MORE-RNAseq:基于RNA-seq数据定量逆转录LINE1表达的管道。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in bioinformatics Pub Date : 2025-05-22 eCollection Date: 2025-01-01 DOI:10.3389/fbinf.2025.1575346
Yutaka Nakachi, Jianbin Du, Risa Watanabe, Yutaro Yanagida, Miki Bundo, Kazuya Iwamoto
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引用次数: 0

摘要

逆转录转座子长点缀核元件-1 (LINE-1, L1)在哺乳动物基因组中占很大比例。一小部分L1s在结构上没有有害突变,它们可以通过一种称为逆转录(RT)的过程来扩增它们的拷贝。RT影响基因组稳定性和基因表达,并参与许多遗传性疾病的发病机制。在数十万个非rt -L1s中测量具有rt能力的L1s (rc-L1s)的表达是了解rt影响的重要步骤。我们开发了来自RNA-seq数据的移动元件源读富集(MORE-RNAseq),这是一个使用人工筛选的L1参考资料计算人类和小鼠中rc-L1s表达的管道。MORE-RNAseq允许在考虑基因组背景的情况下量化总体(所有rc-L1s表达的总和)和单个rc-L1s的表达水平。我们将MORE-RNAseq应用于公开可用的人类和小鼠癌细胞系的RNA-seq数据,这些数据来自报道L1表达增加的研究。我们发现,在基因间和基因内的整体水平上,rc-L1表达显著增加。我们还在基因座水平上发现了差异表达的rc-L1s,这将是下游分析的重要候选者。我们还将我们的方法应用于没有L1表达信息的年轻和老年人体肌肉RNA-seq数据,发现老年样本中rc-L1表达显著增加。我们的方法将有助于利用标准RNA-seq数据了解rc-L1s在各种生理和病理生理条件下的作用。所有脚本都可以在https://github.com/molbrain/MORE-RNAseq上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MORE-RNAseq: a pipeline for quantifying retrotransposition-capable LINE1 expression based on RNA-seq data.

Retrotransposon long interspersed nuclear element-1 (LINE-1, L1) constitutes a large proportion of the mammalian genome. A fraction of L1s, which have no deleterious mutations in the structure, can amplify their copies via a process called retrotransposition (RT). RT affects genome stability and gene expression and is involved in the pathogenesis of many hereditary diseases. Measuring expression of RT-capable L1s (rc-L1s) among the hundreds of thousands of non rc-L1s is an essential step to understand the impact of RT. We developed mobile element-originated read enrichment from RNA-seq data (MORE-RNAseq), a pipeline for calculating expression of rc-L1s using manually curated L1 references in humans and mice. MORE-RNAseq allows for quantification of expression levels of overall (sum of the expression of all rc-L1s) and individual rc-L1s with consideration of the genomic context. We applied MORE-RNAseq to publicly available RNA-seq data of human and mouse cancer cell lines from the studies that reported increased L1 expression. We found the significant increase of rc-L1 expressions at the overall level in both inter- and intragenic contexts. We also identified differentially expressed rc-L1s at the locus level, which will be the important candidates for downstream analysis. We also applied our method to young and aged human muscle RNA-seq data with no prior information about L1 expression, and found a significant increase of rc-L1 expression in the aged samples. Our method will contribute to understand the role of rc-L1s in various physiological and pathophysiological conditions using standard RNA-seq data. All scripts are available at https://github.com/molbrain/MORE-RNAseq.

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2.60
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