The Asian yellow pond turtle (Mauremys mutica) is widely traded in China, and its artificial breeding has now become a major industry. However, the insufficient offspring supply and reproductive decline of farmed turtles make the wild turtles more vulnerable. The present study was mainly designed to quantify the fecundity of M. mutica and attempt to screen for good reproductive performance in females. The genetic variability of the population and its genetic structure were also analysed. The parent–offspring relationships of all offspring in four consecutive years were confirmed using sixteen microsatellite loci. The genetic variability between the parents and offspring was low, and offspring of different years also showed little variability. We summarised the reproductive results of all females and counted the annual number of offspring and the variation in the number of offspring. The females were then divided into three types (stable, undulating and levelling off) according to the continuity. We selected seven females with good reproductive ability, which provided 16.94% of the annual contributions, while there were two females that had no offspring in four years. We also analysed the possible reasons for this difference and the importance of carrying out a family survey. This research can provide the basis and materials for the creation of a good reproductive group and the study of the reproductive biology of turtles in M. mutica aquaculture.

To investigate the genetic diversity and structure of farmed Chinese three-keeled pond turtles (Mauremys reevesii), we performed whole-genome resequencing on 238 individuals from eight farms across six Chinese regions. Genetic diversity indices (nucleotide diversity π, inbreeding coefficient F_HOM, polymorphism information content PIC, observed heterozygosity Ho), principal component analysis (PCA), phylogenetic reconstruction, and population structure analysis were integrated. The results revealed that the Guangdong Maoming (MM) and Anhui Wuwei (WW) populations exhibited the highest genetic diversity (MM: PIC = 0.149, Ho = 0.299; WW: PIC = 0.144, Ho = 0.287), while the Guangdong Huizhou (HZ) and Hunan Changhan (CH) populations showed the lowest diversity due to elevated inbreeding coefficients (HZ: F_HOM = 0.043; CH: F_HOM = 0.041). Low genetic differentiation (F_st = 0.00043–0.04758) indicated limited population divergence. However, PCA and phylogenetic analysis demonstrated that MM and Guangxi Pingxiang (PX) populations formed distinct genetic clusters, suggesting that management differences might contribute to their genetic uniqueness. Admixture analysis identified K = 2 (based on the lowest cross-validation error) as the optimal ancestral cluster number, with MM and PX populations displaying admixed genetic backgrounds while others showed homogeneous compositions. Conservation priorities should focus on preserving MM and PX’s unique genetic resources, introducing genetic material to high-inbreeding populations, and establishing interregional breeding networks. This study provides genomic insights for germplasm conservation and sustainable utilisation of M. reevesii.