Coleoid cephalopods, including squid, cuttlefish and octopus, have large and complex nervous systems and camera-type eyes that are comparable only to features that have independently evolved in the vertebrate lineage. The changes in development that result in the evolution of nervous system size and diversity of neural cell-types are not well understood. Here, we have pioneered live-imaging techniques and performed functional interrogation to show the squid, Doryteuthis pealeii, utilizes mechanisms during retinal neurogenesis that are hallmarks of vertebrate processes. Given the convergent evolution of elaborate visual systems in cephalopods and vertebrates, these results reveal common mechanisms that underlie the growth of highly proliferative neurogenic primordia that may alter ontogenetic allometry and contribute to the evolution of complex nervous systems.

Genes were first identified by using annotated sequences from model organisms from major lineages for BLAST (Altschul et al., 1990) into a custom local database of the D. pealeii transcriptome in Geneious. For top hits the entire sequence in the D. pealeii transcriptome was retrieved, the longest ORF was extracted and translated, then the amino acid sequence was trimmed for coding sequence. To find related sequences, BLASTp was used, searching both the Uniprot database in NCBI and retrieving only select vertebrate and D. melanogaster hits. BLASTp was performed again using the non-redundant protein database, and searching specifically for cephalopods, select mollusks, and Limulus. Trees that were not well resolved after these steps required an additional round of BLASTp, this time including more spiralian and ecdysozoan hits. Full sequences (or as long as is available) were aligned with our D. pealeii sequences for each tree using MAFFT v.7.450 in Geneious (Katoh, 2013). The only exception was our Sox tree where we used the alignment from (Schnitzler et al., 2014), which only included the HMG box of Sox proteins. This alignment focused on early metazoan species, so we added select vertebrates, mollusks, and ecdysozoans as described above, but trimmed sequences to include the HMG box for all. For all alignments we checked sequence redundancy and proper outgroups Fast Trees were made using FastTree2 v.2.1.11 (Price et al., 2010). We constructed maximum-likelihood trees on the FASRC Cannon cluster supported by the FAS Division of Science Research Computing Groat Harvard University. We exported relaxed Phylip formatted alignment files and used IQ-TREE 2 v.2.1.0 with the following settings: iqtree2 -s ALIGNMENT.phy -st AA -nt AUTO -v -m TEST -bb 1000 -alrt 1000 (Minh et al., 2020). Unrooted trees were visualized as rooted by known outgroups and labeled by known annotated orthologues.

Supplemental Data Files

MAFT Multiple Sequence Alignments:

Delta_jagged.phy

EGFR_EphR.phy

ELAV.phy

Fringe.phy

HES.phy

NeuroD_G.phy

RAR.phy

Retinochrome.phy

Sox.phy

VEGFR.phy

IQ Phylogenetic Trees:

211019_Retinochrome.phy.treefile

211020_Delta_jagged.phy.treefile

211027_Fringe.phy.treefile

211027_VEFGR.phy.treefile

211105_EGFR_EphR.phy.treefile

211105_ELAV.phy.treefile

211105_HES.phy.treefile

211105_NeuroD_G.phy.treefile

211112_RAR.phy.treefile

211112_Sox.phy.treefile