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Single Cell Multiomics Across Nine Mammals Reveals Cell Type Specific Regulatory Conservation in the Brain

Code Availability

All code generated for this manuscript is availble in this repository. Click HERE to view code

Figure 1

Abstract

Understanding the gene regulatory mechanisms underlying brain function is crucial for advancing knowledge of the genetic basis of neurologic diseases. Cis-regulatory elements (CREs) play a pivotal role in gene regulation, and their evolutionary conservation can offer valuable insights. Importantly, the function and evolution of CREs are affected not only by primary sequence, but also by the cis- and trans-regulatory context. However, comparative functional analyses across species and cell types have been limited, leaving how these regulatory landscapes evolve in the brain largely unresolved. Here, we generated single-nucleus multiomic (snRNA- and snATAC-seq) data from post-mortem cortex tissue across nine mammalian species and identified candidate CREs (cCREs) in a cell type–specific manner. We developed a multidimensional framework of conservation to assess sites of shared function, integrating sequence, chromatin accessibility, and enhancer–gene linkage information. Using massively parallel reporter assays (MPRA) in human neural progenitor cells and neurons, we measured activity of cCREs including both conserved and human-specific regions. CRISPR interference (CRISPRi) validated conserved enhancer function, including at neurodevelopmentally important genes like FAM181B. Motif enrichment and chromBPnet revealed transcription factors distinguishing conserved versus recent cCREs. Linkage disequilibrium score regression showed both conserved and human-specific cCREs were enriched for neuropsychiatric GWAS risk, while neurodegenerative risk was confined to conserved elements. Our findings define functional dimensions of enhancer conservation and demonstrate how regulatory evolution shapes human brain biology and disease susceptibility.

Data Availability

The raw and processed data generated are available through NCBI GEO under series accession number.

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All code used in Anderson et al. 2025

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