Super-resolution ribosome profiling reveals unannotated translation events in Arabidopsis
Thursday, 2016/11/10 | 07:58:52
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Polly Yingshan Hsu, Lorenzo Calviello, Hsin-Yen Larry Wu, Fay-Wei Li, Carl J. Rothfels, Uwe Ohler, and Philip N. Benfey SignificanceTranslation is the process by which ribosomes decode information in RNA to produce proteins. The resulting proteins constitute cellular structures and regulate diverse functions in all organisms. Translation also affects mRNA stability. As the final step of the central dogma, translation can alter protein production more rapidly than transcription in a changing environment. However, a robust experimental method to define the landscape of the translatome has not been established in many organisms. We developed an advanced experimental approach and used it to discover proteins missed in the annotation of the Arabidopsis genome. This study confirmed computationally predicted noncanonical translation events and uncovered unannotated small proteins that likely have important functions in plants. AbstractDeep 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.
See: http://www.pnas.org/content/113/45/E7126.abstract.html?etoc PNAS November 8 2016; vol.113; no.45: E7126–E7135
Fig. 2. Comparison between the current study and published Arabidopsis ribosome-profiling datasets. (A) Length distribution of ribosome footprints in the current study (Hsu_root and Hsu_shoot), compared with three other published datasets in Arabidopsis (25⇓–27). See SI Materials and Methods for details of the growth conditions for each dataset. Size of footprints isolated in each dataset is compared in Table S1. (B) Percentage of Ribo-seq reads in the max reading frame. Data were extracted from the meta-gene analysis using 28-nt footprints in which most of the datasets display the best 3-nt periodicity. The gray line marks 33%, which is the percentage of reads expected if there is no enrichment in any frame. (C) Number of protein-coding genes with translated ORFs identified by RiboTaper with different sequencing depths. (D) Percentage of protein-coding genes with translated ORFs identified among the expressed protein-coding genes defined by different RNA expression cutoffs. A subset of each dataset (25 million reads) was compared across the studies. |
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