Genome Biology and EvolutionMolecular BiologyPeer-reviewed journal article
Correlated evolutionary rates reveal novel components and cross-compartment connectivity in plant proteostasis systems
Tony C GattsiD, Elizabeth A RehmanniD, Linnea E LaneiD, Daniel B. SloaniD, Evan S. ForsytheiD
Abstract
Plant cells rely on an interconnected network of proteins interacting at many levels (e.g. physical enzyme complexes, gene regulatory modules, and biosynthetic pathways). Pairs of proteins that interact at any of these levels have been shown to exhibit phylogenetic signatures of evolutionary rate covariation (ERC), providing a basis for detecting functional interactions among proteins. Here, we apply ERCnet, a bioinformatic tool for performing genome-scale ERC analyses, to predict a plant protein-protein interactome network. We find a clustered set of proteins that exhibit strong signatures of ERC with the plastid caseinolytic protease (Clp) and other plastid proteostasis components, thus forming a functional module within the network. In addition to including proteins with known or predicted functions in protein import, transcription, translation, and degradation in plastids, the module also includes proteins with previously unknown molecular function, thus providing evidence that these proteins may contribute to plastid proteostasis in novel ways. Perhaps the most surprising members of this module are a set of proteins that are not thought to localize to the plastid at all. These proteins include a mitochondrial-localized pentatricopeptide repeat (PPR) protein with genetic evidence of interaction with the mitochondrial Clp system and two nuclear-localized actin-related proteins involved in chromatin remodeling and epigenetic regulation of nuclear genes. We speculate that these non-plastid-localized proteins act as mediators of organellar crosstalk and retrograde signaling of cellular proteostasis status in plants. In summary, our results highlight the connected nature of plant proteostasis systems and point to a promising set of novel proteostasis protein candidates.
- organism: plant (other)
- assay: protein sequence
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 4
- FWCI
- 4.10
- Field percentile
- top 9%
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