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无参考组装长读转录组测序数据的 RNA-Bloom2 方法。

Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2.

机构信息

Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, V5Z 4S6, Canada.

Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, V5Z 4S6, Canada.

出版信息

Nat Commun. 2023 May 22;14(1):2940. doi: 10.1038/s41467-023-38553-y.

Abstract

Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is little focus on reference-free transcriptome assembly. We introduce "RNA-Bloom2 [ https://github.com/bcgsc/RNA-Bloom ]", a reference-free assembly method for long-read transcriptome sequencing data. Using simulated datasets and spike-in control data, we show that the transcriptome assembly quality of RNA-Bloom2 is competitive to those of reference-based methods. Furthermore, we find that RNA-Bloom2 requires 27.0 to 80.6% of the peak memory and 3.6 to 10.8% of the total wall-clock runtime of a competing reference-free method. Finally, we showcase RNA-Bloom2 in assembling a transcriptome sample of Picea sitchensis (Sitka spruce). Since our method does not rely on a reference, it further sets the groundwork for large-scale comparative transcriptomics where high-quality draft genome assemblies are not readily available.

摘要

长读测序技术自出现以来有了显著的改进。它们的读长,可能跨越整个转录本,有利于重建转录组。现有的长读转录组组装方法主要是基于参考的,迄今为止,很少有研究关注无参考转录组组装。我们引入了“RNA-Bloom2[ https://github.com/bcgsc/RNA-Bloom ]”,这是一种用于长读转录组测序数据的无参考组装方法。使用模拟数据集和 Spike-in 对照数据,我们表明 RNA-Bloom2 的转录组组装质量可与基于参考的方法相媲美。此外,我们发现 RNA-Bloom2 需要竞争方法的峰值内存的 27.0%到 80.6%和总运行时间的 3.6%到 10.8%。最后,我们在组装 Sitka spruce(白皮松)的转录组样本中展示了 RNA-Bloom2。由于我们的方法不依赖于参考基因组,因此它为大规模比较转录组学奠定了基础,而在大规模比较转录组学中,高质量的基因组草图组装不易获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a11/10202958/8f8e96c4b00d/41467_2023_38553_Fig1_HTML.jpg

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