Borja Esteve-Altava

Background: Coincidence of Convergent Amino Acid Substitutions (CAAS) with phenotypic convergences allow pinpointing genes and even individual mutations that are likely to be associated with trait variation within their phylogenetic context. Such findings can provide useful insights into the genetic architecture of complex phenotypes. Here we introduce CAAStools, a set of bioinformatics tools to identify and validate CAAS in orthologous protein alignments for pre-defined groups of species representing the phenotypic values targeted by the user. Implementation and availability: CAAStools source code is available at http://github.com/linudz/caastools , along with documentation and examples. Supplementary information: Supplementary data are available.

The developmental underpinnings and functional consequences of modifications to the limbs during the origin of the tetrapod body plan are increasingly well characterized, but less is understood about the evolution of the tetrapod skull. Decrease in skull bone number has been hypothesized to promote morphological and functional diversification in vertebrate clades, but its impact during the initial rise of tetrapods is unknown. Here, we test this by quantifying topological changes to cranial anatomy in fossil and living taxa bracketing the fin-to-limb transition using anatomical network analysis. We find that bone loss across the origin of tetrapods is associated not only with increased complexity of bone-to-bone contacts but also with decreasing topological diversity throughout the late Paleozoic, which may be related to developmental and/or mechanical constraints. We also uncover a 10-Ma offset between fin-limb and cranial morphological evolution, suggesting that different evolutionary drivers affected these features during the origin of tetrapods.

The primate skull hosts a unique combination of anatomical features among mammals, such as a short face, wide orbits, and big braincase. Together with a trend to fuse bones in late development, these features define the anatomical organization of the skull of primates—which bones articulate to each other and the pattern this creates. Here, I quantified the anatomical organization of the skull of 17 primates and 15 non-primate mammals using anatomical network analysis to assess how the skulls of primates have diverged from those of other mammals, and whether their anatomical differences coevolved with brain size. Results show that primates have a greater anatomical integration of their skulls and a greater disparity among bones than other non-primate mammals. Brain size seems to contribute in part to this difference, but its true effect could not be conclusively proven. This supports the hypothesis that primates have a distinct anatomical organization of the skull, but whether this is related to their larger brains remains an open question.

Animal body parts evolve with variable degrees of integration that nonetheless yield functional adult phenotypes: but, how? The analysis of modularity with Anatomical Network Analysis (AnNA) is used to quantitatively determine phenotypic modules based on the physical connection among anatomical elements, an approach that is valuable to understand developmental and evolutionary constraints. We created anatomical network models of the head, forelimb, and hindlimb of two taxa considered to represent a ‘generalized’ eutherian (placental: mouse) and metatherian (marsupial: opossum) anatomical configuration and compared them with our species, which has a derived eutherian configuration. In these models, nodes represent anatomical units and links represent their physical connection. Here, we aimed to identify: (1) the commonalities and differences in modularity between species, (2) whether modules present a potential phylogenetic character, and (3) whether modules preferentially reflect either developmental or functional aspects of anatomy, or a mix of both. We predicted differences between networks of metatherian and eutherian mammals that would best be explained by functional constraints, versus by constraints of development and/or phylogeny. The topology of contacts between bones, muscles, and bones + muscles showed that, among all three species, skeletal networks were more similar than musculoskeletal networks. There was no clear indication that humans and mice are more alike when compared to the opossum overall, even though their musculoskeletal and skeletal networks of fore‐ and hindlimbs are slightly more similar. Differences were greatest among musculoskeletal networks of heads and next of forelimbs, which showed more variation than hindlimbs, supporting previous anatomical studies indicating that in general the configuration of the hindlimbs changes less across evolutionary history. Most observations regarding the anatomical networks seem to be best explained by function, but an exception is the adult opossum ear ossicles. These ear bones might form an independent module because the incus and malleus are involved in forming a functional primary jaw that enables the neonate to attach to the teat, where this newborn will complete its development. Additionally, the human data show a specialized digit 1 module (thumb/big toe) in both limb types, likely the result of functional and evolutionary pressures, as our ape ancestors had highly movable big toes and thumbs.

