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High throughput error corrected Nanopore single cell transcriptome sequencing

机译:高吞吐量误差校正纳米孔单细胞转录组测序

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Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.
机译:基于液滴的高吞吐量单电池测序技术非常高兴地深入了解细胞到细胞异质性。然而,这些方法仅在短读取测序后允许分析转录物的一个末端。结果,有关剪接和序列异质性的信息丢失。为了克服这种限制,最近介绍了使用长读测序的几种方法。然而,这些技术受到低测序深度和/或缺乏或不准确分配的独特分子标识符(UMIS)的限制,这对于消除PCR偏压和伪影是至关重要的。我们引入了SCNAumi-SEQ,一种与准确的细胞条码和UMI分配策略相结合的牛津纳米孔测序的高吞吐量。 UMI引导误差校正允许在高测序深度下使用10x基因组学单个单元隔离系统产生高精度全长序列信息。我们分析了胚胎小鼠脑中的转录物同种型多样性,表明SCNAumi-SEQ允许在单个细胞水平下定义剪接和SNV(RNA编辑)。

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