A Conserved Supergene Locus Controls Colour Pattern Diversity in Heliconius Butterflies

We studied whether similar developmental genetic mechanisms are involved in both convergent and divergent evolution. Mimetic insects are known for their diversity of patterns as well as their remarkable evolutionary convergence, and they have played an important role in controversies over the respective roles of selection and constraints in adaptive evolution. Here we contrast three butterfly species, all classic examples of Müllerian mimicry. We used a genetic linkage map to show that a locus, Yb, which controls the presence of a yellow band in geographic races of Heliconius melpomene, maps precisely to the same location as the locus Cr, which has very similar phenotypic effects in its co-mimic H. erato. Furthermore, the same genomic location acts as a “supergene”, determining multiple sympatric morphs in a third species, H. numata. H. numata is a species with a very different phenotypic appearance, whose many forms mimic different unrelated ithomiine butterflies in the genus Melinaea. Other unlinked colour pattern loci map to a homologous linkage group in the co-mimics H. melpomene and H. erato, but they are not involved in mimetic polymorphism in H. numata. Hence, a single region from the multilocus colour pattern architecture of H. melpomene and H. erato appears to have gained control of the entire wing-pattern variability in H. numata, presumably as a result of selection for mimetic “supergene” polymorphism without intermediates. Although we cannot at this stage confirm the homology of the loci segregating in the three species, our results imply that a conserved yet relatively unconstrained mechanism underlying pattern switching can affect mimicry in radically different ways. We also show that adaptive evolution, both convergent and diversifying, can occur by the repeated involvement of the same genomic regions

Implementing an urban public health observatory for (near) real-time surveillance for the COVID-19 pandemic

The COVID-19 pandemic is broadly undercutting global health and economies, while disproportionally impacting socially disadvantaged populations. An impactful pandemic surveillance solution must draw from multi-dimensional integration of social determinants of health (SDoH) to contextually inform traditional epidemiological factors. In this article, we describe an Urban Public Health Observatory (UPHO) model which we have put into action in a mid-sized U.S. metropolitan region to provide near real-time analysis and dashboarding of ongoing COVID-19 conditions. Our goal is to illuminate associations between SDoH factors and downstream pandemic health outcomes to inform specific policy decisions and public health planning