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Characterization of the leaf rust responsive ARF genes in wheat (Triticum aestivum L.).

Saket ChandraLopamudra SatapathySrirupa BasuShailendra Kumar JhaManish KumarKunal Mukhopadhyay
Published in: Plant cell reports (2020)
Genome-wide identification, classification, functional characterization and expression analysis of Auxin Responsive Factor (ARF) gene family in wheat reveal their attributes and role during leaf rust infection. Auxins are important plant growth regulators that also impact plant-pathogen interaction. Auxin responsive factors (ARF) are plant specific transcription factors that control responses to auxins. Whole genome investigation of ARF gene family is limited in allohexaploid wheat (Triticum aestivum L.). Comprehensive study of this gene family was carried out by employing the currently available reference genome sequence of wheat. In total, 27 ARF genes were identified and located on the wheat genome as well as were positioned on wheat chromosome arms. Additionally, examination of the predicted genes unveiled a decent degree of relatedness within and among the phylogenetic clades. Leaf rust, caused by the obligate biotrophic fungal pathogen Puccinia triticina, is responsible for drastic loss of wheat crop worldwide reducing grain yield by 10-90%. Expression profiling of ARF genes in retort to leaf rust infection indicated their differential regulation during this plant-pathogen interaction. Highest expression of ARF genes were observed at 12 hpi that was maintained up to 72 hpi during incompatible interaction, whereas the high expression levels receded at 48 hpi during compatible interactions. Few of the identified ARF genes were likely to be post-transcriptionally regulated by microRNAs. Many light and stress responsive elements were detected in the promoter regions of ARF genes. Microsynteny analysis showed the conservation of ARF genes within the members of the Poaceae family. This study provides fundamental details for understanding the different types of ARF genes in wheat and there putative roles during leaf rust-wheat interaction.
Keyphrases
  • genome wide identification
  • transcription factor
  • genome wide
  • bioinformatics analysis
  • poor prognosis
  • dna methylation
  • genome wide analysis
  • machine learning
  • copy number
  • climate change
  • cancer therapy
  • dna binding