Big Data for grasses and herbs
An IPB bioinformatics team together with iDiv partners from Halle, Jena and Wageningen has compiled a comprehensive metabolomics dataset for biodiversity research. The data set contains the metabolite profiles of 13 grassland species grown in plant communities of different diversity levels. The plant material was collected at different time points in the 2017 growing season and subsequently processed continuously. Using UPLC-ESI-Qq-TOF-MS, the scientists generated metabolic profiles of the aerial plant parts and also recorded the visible traits of the investigated species, such as the height of the plants and the number of leaves. Then, they performed raw data pre-processing and prepared the data for statistical analysis in R by applying missing data imputation, batch correction, and validity checks on the visible traits. The comprehensive dataset provides the opportunity to study the metabolic fingerprint of different species in natural plant communities to gain insights into plant adaptation to changing environmental conditions.
The data collection took place as part of the Jena Experiment, which has been running since 2002 as one of the longest biodiversity study in Europe. This DFG-funded project aims to use novel analytical methods to investigate the ecological and evolutionary mechanisms of biodiversity and their role in ecosystem viability.