteins, using mass spectrometry (MS). Historically, there has been little coordination between MS data sets and other omics data. In this project, we have generated a very large database from public RNA-Seq data sets to determine possible coding genes, and queried publicly available rice MS data sets against canonical gene models and RNA-Seq data. The results were able to determine loci where current gene models can be improved (692), find putative new genes (101), and provide experimental validation for >8000 rice genes at the protein-level [1]. All results can be displayed as permanent tracks on Ensembl plants/Gramene databases, using a new standard called proBed [2]. We also analysed PTM data from rice, to understand evolutionary conservation of PTMs and related pathways versus Arabidopsis [3].
[1] Ren, Z., et al. (2018) Mol Cell Proteomics, mcp.RA118.000832. doi: 10.1074/mcp.RA118.000832.
[2] Menschaert, G., et al. (2018) Genome Biology 19, 12
[3] Al-Momani, S., et al. (2018) J Proteomics 181, 152-159