Project description:Land cover change has long been recognized that marked effect the amount of soil organic carbon. However, little is known about microbial-mediated effect processes and mechanism on soil organic carbon. In this study, the soil samples in a degenerated succession from alpine meadow to alpine steppe meadow in Qinghai-Tibetan Plateau degenerated, were analyzed by using GeoChip functional gene arrays.
Project description:Using WGBS we investigated blood DNA methylation profiles of Cooinda the Alpine dingo and determined putative regulatory elements (unmethylated regions, UMRs, and lowly methylated regions, LMRs).
Project description:Anthropogenic disturbances are a primary cause of soil organic carbon (SOC) destabilization in alpine ecosystems. However, effective management is hindered by a """"response delay"""" of macro metrics used to characterize stable carbon pools (e.g., microbial necromass carbon and aggregate associated organic carbon), which respond slowly and therefore do not reflect the immediate impairment of the soil carbon sequestration. To address this, we conducted a multi-omics study on 200 soil samples along a 621-km transect. We observed a """"temporal lag"""": while physical disturbance caused rapid depletion of nucleotide metabolites, stable carbon fractions showed limited responsiveness, masking carbon depletion onset. Through metabolomics and 100-fold stratified subsampling, we identified depletion of specific nucleotides—notably thymidine and guanosine—as early-warning signatures (mean AUROC > 0.90). Metagenomic profiling revealed this depletion is driven by a disturbance-induced taxonomic shift triggering a synchronized suppression: the simultaneous inhibition of genetic capacity for de novo synthesis (mediated by pyrD) and salvage pathways (mediated by deoA). Furthermore, the concurrent lower abundance of korA indicates the disruption of the """"Glutamine Bridge,"""" effectively severing the metabolic link between nucleotide turnover and central carbon/energy metabolism. Our findings identify molecular """"early-warning biomarkers"""" that precede observable carbon loss, providing a sensitive tool for monitoring incipient soil degradation.