Thaumatin-like proteins (TLPs), a family of proteins with high sequence similarity to thaumatin, are shown to be involved in plant defense, and are thus classified into the pathogenesis related protein family 5. Ammopiptanthus nanus is a rare evergreen broad-leaved shrub distributed in the temperate zone of Central Asia, which has a high tolerance to low-temperature stress. To characterize A. nanus TLPs and understand their roles in low-temperature response in A. nanus , a comprehensive analysis of the structure, evolution, and expression of TLP family proteins was performed. A total of 31 TLP genes were detected in the A. nanus genome, and they were divided into four groups based on their phylogenetic positions. The majority of the AnTLPs contained the conserved cysteine residues and were predicted to have the typical three-dimensional structure of plant TLPs. The primary modes of gene duplication of the AnTLP family genes were segmental duplication. The promoter regions of most AnTLP genes contain multiple cis-acting elements related to environmental stress response. Gene expression analysis based on transcriptome data and fluorescence quantitative PCR analysis revealed that several AnTLP genes were involved in cold-stress response. We further showed that a cold-induced AnTLP gene, AnTLP13 , was localized in apoplast, and heterologous expression of the AnTLP13 in Escherichia coli and yeast cells and tobacco leaves enhanced low-temperature stress tolerance when compared with the control cells or seedlings. Our study provided important data for understanding the roles of TLPs in plant response to abiotic stress.
Keyphrases
- genome wide
- genome wide identification
- dna methylation
- copy number
- transcription factor
- escherichia coli
- induced apoptosis
- poor prognosis
- gene expression
- stress induced
- cell cycle arrest
- electronic health record
- genome wide analysis
- high resolution
- big data
- cell proliferation
- oxidative stress
- staphylococcus aureus
- klebsiella pneumoniae
- diabetic rats
- rna seq
- single molecule
- deep learning
- binding protein
- neural network
- pi k akt
- living cells
- artificial intelligence