This project aims to uncover the molecular mechanisms and ecological consequences of adaptation in multiple fish species and their associated parasites by integrating cutting-edge omics approaches. These include RNA-seq, ATAC-seq, whole-genome resequencing, metabarcoding, and genome complexity reduction techniques such as RAD-seq and ddRAD-seq. Additionally, our research emphasizes population genomics to investigate how anthropogenic and natural factorsshape population structure, influence genetic diversity, and impact key evolutionary processes that drive biodiversity. For our ongoing projects, we manage approximately 16 TB of genomic data across various datasets, including RAD-seq, WGS, and other high-throughput sequencing approaches. Among these, we currently store low-coverage whole-genome data from 376 Perca fluviatilis (~1 TB, 3x coverage) and WGS data from 222 P. fluviatilis (~2.6 TB, 10x coverage, raw data) from a long-term evolutionary heating experiment. These datasets require substantial computational resources for processing and analysis, and many of these analyses are still ongoing. Additional storage capacity remains crucial to fully utilize the available genomic data and continue our research. At the end of last year, we secured two new projects focusing on RAD-seq analyses in asp (Leuciscus aspius) and grayling (Thymallus thymallus) (~0.5 TB). Furthermore, by the end of this year, we anticipate a significant expansion of our data repository to accommodate genomic sequences from five new species as part of an upcoming landscape genomics project. Given the scale of our research and the increasing volume of high-throughput sequencing data, continued access to NAISS computing resources and storage is essential to ensure the success of our genomic and ecological studies.