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Gene duplication is an important process of molecular evolutionary change, though identifying these events and their functional implications remains challenging. Studies on gene duplication more often focus on the presence of paralogous genes within the genomes and less frequently explore shifts in expression. We investigated the evolutionary history of calsequestrin (CASQ), a crucial calcium-binding protein in the junctional sarcoplasmic reticulum of muscle tissues. CASQ exists in jawed vertebrates as subfunctionalized paralogs CASQ1 and CASQ2 expressed primarily in skeletal and cardiac muscles, respectively. We used an enhanced sequence dataset to support initial duplication of CASQl in a jawed fish ancestor prior to the divergence of cartilaginous fishes. Surprisingly, we find CASQ2 is the predominant skeletal muscle paralog in birds, while CASQ1 is either absent or effectively nonfunctional. Changes in the amino acid composition and electronegativity of avian CASQ2 suggest enhancement to calcium-binding properties that preceded the loss of CASQ1. We identify this phenomenon as CASQ2 “synfunctionalization,” where one paralog functionally replaces another. While additional studies are needed to fully understand the dynamics of CASQ1 and CASQ2 in bird muscles, the long and consistent history of CASQ subfunctions outside of birds indicate a substantial evolutionary pressure on calcium-cycling processes in muscle tissues, likely connected to increased avian cardiovascular and metabolic demands. Our study provides an important insight into the molecular evolution of birds and shows how gene expression patterns can be comparatively studied across phylum-scale deep time to reveal key evolutionary events 

Abstract Uncrewed aerial vehicles are integral to a smart city framework, but the dynamic environments above and within urban settings are dangerous for autonomous flight. Wind gusts caused by the uneven landscape jeopardize safe and effective aircraft operation. Birds rapidly reject gusts by changing their wing shape, but current gust alleviation methods for aircraft still use discrete control surfaces. Additionally, modern gust alleviation controllers challenge small uncrewed aerial vehicle power constraints by relying on extensive sensing networks and computationally expensive modeling. Here we show end-to-end deep reinforcement learning forgoing state inference to efficiently alleviate gusts on a smart material camber-morphing wing. In a series of wind tunnel gust experiments at the University of Michigan, trained controllers reduced gust impact by 84% from on-board pressure signals. Notably, gust alleviation using signals from only three pressure taps was statistically indistinguishable from using six pressure tap signals. By efficiently rejecting environmental perturbations, reduced-sensor fly-by-feel controllers open the door to small uncrewed aerial vehicle missions in cities. 

Birds perform astounding aerial maneuvers by actuating their shoulder, elbow, and wrist joints to morph their wing shape. This maneuverability is desirable for similar-sized uncrewed aerial vehicles (UAVs) and can be analyzed through the lens of dynamic flight stability. Quantifying avian dynamic stability is challenging as it is dictated by aerodynamics and inertia, which must both account for birds’ complex and variable morphology. To date, avian dynamic stability across flight conditions remains largely unknown. Here, we fill this gap by quantifying how a gull can use wing morphing to adjust its longitudinal dynamic response. We found that it was necessary to adjust the shoulder angle to achieve trimmed flight and that most trimmed configurations were longitudinally stable except for configurations with high wrist angles. Our results showed that as flight speed increases, the gull could fold or sweep its wings backward to trim. Further, a trimmed gull can use its wing joints to control the frequencies and damping ratios of the longitudinal oscillatory modes. We found a more damped phugoid mode than similar-sized UAVs, possibly reducing speed sensitivity to perturbations, such as gusts. Although most configurations had controllable short-period flying qualities, the heavily damped phugoid mode indicates a sluggish response to control inputs, which may be overcome while maneuvering by morphing into an unstable flight configuration. Our study shows that gulls use their shoulder, wrist, and elbow joints to negotiate trade-offs in stability and control and points the way forward for designing UAVs with avian-like maneuverability. 

Gliding birds perform feats that challenge even our most advanced similar-sized unmanned aerial vehicles (UAV). Their ostensible skill supports a pervasive belief that birds are highly efficient gliders that outperform modern UAVs. which led us to ask: are gliding birds truly more efficient than UAVs? Avian flight efficiency a well-studied topic and often cited as the inspiration for novel UAV designs. Despite the multitude of studies that have quantified the aerodynamic efficiency of gliding birds, there is no comprehensive summary of their findings. This is problematic because differing methodologies have inconsistent levels of uncertainty. As such, the lack of consolidated information on gliding bird efficiency inhibits a true comparison to UAVs. To fill this gap, we surveyed published theoretical and experimental estimates of avian aerodynamic efficiency and investigated the uncertainty of each method. We found that there was substantial variation in the aerodynamic efficiency predicted by different methods, which can lead to disparate conclusions on gliding bird efficiency. Our survey showed that measurements on live birds gliding in wind tunnels provide a reliable minimum estimate on a birds’ aerodynamic efficiency and allows the quantification of the wing configurations used in flight. Next, we surveyed the aeronautical literature to collect all published aerodynamic efficiencies of similar-sized, non-copter UAVs. The consolidated information allowed a direct comparison of modern UAVs and gliding birds. Contrary to our expectation, we found that there is no definitive evidence that any gliding bird species is either more or less efficient than a similar-sized UAV. This non-result highlights a critical need for new technology and analytical advances that can reduce the uncertainty associated with estimating a gliding bird’s aerodynamic efficiency. Nevertheless, our survey indicated that UAV designs informed by species flying within subcritical regimes may extend their operational range into lower Reynolds number regimes.