@article{oai:nagoya.repo.nii.ac.jp:00023011, author = {Ogawa, Tomohiko and Mori, Akiko and Igari, Kadunari and Morita, Terao Miyo and Tasaka, Masao and Uchida, Naoyuki}, issue = {6}, journal = {Plant and Cell Physiology}, month = {Mar}, note = {Plants possess disease resistance (R) proteins encoded by R genes, and each R protein recognizes a specific pathogen factor(s) for immunity. Interestingly, a remarkably high degree of polymorphisms in R genes, which are traces of past mutation events during evolution, suggest the rapid diversification of R genes. However, little is known about molecular aspects that facilitate the rapid change of R genes because of the lack of tools that enable us to monitor de novo R gene mutations efficiently in an experimentally feasible time scale, especially in living plants. Here we introduce a model assay system that enables efficient in planta detection of de novo mutation events in the Arabidopsis thaliana R gene UNI in one generation. The uni-1D mutant harbors a gain-of-function allele of the UNI gene. uni-1D heterozygous individuals originally exhibit dwarfism with abnormally short stems. However, interestingly, morphologically normal stems sometimes emerge spontaneously from the uni-1D plants, and the morphologically reverted tissues carry additional de novo mutations in the UNI gene. Strikingly, under an extreme condition, almost half of the examined population shows the reversion phenomenon. By taking advantage of this phenomenon, we demonstrate that the reversion frequency is remarkably sensitive to a variety of fluctuations in DNA stability, underlying a mutable tendency of the UNI gene. We also reveal that activities of the salicylic acid pathway and DNA damage sensor pathway are involved in the reversion phenomenon. Thus, we provide an experimentally feasible model tool to explore factors and conditions that significantly affect the R gene mutation phenomenon.}, pages = {1123--1132}, title = {Efficient In Planta Detection and Dissection of De Novo Mutation Events in the Arabidopsis thaliana Disease Resistance Gene UNI}, volume = {57}, year = {2016} }