Integrative CUT&Tag-RNA-Seq Analysis of Histone Variant MacroH2A1-Dependent Orchestration of Human Induced Pluripotent Stem Cell Reprogramming

Abstract

Aim: Human induced pluripotent stem cells (iPSCs) are inefficiently derived from somatic cells by overexpression of defined transcription factors. Overexpression of H2A histone variant macroH2A1.1, but not macroH2A1.2, leads to increased iPSC reprogramming by unclear mechanisms. Materials & methods: Cleavage under targets and tagmentation (CUT&Tag) allows robust epigenomic profiling of a low cell number. We performed an integrative CUT&Tag-RNA-Seq analysis of macroH2A1-dependent orchestration of iPSCs reprogramming using human endothelial cells. Results: We demonstrate wider genome occupancy, predicted transcription factors binding, and gene expression regulated by macroH2A1.1 during reprogramming, compared to macroH2A1.2. MacroH2A1.1, previously associated with neurodegenerative pathologies, specifically activated ectoderm/neural processes. Conclusion: CUT&Tag and RNA-Seq data integration is a powerful tool to investigate the epigenetic mechanisms occurring during cell reprogramming.

Keywords::

• CUT&Tag
• induced pluripotent stem cells
• iPSCs
• macroH2A1
• reprogramming
• somatic cells

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.tandfonline.com/doi/suppl/10.2217/epi-2023-0267

Conceptualization: T Mazza and M Vinciguerra. Methodology: N Liorni, A Napoli and S Castellana. Software: N Liorni. Formal analysis: N Liorni, A Napoli, S Castellana, S Giallongo and T Mazza. Investigation: S Giallongo, O Lo Re and D Řeháková. Resources: D Řeháková and I Koutná. Data curation: N Liorni, S Giallongo and O Lo Re. Writing – original draft: N Liorni, T Mazza and M Vinciguerra. Writing – review and editing: N Liorni, A Napoli, S Castellana, DR, O Lo Re, I Koutná, T Mazza and M Vinciguerra. Supervision: I Koutná, T Mazza and M Vinciguerra. Project administration: M Vinciguerra. Funding acquisition: T Mazza and M Vinciguerra.

Acknowledgments

The authors thank Genomix4Life (Baronissi, Italy) and CEITEC (Brno, Czech Republic) for excellent technical assistance with genomics and transcriptomics approaches, respectively.

Financial disclosure

This research was funded by the European Regional Development Fund-Project MAGNET (CZ.02.1.01/0.0/0.0/15_003/0000492), the Ministry of Health of the Czech Republic (NV18-03-00058), the Italian Ministry of Health and ‘5x1000’ voluntary contributions (R22-5x1000), and by the European Commission Horizon 2020 Framework Program (project 856871—TRANSTEM). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Data sharing statement

The RNA-seq data [22] was deposited into GEO with the dataset identifier GSE164396. Genomics sequences obtained in this study by CUT&Tag has been deposited into GEO with the dataset identifier GSE214013.