Modeling mutation accumulation and expansion in long-lived trees with complex branching structure

Somatic mutations accumulated in trees have now become quantitatively detectable with recent progresses in next-generation sequencing (NGS) technology. This is the first step to understand the impacts of somatic mutations on longevity of trees. However, NGS can only detect mutations that are shared by majority of stem cells. Minor somatic mutations may be hidden in many branches in the same individual. Because the processes of mutation accumulation and expansion remain poorly understood, we constructed a mathematical model at the stem cell population level to simulate these processes in silico. In our model, the growth of tree is described as a combination of elongation and branching processes. At these processes, stem cells in each meristem can be selected randomly or cell lineage persists for each stem cell without random selection. Depending on the randomness in stem cell selections, we developed three different models and compared the number and pattern of accumulated mutations among models in a branching structure measured in a Popular tree. We found that randomness in the selection process contributes to a decreased accumulation of somatic mutations. Comparison of our predictions with the data highlighted the possibility that more somatic mutations are accumulated in long-lived trees than previously expected.