Genome-wide identification and characterization of aquaporins in mangrove plant Kandelia obovata and its role in response to the intertidal environment.
Zejun GuoDongna MaJing LiMingyue WeiLudan ZhangLichun ZhouXiaoxuan ZhouShanshan HeLin WangYingjia ShenQingshun Quinn LiHai-Lei ZhengPublished in: Plant, cell & environment (2022)
Aquaporins (AQPs) play important roles in plant growth, development and tolerance to environmental stresses. To understand the role of AQPs in the mangrove plant Kandelia obovata, which has the ability to acquire water from seawater, we identified 34 AQPs in the K. obovata genome and analysed their structural features. Phylogenetic analysis revealed that KoAQPs are homologous to AQPs of Populus and Arabidopsis, which are evolutionarily conserved. The key amino acid residues were used to assess water-transport ability. Analysis of cis-acting elements in the promoters indicated that KoAQPs may be stress- and hormone-responsive. Subcellular localization of KoAQPs in yeast showed most KoAQPs function in the membrane system. That transgenic yeast with increased cell volume showed that some KoAQPs have significant water-transport activity, and the substrate sensitivity assay indicates that some KoAQPs can transport H 2 O 2 . The transcriptome data were used to analyze the expression patterns of KoAQPs in different tissues and developing fruits of K. obovata. In addition, real-time quantitative PCR analyses combined transcriptome data showed that KoAQPs have complex responses to environmental factors, including salinity, flooding and cold. Collectively, the transport of water and solutes by KoAQPs contributed to the adaptation of K. obovata to the coastal intertidal environment.
Keyphrases
- genome wide
- plant growth
- single cell
- cell wall
- gene expression
- amino acid
- transcription factor
- rna seq
- dna methylation
- electronic health record
- big data
- high throughput
- stem cells
- climate change
- microbial community
- drug delivery
- copy number
- human health
- cell therapy
- risk assessment
- stress induced
- deep learning
- bone marrow
- cancer therapy
- long non coding rna
- solid phase extraction