RIP-seq reveals LINE-1 ORF1p association with p-body enriched mRNAs

RIP-seq 揭示 LINE-1 ORF1p 与 p-body 富集的 mRNA 关联

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作者:Erica M Briggs #, Wilson McKerrow #, Paolo Mita, Jef D Boeke, Susan K Logan, David Fenyö

Background

Long INterspersed Element-1 (LINE-1) is an autonomous retroelement able to "copy-and-paste" itself into new loci of the host genome through a process called retrotransposition. The LINE-1 bicistronic mRNA codes for two proteins, ORF1p, a nucleic acid chaperone, and ORF2p, a protein with endonuclease and reverse transcriptase activity. Both proteins bind LINE-1 mRNA in cis and are necessary for retrotransposition. While LINE-1 transcription is usually repressed in most healthy somatic cells through a plethora of mechanisms, ORF1p expression has been observed in nearly 50% of tumors, and new LINE-1 insertions have been documented in a similar fraction of tumors, including prostate cancer.

Conclusion

Our results show a significant remodeling of LINE-1 loci expression in androgen independent cell lines when compared to parental androgen dependent cells. Additionally, we found that ORF1p bound a significant amount of non-LINE-1 mRNA, and that the enriched ORF1p bound mRNAs are also amplified in LINE-1 expressing TCGA prostate tumors, indicating the biological relevance of our findings to prostate cancer.

Results

Here, we utilized RNA ImmunoPrecipitation (RIP) and the L1EM analysis software to identify ORF1p bound RNA in prostate cancer cells. We identified LINE-1 loci that were expressed in parental androgen sensitive and androgen independent clonal derivatives. In all androgen independent cells, we found higher levels of LINE-1 RNA, as well as unique expression patterns of LINE-1 loci. Interestingly, we observed that ORF1p bound many non-LINE-1 mRNA in all prostate cancer cell lines evaluated, and polyA RNA, and RNA localized in p-bodies were especially enriched. Furthermore, the expression levels of RNAs identified in our ORF1p RIP correlated with RNAs expressed in LINE-1 positive tumors from The Cancer Genome Atlas (TCGA).

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