Maogeng Yang†, Shoukun Chen†, Zhangping Huang†, Shang Gao, Tingxi Yu, Tingting Du, Hao Zhang,Xiang Li5, Chun-Ming Liu*, Shihua Chen,*and Huihui Li,*

The Plant Journal, 2023, IF 7.091

DOI: 10.1111/tpj.16397

ABSTRACT:

Spartina alterniflorais a halophyte that can survive in high-salinity environments, and it is phylogeneticallyclose to important cereal crops, such as maize and rice. It is of scientific interest to understand whyS. alternifloracan live under such extremely stressful conditions. The molecular mechanism underlying its high-saline toleranceis still largely unknown. Here we investigated the possibility that high-affinity K+transporters (HKTs), which func-tion in salt tolerance and maintenance of ion homeostasis in plants, are responsible for salt tolerance inS. alterniflora.To overcome the imprecision and unstable of the gene screening method caused by the conven-tional sequence alignment, we used a deep learning method, DeepGOPlus, to automatically extract sequenceand protein characteristics from our newly assemble S. alterniflora genome to identify SaHKTs. Results showedthat a total of 16HKTgenes were identified. The number ofS. alterniflora HKTs (SaHKTs) is larger than that inall other investigated plant species except wheat. Phylogenetically related SaHKT members had similar genestructures, conserved protein domains andcis-elements. Expression profiling showed that most SaHKT genes are expressed in specific tissues and are differentially expressed under salt stress. Yeast complementationexpression analysis showed that type I members SaHKT1;2, SaHKT1;3 and SaHKT1;8 and type II members SaHKT2;1, SaHKT2;3 and SaHKT2;4 had low-affinity K+uptake ability and that type II members showed strongerK+affinity than rice andArabidopsis HKTs, as well as most SaHKTs showed preference for Na+transport. Webelieve the deep learning-based methods are powerful approaches to uncovering new functional genes, and theSaHKTgenes identified are important resources for breeding new varieties of salt-tolerant crops