Section of Genetic Medicine, University of Chicago, Chicago, IL, 60637, USA.
Nat Commun. 2024 Jun 19;15(1):5229. doi: 10.1038/s41467-024-49242-9.
Single-cell RNA sequencing (scRNA-seq) has been widely used to characterize cell types based on their average gene expression profiles. However, most studies do not consider cell type-specific variation across donors. Modelling this cell type-specific inter-individual variation could help elucidate cell type-specific biology and inform genes and cell types underlying complex traits. We therefore develop a new model to detect and quantify cell type-specific variation across individuals called CTMM (Cell Type-specific linear Mixed Model). We use extensive simulations to show that CTMM is powerful and unbiased in realistic settings. We also derive calibrated tests for cell type-specific interindividual variation, which is challenging given the modest sample sizes in scRNA-seq. We apply CTMM to scRNA-seq data from human induced pluripotent stem cells to characterize the transcriptomic variation across donors as cells differentiate into endoderm. We find that almost 100% of transcriptome-wide variability between donors is differentiation stage-specific. CTMM also identifies individual genes with statistically significant stage-specific variability across samples, including 85 genes that do not have significant stage-specific mean expression. Finally, we extend CTMM to partition interindividual covariance between stages, which recapitulates the overall differentiation trajectory. Overall, CTMM is a powerful tool to illuminate cell type-specific biology in scRNA-seq.
单细胞 RNA 测序 (scRNA-seq) 已被广泛用于根据细胞的平均基因表达谱来描述细胞类型。然而，大多数研究并未考虑供体之间的细胞类型特异性变化。对这种细胞类型特异性个体间变化进行建模可以帮助阐明细胞类型特异性生物学，并为复杂性状的基因和细胞类型提供信息。因此，我们开发了一种新的模型，称为 CTMM（细胞类型特异性线性混合模型），用于检测和量化个体之间的细胞类型特异性变化。我们使用广泛的模拟来证明 CTMM 在现实环境中是强大且无偏的。我们还推导出了针对细胞类型特异性个体间变化的校准测试，由于 scRNA-seq 中的样本量较小，因此这是具有挑战性的。我们将 CTMM 应用于人类诱导多能干细胞的 scRNA-seq 数据，以描述细胞分化为内胚层时供体之间的转录组变化。我们发现，供体之间几乎 100%的全转录组变异性是分化阶段特异性的。CTMM 还鉴定了具有统计学意义的样本间阶段特异性变异性的个体基因，包括 85 个没有显著阶段特异性平均表达的基因。最后，我们将 CTMM 扩展到阶段间个体间协方差的划分，这再现了整体分化轨迹。总体而言，CTMM 是阐明 scRNA-seq 中细胞类型特异性生物学的强大工具。
