Jiarun Gong

Forest germplasm resources are indispensable resources for ecosystem stability and economic value. However, they are increasingly threatened by environmental changes and human activities and urgently need advanced management methods. Concurrently, traditional management methods are unable to cope with the increasingly complex data in the era of advanced information technology. Therefore, we developed DEFGermplasm (https://defgermplasm.com), a digital platform utilizing Flask framework, Python, MySQL, NGINX, Gunicorn, HTML5, JavaScript, JBrowse, SequenceServer, Seaborn, and Echarts, taking the germplasm resources of pecan, hickory, Chinese fir, and phoebe. The platform integrates genomic, transcriptomic, phenotypic, and physiological data, utilizing user-friendly visualization tools to achieve intuitive data presentation. Gene expression heat maps reveal tissue-specific patterns, interactive phenotypic trait visualizations supporting breeding and trait selection, and cross-species analyses uncovering gene conservation and functional adaptation. For example, the WRINKLED1 transcription factor showed roles across nut-bearing and timber species. Additionally, the platform's sequence alignment and homology search tool facilitate comprehensive exploration of gene families, while genome visualization tools provide detailed insights into genomic structures and regulatory elements. By integrating diverse datasets with intuitive visualization tools, DEFGermplasm enhances forest germplasm research, supporting breeding and conservation initiatives. This study underscores the transformative potential of digital platforms in forest genetics and sustainable resource management.