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Geospiza

geospiza.com

Founded Year

1997

Stage

Acquired | Acquired

Total Raised

$3.08M

About Geospiza

Geospiza is a developer of enterprise-class software systems for workflow management of genetic analysis. Geospiza aims to meet the combined laboratory, data management and analytical needs of biotechnology and pharmaceutical companies, universities, researchers, contract core and diagnostic laboratories involved in genetic testing and manufacturing bio-therapeutics.Geospiza's solutions aim to help reduce the amount of manual work required to manage and make sense of the vast amounts of genetic information being generated by clinical and life science research laboratories worldwide. Geospiza makes software for crunching the vast amounts of genetic data. When a laboratory uses Genesifter Lab Edition, the goals are that the laboratory should be able to significantly increase capacity, reduce their backlog, eliminate errors due to manual processes, and speed time to discovery. The software is being used today for clinical DNA testing and bio-therapeutic manufacturing as well as contract core lab services and basic research and discovery.

Headquarters Location

3411 Thorndyke Avenue West

Seattle, Washington, 98119,

United States

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Latest Geospiza News

Evolutionary and ontogenetic changes of the anatomical organization and modularity in the skull of archosaurs

Sep 30, 2020

Abstract Comparative anatomy studies of the skull of archosaurs provide insights on the mechanisms of evolution for the morphologically and functionally diverse species of crocodiles and birds. One of the key attributes of skull evolution is the anatomical changes associated with the physical arrangement of cranial bones. Here, we compare the changes in anatomical organization and modularity of the skull of extinct and extant archosaurs using an Anatomical Network Analysis approach. We show that the number of bones, their topological arrangement, and modular organization can discriminate birds from non-avian dinosaurs, and crurotarsans. We could also discriminate extant taxa from extinct species when adult birds were included. By comparing within the same framework, juveniles and adults for crown birds and alligator (Alligator mississippiensis), we find that adult and juvenile alligator skulls are topologically similar, whereas juvenile bird skulls have a morphological complexity and anisomerism more similar to those of non-avian dinosaurs and crurotarsans than of their own adult forms. Clade-specific ontogenetic differences in skull organization, such as extensive postnatal fusion of cranial bones in crown birds, can explain this pattern. The fact that juvenile and adult skulls in birds do share a similar anatomical integration suggests the presence of a specific constraint to their ontogenetic growth. Introduction The skulls of archosaurs are morphologically and functionally diverse, with clade-specific specialized features that set apart crurotarsans (extant crocodilians and their stem lineage) from avemetatarsalians (birds and non-avian dinosaurs) 1 , 2 , 3 , 4 , 5 , 6 , 7 , as reviewed by Brusatte et al. 8 . The evolution and diversification of the skull of archosaurs have been associated with changes in the patterns of phenotypic integration and modularity 9 , 10 , 11 , 12 , 13 . For more information on integration and modularity in shape, see the review by Klingenberg 14 . Different regions of the skull may act as anatomical modules that can evolve, function, and develop semi-independently from one another. Bones within a same module tend to co-vary in shape and size more with each other than with bones from other such variational modules 15 , 16 , 17 , 18 . In addition, the bones of the skull can also modify their physical articulations so that some groups of bones are more structurally integrated than others, and, hence, we can recognize them as distinct anatomical-network modules, which had been defined by Eble as a type of organizational modules 15 , 19 , 20 . The relationship between anatomical-network modules and variational modules is not yet fully understood, but it is thought that network anatomy constrains growth patterns and shape variation 21 , 22 , 23 . Changes in the anatomical organization of the skull in archosaurs have been concomitant with a broader evolutionary trend in tetrapods toward a reduction in the number of skull bones due to loses and fusions, a phenomenon known as the Williston’s law 24 , 25 , 26 . Understanding how the bones are globally arranged to each other allows us to measure the anatomical complexity and organization of body parts, and explain how structural constraints might have influenced the direction of evolution 25 , 26 , 27 , 28 . Werneburg et al. compared the skull network-anatomy of a highly derived Tyrannosaurus rex, Alligator mississippiensis and Gallus gallus with that of an opossum, a tuatara, and a turtle 29 . They found that the tyrannosaur has the most modular skull organization among these amniotes, with a modular separation of the snout in upper and lower sub-modules and the presence of a lower adductor chamber module. However, the specific anatomical changes in the organization of the archosaur skull during their evolutionary