Supporting Dataset for Evolution of Root Nodule Symbiosis via Paleopolyploidy and Modular Pathway Rewiring

Supporting Dataset for Evolution of Root Nodule Symbiosis via Paleopolyploidy and Modular Pathway Rewiring 1.GenomeQualityScripts for Genome Quality Assessment2.Phylogeny-based-genetic-dissection - 01-GeneFamilyBenchmark Benchmark of gene family grouping of PhyloGDS with stat-of-art tools using the Bilateria gene set - 02-Patched_genomes_of_SP204 Contains CDS/PEP/GFF3/FA of genomes patched with Medicago truncatula genes, their original source is available in citations.txt - 03-SpeciesTrees Contains RAxML tree, Astral tree, and Time tree of SP204 - 04-GetGeneFamilies Get gene families from OrthoFinder2, RBH, and MCScanX - 05-GeneTrees RAxML tree and DLC results for the 34033 Medicago truncatula genes - 06-GeneAge Estimating age of gene origins from DLC results3.Cross-species_RNA-Seq - 01-RNA-Seq_experiments_per_species Log2FC for the 19 species - 02-Map_log2FC_to_Reference Map Log2FC in each species to the reference genome of Medicago - 03-Ancestral_GRN-RNS Ancestral trait reconstruction of GRN-RNS - 04-Permutation_for_Pathway_Enrichment_analysis Permutation tests - 05-Gene_trees_with_Divergence_Time_and_Expression Gene trees with divergence time estimated and log2FC, in PDF format4.AI_prediction - 01-Get_shapley_scores Calculate Shapley scores in promoters of nodule-induced genes - 02-Network-plot Network plot of GRN-RNS in each phylogenetic age - 03-GRN-RNS-Targets-Ratio Ratio of newly gained genes binded by pre-existing TFs in each GRN-RNS - 04-Monte-Carlo Monte Carlo simulations5.Gene_loss - 01.GetConservedGenes Get genes conserved in over 70% core eudicots outgroups - 02.Permutations The null distribution of GRN-RNS gene numbers in different sample sizes - 03.CladeWide RNS-associated gene loss identified in 94 species of the nitrogen-fixing clade - 04.PairWise RNS-associated gene loss identified in nine closely related species pairsSupportingTables Supporting tables for the manuscriptutil Contained the core python module (iga) for the analysis, install first to reproduce the analysis