Machine learning identification of enhancers in the rhesus macaque genome

Jing He¹, BaDoi N Phan², Willa G Kerkhoff¹, Aydin Alikaya¹, Tao Hong³, Olivia R Brull¹, J Megan Fredericks¹, Morgan Sedorovitz⁴, Chaitanya Srinivasan⁵, Michael J Leone², Olivia M Wirfel¹, Ashley Brown⁶, Samuel Dauby¹, Rachel K Tittle¹, Meng K Lin¹, Bryan M Hooks¹, Andreea C Bostan¹, Omar A Gharbawie¹, Leah C Byrne⁴, Andreas R Pfenning⁷, William R Stauffer⁸

Affiliations

¹ Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
² Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA; University of Pittsburgh-Carnegie Mellon University Medical Scientist Training Program, Pittsburgh, PA 15213, USA.
³ Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; Program in Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
⁴ Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
⁵ Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
⁶ Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
⁷ Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: apfenning@cmu.edu.
⁸ Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA. Electronic address: wrs@pitt.edu.

PMID: 40403706
DOI: 10.1016/j.neuron.2025.04.030

Machine learning identification of enhancers in the rhesus macaque genome

Jing He et al. Neuron. 2025.

. 2025 May 21;113(10):1548-1561.e8.

doi: 10.1016/j.neuron.2025.04.030.

Authors

Affiliations

¹ Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
² Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA; University of Pittsburgh-Carnegie Mellon University Medical Scientist Training Program, Pittsburgh, PA 15213, USA.
³ Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; Program in Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
⁴ Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
⁵ Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
⁶ Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
⁷ Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: apfenning@cmu.edu.
⁸ Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA. Electronic address: wrs@pitt.edu.

PMID: 40403706
DOI: 10.1016/j.neuron.2025.04.030

Abstract

Nonhuman primate (NHP) neuroanatomy and cognitive complexity make NHPs ideal models to study human neurobiology and disease. However, NHP circuit-function investigations are limited by the availability of molecular reagents that are effective in NHPs. This calls for reagent development approaches that prioritize NHPs. Therefore, we derived enhancers from the NHP genome. We defined cell-type-specific open chromatin regions (OCRs) in single-cell data from rhesus macaques. We trained machine-learning models to rank those OCRs according to their potential as cell-type-specific enhancers for cells in the dorsolateral prefrontal cortex (DLPFC). We packaged the top-ranked layer-3-pyramidal-neuron enhancer into AAV and injected it into the macaque DLPFC. Expression was mostly restricted to layers 2 and 3 and confirmed with light-driven activation of channelrhodopsin. These results provide a crucial tool for studying the causal functions of DLPFC and provide a roadmap for optimized gene delivery in primates.

Keywords: AAV; DLPFC; cell types; cell-type-specific; cognition; dorsolateral prefrontal cortex; enhancer; machine learning; optogenetics; rhesus monkey.

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Conflict of interest statement

Declaration of interests J.H., B.N.P., L.C.B., W.R.S., and A.R.P. are inventors on AAV patent applications. L.C.B. is a co-founder of Avista Therapeutics and VegaVect. M.S. is an employee of Avista Therapeutics. A.R.P. is founder and CEO of Snail Biosciences. A.R.P. and B.N.P. have Snail Biosciences stockholdings.

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Machine learning identification of enhancers in the rhesus macaque genome

Affiliations

Machine learning identification of enhancers in the rhesus macaque genome

Authors

Affiliations

Abstract

Conflict of interest statement

MeSH terms