深度转录组学揭示泛神经元基因的细胞特异性异构体。

Deep transcriptomics reveals cell-specific isoforms of pan-neuronal genes.

作者信息

Wolfe Zachery, Liska David, Norris Adam

机构信息

Department of Biochemistry, University of California, Riverside, Riverside, CA, USA.

Office of Information Technology, Southern Methodist University, Dallas, TX, USA.

出版信息

Nat Commun. 2025 May 16;16(1):4507. doi: 10.1038/s41467-025-58296-2.

Abstract

Profiling alternative splicing in single neurons using RNA-seq is challenging due to low capture efficiency and sensitivity. We therefore know much less about splicing patterns and regulation across neurons than we do about gene expression. Here we leverage unique attributes of C. elegans to investigate deep neuron-specific transcriptomes with biological replicates generated by the CeNGEN consortium, enabling high-confidence assessment of splicing across neuron types even for lowly-expressed genes. Global splicing maps reveal several striking observations, including pan-neuronal genes harboring cell-specific splice variants, and abundant differential intron retention across neuron types. We develop an algorithm to identify unique cell-specific expression patterns, which reveals both cell-specific isoforms and potential regulatory factors establishing these isoforms. Genetic interrogation of these factors in vivo identifies three distinct splicing factors employed to control splicing in a single neuron. Finally, we develop a user-friendly platform for spatial transcriptomic visualization of these splicing patterns with single-neuron resolution.

摘要

由于捕获效率和灵敏度较低,利用RNA测序分析单个神经元中的可变剪接具有挑战性。因此,我们对神经元间剪接模式和调控的了解远少于对基因表达的了解。在这里,我们利用秀丽隐杆线虫的独特特性,通过CeNGEN联盟生成的生物学重复来研究深度神经元特异性转录组,即使对于低表达基因,也能对不同神经元类型的剪接进行高可信度评估。全局剪接图谱揭示了几个显著的观察结果,包括含有细胞特异性剪接变体的泛神经元基因,以及不同神经元类型间大量的差异内含子保留。我们开发了一种算法来识别独特的细胞特异性表达模式,该算法揭示了细胞特异性异构体和建立这些异构体的潜在调控因子。在体内对这些因子进行基因研究,确定了三种用于控制单个神经元剪接的不同剪接因子。最后,我们开发了一个用户友好的平台,用于以单神经元分辨率对这些剪接模式进行空间转录组可视化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8cd9/12084633/8324fe9bc37a/41467_2025_58296_Fig1_HTML.jpg

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