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FUS突变小鼠中低读取深度QuantSeq 3'测序与全RNA测序的比较

A Comparison of Low Read Depth QuantSeq 3' Sequencing to Total RNA-Seq in FUS Mutant Mice.

作者信息

Jarvis Seth, Birsa Nicol, Secrier Maria, Fratta Pietro, Plagnol Vincent

机构信息

UCL Queen Square Institute of Neurology, London, United Kingdom.

UCL Genetics Institute, London, United Kingdom.

出版信息

Front Genet. 2020 Nov 19;11:562445. doi: 10.3389/fgene.2020.562445. eCollection 2020.

Abstract

Transcriptomics is a developing field with new methods of analysis being produced which may hold advantages in price, accuracy, or information output. QuantSeq is a form of 3' sequencing produced by Lexogen which aims to obtain similar gene-expression information to RNA-seq with significantly fewer reads, and therefore at a lower cost. QuantSeq is also able to provide information on differential polyadenylation. We applied both QuantSeq at low read depth and total RNA-seq to the same two sets of mouse spinal cord RNAs, each comprised by four controls and four mutants related to the neurodegenerative disease amyotrophic lateral sclerosis. We found substantial differences in which genes were found to be significantly differentially expressed by the two methods. Some of this difference likely due to the difference in number of reads between our QuantSeq and RNA-seq data. Other sources of difference can be explained by the differences in the way the two methods handle genes with different primary transcript lengths and how likely each method is to find a gene to be differentially expressed at different levels of overall gene expression. This work highlights how different methods aiming to assess expression difference can lead to different results.

摘要

转录组学是一个不断发展的领域,新的分析方法不断涌现,这些方法可能在价格、准确性或信息输出方面具有优势。QuantSeq是Lexogen公司开发的一种3'测序形式,旨在用明显更少的读数获得与RNA测序相似的基因表达信息,从而降低成本。QuantSeq还能够提供差异多聚腺苷酸化的信息。我们将低读数深度的QuantSeq和全RNA测序应用于两组相同的小鼠脊髓RNA,每组由四个与神经退行性疾病肌萎缩侧索硬化相关的对照和四个突变体组成。我们发现,两种方法在哪些基因被显著差异表达方面存在实质性差异。这种差异部分可能是由于我们的QuantSeq和RNA测序数据之间读数数量的差异。其他差异来源可以通过两种方法处理具有不同初级转录本长度的基因的方式差异,以及每种方法在不同总体基因表达水平下发现基因差异表达的可能性差异来解释。这项工作突出了旨在评估表达差异的不同方法如何导致不同的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4718/7717943/1b55d1fd640a/fgene-11-562445-g001.jpg

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