Neuronal Gene Architecture in Cancer borealis Revealed by Long-Read Genome Assembly and Deep Transcriptomic Analysis

Understanding the underlying neuronal function in non-model organisms requires accurate resolution of gene structure and transcript diversity. Here, we present a comprehensive genome annotation tor the Jonah crab (Cancer borealis), a key experimental system in crustacean neurobiology, with a particular focus on transcriptome-supported neuronal gene architecture. By integrating long-read genome assembly with extensive transcriptomic evidence, we reconstructed gene models with high confidence, enabling detailed characterization of exon-intron organization, alternative splicing, and isotorm diversity across gene families. Functional classification revealed extensive representation of neural-associated gene classes, including ion channels and receptors, transporters, enzymes, zinc finger proteins, histones, structural proteins, and cell adhesion molecules, alongside a large set of previously uncharacterized genes. In this study we particularly focused on the neuronal and ion channel gene families known to underlie circuit-level neuronal function in C. borealis. We provide an in-depth analysis of 87 genes spanning 17 neural-related gene families and 41 neuropeptides, detailing chromosomal localization, gene length, exon-intron configuration, and transcript-supported isotorm structure. For many of these genes, transcriptomic data confirmed expression and refined coding boundaries. Comparisons with existing transcriptomic datasets demonstrate strong concordance in gene expression patterns while also revealing novel transcripts and expanded gene family members not previously annotated. Together, this genome and transcriptome-integrated annotation establishes a high-resolution framework tor studying neuronal gene organization in C. borealis. T his resource enables direct connections between gene architecture, transcript diversity, and neural function, supporting future investigations in crustacean neurogenomics, comparative genomics, and the evolution of nervous system complexity.