Transmitochondrial pigs reveal causal effects of mitochondrial DNA on backfat thickness via nuclear epigenetic reprogramming.
Mitochondrial DNA (mtDNA) polymorphisms have been associated with production traits in farm animals, including backfat thickness in pigs, yet direct in vivo evidence establishing a causal link between specific mtDNA haplotypes and fat deposition remains limited. In this study, we generated transmitochondrial pigs (mitopigs) by combining the Dapulian nuclear genome with Wuzhishan mtDNA via somatic cell nuclear transfer, introducing 23 mtDNA mutations relative to controls. Mitopigs exhibited significantly increased backfat thickness at 5 months, a difference that persisted in their offspring, without significant differences in body weight, body size, or litter size. Fibroblasts derived from mitopigs exhibited reduced mtDNA copy numbers, decreased expression of mitochondrial biogenesis genes (PPARA, PPARGC1A, RRM2B, and LRPPRC), impaired mitochondrial respiration, elevated reactive oxygen species (ROS), and upregulated adipogenic transcription factors (CEBPA, CEBPB, and PPARG). Consistent with these fibroblast findings, backfat tissue of mitopigs showed corresponding upregulation of adipogenic transcription factors and downregulation of mitochondrial biogenesis genes. Integrated transcriptomic and whole-genome bisulfite sequencing (WGBS) analyses revealed nuclear transcriptional reprogramming that was closely associated with differential DNA methylation, predominantly affecting mitochondrial function and lipid metabolism pathways. Mitopig fibroblasts also showed a pro-inflammatory response to lipopolysaccharide stimulation, with elevated expression of IL-12, NOS2, RELA, and TNF-α. Our findings provide direct in vivo evidence that mtDNA variants regulate adiposity in pigs through mitochondrial dysfunction, oxidative stress, and nuclear epigenetic modulation, highlighting the potential for incorporating mtDNA haplotype information into pig breeding programs as a complementary strategy to nuclear genomic selection.