When Bigger Is Better: 3D RNA Profiling of the Developing Head in the Catshark Scyliorhinus canicula

Abstract

We report the adaptation of RNA tomography, a technique allowing spatially resolved, genome-wide expression profiling, to a species occupying a key phylogenetic position in gnathostomes, the catshark Scyliorhinus canicula. We focused analysis on head explants at an embryonic stage, shortly following neural tube closure and of interest for a number of developmental processes, including early brain patterning, placode specification or the establishment of epithalamic asymmetry. As described in the zebrafish, we have sequenced RNAs extracted from serial sections along transverse, horizontal and sagittal planes, mapped the data onto a gene reference taking advantage of the high continuity genome recently released in the catshark, and projected read counts onto a digital model of the head obtained by confocal microscopy. This results in the generation of a genome-wide 3D atlas, containing expression data for most protein-coding genes in a digital model of the embryonic head. The digital profiles obtained for candidate forebrain regional markers along antero-posterior, dorso-ventral and left-right axes reproduce those obtained by in situ hybridization (ISH), with expected relative organizations. We also use spatial autocorrelation and correlation as measures to analyze these data and show that they provide adequate statistical tools to extract novel expression information from the model. These data and tools allow exhaustive searches of genes exhibiting any predefined expression characteristic, such a restriction to a territory of interest, thus providing a reference for comparative analyses across gnathostomes. This methodology appears best suited to species endowed with large embryo or organ sizes and opens novel perspectives to a wide range of evo-devo model organisms, traditionally counter-selected on size criterion.

Decoding the Transcriptome of Sharks, Rays, and Chimaeras: Insights into Their Physiology, Morphology, Evolution, and Biomedical Applications

“…The boom of entries occurring in 2018 is mostly related with the work by Hara et al [107] with more than 100 entries, and Swenson et al [108] which accounts for more than 50 entries. Likewise, the year of 2022 had the work published by Mayeur et al [109] that contributed solely with almost 100 entries. When researching the transcriptomes available on NCBI platform [110], using the SRA database, filtered for RNA entries and for bony fishes and cartilaginous fishes, it is clear the discrepancy between these two groups.…”

“…The development of sequencing technologies turned them cheaper and faster over time, opening the possibility of producing a tridimensional image of the RNA Profiling on zebrafish, combining techniques of RNA-Seq and computed tomography [140]. A similar methodology was used on S. canicula, on the forebrain of the embryos [109], even though the resolution was not at a cellular level, as the third-generation sequencing enables. It was possible to correctly show the expression details, such as the differences of the paralogs of Nkx, Six, and the asymmetric left/dorsal restrictors, Lefty2/Nodal/Vg1.…”

Analysis of a shark reveals ancient, Wnt dependent, habenular asymmetries in jawed vertebrates

“…Reads obtained from each one of the three left and right habenula pools were pseudo-mapped onto an annotated database of reference gene models 27 (described in Mayeur et al, manuscript in revision) and pseudo-counted using a k-mer quantification method, kallisto 28 . Contigs exhibiting statistically significant count differences between the left and right habenulae were identified using the Wald test implemented in sleuth 29 (q-value threshold 5E-02).…”

3D RNA profile of habenulae in the catsharkScyliorhinus canicula: a reference in jawed vertebrates

“…This corresponds to approximately 1.59M reads per section but a substantial heterogeneity was observed, in part due to differences in the amount of tissue in the section. For the bioinformatic analysis, reads were demultiplexed and mapped onto a gene reference obtained taking advantage of the catshark genome NCBI annotation and of transcriptomic resources available in our laboratory (Mayeur et al, 2021). This allowed the generation of transcriptomic expression profiles for any predicted gene along each section plane.…”