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Genome-Wide Identification and Characterization of the Shaker-Type K + Channel Genes in Prunus persica (L.) Batsch.

Yong YangJinlong HanYue ZhangShizhuo LinMeixia LiangLi-Zi ZhaoZhizhong Song
Published in: International journal of genomics (2022)
Shaker-type K + channels are critical for plant K + acquisition and translocation that play key roles during plant growth and development. However, molecular mechanisms towards K + channels are extremely rare in fruit trees, especially in peach. In this study, we identified 7 putative shaker-type K + channel genes from peach, which were unevenly distributed on 5 chromosomes. The peach shaker K + channel proteins were classified into 5 subfamilies, I-V, and were tightly clustered with pear homologs in the phylogenetic tree. Various cis -acting regulatory elements were detected in the promoter region of the shaker-type K + channel genes, including phytohormone-responsive, abiotic stress-responsive, and development regulatory elements. The peach shaker K + channel genes were expressed differentially in distinct tissues, and PpSPIK was specifically expressed in the full-bloom flowers; PpKAT1 and PpGORK were predominantly expressed in the leaves, while PpAKT1 , PpKC1 , and PpSKOR were majorly expressed in the roots. The peach shaker K + channel genes were differentially regulated by abiotic stresses in that K + deficiency, and ABA treatment mainly increased the shaker K + channel gene expression throughout the whole seedling, whereas NaCl and PEG treatment reduced the shaker K + channel gene expression, especially in the roots. Moreover, electrophysiological analysis demonstrated that PpSKOR is a typical voltage-dependent outwardly rectifying K + channel in peach. This study lays a molecular basis for further functional studies of the shaker-type K + channel genes in peach and provides a theoretical foundation for K + nutrition and balance research in fruit trees.
Keyphrases
  • genome wide
  • gene expression
  • dna methylation
  • genome wide identification
  • transcription factor
  • genome wide analysis
  • cancer therapy
  • copy number
  • replacement therapy
  • stress induced
  • neural network