Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome

Kerry A. Ramsbottom, Ananth Prakash, Yasset Perez-Riverol, Oscar Martin Camacho, Zhi Sun, Deepti J. Kundu, Emily Bowler-Barnett, Maria Martin, Jun Fan, Dmytro Chebotarov, Kenneth L. McNally, Eric W. Deutsch, Juan Antonio Vizcaíno, Andrew R. Jones

Research output: Contribution to journalArticlepeer-review

Abstract

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

Original languageEnglish
Pages (from-to)2518-2531
Number of pages14
JournalJournal of Proteome Research
Volume23
Issue number7
DOIs
Publication statusPublished - 5 Jul 2024
Externally publishedYes

Keywords

  • Oryza sativa
  • database searching
  • false localization rate
  • phosphoproteomics
  • software
  • statistics

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