In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics was unfolded with the introduction of dozens of novel instruments that incorporate additional data dimensions through innovative acquisition methodologies, in turn inspiring specialized data analysis pipelines. Simultaneously, a growing number of proteomics datasets have been made publicly available through data repositories such as ProteomeXchange, Zenodo and Skyline Panorama. However, developing algorithms to mine this data and assessing the performance on different platforms is currently hampered by the lack of a single benchmark experimental design. Therefore, we acquired a hybrid proteome mixture on different instrument platforms and in all currently available families of data acquisition. Here, we present a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset acquired using several of the most commonly used current day instrumental platforms. The dataset consists of over 700 LC-MS runs, including adequate replicates allowing robust statistics and covering over nearly 10 different data formats, including scanning quadrupole and ion mobility enabled acquisitions. Datasets are available via ProteomeXchange (PXD028735).

Adaptive trait divergence between populations is regulated by genetic and non-genetic processes. Compared to genetic change, epigenetic change is unstable and short-lived, questioning its contribution to long-term adaptive potential. However, epigenetic change can accumulate over time, and may result in beneficial epigenetic memories where environments are heterogeneous. Diverging epigenetic memories have been observed across large spatial scales, and can persist through multiple generations even in the absence of the causative environmental stressor. It is unknown, however, how and to what extent epigenetic memories contribute to fine-scale population structure and evolution. Here, we performed whole genome bisulfite sequencing on 30 Fragaria vesca F1 plants originating from distinct ecological settings and grown in a controlled environment. Specifically, we compared methylation patterns between a steep, altitudinal gradient (<2 km) and a wide spatial gradient (>500 km). If epigenetic variation is random, arising from errors during replication and without evolutionary implications, one would expect similar amounts of epigenetic variation across populations and no spatial scale-effect. Here, we find that epigenetic memories arise even at fine spatial scale, and that both parallel and non-parallel biological processes underpin epigenetic divergence at distinct spatial scales. For example, demethylation of transposable elements consistently occurred at the large but not the small spatial scale, while methylation differentiation for most biological processes were shared between spatial scales. Acute drought stress did not result in significant epigenetic differentiation, indicating that repeated historical stress levels associated with heterogeneous environmental conditions are required for acquiring a stable epigenetic memory and for coping with future environmental change.