Ancient trees are precious "living relics" in the biological world. They play a crucial role in ecosystems, providing rich habitats and living conditions for various organisms. Additionally, they contain abundant genetic information. Protecting ancient trees essentially means safeguarding biodiversity and associated genetic resources. Moreover, ancient trees serve as a foundation for studying historical changes in ancient environments and patterns of biological migration. However, the survival of ancient trees is currently faced with numerous threats, among which viral diseases are one of the more serious factors. These viruses can cause ancient trees to weaken, leaves to turn yellow, and even result in the death of entire plants, posing a significant threat to ecosystems and biodiversity.

In the Beijing area, ancient trees are not only abundant but also diverse, encompassing most common northern varieties of ancient trees. They carry the weighty historical and cultural memories of the region and are an indispensable part of both urban and rural landscapes. Viral infection is one of the main threats to the survival of ancient trees. Therefore, it is critical to conduct research on viral diseases affecting ancient trees in the Beijing area.

The detection of plant viruses based on high-throughput sequencing technology utilizes the RNA interference (RNAi) mechanism. After virus infection, the innate immune system cuts viral RNA into small interfering RNAs (siRNAs) of 21 or 22 nucleotides using DICER enzymes, which is then amplified by RNA-dependent RNA polymerase (RdRP). These siRNAs guide ARGONAUTE proteins to silence infected viral RNA via the RNAi mechanism, causing virus-derived siRNAs to automatically accumulate within the host and be detected through sRNA deep sequencing, thereby effectively identifying plant viruses. This study employs high-throughput sequencing technology to identify and classify viruses found in various ancient trees, analyzing sequencing data to understand their types, distribution, and abundance. Based on these results, we aim to construct a virus detection platform for ancient trees to support virus prevention and resistance breeding. Through this research, we can provide scientific evidence and technical support for the prevention and management of viral diseases in ancient trees, thus promoting the protection and sustainable utilization of ancient tree resources.