Iso-Seq 能够以单细胞分辨率发现人类视网膜中的新型同工酶变体

Luozixian Wang, Daniel Urrutia-Cabrera, Sandy Shen-Chi Hung, Alex W Hewitt, Samuel W Lukowski, Careen Foord, Peng-Yuan Wang, Hagen Tilgner, Raymond Wong
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引用次数: 0

摘要

最近对人类视网膜进行的单细胞转录组分析提供了重要信息,使人们能够深入了解异质性视网膜细胞群中的遗传信号,从而产生视觉。然而,传统的单细胞 RNAseq 3' 短线程测序并不适合鉴定同工酶变异。在这里,我们利用全长测序的 Iso-Seq 技术,以单细胞分辨率对人类视网膜进行剖析,从而发现同工酶变体。我们生成了一个视网膜转录组数据集,该数据集由来自三个供体视网膜的 25,302 个细胞核组成,在主要视网膜细胞类型中检测到 49,710 个已知转录本和 241,949 个新转录本。我们调查了利用替代启动子驱动转录本变异表达的情况,结果显示,在主要视网膜细胞类型中,1%-8%的基因利用了多个启动子。此外,我们的研究结果还对遗传性视网膜疾病(IRD)基因的新转录本变体进行了基因表达谱分析,并确定了主要视网膜细胞类型中外显子剪接的不同用法。总之,我们利用全长测序技术生成了单细胞分辨率的人类视网膜转录组数据集。我们的研究凸显了 Iso-Seq 在绘制人类视网膜同工酶组多样性图谱方面的潜力,为视网膜复杂的转录组景观提供了更广阔的视野。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iso-Seq enables discovery of novel isoform variants in human retina at single cell resolution
Recent single cell transcriptomic profiling of the human retina provided important insights into the genetic signals in heterogeneous retinal cell populations that enable vision. However, conventional single cell RNAseq with 3' short-read sequencing is not suitable to identify isoform variants. Here we utilized Iso-Seq with full-length sequencing to profile the human retina at single cell resolution for isoform discovery. We generated a retina transcriptome dataset consisting of 25,302 nuclei from three donor retina, and detected 49,710 known transcripts and 241,949 novel transcripts across major retinal cell types. We surveyed the use of alternative promoters to drive transcript variant expression, and showed that 1-8% of genes utilized multiple promoters across major retinal cell types. Also, our results enabled gene expression profiling of novel transcript variants for inherited retinal disease (IRD) genes, and identified differential usage of exon splicing in major retinal cell types. Altogether, we generated a human retina transcriptome dataset at single cell resolution with full-length sequencing. Our study highlighted the potential of Iso-Seq to map the isoform diversity in the human retina, providing an expanded view of the complex transcriptomic landscape in the retina.
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