Johnson, W. E. Origins and evolutionary consequences of ancient endogenous retroviruses. Nat. Rev. Microbiol. 17, 355–370 (2019).
Barau, J. et al. The DNA methyltransferase DNMT3C protects male germ cells from transposon activity. Science 354, 909–912 (2016).
Tam, O. H., Ostrow, L. W. & Gale Hammell, M. Diseases of the nERVous system: retrotransposon activity in neurodegenerative disease. Mob. DNA 10, 32 (2019).
Shi, H., Wei, J. & He, C. Where, when, and how: context-dependent functions of RNA methylation writers, readers, and erasers. Mol. Cell 74, 640–650 (2019).
Patil, D. P., Pickering, B. F. & Jaffrey, S. R. Reading m6A in the transcriptome: m6A-binding proteins. Trends Cell Biol. 28, 113–127 (2018).
Goodier, J. L. & Kazazian, H. H., Jr. Retrotransposons revisited: the restraint and rehabilitation of parasites. Cell 135, 23–35 (2008).
Gagnier, L., Belancio, V. P. & Mager, D. L. Mouse germ line mutations due to retrotransposon insertions. Mob. DNA 10, 15 (2019).
Hancks, D. C. & Kazazian, H. H. Jr. Roles for retrotransposon insertions in human disease. Mob. DNA 7, 9 (2016).
Zamudio, N. & Bourc’his, D. Transposable elements in the mammalian germline: a comfortable niche or a deadly trap? Heredity 105, 92–104 (2010).
Rowe, H. M. et al. KAP1 controls endogenous retroviruses in embryonic stem cells. Nature 463, 237–240 (2010).
Li, W. et al. MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens. Genome Biol. 15, 554 (2014).
Fukuda, K., Okuda, A., Yusa, K. & Shinkai, Y. A CRISPR knockout screen identifies SETDB1-target retroelement silencing factors in embryonic stem cells. Genome Res. 28, 846–858 (2018).
Liu, X. et al. UHRF1 targets DNMT1 for DNA methylation through cooperative binding of hemi-methylated DNA and methylated H3K9. Nat. Commun. 4, 1563 (2013).
Sadic, D. et al. Atrx promotes heterochromatin formation at retrotransposons. EMBO Rep. 16, 836–850 (2015).
Maksakova, I. A. et al. H3K9me3-binding proteins are dispensable for SETDB1/H3K9me3-dependent retroviral silencing. Epigenetics Chromatin 4, 12 (2011).
Wen, J. et al. Zc3h13 regulates nuclear RNA m6A methylation and mouse embryonic stem cell self-renewal. Mol. Cell 69, 1028–1038.e6 (2018).
Ping, X. L. et al. Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 24, 177–189 (2014).
Greenberg, M. V. C. & Bourc’his, D. Cultural relativism: maintenance of genomic imprints in pluripotent stem cell culture systems. Curr. Opin. Genet. Dev. 31, 42–49 (2015).
Liu, J. et al. N6-methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription. Science 367, 580–586 (2020).
Geula, S. et al. m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation. Science 347, 1002–1006 (2015).
Dominissini, D. et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 485, 201–206 (2012).
Batista, P. J. et al. m6A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell 15, 707–719 (2014).
Meyer, K. D. et al. Comprehensive analysis of mRNA methylation reveals enrichment in 3′ UTRs and near stop codons. Cell 149, 1635–1646 (2012).
Abakir, A. et al. N6-methyladenosine regulates the stability of RNA:DNA hybrids in human cells. Nat. Genet. 52, 48–55 (2020).
Nishimura, K., Fukagawa, T., Takisawa, H., Kakimoto, T. & Kanemaki, M. An auxin-based degron system for the rapid depletion of proteins in nonplant cells. Nat. Methods 6, 917–922 (2009).
Li, Y. et al. N6-Methyladenosine co-transcriptionally directs the demethylation of histone H3K9me2. Nat. Genet. 52, 870–877 (2020).
Zaccara, S. & Jaffrey, S. R. A unified model for the function of YTHDF proteins in regulating m6A-modified mRNA. Cell 181, 1582–1595.e18 (2020).
Lasman, L. et al. Context-dependent functional compensation between Ythdf m6A reader proteins. Genes Dev. 34, 1373–1391 (2020).
Ries, R. J. et al. m6A enhances the phase separation potential of mRNA. Nature 571, 424–428 (2019).
Lu, C., Contreras, X. & Peterlin, B. M. P. P bodies inhibit retrotransposition of endogenous intracisternal A particles. J. Virol. 85, 6244–6251 (2011).
Haeussler, M. et al. Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 17, 148 (2016).
Walter, M., Teissandier, A., Pérez-Palacios, R. & Bourc’his, D. An epigenetic switch ensures transposon repression upon dynamic loss of DNA methylation in embryonic stem cells. eLife 5, 1–30 (2016).
Chen, C. Y. A., Ezzeddine, N. & Shyu, A. B. Messenger RNA half-life measurements in mammalian cells. Methods Enzymol. 448, 335–357 (2008).
Skene, P. J. & Henikoff, S. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife 6, 1–35 (2017).
Didion, J. P., Martin, M. & Collins, F. S. Atropos: specific, sensitive, and speedy trimming of sequencing reads. PeerJ 5, e3720 (2017).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Bailly-Bechet, M., Haudry, A. & Lerat, E. ‘One code to find them all’: a perl tool to conveniently parse RepeatMasker output files. Mob. DNA 5, 1–15 (2014).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
Gel, B. et al. regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests. Bioinformatics 32, 289–291 (2016).
Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).
Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44 (W1), W160–W165 (2016).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Zhang, T., Zhang, S. W., Zhang, L. & Meng, J. trumpet: transcriptome-guided quality assessment of m6A-seq data. BMC Bioinformatics 19, 260 (2018).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).