DOI: 10.5061/dryad.hx3ffbgp7
title: Plastid-nuclear ERCnet analysis results

description: 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. Furthermore, 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 prior 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.
description: The data included here are the output of the ERCnet program. See
 the ERCnet GItHub page (https://github.com/EvanForsythe/ERCnet) for deteailed descriptions of outfile files.
description: # Plastid-nuclear ERCnet analysis results
 [https://doi.org/10.5061/dryad.hx3ffbgp7](https://doi.org/10.5061/dryad.hx3ffbgp7) ## Description of the data and file structure The data deposited here are a zipped folder containing several subfolders. These folders contain the output files and metadata from the ERCnet program. ### Files and variables #### File: OUT_ERC_Final.zip **Description:**  From ERCnet GitHub README (release v1.1.0): Below is a brief description of each of the files and subdirectories that are output during a run of ERCnet. Many of the files created are intermediate files, which you likely will not need to inspect. Directories are shown in the order in which they're created during the ERCnet workflow. * `ERCnet-1.1.0.zip`: contains a clone of the ERCnet code used for this analysis. * `Species_mapping.csv`: shows how ERCnet recognizes species IDs * `Seq_counts_per_species.csv`: shows how many homologs from each species were found in each gene family * `SpeciesTree_rooted_node_labels.txt`: a copy of the species tree from Orthofinder * `Filtered_genefam_dataset.csv`: each row represents a gene family (hierarchical orthogroup [HOG] from orthofinder) and the seq IDs of all the sequences in the gene family * `benchmark/`: log files that track the runtime of each step of ERCnet. If steps are performed multiple times, files will be appended with numbers in ascending order. * `HOG_seqs/`: contains a seperate file for each gene family (hierarchical orthogroup [HOG] from orthofinder). * `Alns/`: contains a seperate file with a multiple sequences alignment for each HOG * `TAPER_Alns/`: an (optional) version of the alignments that have been cleaned using TAPER * `Gb_alns`: a version of the alignments that have been cleaned using GBLOCKS. **These are the final alignments used to infer trees with optimized branch lengths.** Files ending in "reduced" were generated by RAxML when identical sequences are found within an alignment, but these reduced versions are not used in downstream analyses.  * `Aln_pruning/`: stores information about sequences that were pruned from alignments because GBLOCKS yielded only gaps * `HOG_subtrees`: orthfinder produces gene trees for each orthogroup (OG); however, ERCnet works with HOGs (which are subtrees of the larger OG tree). This folder contains the subtrees that are extracted from the larger OG tree. * `Non-binary_subtrees.txt`: documents any gene families that were dropped from analysis because gene trees (from orthofinder) were non-bifurcating, which causes errors in R. * `BS_reps/`: subtrees (see HOG_subtrees) are used as a constraint tree and raxml bootstrapping is performed to get confidence values for each branch on the constraint tree. This directory stores the replicate files. * `BS_trees/`: subtrees with BS confidence scores (from BS_reps) * `SpeciesTree_mapped_names.txt`: Version of the species tree with the mapped species IDs from Species_mapping.csv. * `Rearranged_trees/`: the treerecs prpgram is used to rearrange any poorly supported branches (&lt;80% bootstrap support) so that the branches best match the species tree. * `BL_trees/`: branch length optimization is performed on the rearranged version of the tree. This folder contains three types of files output by the raxml program. Only files starting in RAxML_result* are used in downstream analyses. **These trees are the final gene trees used to perform ERC**. * `DLC_par/`: The last step in Phylogenomics.py creates the inputs (*NODES_BL.txt files), needed to run DLCpar,  which helps map gene trees to the species tree. GTST_reconciliation.py writes additional files to this directory, resulting in five file types generated by the DLCpar program. Only files ending in *dlcpar.locus.recon are used in downstream steps of ERCnet. * `BL_results/`: contains the branch lengths that were measured from the BL_trees/ trees. ERCnet measures branches by both branch-by-branch (BXB) and root-to-tip (R2T) methods. This directory also contains the normalized branch lengths, in which each branch length is normalized by the genome-wide average branch legth for that particular branch. Normalized branch lengths are used for downstream ERC correlation analyses.  * `ERC_results/`: This directory contains the results of the all-by-all ERC analysis. This folder will contain seperate ERC results for BXB vs R2T (depending on user selection). See below for the description of the column headers in the ERC_results tsv file. This directory will also contain a subdirectory, `Filtered_results/`, with a tsv file of 'ERC hits' (generated during Network_analyses.py). * Column headers in the ERC_results tsv file * **GeneA_HOG**: HOG id for 'gene A' (note gene A vs B are abirary terms to denote the two genes being compared in the pairwise ERC comparison) * **GeneA_ID**: the seqID for gene A from the 'focal species' (defined be the user) * **GeneB_HOG**: HOG id for 'gene B' * **GeneB_ID**: the seqID for gene B from the 'focal species' (defined be the user) * **Overlapping_branches**: number of branches shared between gene tree A and B. This is the number of points of the linear correlation plot for a give ERC comparison * **Slope**: Slope of the best fit line * **P_R2**: Pearson correlation R-squared * **P_Pval**: Pearson correlation P-value * **S_R2**: Spearman correlation R-squared * **S_Pval**: Spearman correlation P-value * **P_FDR_Corrected_Pval**: FDR corrected version of the Pearson p-value * **S_FDR_Corrected_Pval**: FDR corrected version of the Spearman p-value * `Network_analyses/`: This directory contains networks displaying the 'ERC hits'. ERC hits are defined by the user according the p-value and r-squared cutoffs during Network_analyses.py. If the user tries several different filtering cutoffs, seperate versions of the network files will be stored here. The file names indicate the cutoffs chosen (e.g. "0.0001_0.5" indicates filtering thresholds of p&lt;0.0001 and r2&gt;0.5). To begin inspecting these results, we recommend first looking at the ERC_network*.pdf file. This will give a quick (and sometimes ugly) view of the network. For more detailed inspection, we recommend using the cytoscape GUI program and importing the Cytoscape_network*.graphml file. This creates a much more human-readable and interactive version or the network. `BINGO_analysis/` contains the outputs of GO enrichment analyses performed using the Cytoscape plugin BINGO.  Network_assortativity_Filtered_ERC_results_R2T_3_0.0001_0.5_fg_trimcutoff_0.pdf contains the output of the functional clustering assortativity analysis. Plastnuc_fig_prep.cys and Peptidase_ERC_network.cys contain the cytoscape sessions used to generate network figures displaying subcellular localization and proteolysis attributes, respectively. All other files are supplementary files not directly used in the study. # Access information Other publicly accessible locations of the data: * NA Data was derived from the following sources: * [https://github.com/EvanForsythe/ERCnet](https://github.com/EvanForsythe/ERCnet)