Functional reorganization of microbial decomposers drives dead biomass degradation differentiation during plantation development

Dataset OverviewThis dataset contains all necessary data and code to reproduce the Module Function Analysis presented in the article "Functional reorganization of microbial decomposers drives dead biomass degradation differentiation during plantation development". The research investigates how microbial decomposer communities and their carbohydrate-active enzyme (CAZyme) systems reorganize during plantation development, with implications for soil carbon cycling and ecosystem management.Research ContextAbstract from the original study:Afforestation enhances soil carbon storage through plant and microbial necromass accumulation, yet the roles of carbohydrate-active enzymes (CAZymes) and the microorganisms that encode them (biomass-decomposers) during plantation development remain poorly understood. Here, we integrated shotgun metagenomics with network analysis to decipher the successional dynamics of CAZyme-encoding genes, biomass-decomposers, and their functional linkages across a chronosequence of plantation development in northeastern China. Plantation development increased the abundance of CAZymes involved in lignin, chitin, and glucan degradation. Network analysis of biomass-decomposers revealed that the dominant function of key module M1 gradually shifted from peptidoglycan to lignin degradation through network reorganization during development. Across all developmental stages, the key modules whose dominant functions were peptidoglycan and hemicellulose degradation consistently harbored keystone species. In the overlap-network, these two functions served as dominant functions in more than one key module, confirming their essential role in maintaining fundamental community functions. Stochastic processes predominantly governed the assembly of biomass-decomposers, with increasing influence during development. Soil organic carbon was the primary driver of both biomass-degrading CAZymes and decomposers, with CAZymes further structured by pH and nitrate nitrogen, whereas biomass-decomposers responded to moisture and total nitrogen. Overall, these findings provide new insights into belowground C cycling during plantation development, potentially guiding improved ecosystem management practices for forest restoration.Dataset Contents1. Core Analysis Script (microbial_module_analysis.R)Complete R pipeline for module-function analysisProcesses gene contribution data to calculate functional weights within microbial modulesPerforms integration of metagenomic data with network analysis resultsGenerates module-function association metrics used in the study2. Required Data Files Essential Input Files:Group.csv - Sample metadata with group assignmentsGroup_nodes_list.csv - Module assignments for microbial taxagene_annotation.csv - Functional annotations for CAZyme genesGroup_gene_contribution_matrix.csv - Species-gene presence matrixGene Contribution Data:Directory containing multiple .tsv files (one per CAZyme gene)Each file contains per-sample contribution values for microbial taxaFiles named by gene identifier (e.g., AA1.tsv, AA2.tsv)Other Data:Biomass.csv: The relative abundance (TPM) of CAZyme genes involved in this studyMicrobes.csv: The relative abundance of biomass-decomposers involved in this study