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<p>The research aims to find microRNAs (miRNAs) that link with micronutrient deficiency levels of iron (Fe), copper (Cu) and zinc (Zn) in the foxtail millet (<i>Setaria italica</i>). The study utilized the complete and mature miRNA sequences from miRBase database before performing BLASTn sequence comparisons against genomic resources available in NCBI and Ensembl Plants. Secondary structures from the identified sequences were predicted by the mfold tool after the “Coding Potential Calculator (CPC)” evaluated their coding potential. The “psRNATarget” prediction tool determined the target genes for identified miRNAs, after that protein–protein interaction (PPI) revealed their functional composition. The present study revealed sit-miR171, sit-miR169, and sit-miR166 as significant miRNAs that appear to manage plant reactions to deficiencies of Fe and Zn. Further, phylogenetics study found that the precursor sequences of sit-miR171, sit-miR169, and sit-miR166 clustered distinctly with their respective orthologues in <i>Setaria italica</i>, showing strong bootstrap support (100%). The study provides insights into plant micronutrient stress regulatory networks, laying a foundation for future crop improvement efforts and highlighting the need for experimental validation.</p>

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Computational identification of micro-nutrient (iron and zinc) deficiency related miRNAs and their targets in foxtail millet (Setaria italica)

  • 期刊论文

  • 发表日期：

    2025年11月26日

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  • K. Siddaardha Duggirala,
  • Surbhi Panwar,
  • Adarsh Kumar Shukla,
  • Raushan Kumar Jha,
  • Prasun Choudhary,
  • Ashwani Kumar

摘要

The research aims to find microRNAs (miRNAs) that link with micronutrient deficiency levels of iron (Fe), copper (Cu) and zinc (Zn) in the foxtail millet (Setaria italica). The study utilized the complete and mature miRNA sequences from miRBase database before performing BLASTn sequence comparisons against genomic resources available in NCBI and Ensembl Plants. Secondary structures from the identified sequences were predicted by the mfold tool after the “Coding Potential Calculator (CPC)” evaluated their coding potential. The “psRNATarget” prediction tool determined the target genes for identified miRNAs, after that protein–protein interaction (PPI) revealed their functional composition. The present study revealed sit-miR171, sit-miR169, and sit-miR166 as significant miRNAs that appear to manage plant reactions to deficiencies of Fe and Zn. Further, phylogenetics study found that the precursor sequences of sit-miR171, sit-miR169, and sit-miR166 clustered distinctly with their respective orthologues in Setaria italica, showing strong bootstrap support (100%). The study provides insights into plant micronutrient stress regulatory networks, laying a foundation for future crop improvement efforts and highlighting the need for experimental validation.