ReviewaBIOTECH2026
Detection technologies for RNA modifications and their applications in plants.
Review in aBIOTECH, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Chemical modifications of RNA molecules play diverse regulatory roles in gene expression by influencing RNA biogenesis, stability, and translation. Emerging evidence indicates that RNA modifications in plants have functional significance for enhancing crop performance, stress resistance, and agricultural productivity. Recent advances in quantitative mapping of RNA modifications at the single-base level have highlighted the critical roles of RNA modifications in regulating RNA metabolism and translation in mammals. However, our understanding of the regulatory roles of these chemical modifications at the single-base level remains limited in plants, hindering deeper insights into their biological significance. This gap can be attributed to the limited use of advanced base-resolution detection technologies in plant research. Here, we systematically review both conventional and base-resolution methods that have been used to detect RNA modifications in mammals and plants. We highlight the implications of RNA modifications at the single-base level, and discuss how modification levels could be manipulated during crop improvement and breeding to regulate RNA metabolism and translation without altering amino acid sequences.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.