transitions more generally have never been characterized. More recently, Plateau and Foth used anatomical network analysis to study postnatal ontogenetic changes in the skulls of crown bird and non-avian theropods 30 . They found that early juvenile crown birds have skulls that are less integrated and more modular than those of more derived birds, resembling their non-avian theropod ancestors. Here, we compared the anatomical organization and modularity of the skull of archosaurs using Anatomical Network Analysis (AnNA) 31 to highlight how skull topology has changed in evolutionary and developmental scales. We chose AnNA over more conventional methods, such as geometric morphometrics, to understand how major re-organizations of the skull (i.e. loss and fusion of bones) affect the overall anatomy regardless of shape. We created network models of the skull for 21 species of archosaurs, including taxa representing key evolutionary transitions from early pseudosuchians to crocodiles, from non-avian theropods to modern birds, and from paleognath birds to neognaths. Our dataset also includes a representative ornithischian, a sauropodomorph, and a basal saurischian (Supplementary Information 1 ) for comparison. To understand the significance of the ontogenetic transitions in archosaur skulls, we provided our dataset with juvenile skulls for extant birds and alligator. Network models of the skull were built by coding individual cranial bones and their articulations with other bones as the nodes and links of a network, respectively (Fig. 1 ). Network modules, defined as a group of bones with more articulations among them than to other bones outside the module, were identified heuristically using a community detection algorithm. We compared skull architectures using topological variables (i.e. network parameters) that capture whole-skull anatomical feature (modelling and analysis of anatomical networks were detailed previously 20 , 25 , 31 ). Figure 1 Anatomical network models. Example of the network models for three archosaurian skulls: (A) Aetosaurus from Schoch (2007) 63 ; (B) Plateosaurus from Prieto-Marquez and Norell (2011) 107 ; (C) Gallus from Digimorph. The pair-wise articulations among the bones of skulls (left) are formalized as network models (middle) and later analyzed, for example, to identify the skull anatomical node-based modules (right). See “ Materials and methods ” for details. Networks and network modules and their respective complexity, integration, modularity, and anisomerism could be quantified by network parameters density of connections, clustering coefficient, path length, heterogeneity of connections, and parcellation 20 , 23 , 31 , 32 . Here, complexity is defined as the relationship of bones in a skull and is associated with how abundant are the interactions that bones have with each other (i.e. density of connections), how interdependent or integrated the bones are (i.e. clustering coefficient), and proximity between nodes (i.e. path length). A more complex network would have higher density, higher clustering coefficient, and shorter path length. Anisomerism is defined as a deviation among anatomical parts 33 and could be observed by the specialization of bones and measured by heterogeneity of connections, i.e. how each bone has a different number of connection 25 . Modularity is measured by parcellation, which is the number of modules and the consistency in the number of bones per module. Materials and methods Sampling We sampled extinct and extant species, and for some forms included both adults and juveniles to account for ontogenetic trends within archosaurs. Namely, adults Aetosaurus ferratus, Archaeopteryx lithographica, Citipati osmolskae, Coelophysis bauri, Compsognathus longipes, Dakosaurus andiniensis, Desmatosuchus haplocerus, Dibothrosuchus elaphros, Dilophosaurus wetherilli, Eoraptor lunensis, Ichthyornis dispar, Plateosaurus engelhardti, Psittacosaurus lujiatunensis, Riojasuchus tenuisceps, Sphenosuchus acutus, Velociraptor mongoliensis, Gallus gallus, Geospiza fortis and Nothura maculosa; and juveniles Gallus gallus, Geospiza fortis, Nothura maculosa and Alligator mississippiensis. Within our sample set, eight species represent the transition from crurotarsan archosaur ancestor to modern crocodilians and 13 species represent the transition from non-avian theropods to modern birds as described previously 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 . Due to the sample size limitation for extinct taxa, reconstructed and type forms were used to represent each taxon and intraspecific variation could not be accounted for. Phylogenetic context We created a phylogenetic tree (Fig. 2 ) based on the previous studies 34 , 35 , 36 , 37 , 39 , 40 , 41 , 42 , 43 , 44 . The tree was calibrated using the R package paleotree 45 by the conservative “equal” method 46 , 47 ; branching events were constrained using the minimum dates for known internal nodes based on fossil data from Benton and Donoghue 48 (listed in Supplementary Table S3 ) and the first and last occurrences of all 21 species from the Paleobiology Database using the paleobioDB package 49 in R. Because there were two extinct Nothura species in the Paleobiology Database, the last occurrence for extant Nothura species was adjusted to 0 (Supplementary Table S2 ). Figure 2 