Introducing Trait Networks to Elucidate the Fluidity of Organismal Evolution Using Palaeontological Data.
Ontology highlight
ABSTRACT:
SUBMITTER: Lord E
PROVIDER: S-EPMC6761957 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Integrating -omics data with biological networks such as protein-protein interaction networks is a popular and useful approach to interpret expression changes of genes in changing conditions, and to identify relevant cellular pathways, active subnetworks or network communities. Yet, most -omics data integration tools are restricted to static networks and therefore cannot easily be used for analyzing time-series data. Determining regulations or exploring the network structure over time requires time-dependent networks which incorporate time as one component in their structure. Here, we present a method to project time-series data on sequential layers of a multilayer network, thus creating a temporal multilayer network (tMLN). We implemented this method as a Cytoscape app we named TimeNexus. TimeNexus allows to easily create, manage and visualize temporal multilayer networks starting from a combination of node and edge tables carrying the information on the temporal network structure. To allow further analysis of the tMLN, TimeNexus creates and passes on regular Cytoscape networks in form of static versions of the tMLN in three different ways: (i) over the entire set of layers, (ii) over two consecutive layers at a time, (iii) or on one single layer at a time. We combined TimeNexus with the Cytoscape apps PathLinker and AnatApp/ANAT to extract active subnetworks from tMLNs. To test the usability of our app, we applied TimeNexus together with PathLinker or ANAT on temporal expression data of the yeast cell cycle and were able to identify active subnetworks relevant for different cell cycle phases. We furthermore used TimeNexus on our own temporal expression data from a mouse pain assay inducing hindpaw inflammation and detected active subnetworks relevant for an inflammatory response to injury, including immune response, cell stress response and regulation of apoptosis. TimeNexus is freely available from the Cytoscape app store at https://apps.cytoscape.org/apps/TimeNexus .
| S-EPMC8249521 | biostudies-literature
Project description:Non-uniform rates of morphological evolution and evolutionary increases in organismal complexity, captured in metaphors like "adaptive zones", "punctuated equilibrium" and "blunderbuss patterns", require more elaborate explanations than a simple gradual accumulation of mutations. Here we argue that non-uniform evolutionary increases in phenotypic complexity can be caused by a threshold-like response to growing ecological pressures resulting from evolutionary diversification at a given level of complexity. Acquisition of a new phenotypic feature allows an evolving species to escape this pressure but can typically be expected to carry significant physiological costs. Therefore, the ecological pressure should exceed a certain level to make such an acquisition evolutionarily successful. We present a detailed quantitative description of this process using a microevolutionary competition model as an example. The model exhibits sequential increases in phenotypic complexity driven by diversification at existing levels of complexity and a resulting increase in competitive pressure, which can push an evolving species over the barrier of physiological costs of new phenotypic features.
| S-EPMC6793884 | biostudies-literature
Project description:The position of the earliest-derived living molluscs, the Polyplacophora (chitons) and shell-less vermiform Aplacophora, remains highly contentious despite many morphological, developmental and molecular studies of extant organisms. These two groups are thought to represent either a basal molluscan grade or a clade (Aculifera) sister to the 'higher' molluscs (Conchifera). These incompatible hypotheses result in very different predictions about the earliest molluscs. A new cladistic analysis incorporating both Palaeozoic and extant molluscs is presented here. Our results support the monophyly of Aculifera and suggest that extant aplacophorans and polyplacophorans both derive from a disparate group of multivalved molluscs in two major clades. Reanalysis of the critical Ordovician taxon 'Helminthochiton' thraivensis shows that this animal lacks a true foot despite bearing polyplacophoran-like valves. Its position within our phylogenetic reconstruction indicates that many fossil 'polyplacophorans' in the order Palaeoloricata are likely to represent footless stem-group aplacophorans. 'H.' thraivensis and similar forms such as Acaenoplax may be morphological stepping stones between chitons and the shell-less aplacophorans. Our results imply that crown-group molluscan synapomorphies include serial repetition, the presence of a foot, a mineralized scleritome and a creeping rather than worm-like mode of life.
