Obesity has been a problem in the last decades since the development of certain technologies has led to a faster pace of life, resulting in nutritional changes. Domestic pigs are an excellent animal model in recognition of adiposity-related processes, corresponding to the size of individual organs, the distribution of body fat in the organism, and similar metabolism. The present study applied next-generation sequencing to identify adipose tissue (AT) transcriptomic signals related to increased fat content by identifying differentially expressed genes (DEGs), including long non-coding RNAs in Złotnicka White pigs (n=16). Moreover, besides commonly used functional analysis, we applied the Freiburg RNA tool to predict DE lncRNA targets based on calculation hybridisation energy. And in addition, DE lncRNAs were recognized based on information available in databases. The obtained results show that close to 230 gene expressions were found to be dependent on fat content, including 8 lncRNAs. The most interesting was that among identified DE lncRNAs was transcript corresponding to human MALAT1, which was previously considered in the obesity-related context. Moreover, it was determined that in