Identification of Growth-Related Key Genes Based on Nonlinear Fitting of Weight Growth Curves in Min Pigs

The Min pig, a Chinese indigenous breed, is valued for its excellent meat quality and stress tolerance. Nevertheless, its growth rate falls considerably short of commercial pig breeds, a pattern typical of most unselected indigenous populations, and marked individual variation further undermines its economic viability. To explore the genetic basis of this variation, we evaluated a series of nonlinear fixed-effects and mixed-effects models based on the Gompertz, Logistic, and von Bertalanffy functions using body weight records from 92 Min pigs. Model selection was based on AIC, BIC, and leave-one-out cross-validation. The best-fitting model was a Logistic nonlinear mixed-effects model with individual-level random effects on all three growth parameters (Asymptotic weight, timing parameter, and be parameter), which clearly outperformed models with simpler random-effect structures and fixed-effects models. From this model, we identified three characteristic growth transition points: the early transition point (Growth Rate Index, GRI) at 94.83 days (22.32 kg), the single inflection point (Maximum Growth Rate, MGR) at 166.06 days (52.80 kg), and the late transition point (Late Growth Rate Index, LGRI) at 237.29 days (83.29 kg), with a maximum absolute growth rate of 488.2 g/day. These points partitioned growth into initial acceleration, rapid growth, deceleration, and Asymptotic growth phases. Using individual fitted growth curves, we selected five fast-growing and five slow-growing pigs that reached approximately 90 kg during the plateau phase, defined as a predicted body weight of at least 95% of the individual Asymptotic weight. The fast-growing group reached 90 kg at 240.5 ± 20.42 days, whereas the slow-growing group reached the same weight at 286.67 ± 19.20 days. At the 90 kg slaughter weight, we collected longissimus dorsi muscle samples from these pigs during the plateau phase and performed RNA-seq. Transcriptome analysis revealed 864 differentially expressed genes between the two groups, with 540 upregulated and 324 downregulated in the fast-growing group. Pathway enrichment implicated the PI3K-Akt and TGF-β signaling pathways in muscle development, and differential expression of IGFN1, DCN, COL3A1, MYOC, COL1A2, COL1A1, and IGF2 may explain the growth variation between the groups. In summary, the Logistic mixed-effects model with individual-level random effects on all growth parameters effectively captures the growth pattern of Min pigs, and the PI3K-Akt and TGF-β pathways likely mediate growth differences in this breed.