Induced pluripotent stem cells (iPSCs) can be derived from differentiated cells, enabling the generation of personalized disease models by differentiating patient-derived iPSCs into disease-relevant cell lines. While genetic variability between different iPSC lines affects differentiation potential, how this variability in somatic cells affects pluripotent potential is less understood. We generated and compared transcriptomic data from 72 dermal fibroblast–iPSC pairs with consistent variation in reprogramming efficiency. By considering equal numbers of samples from self-reported African Americans and White Americans, we identified both ancestry-dependent and ancestry-independent transcripts associated with reprogramming efficiency, suggesting that transcriptomic heterogeneity can substantially affect reprogramming. Moreover, reprogramming efficiency–associated genes are involved in diverse dynamic biological processes, including cancer and wound healing, and are predictive of 5-year breast cancer survival in an independent cohort. Candidate genes may provide insight into mechanisms of ancestry-dependent regulation of cell fate transitions and motivate additional studies for improvement of reprogramming.

诱导多能干细胞 (iPSCs) 可以来自分化细胞，通过将患者来源的 iPSCs 分化为与疾病相关的细胞系，从而能够生成个性化的疾病模型。虽然不同 iPSC 系之间的遗传变异性会影响分化潜能，但体细胞中的这种变异性如何影响多能潜能却知之甚少。我们生成并比较了来自 72 个真皮成纤维细胞-iPSC 对的转录组数据，这些数据在重编程效率方面具有一致的变化。通过考虑来自自我报告的非洲裔美国人和白人美国人的相同数量的样本，我们确定了与重编程效率相关的祖先依赖和祖先独立的转录本，这表明转录组异质性可以显着影响重编程。而且，重编程效率相关基因参与多种动态生物过程，包括癌症和伤口愈合，并在独立队列中预测 5 年乳腺癌存活率。候选基因可以提供对细胞命运转变的祖先依赖性调节机制的深入了解，并激发更多研究以改善重编程。