Adaptive evolution and structure modeling of rbcL gene in Ephedra

Predicting the comprehensive geospatial pattern of two ephedrine-type alkaloids for Ephedra sinica in Inner Mongolia

Ephedra sinica Stapf. is a shrubby plant widely used in traditional Chinese medicine due to its high level of medicinal value, thus, it is in high demand. Ephedrine (E) and pseudoephedrine (PE) are key medicinal components and quality indicators for E. sinica. These two ephedrine-type alkaloids are basic elements that exert the medicinal effect of E. sinica. Recently, indiscriminate destruction and grassland desertification have caused the quantity and quality of these pharmacological plants to degenerate. Predicting potentially suitable habitat for high-quality E. sinica is essential for its future conservation and domestication. In this study, MaxEnt software was utilized to map suitable habitats for E. sinica in Inner Mongolia based on occurrence data and a set of variables related to climate, soil, topography and human impact. The model parametrization was optimized by evaluating alternative combinations of feature classes and values of the regularization multiplier. Second, a geospatial quality model was fitted to relate E and PE contents to the same environmental variables and to predict their spatial patterns across the study area. Outputs from the two models were finally coupled to map areas predicted to have both suitable conditions for E. sinica and high alkaloid content. Our results indicate that E. sinica with high-quality E content was mainly distributed in the Horqin, Ulan Butong and Wulanchabu grasslands. E. sinica with high-quality PE content was primarily found in the Ordos, Wulanchabu and Ulan Butong grasslands. This study provides scientific information for the protection and sustainable utilization of E. sinica. It can also help to control and prevent desertification in Inner Mongolia.

Analysis of Adaptive Evolution and Coevolution of rbcL Gene in the Genus Galdieria (Rhodophyta)

To research the adaptive evolution and coevolution of the rbcL gene in the genus Galdieria, 36 sequences were selected. The bioinformatics of proteins encoded by rbcL genes of Galdieria were analyzed, and phylogenetic trees were constructed by the maximum-likelihood method. Then, adaptive evolution and coevolution were analyzed. The phylogenetic tree showed that the inner groups were clustered into four branches, in which the sequences of Galdieria maxima were divided into two small branches, and the posterior probability of each branch is above 94.9%. Eleven reliable positive selection sites were detected in the branched-site model, indicating that the rbcL protein-coding gene of Galdieria underwent adaptive evolution to adapt to extreme environments. Site 269 F is located in the loop 6 domain, while sites 272 D and 273 W are located in the 6-helix structure. Many coevolution pairs were detected, which were closely related to the hydrophobic and molecular weight correlation values of amino acids. The results are helpful to research the evolution process of freshwater red algae, to explore the changes of its essential genes and protein functions to adapt to different environmental pressures, and to understand the close relationship between amino acids in proteins and the molecular mechanism of evolution.