Biology subjects

Rehmann, E. A.

Publications and source records attributed to Rehmann, E. A..

3 recordsLinked to original sources

bioRxiv2026

Gene repertoire expansion and cis-regulatory diversification shaped 26S proteasome evolution within a proteostasis-centered network

The 26S proteasome is essential for proteostasis and constitutes one of the most conserved molecular machineries in eukaryotes. Its homeostasis is maintained by a mechanistically conserved feedback loop involving kingdom-specific components. Yet, how the proteasome subunits and associated regulatory feedback loop have evolved to accommodate ever-changing cellular context is poorly understood. Here, we combine gene duplicate analysis, cis-regulatory element identification, functional validation, and protein network inference to investigate the evolution of plant 26S proteasome. Proteasome gene repertoires expanded largely independently across plant lineages, with paralogs showing shifts in post-translational modification sites and pronounced transcriptional divergence in response to environmental cues. Comparative analysis of 26S proteasome gene promoters revealed extensive diversification of proteasome-associated cis-elements across plants, with repeated enrichment of related motifs. These observations led to the identification of telomere repeat-binding proteins (TRBs) as novel transcriptional regulators of proteasome genes in A. thaliana, through association with the previously characterized PRCE motif. Finally, evolutionary rate covariation analysis identified a conserved proteasome-associated network connected through proteasome-associated cis-elements and unifying cellular proteostasis. Together, our results indicate that plant 26S proteasome is controlled by a regulatory architecture that combines conserved cis-regulatory mechanisms, lineage-specific innovation, and stress-responsive paralog specialization at the center of the proteostasis network; offering a new perspective on the evolution of one of the most essential molecular complexes.

plant biology↗

bioRxiv2024

Correlated evolutionary rates reveal novel components and cross-compartment connectivity in plant proteostasis systems

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.

molecular biology↗

bioRxiv2024

Phylogenomic prediction of interaction networks in the presence of gene duplication

Assigning gene function from genome sequences is a rate-limiting step in molecular biology research. A proteins position within an interaction network can potentially provide insights into its molecular mechanisms. Phylogenetic analysis of evolutionary rate covariation (ERC) in protein sequence has been shown to be effective for large-scale prediction of functional relationships and interactions. However, gene duplication, gene loss, and other sources of phylogenetic incongruence are barriers for analyzing ERC on a genome-wide basis. Here, we developed ERCnet, a bioinformatic program designed to overcome these challenges, facilitating efficient all- vs-all ERC analyses for large protein sequence datasets. We simulated proteome datasets and found that ERCnet achieves combined false positive and negative error rates well below 10% and that our novel branch-by-branch length measurements outperforms root-to-tip approaches in most cases, offering a valuable new strategy for performing ERC. We also compiled a sample set of 35 angiosperm genomes to test the performance of ERCnet on empirical data, including its sensitivity to user-defined analysis parameters such as input dataset size and branch-length measurement strategy. We investigated the overlap between ERCnet runs with different species samples to understand how species number and composition affect predicted interactions and to identify the protein sets that consistently exhibit ERC across angiosperms. Our systematic exploration of the performance of ERCnet provides a roadmap for design of future ERC analyses to predict functional interactions in a wide array of genomic datasets. ERCnet code is freely available at https://github.com/EvanForsythe/ERCnet.

genomics↗