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Soybean CALCIUM-DEPENDENT PROTEIN KINASE17 Positively Regulates Plant Resistance to Common Cutworm ( Spodoptera litura Fabricius).

Huiqi WangXiao LiFenglin SuHailun LiuDezhou HuFang HuangDeyue YuHui Wang
Published in: International journal of molecular sciences (2022)
Soybean is frequently attacked by herbivorous pests throughout the growth period. Exploring anti-insect genes to improve insect resistance in soybean is an important soybean breeding goal. Here, we cloned and characterized the gene for a quantitative trait locus (QTL) related to insect resistance, Glyma.06g189600 , which encodes CALCIUM-DEPENDENT PROTEIN KINASE17 ( GmCDPK17 ) in soybean. The pairwise sequence alignment analysis revealed that the presumed protein of GmCDPK17 shares 52.06% similarity with that of GmCDPK38 , a known negative regulatory gene of insect resistance in soybean. Ectopic expression of GmCDPK17 and GmCDPK38 restored the phenotypes of the Arabidopsis insect-susceptible mutant cpk10 and insect-resistant mutant cpk28 , respectively. Moreover, transgenic hairy roots of the soybean cultivar Jack were generated by Agrobacterium -mediated transformation. Overexpression of GmCDPK17 increased soybean hairy root resistance to common cutworm (CCW), while RNA interference of the gene decreased soybean hairy root resistance to CCW. Sequencing data from the cultivated and wild soybeans were used to analyze the genetic diversity of GmCDPK17 . This gene was subjected to domestication selection. Six and seven haplotypes (Haps) were identified in cultivated and wild soybeans, respectively. The resistance Hap1 is not widely used in cultivated soybeans and is mainly distributed at low latitudes. Accessions with resistance haplotypes of the GmCDPK17 and GmCDPK38 genes showed high resistance to CCW. Altogether, we revealed a novel positive regulatory insect resistance gene, GmCDPK17 , which may further improve insect resistance in soybean.
Keyphrases
  • genome wide
  • transcription factor
  • protein kinase
  • genetic diversity
  • copy number
  • aedes aegypti
  • poor prognosis
  • zika virus
  • big data
  • electronic health record
  • mass spectrometry
  • drug induced
  • data analysis