Rhythm‐generating circuits in the vertebrate hindbrain form synaptic connections with cranial and spinal motor neurons, to generate coordinated, patterned respiratory behaviors. Zebrafish provide a uniquely tractable model system to investigate the earliest stages in respiratory motor circuit development in vivo. In larval zebrafish, respiratory behaviors are carried out by muscles innervated by cranial motor neurons—including the facial branchiomotor neurons (FBMNs), which innervate muscles that move the jaw, buccal cavity, and operculum. However, it is unclear when FBMNs first receive functional synaptic input from respiratory pattern‐generating neurons, and how the functional output of the respiratory motor circuit changes across larval development. In the current study, we used behavior and calcium imaging to determine how early FBMNs receive functional synaptic inputs from respiratory pattern‐generating networks in larval zebrafish. Zebrafish exhibited patterned operculum movements by 3 days postfertilization (dpf), though this behavior became more consistent at 4 and 5 dpf. Also by 3dpf, FBMNs fell into two distinct categories (“rhythmic” and “nonrhythmic”), based on patterns of neural activity. These two neuron categories were arranged differently along the dorsoventral axis, demonstrating that FBMNs have already established dorsoventral topography by 3 dpf. Finally, operculum movements were coordinated with pectoral fin movements at 3 dpf, indicating that the operculum behavioral pattern was driven by synaptic input. Taken together, this evidence suggests that FBMNs begin to receive initial synaptic input from a functional respiratory central pattern generator at or prior to 3 dpf. Future studies will use this model to study mechanisms of normal and abnormal respiratory circuit development.

Long-read sequencing technologies have been constrained by high error rates and large sample input requirements. The recent introduction of HiFi sequencing has enabled highly accurate detection of single-nucleotide variants (SNVs) from long reads (10-15 kb). However, a major limiting factor is the amount of sample input required, where current protocols require ≥15 micrograms of DNA. Here we report Ultra-Low Input High Fidelity Sequencing (ULI-HiFi), an amplification-based library preparation that reduces this input to 10 nanograms of DNA, a more than 10,000-fold reduction in sample input. When the ultra-low input method was tested using a benchmark genome, HG002, we observed high precision and improved recall of structural variants compared to a ground truth dataset from the Genome in a Bottle Consortium. We also benchmarked small variants and reported the accurate analysis of many variants in clinically important genes that are unmappable with short reads. We used this strategy to sequence tumor and polyp samples from a patient with familial adenomatous polyposis, a hereditary form of colon cancer, which revealed SNVs and structural variants not detected by short-read techniques. This strategy will enable the improved characterization of genetic variants from limited clinical samples. Citation Format: Hayan Lee, Graham Erwin, Aaron Horning, Raushun Kirtikar, Emmett Griffin-Baldwin, William Rowell, Philip Li, Sarah Kingan, Michael P. Snyder. Ultra-Low Input High-Fidelity (ULI-HiFi) long-reads uncover variants in genomic dark matter from pre-cancer polyp and tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2706.