| S-EPMC2274978 | biostudies-literature
Project description:Among the different providers of health care big data in Korea, the data provided by the National Health Insurance Database include the medical information of all the citizens who have subscribed to medical insurance. As such, the data have representativeness and completeness. In order to conduct research using these National Health Insurance Database data, it is necessary to understand the characteristics of the claim data to avoid various biases, and to control confounding variables when making various operational definitions in the planning stage of the research. Moreover, without a proper understanding of the big data, it is possible during the analysis and data interpretation to mistakenly interpret the correlation between variables as a causal relationship. Therefore, in order to help advanced medical science, which reflects the medical reality such as medical expenses and number of hospital visits by clearly recognizing and analyzing the characteristics and limitations of health care big data, this author has dealt with the use of data sharing services provided by the National Health Insurance Database.
| S-EPMC7280883 | biostudies-literature
Project description:Motivation: A central goal of current biology is to establish a complete functional link between the genotype and phenotype, known as the so-called genotype-phenotype map. With the continuous development of high-throughput technology and the decline in sequencing costs, multi-omics analysis has become more widely employed. While this gives us new opportunities to uncover the correlation mechanisms between single-nucleotide polymorphism (SNP), genes, and phenotypes, multi-omics still faces certain challenges, specifically: 1) When the sample size is large enough, the number of omics types is often not large enough to meet the requirements of multi-omics analysis; 2) each omics' internal correlations are often unclear, such as the correlation between genes in genomics; 3) when analyzing a large number of traits (p), the sample size (n) is often smaller than p, n << p, hindering the application of machine learning methods in the classification of disease outcomes. Results: To solve these issues with multi-omics and build a robust classification model, we propose a graph-embedded deep neural network (G-EDNN) based on expression quantitative trait loci (eQTL) data, which achieves sparse connectivity between network layers to prevent overfitting. The correlation within each omics is also considered such that the model more closely resembles biological reality. To verify the capabilities of this method, we conducted experimental analysis using the GSE28127 and GSE95496 data sets from the Gene Expression Omnibus (GEO) database, tested various neural network architectures, and used prior data for feature selection and graph embedding. Results show that the proposed method could achieve a high classification accuracy and easy-to-interpret feature selection. This method represents an extended application of genotype-phenotype association analysis in deep learning networks.
| S-EPMC9421127 | biostudies-literature
Project description:The intervertebral disc (IVD) has long been considered unique to mammals. Palaeohistological sampling of 17 mostly extinct clades across the amniote tree revealed preservation of different intervertebral soft tissue types (cartilage, probable notochord) seen in extant reptiles. The distribution of the fossilised tissues allowed us to infer the soft part anatomy of the joint. Surprisingly, we also found evidence for an IVD in fossil reptiles, including non-avian dinosaurs, ichthyosaurs, plesiosaurs, and marine crocodiles. Based on the fossil dataset, we traced the evolution of the amniote intervertebral joint through ancestral character state reconstruction. The IVD evolved at least twice, in mammals and in extinct diapsid reptiles. From this reptilian IVD, extant reptile groups and some non-avian dinosaurs independently evolved a synovial ball-and-socket joint. The unique birds dorsal intervertebral joint evolved from this dinosaur joint. The tuatara and some geckos reverted to the ancestral persisting notochord.
| S-EPMC7445751 | biostudies-literature
Project description:There is a growing awareness that traits do not evolve individually but rather are organized as modular networks of covarying traits. Although the importance of multi-trait correlation has been linked to the ability to evolve in response to new environmental conditions, the evolvability of the network itself has to date rarely been assessed experimentally. By following the evolutionary dynamics of a model bacterium adapting to plant roots, we demonstrate that the whole structure of the trait correlation network is highly dynamic. We experimentally evolved Pseudomonas protegens, a common rhizosphere dweller, on the roots of Arabidopsis thaliana. We collected bacteria at regular intervals and determined a range of traits linked to growth, stress resistance, and biotic interactions. We observed a rapid disintegration of the original trait correlation network. Ancestral populations showed a modular network, with the traits linked to resource use and stress resistance forming two largely independent modules. This network rapidly was restructured during adaptation, with a loss of the stress resistance module and the appearance of new modules out of previously disconnected traits. These results show that evolutionary dynamics can involve a deep restructuring of phenotypic trait organization, pointing to the emergence of novel life history strategies not represented in the ancestral phenotype.
