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How do we know that plants listen: Advancements and limitations of transcriptomic profiling for the identification of sound-specific biomarkers in tomato.

Seon-Kyu KimMi-Jeong JeongChoong-Min Ryu
Published in: Plant signaling & behavior (2018)
Sound vibration has been recently identified as an important physical trigger to elicit plant responses. Naturally occurring sound waves modulate diverse aspects of plant physiology, such as root growth, stress responses, and seed germination. However, it has been debated whether plants perceive artificially generated sound vibration and exhibit similar phenotypic changes to those exhibited after perception of natural sound waves. Recently, analysis of RNA-Seq and microRNA-Seq using tomato fruits treated with optimized sound waves to attenuate fruit ripening revealed sound-specific microRNAs, which could be used as sound-specific biomarkers in tomato. These data provide solid molecular evidence of sound perception in plants. Despite these results, there are obvious limitations of biomarkers' specificity and selectivity that need be addressed to facilitate the application of sound treatment in agriculture. Here, the pros and cons of sequencing technologies used to identify sound-associated molecules suggest recommendations for the effective identification of biomarkers responsive to sound treatment in plants.
Keyphrases
  • single cell
  • rna seq
  • climate change
  • machine learning
  • high frequency
  • gene expression
  • drug delivery
  • cancer therapy
  • clinical practice
  • big data
  • artificial intelligence
  • cell wall
  • data analysis