Data from: Super-resolution ribosome profiling reveals unannotated translation events in Arabidopsis

Deep sequencing of ribosome footprints (ribosome profiling) maps and quantifies mRNA translation. Because ribosomes decode mRNA every 3 nt, the periodic property of ribosome footprints could be used to identify novel translated ORFs. However, due to the limited resolution of existing methods, the 3-nt periodicity is observed mostly in a global analysis, but not in individual transcripts. Here, we report a protocol applied to Arabidopsis that maps over 90% of the footprints to the main reading frame and thus offers super-resolution profiles for individual transcripts to precisely define translated regions. The resulting data not only support many annotated and predicted noncanonical translation events but also uncover small ORFs in annotated noncoding RNAs and pseudogenes. A substantial number of these unannotated ORFs are evolutionarily conserved, and some produce stable proteins. Thus, our study provides a valuable resource for plant genomics and an efficient optimization strategy for ribosome profiling in other organisms.

核糖体足迹深度测序（ribosome profiling）可对信使RNA（messenger RNA，mRNA）的翻译过程进行定位与定量分析。由于核糖体每3个核苷酸（nucleotide，nt）解码一次mRNA，核糖体足迹的周期性特征可用于识别新型翻译型开放阅读框（open reading frame，ORF）。然而，受现有方法分辨率所限，3nt周期性特征大多仅能在全局分析中被观测到，而无法在单个转录本中实现检测。本研究针对拟南芥开发了一套实验流程，可将90%以上的核糖体足迹定位至主要阅读框，进而为单个转录本提供超高分辨率的图谱，以精准界定其翻译区域。所得数据不仅佐证了大量已注释及预测的非经典翻译事件，还在已注释的非编码RNA（noncoding RNA，ncRNA）与假基因中发现了小型开放阅读框。其中大量未注释的ORF具有进化保守性，部分还可编码稳定的蛋白质。因此，本研究为植物基因组学提供了宝贵的研究资源，同时也为其他物种的核糖体谱分析提供了高效的优化策略。