Livestock species offer a unique opportunity to trace the evolutionary trajectory of genetic and epigenetic patterns over time. This unique advantage arises from the ability to gather substantial sample sizes across generations and investigate selection signatures in order to understand breed evolution and selection strategies. The contemporary selection models still fail to estimate full heritabilities as they solely focus on the genetic component. Therefore, a better understanding of epigenetics changes through time could help improve informativeness of selection models by accounting for epigenetic heritabilities in breeding decisions. Such development is crucial, especially in the current context of adaptation to climate change and evolution of breeding conditions to better address contemporary challenges encompassing animal resilience, health and welfare, reduced resource use and environmental impact. For this study, we had access to an extensive dataset spanning more than two decades pertaining from a selected sino-european pig breed. Our focus lies on the analysis of sperm samples from 15 continuous generations. Leveraging recent technological developments, such as Oxford Nanopore Technology (ONT) sequencing, we were able to obtain high quality sequencing information for both the genome and the epigenome. Therefore, for each generation, we sequenced a pool of sperm coming from 4 to 16 boars using the PromethION instrument from ONT. This provided whole genome sequences with about 30X coverage and full information on the methylation status for 30 million CpG sites for each pool. Using the R packages DSS and edgeR, we identified differentially methylated regions across generations and using the poisson log normal models, implemented in PLNmodels, we clustered CpGs having similar evolution with the objective to see variation along the genome and through time. As an illustrative example, we specifically focus on one region of interest on chromosome 7 that has been identified in the literature as harboring multiple quantitative trait loci in our breed of interest. We found differentially methylated regions, with CpGs clustering in groups having similar methylation ratio evolution across successive generations. With the data gathered in this project we aim to contribute to the development of a statistical model to identify epigenetic selection signatures. When highlighted, such regions will be linked to selection decisions that the Taizumu breed went through. In a broader sense, we aim to contribute in adjustments to selection models in order to include multi and transgenerational epigenetic changes to better account for the missing, non genetic, heritability in selection decisions. Acknowledgements H2020 grant agreement N°101000236 (GEroNIMO) and FEDER-FSE MIDI-PYRENEES ET GARONNE 2014-2020 (SeqOccIn).