Mandibular muscle troponin of the Florida carpenter ant Camponotus floridanus: extending our insights into invertebrate Ca2+ regulation

De novo sequencing, diploid assembly, and annotation of the black carpenter ant, Camponotus pennsylvanicus, and its symbionts by one person for $1000, using nanopore sequencing

The black carpenter ant (Camponotus pennsylvanicus) is a pest species found widely throughout North America. From a single individual I used long-read nanopore sequencing to assemble a phased diploid genome of 306 Mb and 60X coverage, with quality assessed by a 97.0% BUSCO score, improving upon other ant assemblies. The mitochondrial genome reveals minor rearrangements from other ants. The reads also allowed assembly of parasitic and symbiont genomes. I include a complete Wolbachia bacterial assembly with a size of 1.2 Mb, as well as a commensal symbiont Blochmannia pennsylvanicus, at 791 kb. DNA methylation and hydroxymethylation were measured at base-pair resolution level from the same reads and confirmed extremely low levels seen in the Formicidae family. There was moderate heterozygosity, with 0.16% of bases being biallelic from the parental haplotypes. Protein prediction yielded 14 415 amino acid sequences with 95.8% BUSCO score and 86% matching to previously known proteins. All assemblies were derived from a single MinION flow cell generating 20 Gb of sequence for a cost of $1047 including consumable reagents. Adding fixed costs for equipment brings the total for an ant-sized genome to less than $5000. All analyses were performed in 1 week on a single desktop computer.

A Roadmap to Reconstructing Muscle Architecture from CT Data

Skeletal muscle is responsible for voluntary force generation across animals, and muscle architecture largely determines the parameters of mechanical output. The ability to analyze muscle performance through muscle architecture is thus a key step towards better understanding the ecology and evolution of movements and morphologies. In pennate skeletal muscle, volume, fiber lengths, and attachment angles to force transmitting structures comprise the most relevant parameters of muscle architecture. Measuring these features through tomographic techniques offers an alternative to tedious and destructive dissections, particularly as the availability of tomographic data is rapidly increasing. However, there is a need for streamlined computational methods to access this information efficiently. Here, we establish and compare workflows using partially automated image analysis for fast and accurate estimation of animal muscle architecture. After isolating a target muscle through segmentation, we evaluate freely available and proprietary fiber tracing algorithms to reconstruct muscle fibers. We then present a script using the Blender Python API to estimate attachment angles, fiber lengths, muscle volume, and physiological cross-sectional area. We apply these methods to insect and vertebrate muscle and provide guided workflows. Results from fiber tracing are consistent compared to manual measurements but much less time-consuming. Lastly, we emphasize the capabilities of the open-source three-dimensional software Blender as both a tool for visualization and a scriptable analytic tool to process digitized anatomical data. Across organisms, it is feasible to extract, analyze, and visualize muscle architecture from tomography data by exploiting the spatial features of scans and the geometric properties of muscle fibers. As digital libraries of anatomies continue to grow, the workflows and approach presented here can be part of the open-source future of digital comparative analysis.