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Glial cells are essential for functionality of the nervous system. Growing evidence underscores the importance of astrocytes; however, analogous astroglia in peripheral organs are poorly understood. Using confocal time-lapse imaging, fate mapping, and mutant genesis in a zebrafish model, we identify a neural crest–derived glial cell, termed nexus glia, which utilizes Meteorin signaling via Jak/Stat3 to drive differentiation and regulate heart rate and rhythm. Nexus glia are labeled with gfap, glast, and glutamine synthetase, markers that typically denote astroglia cells. Further, analysis of single-cell sequencing datasets of human and murine hearts across ages reveals astrocyte-like cells, which we confirm through a multispecies approach. We show that cardiac nexus glia at the outflow tract are critical regulators of both the sympathetic and parasympathetic system. These data establish the crucial role of glia on cardiac homeostasis and provide a description of nexus glia in the PNS.

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Single-cell RNA sequencing is a new frontier across all biology, particularly in neuroscience. While powerful for answering numerous neuroscience questions, limitations in sample input size, and initial capital outlay can exclude some researchers from its application. Here, we tested a recently introduced method for scRNAseq across diverse scales and neuroscience experiments. We benchmarked against a major current scRNAseq technology and found that PIPseq performed similarly, in line with earlier benchmarking data. Across dozens of samples, PIPseq recovered many brain cell types at small and large scales (1,000-100,000 cells/sample) and was able to detect differentially expressed genes in an inflammation paradigm. Similarly, PIPseq could detect expected and new differentially expressed genes in a brain single cell suspension from a knockout mouse model; it could also detect rare, virally-labelled cells following lentiviral targeting and gene knockdown. Finally, we used PIPseq to investigate gene expression in a nontraditional model species, the little skate (Leucoraja erinacea). In total, PIPSeq was able to detect single-cell gene expression changes across models and species, with an added benefit of large scale capture and sequencing of each sample.