Mammals vary 100-fold in their maximum lifespan. This enormous variation is the result of the adaptations of each species to their own biological trade-offs and ecological conditions. Comparative genomics studies have demonstrated that the genomic factors underlying the lifespans of species and the longevity of individuals are shared across the tree of life. Here, we set out to compare protein-coding regions across the mammalian phylogeny, aiming to detect individual amino acid changes shared by the most long-lived mammal species and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 amino acid changes in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (p=0.003). The detected genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 amino acids, located in 996 different genes, showed a significant association with maximum lifespan in a phylogenetically controlled test. Interestingly, most of the detected amino acids positions do not vary in extant human populations (>81.2%) or have allele frequencies below 1% (99.78%), Consequently, almost none could have been detected by Genome-Wide Association Studies (GWAS). Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected by chance, successfully demonstrating for the first time that comparative genomics can be used to enhance the interpretation of human GWAS. Finally, we show that the human longevity-associated proteins coded by the detected genes are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan.

The study of morphological modularity using anatomical networks is growing in recent years. A common strategy to find the best network partition uses community detection algorithms that optimize the modularity Q function. Because anatomical networks and their modules tend to be small, this strategy often produces two problems. One is that some algorithms find inexplicable different modules when one inputs slightly different networks. The other is that algorithms find asymmetric modules in otherwise symmetric networks. These problems have discouraged researchers to use anatomical network analysis and boost criticisms to this methodology. Here, I propose a node-based informed modularity strategy (NIMS) to identify modules in anatomical networks that bypass resolution and sensitivity limitations by using a bottom-up approach. Starting with the local modularity around every individual node, NIMS returns the modular organization of the network by merging non-redundant modules and assessing their intersection statistically using combinatorial theory. Instead of acting as a black box, NIMS allows researchers to make informed decisions about whether to merge non-redundant modules. NIMS returns network modules that are robust to minor variation and does not require optimization of a global modularity function. NIMS may prove useful to identify modules also in small ecological and social networks.

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.

The use of anatomical networks to study the modular organization of morphological systems and their evolution is growing in recent years. A common strategy to find the best partition of anatomical networks into modules is to use a community detection algorithm that tries to optimize the modularity Q function. However, this strategy overlooks the fact that Q has a resolution limit for small modules, which is often the case in anatomical networks. This produces two problems. One is that some algorithms find inexplicable different modules when we input slightly different networks. The other is that algorithms find asymmetric modules in otherwise symmetric networks. These problems have discouraged researchers to use anatomical network analysis and boost criticisms to this methodology. Here, I propose a Node-based Informed Modularity Strategy (NIMS) to identify modules in anatomical networks that bypass resolution and sensitivity limitations by using a bottom-up approach. Starting with the local modularity around every individual node, NIMS returns the modular organization of the network by merging non-redundant modules and assessing their intersection statistically using combinatorial theory. Instead of acting as a black box, NIMS allows researcher to make informed decisions about whether to merge non-redundant modules. NIMS returns network modules that are robust to minor variation and does not require to optimize a global modularity function. NIMS may prove useful to identify modules also in small ecological and social networks.

Cranial sutures are growth and stress diffusion sites that connect the bones protecting the brain. The closure of cranial suture is a key feature of mammalian late development and evolution, which can also lead to head malformations when it occurs prematurely (craniosynostosis). To unveil the phenotypic and genetic causes of suture closure in evolution, we examined 48 mammalian species searching for (i) causal links between suture patency, brain size, and diet using phylogenetic path analysis; and (ii) instances of genome-phenome convergence amino acid substitutions. Here we show that brain size and the anteroposterior order of ossification of the skull are the two main causes of sutures patency in evolution. We also identified three novel candidate genes for suture closure in evolution (HRNR, KIAA1549 , and TTN ), which have never been reported in clinical studies of craniosynostosis. Our results suggest that different genetic pathways underlie cranial suture closure in evolution and disease.