Phylogenetic framework. A phylogenetic tree was created based on the evolutionary relations among taxa as detailed in previous work 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 . Bifurcation times were calibrated based on fossil dates from Benton and Donoghue 48 using the equal method in the paleotree package 45 , 46 , 47 . First and last occurrences were from Paleobiology Database (details listed in Supplementary Table S2 ). Silhouettes were from Phylopic.org. See methods for details. Network modelling We built anatomical network models for each archosaur skull in our sample set based on detailed literature descriptions and CT scans of complete skulls (see Supplementary Information 1 ). Skull bones were represented as the nodes of the network model and their pair-wise articulations (e.g. sutures and synchondroses) were represented as links between pairs of nodes (Fig. 1 ). Skull network models were formalized as binary adjacency matrices, in which a 1 codes for two bones articulating and a 0 codes for absence of articulation. Bones that were fused together without trace of a suture in the specimens examined were formalized as a single individual bone. Network analysis Following Esteve-Altava et al. 28 , we quantified the following topological variables for each network model: the number of nodes (N), the number of links (K), the density of connections (D), the mean clustering coefficient (C), the mean path length (L), the heterogeneity of connections (H), the assortativity of connections (A), and the parcellation (P). The morphological interpretation of these topological variables has been detailed elsewhere 28 . A summary is provided here. N and K represent the direct count of the number of individual bones and articulations observed in the skull. D is the number of connections divided by the maximum number of possible connections (it ranges from 0 to 1); D is a proxy measure for morphological complexity. C is the average number of neighboring bones that connect to one another in a network (i.e., actual triangles of nodes compared to the maximum possible): a value close to 1 shows all neighboring bones connect to each other while a value close to 0 shows neighboring bones do not connect to each other; C is a proxy measure for anatomical integration derived from co-dependency between bones. L measures average number of links separating two nodes (it ranges from 1 to N − 1); L is a proxy measure of anatomical integration derived from the effective proximity between bones. H measures how heterogeneous connections are in a network: skulls composed of bones with a different number of articulations have higher H values. If all bones had the same number of connections (i.e., H = 0), it means that all bones were connected in the same way and the skull had a regular shape. A measures whether nodes with the same number of connections connect to each other (it ranges from − 1 to 1); H and A are a proxy measure for anisomerism or diversification of bones. P measures the number of modules and the uniformity in the number of bones they group (it ranges from 0 to 1); P is a proxy for the degree of modularity in the skull. Calculating P requires a given partition of the network into modules (see next below). Network parameters were quantified in R 50 using the igraph package 51 . Networks visualization was made using the visNetwork package 52 and Cytoscape 53 . Principal component analysis We performed a Principal Component Analysis (PCA) of the eight topological variables with a singular value decomposition of the centered and scaled measures. On the resulting PCs, we used a PERMANOVA (10,000 iterations) to test whether topological variables discriminate between: (1) Avialae and non-Avialae; (2) adults and juveniles; (3) extinct and extant; (4) Crurotarsi and Avemetatarsalia; (5) Neornithes and non-Neornithes; (6) early flight, can do soaring flight, can do flapping flight, gliding, and flightless (details in Supplementary Table S5 ); (7) Crurotarsi, non-avian Dinosauria, and Aves; and (8) carnivorous, omnivorous, and herbivorous (dietary information in Supplementary Information 4 ). First, we performed the tests listed above for all archosaurs. Then, we repeated these tests for a sub-sample that included all archosaurs, except for all modern birds. Next, we repeated these tests for a sub-sample that included all archosaurs, except for adult birds. Modularity analysis To find the optimal partition into network modules we used a node-based informed modularity strategy 54 . This method starting with the local modularity around every individual node, using cluster_spinglass function in igraph 51 , then it returns the modular organization of the network by merging non-redundant modules and assessing their intersection statistically using combinatorial theory 55 . Ethical approval All methods were carried out in accordance with relevant guidelines and regulations from Imperial College ethics committee and were approved by Imperial College. Results Topological discrimination of skull bones A Principal Component Analysis (PCA) of the eight topological variables measured in skull network models discriminates skulls with different anatomical organizations (Supplementary Figs. S1 – S3 ). When all sampled skulls are compared together, the first three principal components (PCs) explain 