Transposable elements (TEs) are mobile DNA repeats known to shape the evolution of eukaryotic genomes. In complex organisms, they exhibit tissue-specific transcription. However, understanding their role in cellular diversity across most tissues remains a challenge, when employing single-cell RNA sequencing (scRNA-seq), due to their widespread presence and genetic similarity. To address this, we present IRescue (Interspersed Repeats single-cell quantifier), a software capable of estimating the expression of TE subfamilies at the single-cell level. IRescue incorporates a unique UMI deduplication algorithm to rectify sequencing errors and employs an Expectation-Maximization procedure to effectively redistribute the counts of multi-mapping reads. Our study showcases the precision of IRescue through analysis of both simulated and real single cell and nuclei RNA-seq data from human colorectal cancer, brain, skin aging, and PBMCs during SARS-CoV-2 infection and recovery. By linking the expression patterns of TE signatures to specific conditions and biological contexts, we unveil insights into their potential roles in cellular heterogeneity and disease progression.

中文翻译：

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IRescue：单细胞水平转座因子表达的不确定性感知定量


转座因子 （TE） 是已知塑造真核基因组进化的移动 DNA 重复序列。在复杂生物体中，它们表现出组织特异性转录。然而，由于它们的广泛存在和遗传相似性，当采用单细胞 RNA 测序 （scRNA-seq） 时，了解它们在大多数组织中的细胞多样性中的作用仍然是一个挑战。为了解决这个问题，我们提出了 IRescue （Interspersed Repeats single-cell quantifier），这是一种能够在单细胞水平上估计 TE 亚家族表达的软件。IRescue 采用独特的 UMI 重复数据删除算法来纠正测序错误，并采用期望最大化程序来有效地重新分配多映射读取的计数。我们的研究通过分析来自 SARS-CoV-2 感染和恢复过程中人类结直肠癌、大脑、皮肤衰老和 PBMC 的模拟和真实单细胞和细胞核 RNA-seq 数据，展示了 IRescue 的精确性。通过将 TE 特征的表达模式与特定条件和生物学背景联系起来，我们揭示了它们在细胞异质性和疾病进展中的潜在作用。