| S-EPMC8252368 | biostudies-literature
Project description:SYNOPSIS:Standards-based data management facilitates data preservation, discoverability, and access for effective data reuse within research groups and across communities of researchers. Data sharing requires community consensus on standards for data management, such as storage and formats for digital data preservation, metadata (i.e., contextual data about the data) that should be recorded and stored, and data access. Video imaging is a valuable tool for measuring time-varying phenotypes in organismal biology, with particular application for research in functional morphology, comparative biomechanics, and animal behavior. The raw data are the videos, but videos alone are not sufficient for scientific analysis. Nearly endless videos of animals can be found on YouTube and elsewhere on the web, but these videos have little value for scientific analysis because essential metadata such as true frame rate, spatial calibration, genus and species, weight, age, etc. of organisms, are generally unknown. We have embarked on a project to build community consensus on video data management and metadata standards for organismal biology research. We collected input from colleagues at early stages, organized an open workshop, "Establishing Standards for Video Data Management," at the Society for Integrative and Comparative Biology meeting in January 2017, and then collected two more rounds of input on revised versions of the standards. The result we present here is a rubric consisting of nine standards for video data management, with three levels within each standard: good, better, and best practices. The nine standards are: (1) data storage; (2) video file formats; (3) metadata linkage; (4) video data and metadata access; (5) contact information and acceptable use; (6) camera settings; (7) organism(s); (8) recording conditions; and (9) subject matter/topic. The first four standards address data preservation and interoperability for sharing, whereas standards 5-9 establish minimum metadata standards for organismal biology video, and suggest additional metadata that may be useful for some studies. This rubric was developed with substantial input from researchers and students, but still should be viewed as a living document that should be further refined and updated as technology and research practices change. The audience for these standards includes researchers, journals, and granting agencies, and also the developers and curators of databases that may contribute to video data sharing efforts. We offer this project as an example of building community consensus for data management, preservation, and sharing standards, which may be useful for future efforts by the organismal biology research community.
| S-EPMC5886321 | biostudies-literature
Project description:Adaptive laboratory evolution is highly effective for improving desired traits through natural selection. However, its applicability is inherently constrained to growth-correlated traits precluding traits of interest that incur a fitness cost, such as metabolite secretion. Here, we introduce the concept of tacking trait enabling natural selection of fitness-costly metabolic traits. The concept is inspired from the tacking maneuver used in sailing for traversing upwind. We use first-principle metabolic models to design an evolution niche wherein the tacking trait and fitness become correlated. Adaptive evolution in this niche, when followed by the reversal to the original niche, manifests in the improvement of the desired trait due to biochemical coupling between the tacking and the desired trait. We experimentally demonstrate this strategy, termed EvolveX, by evolving wine yeasts for increased aroma production. Our results pave the way for precision laboratory evolution for biotechnological and ecological applications.
2022-07-12 | PXD023171 | Pride
Project description:Mutualisms may be "key innovations" that spur lineage diversification by augmenting niche breadth, geographic range, or population size, thereby increasing speciation rates or decreasing extinction rates. Whether mutualism accelerates diversification in both interacting lineages is an open question. Research suggests that plants that attract ant mutualists have higher diversification rates than non-ant associated lineages. We ask whether the reciprocal is true: does the interaction between ants and plants also accelerate diversification in ants, i.e. do ants and plants cooperate-and-radiate? We used a novel text-mining approach to determine which ant species associate with plants in defensive or seed dispersal mutualisms. We investigated patterns of lineage diversification across a recent ant phylogeny using BiSSE, BAMM, and HiSSE models. Ants that associate mutualistically with plants had elevated diversification rates compared to non-mutualistic ants in the BiSSE model, with a similar trend in BAMM, suggesting ants and plants cooperate-and-radiate. However, the best-fitting model was a HiSSE model with a hidden state, meaning that diversification models that do not account for unmeasured traits are inappropriate to assess the relationship between mutualism and ant diversification. Against a backdrop of diversification rate heterogeneity, the best-fitting HiSSE model found that mutualism actually decreases diversification: mutualism evolved much more frequently in rapidly diversifying ant lineages, but then subsequently slowed diversification. Thus, it appears that ant lineages first radiated, then cooperated with plants.
| S-EPMC6776258 | biostudies-literature