15Eyespots on the wings of nymphalid butterflies represent colorful examples of the process of pattern 16 formation, yet the developmental origins and the mechanisms behind eyespot differentiation are still 17 not fully understood. Here we re-examine the function of Distal-less (Dll) in eyespot development, 18 which is still unclear. We show that CRISPR-Cas9 induced exon 2 mutations in Bicyclus anynana leads 19 to exon skipping and ectopic eyespots on the wing. Exon 3 mutations, however, lead to null/missense 20 transcripts, missing eyespots, lighter wing coloration, loss of scales, and a variety of other phenotypes 21 implicating Dll in the process of eyespot differentiation. Reaction-diffusion modeling enabled 22 exploration of the function of Dll in eyespot formation, and accurately replicated a wide-range of 23 mutant phenotypes. These results confirm that Dll is a required activator of eyespot development, scale 24 growth and melanization and point to a new mechanism of alternative splicing to achieve Dll over-25 expression phenotypes. 27The genetic and developmental origins of the bullseye color patterns on the wings of nymphalid 28 butterflies are still poorly understood. Eyespots originated once in ancestors of this butterfly lineage, 29 around 90 million years ago 1-3 , to most likely function as targets for deflecting predators away from 30 the butterfly's vulnerable body 1,4,5 . Eyespots may have originated via the co-option of a network of 31 pre-wired genes because several of the genes associated with eyespots gained their novel expression 32 domain concurrently with the origin of eyespots 3 . Some of these genes have since lost their expression 33 in eyespots, without affecting eyespot development, suggesting that they did not play a functional role 34 in eyespot development from the very beginning 3 . Yet, one of the genes, Distal-less (Dll), has remained 35 associated with eyespots in most nymphalid species examined so far, suggesting that it may have played 36 a functional role in eyespot origins 3,6 . 38The function of Dll in eyespot development was initially investigated in B. anynana using transgenic 39 over-expression, RNAi, and ectopic expression tools 7 . Overexpressing Dll in B. anynana led to the 40 appearance of small additional eyespots on the wing as well as larger eyespots, whereas Dll down-41 regulation produced smaller eyespots, strongly implicating Dll as an activator of eyespot development 42 7 . However, a recent study using CRISPR-Cas9 to knock-out Dll function in the painted lady butterfly, 43Vanessa cardui contradicted these findings. Zhang and Reed (2016) 8 found that using two guides to 44 disrupt exon 2 in Dll led to the appearance not only of distally extended eyespots but also of ectopic 45 eyespots developing in novel locations on the wing. These observations led to a conclusion that Dll 46 represses eyespot development. In addition, these researchers also showed that targeting the same 47 exon in another butterfly, Junonia coenia, produced darker wing pigmentation, wher...

During development, organs must form with precise shapes and sizes. Organ morphology is not always obtained through growth; a classic counterexample is condensation of the nervous system during Drosophila embryogenesis. The mechanics underlying such condensation remain poorly understood. Here, we combine in toto live-imaging, biophysical and genetic perturbations, and atomic force microscopy to characterize the condensation of the Drosophila ventral nerve cord (VNC) during embryonic development at both subcellular and tissue scales. This analysis reveals that condensation is not a unidirectional continuous process, but instead occurs through oscillatory contractions alternating from anterior and posterior ends. The VNC mechanical properties spatially and temporally vary during its condensation, and forces along its longitudinal axis are spatially heterogeneous, with larger ones exerted between neuromeres. We demonstrate that the process of VNC condensation is dependent on the coordinated mechanical activities of neurons and glia. Finally, we show that these outcomes are consistent with a viscoelastic model of condensation, which incorporates time delays due to the different time scales on which the mechanical processes act, and effective frictional interactions. In summary, we have defined the complex and progressive mechanics driving VNC condensation, providing insights into how a highly viscous tissue can autonomously change shape and size.