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Neurons in the brainstem preBötzinger complex (preBötC) generate the rhythm and rudimentary motor pattern for inspiratory breathing movements. We performed whole-cell patch-clamp recordings from inspiratory neurons in the preBötC of neonatal mouse slices that retain breathing-related rhythmicityin vitro. We classified neurons based on their electrophysiological properties and genetic background, and then aspirated their cellular contents for single-cell RNA sequencing (scRNA-seq). This data set provides the raw nucleotide sequences (FASTQ files) and annotated files of nucleotide sequences mapped to the mouse genome (mm10 from Ensembl), which includes the fragment counts, gene lengths, and fragments per kilobase of transcript per million mapped reads (FPKM). These data reflect the transcriptomes of the neurons that generate the rhythm and pattern for inspiratory breathing movements.

 

Breathing depends on interneurons in the preBötzinger complex (preBötC) derived fromDbx1-expressing precursors. Here we investigate whether rhythm- and pattern-generating functions reside in discrete classes of Dbx1 preBötC neurons. In a slice model of breathing with ~ 5 s cycle period, putatively rhythmogenic Type-1 Dbx1 preBötC neurons activate 100–300 ms prior to Type-2 neurons, putatively specialized for output pattern, and 300–500 ms prior to the inspiratory motor output. We sequenced Type-1 and Type-2 transcriptomes and identified differential expression of 123 genes including ionotropic receptors (Gria3, Gabra1) that may explain their preinspiratory activation profiles and Ca²⁺signaling (Cracr2a,Sgk1) involved in inspiratory and sigh bursts. Surprisingly, neuropeptide receptors that influence breathing (e.g., µ-opioid and bombesin-like peptide receptors) were only sparsely expressed, which suggests that cognate peptides and opioid drugs exert their profound effects on a small fraction of the preBötC core. These data in the public domain help explain the neural origins of breathing.

 

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.