Mining salt stress-related genes in Spartina alterniflora via analyzing co-evolution signal across 365 plant species using phylogenetic profiling

With the increasing number of sequenced species, phylogenetic profiling (PP) has become a powerful method to predict functional genes based on co-evolutionary information. However, its potential in plant genomics has not yet been fully explored. In this context, we combined the power of machine learning and PP to identify salt stress-related genes in a halophytic grass, Spartina alterniflora, using evolutionary information generated from 365 plant species. Our results showed that the genes highly co-evolved with known salt stress-related genes are enriched in biological processes of ion transport, detoxification and metabolic pathways. For ion transport, five identified genes coding two sodium and three potassium transporters were validated to be able to uptake Na+. In addition, we identified two orthologs of trichome-related AtR3-MYB genes, SaCPC1 and SaCPC2, which may be involved in salinity responses. Genes co-evolved with SaCPCs were enriched in functions related to the circadian rhythm and abiotic stress responses. Overall, this work demonstrates the feasibility of mining salt stress-related genes using evolutionary information, highlighting the potential of PP as a valuable tool for plant functional genomics.

Automated summary

By combining machine learning and phylogenetic profiling, this study identified salt stress-related genes in a halophytic grass using evolutionary information from 365 plant species. The co-evolved genes were found to be enriched in ion transport, detoxification, and metabolic pathways. The findings demonstrate the feasibility and potential of phylogenetic profiling as a valuable tool for plant functional genomics.