Pereskia aculeata is a potential new crop species that has both food and medicinal (antinociceptive activity) properties. However, comprehensive genomic research on P. aculeata is still lacking, particularly concerning its organelle genome. In this study, P. aculeata was studied to sequence the mitochondrial genome (mitogenome) and to ascertain the assembly, informational content, and developmental expression of the mitogenome. The findings revealed that the mitogenome of P. aculeata is circular and measures 515,187 bp in length with a GC content of 44.05%. It contains 52 unique genes, including 33 protein-coding genes, 19 tRNA genes, and three rRNA genes. Additionally, the mitogenome analysis identified 165 SSRs, primarily consisting of tetra-nucleotides, and 421 pairs of dispersed repeats with lengths greater than or equal to 30, which were mainly forward repeats. Based on long reads and PCR experiments, we confirmed that two pairs of long-fragment repetitive elements were highly involved with the mitogenome recombination process. Furthermore, there were 38 homologous fragments detected between the mitogenome and chloroplast genome, and the longest fragment was 3962 bp. This is the first report on the mitogenome in the family Cactaceae. The decoding of the mitogenome of P. aculeata will provide important genetic materials for phylogenetic studies of Cactaceae and promote the utilization of species germplasm resources.

Prunus tomentosa (Thunb.) Wall has high nutritional value and medicinal effects. It is widespread in China; however, most plants growing in the wild are near extinction in many places. Predicting the potential distribution of P. tomentosa under climate change is helpful for cultivating and protecting wild germplasm resources. We used two general circulation models (CCSM4 and MIROC-ESM) and two future climate scenarios (RCP4.5 and RCP8.5) to predict P. tomentosa’s present and future geographical distribution. A total of 137 distribution data points and 19 bioclimatic variables were imported into the maximum entropy model (MaxEnt). The optimal parameter combination (feature class LQHPT, regularized multiplier 3.0) was selected with corrected Akaike Information Criterion as the index. The results showed that at present and in the future, P. tomentosa was distributed across the northern provinces, with Gansu, Shanxi, Shaanxi, and Henan being the most suitable regions. Compared with the current climatic conditions, the potential growing area of P. tomentosa will move north, and the growing area will increase, especially in Xinjiang, where the low-impact zone area decreases. Temperature and humidity were the main variables affecting the potential distribution of the plant, including the average temperature in the coldest season (Bio11) and precipitation in the warmest season (Bio18).