Single-cell transcriptomics (scRNAseq) holds the promise to generate definitive atlases of cell types. We review scRNAseq studies of conventional CD4+ αβ T cells performed in a variety of challenged contexts (infection, tumor, allergy) that aimed to parse the complexity and representativity of previously defined CD4+ T cell types, lineages, and cosmologies. With a few years' experience, the field has realized the difficulties and pitfalls of scRNAseq. With the very high-dimensionality of scRNAseq data, subset definitions based on low-dimensionality marker combinations tend to fade or blur: cell types prove more complex than expected; transcripts of key defining transcripts (cytokines, chemokines) are distributed as broad and partially overlapping continua; boundaries with innate lymphocytes are blurred. Tissue location and activation, either cytokine-driven or TCR-driven, determine Teff heterogeneity in sometimes unexpected ways. Emerging techniques for lineage and trajectory tracing, and RNA-protein connections, will further help define the space of differentiated CD4+ T cell heterogeneity.

中文翻译：

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CD4+ teff 细胞异质性：从单细胞转录组学的角度。

单细胞转录组学 (scRNAseq) 有望生成确定的细胞类型图谱。我们回顾了在各种挑战环境（感染、肿瘤、过敏）中进行的传统 CD4+ αβ T 细胞的 scRNAseq 研究，旨在解析先前定义的 CD4+ T 细胞类型、谱系和宇宙学的复杂性和代表性。凭借几年的经验，该领域已经意识到 scRNAseq 的困难和陷阱。由于 scRNAseq 数据的维数非常高，基于低维标记组合的子集定义往往会褪色或模糊：细胞类型证明比预期的更复杂；关键定义转录本（细胞因子、趋化因子）的转录本分布为广泛且部分重叠的连续体；与先天淋巴细胞的界限是模糊的。组织定位和激活，细胞因子驱动或 TCR 驱动，有时会以意想不到的方式确定 Teff 的异质性。用于谱系和轨迹追踪以及 RNA-蛋白质连接的新兴技术将进一步帮助定义分化的 CD4+ T 细胞异质性的空间。