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Haines, Grant; Stuart, Yoel; Hanson, Dieta; Tasneem, Tania; Bolnick, Daniel; Larsson, Hans; Hendry, Andrew 2021-09-04 Recent methodological advances have led to a rapid expansion of evolutionary studies employing three-dimensional landmark-based geometric morphometrics (GM). GM methods generally enable researchers to capture and compare complex shape phenotypes, and to quantify their relationship to environmental gradients. However, some recent studies have shown that the common, inexpensive, and relatively rapid two-dimensional GM methods can distort important information and produce misleading results because they cannot capture variation in the depth (Z) dimension. We use micro-CT scanned threespine stickleback (Gasterosteus aculeatus Linnaeus, 1758) from six parapatric lake-stream populations on Vancouver Island, British Columbia, to test whether the loss of the depth dimension in 2D GM studies results in misleading interpretations of parallel evolution. Using joint locations described with 2D or 3D landmarks, we compare results from separate 2D and 3D shape spaces, from a combined 2D-3D shape space, and from estimates of biomechanical function. We show that, although shape is distorted enough in 2D projections to strongly influence the interpretation of morphological parallelism, estimates of biomechanical function are relatively robust to the loss of the Z dimension. https://creativecommons.org/publicdomain/zero/1.0/
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Kuzmin, Elena; VanderSluis, Benjamin; Wang, Wen; Tan, Guihong; Deshpande, Raamesh; Chen, Yiqun; Usaj, Matej; Balint, Attila; Mattiazzi Usaj, Mojca; van Leeuwen, Jolanda; Koch, Elizabeth N.; Pons, Carles; Dagilis, Andrius Jonas; Pryszlak, Michael; Wang, Jason Zi Yang; Hanchard, Julia; Riggi, Margot; Xu, Kaicong; Heydari, Hamed; San Luis, Bryan-Joseph; Shuteriqi, Ermira; Zhu, Hongwei; Van Dyk, Nydia; Sharifpoor, Sara; Costanzo, Michael; Loewith, Robbie; Caudy, Amy; Bolnick, Daniel; Brown, Grant W.; Andrews, Brenda J.; Boone, Charles; Myers, Chad L. 2019-03-30 To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.

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