Evidence map›Paper›PMID 40475058›Full record

ArticleFrontiers in bioinformatics2025

MORE-RNAseq: a pipeline for quantifying retrotransposition-capable LINE1 expression based on RNA-seq data.

Yutaka Nakachi, Jianbin Du, Risa Watanabe, Yutaro Yanagida, Miki Bundo, Kazuya Iwamoto

Abstract read
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Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yutaka Nakachi *Department of Molecular Brain Science, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Jianbin Du *Department of Molecular Brain Science, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Risa WatanabeDepartment of Molecular Brain Science, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Yutaro YanagidaDepartment of Molecular Brain Science, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Miki BundoDepartment of Molecular Brain Science, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Kazuya IwamotoDepartment of Molecular Brain Science, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

agingcancerexpressionLINE-1 (L1)retrotransposonRNA-seqtranscription

Identifiers

PMID40475058
PMCPMC12138260

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.