89.4% of the total variation of the sample. PC1 (57.5%) discriminates skulls by number of their bones (N), density of connections (D), and degree of modularity (P). PC2 (21.3%) discriminates skulls by their degree of integration (C) and anisomerism (H). Finally, PC3 (10.6%) discriminates skulls by whether bones with similar number of articulations connect with each other (A). PERMANOVA tests confirm that different skull anatomies map onto different regions of the morphospace. Thus, we can discriminate: Avialae (Aves plus Ichthyornis and Archaeopteryx) versus non-Avialae (F1,23 = 4.124, p = 0.006699; Fig. 3 B); Neornithes plus toothless archosaurs versus archosaurs with teeth (F1,23 = 6.99, p = 0.0005999; Fig. 3 C); Aves (include all modern birds) versus Crurotarsi versus non-avian Dinosauria (F2,22 = 3.837, p = 0.000699; Fig. 3 D); and extant and extinct species (F1,23 = 4.304, p = 0.0017; Supplementary Fig. S1 C). However, we find no statistically significant difference in morphospace occupation between crurotarsans and avemetatarsalians (F1,23 = 1.46, p = 0.2002, Supplementary Fig. S1 D). Figure 3 Principal components decomposition of topological variables. (A) Skull distribution for each taxon (see labels below). (B) Comparison of Avialae versus non-Avialae shows that non-Avialae occupy part of the Avialae morphospace. (C) Comparison of Neornithes versus non-Neornithes shows that non-Neornithes overlap with part of the Neornithes morphospace. Orange dotted arrows show the ontogenetic change in modern birds from juvenile stage to adult stage. (D) Comparison of Aves, Crurotarsi, and Dinosauria shows that they occupied different morphospace. Ellipses show a normal distribution confidence interval around groups for comparison. Labels: N, Number of nodes; K, Number of links; D, Density of Connection; C, Mean clustering coefficient; H, Heterogeneity of connection; L, Mean path length; A, Assortativity of connection; P, Parcellation. Aeto, Aetosaurus; AllA, adult Alligator; AllJ, juvenile Alligator; Arcx, Archaeopteryx; Citi, Citipati; Coel, Coelophysis; Comp, Compsognathus; Croc, Crocodylus; Dako, Dakosaurus; Desm, Desmatosuchus; Dibo, Dibothrosuchus; Dilo, Dilophosaurus; Eora, Eoraptor; GalA, adult Gallus; GalJ, juvenile Gallus; GeoA, adult Geospiza; GeoJ, juvenile Geospiza; Icht, Ichthyornis; NotA, adult Nothura; NotJ, juvenile Nothura; Plat, Plateosaurus; Psit, Psittacosaurus; Rioj, Riojasuchus; Sphe, Sphenosuchus; Velo, Velociraptor. Silhouettes were from Phylopic.org. The skulls of birds, crocodilians, and dinosaurs develop from ossification centres with comparable spatial locations in the embryonic head 74 . When both evolutionary and ontogenetic cranial shape variation was compared among crocodilians, Morris and colleagues showed that at mid- to late embryonic stages, cranial shapes originated from a conserved region of skull shape morphospace 92 . They suggested that crocodilian skull morphogenesis at early and late embryonic stages are controlled by signaling molecules that are important in other amniotes as well, such as Bmp4, calmodulin, Sonic hedgehog (Shh); and Indian hedgehog 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 . Then, from late prenatal stages onward, snout of crocodilians narrows 100 and elongates following different ontogenetic trajectories to give the full spectrum of crocodilian cranial diversity 92 . Another major transformation in archosaurian evolution is the origin of skulls of early and modern birds from the snouted theropods. This transition involved two significant heterochronic shifts 34 , 101 . First, avians evolved highly paedomorphic skull shapes compared to their ancestors by developmental truncation 34 . This was followed, by a peramorphic shift where primitively paired premaxillary bones fused and the resulting beak bone elongated to occupy much of the new avian face 101 . By comparison, the skull of Alligator undergoes extensive morphological change and closing of the interfrontal and interparietal sutures during embryogenesis is followed by the prolonged postnatal and maturation periods, with the lack of suture closure and even widening of some sutures 102 , 103 . Bailleul et al. suggested that mechanisms that inhibit suture closure, rather than bone resorption, cause the alligator sutures to remain open during ontogeny 103 . Nevertheless, juvenile and adult alligators share the same cranial topology featuring similar module compositions and both occupy a region of morphospace close to Crocodylus (Fig. 4 D and Supplementary Fig. S10 ; Supplementary Tables S4 and S8 ). Such topological arrangement suggests that conserved molecular, cellular, and developmental genetic processes underlie skull composition and topology observed across crocodilians. Likewise, oviraptorid dinosaurs, as represented by Citipati, display their own unique skull shape and ontogenetic transformation 34 , while retaining a topology conserved with other theropods. Combined, this evidence suggests that developmental mechanisms controlling skull composition and interaction among skull elements are conserved among theropods. The process of osteogenesis underlies the shape and topology of the bony skull. In chicken embryo, inhibition of FGF and WNT signaling pathways prevented fusion of the suture that separates the left and right premaxilla, disconnected