An in vivo systemic massively parallel platform for deciphering animal tissue-specific regulatory function

• Published in: Frontiers in genetics Vol. 16; p. 1533900
• Main Authors: Brown, Ashley R., Fox, Grant A., Kaplow, Irene M., Lawler, Alyssa J., Phan, BaDoi N., Gadey, Lahari, Wirthlin, Morgan E., Ramamurthy, Easwaran, May, Gemma E., Chen, Ziheng, Su, Qiao, McManus, C. Joel, van de Weerd, Robert, Pfenning, Andreas R.
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 09.04.2025
• Subjects: aav; brain; enhancer; Genetics; in vivo; machine learning; PHP.eB; enhancer; tissue specific; transcriptional regulation; aav; in vivo; PHP.eB; brain; machine learning
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2025.1533900

Introduction: Transcriptional regulation is an important process wherein non-protein coding enhancer sequences play a key role in determining cell type identity and phenotypic diversity. In neural tissue, these gene regulatory processes are crucial for coordinating a plethora of interconnected and regionally specialized cell types, ensuring their synchronized activity in generating behavior. Recognizing the intricate interplay of gene regulatory processes in the brain is imperative, as mounting evidence links neurodevelopment and neurological disorders to non-coding genome regions. While genome-wide association studies are swiftly identifying non-coding human disease-associated loci, decoding regulatory mechanisms is challenging due to causal variant ambiguity and their specific tissue impacts. Methods: Massively parallel reporter assays (MPRAs) are widely used in cell culture to study the non-coding enhancer regions, linking genome sequence differences to tissue-specific regulatory function. However, widespread use in animals encounters significant challenges, including insufficient viral library delivery and library quantification, irregular viral transduction rates, and injection site inflammation disrupting gene expression. Here, we introduce a systemic MPRA (sysMPRA) to address these challenges through systemic intravenous AAV viral delivery. Results: We demonstrate successful transduction of the MPRA library into diverse mouse tissues, efficiently identifying tissue specificity in candidate enhancers and aligning well with predictions from machine learning models. We highlight that sysMPRA effectively uncovers regulatory effects stemming from the disruption of MEF2C transcription factor binding sites, single-nucleotide polymorphisms, and the consequences of genetic variations associated with late-onset Alzheimer‘s disease. Conclusion: SysMPRA is an effective library delivering method that simultaneously determines the transcriptional functions of hundreds of enhancers in vivo across multiple tissues.