the premaxilla-palatine articulation and changed their shapes giving the distal face a primitive snout-like appearance 101 . The site of bone fusion in experimental unfused, snout-like chicken premaxillae showed reduced expression of skeletal markers Runx2, Osteopontin, and the osteogenic marker Col I 101 , implying localized molecular mechanisms regulating suture closure and shape of individual cranial bones. Thus, changes in gene expression during craniofacial patterning in avians 95 , 96 , 98 , 104 , 105 , 106 , non-avian dinosaurs, and crocodilians 92 , 101 contribute to the clade-specific differences in skull anatomical organization resulting from the similar patterns of bone fusion of bones. Finally, we observe some network modules where some bones within the same modules in juveniles will later fuse in adult birds, but not in A. mississippiensis (Supplementary Information 5 ; Fig. 4 E and Supplementary Fig. S10 , Supplementary Table S4 ). For example, in Nothura, premaxilla, nasal, parasphenoid, pterygoid, vomer, and maxilla grouped in the same juvenile module will later fuse during formation of the upper beak in the adult. In A. mississippiensis, premaxilla, maxilla, nasal, lacrimal, prefrontal, jugal, frontal, and ectopterygoid are also in the same juvenile module, but remain separate structures in adult. These findings suggest that bones within the same module may be more likely to fuse together in ontogeny but doing so is a lineage-specific feature. Comparisons of juveniles and adults for extant birds and the alligator revealed ontogenetic changes linked to the evolution of the skull organization in archosaurs. Whereas the anatomical organization of the skull of juvenile alligators resembles that of adults, the anatomy of juvenile modern birds is closer to that of non-avian dinosaurs than to that of adult avians of the same species in terms of morphological complexity and anisomerism, probably due to the spatial arrangements of ossification centres at embryonic stages 74 , 90 , 91 . More specifically, the differences in skull organization between crown birds and non-avian dinosaurs could be explained by postnatal fusion of bones. Conclusion A network-based comparison of the cranial anatomy of archosaurs shows that differences within and among archosaurian clades are associated with an increase of anatomical complexity, a reduction in number of bones (as predicted by the Williston’s Law), and an increase of anisomerism marked by bone fusion, for both crurotarsans and avemetatarsalians. Our findings indicate that the anatomical organization of the skull is controlled by developmental mechanisms that diversified across and within each lineage: heterotopic changes in craniofacial patterning genes, heterochronic prenatal fusion of ossification centres 74 , 90 , 91 , and lineage-specific postnatal fusion of sutures. Some of these mechanisms have been shown to be conserved in other tetrapods. For example, heterotopy of craniofacial patterning genes also took place between chick and mice embryos 95 , 96 , 106 . Hu and Marcucio showed that mouse frontonasal ectodermal zone could alter the development of the avian frontonasal process, suggesting a conserved mechanism for frontonasal development in vertebrates 96 . Our findings illustrate how a comparative analysis of the anatomical organization of the skull can reveal both common and disparate patterns and processes determining skull evolution in vertebrates. Data availability References 1. Gauthier, J. Saurischian monophyly and the origin of birds. Mem. Calif. Acad. Sci. 8, 1–55 (1986). Acknowledgements We thank Jake Horton for coding the adult and juvenile matrices for Alligator mississippiensis and Crocodylus moreletii, Patrick Campbell of Natural History Museum London for providing reptile specimens, Alfie Gleeson and Digimorph for CT scans of crocodiles, and staff from Natural History Museum library for literature search. BE-A has received financial support through the Postdoctoral Junior Leader Fellowship Programme from “la Caixa” Banking Foundation (LCF/BQ/LI18/11630002) and also thanks the Unidad de Excelencia María de Maeztu funded by the AEI (CEX2018-000792-M). HWL’s Master Thesis that inspired this project was funded by Imperial College London and Natural History Museum, London. Author information Affiliations Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, Berkshire, UK Hiu Wai Lee & Arhat Abzhanov Natural History Museum, Cromwell Road, London, SW7 5BD, UK Hiu Wai Lee & Arhat Abzhanov Institute of Evolutionary Biology (UPF-CSIC), Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain Borja Esteve-Altava Supplementary information Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Geospiza Frequently Asked Questions (FAQ)

  • When was Geospiza founded?

    Geospiza was founded in 1997.

  • Where is Geospiza's headquarters?

    Geospiza's headquarters is located at 3411 Thorndyke Avenue West, Seattle.

  • What is Geospiza's latest funding round?

    Geospiza's latest funding round is Acquired.

  • How much did Geospiza raise?

    Geospiza raised a total of $3.08M.

  • Who are the investors of Geospiza?

    Investors of Geospiza include PerkinElmer, National Institutes of Health, Steve Wood, Dan Rosen, Gordon Gardiner and 3 more.

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