Modelling speciation: Problems and implications.

Darwin's and Wallace's 1859 explanation that novel speciation resulted from natural variants that had been subjected to selection was refined over the next 150 years as genetic inheritance and the importance of mutation-induced change were discovered, the quantitative theory of evolutionary population genetics was produced, the speed of genetic change in small populations became apparent and the ramifications of the DNA revolution became clear. This paper first discusses the modern view of speciation in its historical context. It then uses systems-biology approaches to consider the many complex processes that underpin the production of a new species; these extend in scale from genes to populations with the processes of variation, selection and speciation being affected by factors that range from mutation to climate change. Here, events at a particular scale level (e.g. protein network activity) are activated by the output of the level immediately below (i.e. gene expression) and generate a new output that activates the layer above (e.g. embryological development), with this change often being modulated by feedback from higher and lower levels. The analysis shows that activity at each level in the evolution of a new species is marked by stochastic activity, with mutation of course being the key step for variation. The paper examines events at each of these scale levels and particularly considers how the pathway by which mutation leads to phenotypic variants and the wide range of factors that drive selection can be investigated computationally. It concludes that, such is the complexity of speciation, most steps in the process are currently difficult to model and that predictions about future speciation will, apart from a few special cases, be hard to make. The corollary is that opportunities for novel variants to form are maximised.

Tinkering and the Origins of Heritable Anatomical Variation in Vertebrates.

Evolutionary change comes from natural and other forms of selection acting on existing anatomical and physiological variants. While much is known about selection, little is known about the details of how genetic mutation leads to the range of heritable anatomical variants that are present within any population. This paper takes a systems-based view to explore how genomic mutation in vertebrate genomes works its way upwards, though changes to proteins, protein networks, and cell phenotypes to produce variants in anatomical detail. The evidence used in this approach mainly derives from analysing anatomical change in adult vertebrates and the protein networks that drive tissue formation in embryos. The former indicate which processes drive variation-these are mainly patterning, timing, and growth-and the latter their molecular basis. The paper then examines the effects of mutation and genetic drift on these processes, the nature of the resulting heritable phenotypic variation within a population, and the experimental evidence on the speed with which new variants can appear under selection. The discussion considers whether this speed is adequate to explain the observed rate of evolutionary change or whether other non-canonical, adaptive mechanisms of heritable mutation are needed. The evidence to hand suggests that they are not, for vertebrate evolution at least.

C.H. Waddington's differences with the creators of the modern evolutionary synthesis: a tale of two genes.

In 2011, Peterson suggested that the main reason why C.H. Waddington was essentially ignored by the framers of the modern evolutionary synthesis in the 1950s was because they were Cartesian reductionists and mathematical population geneticists while he was a Whiteheadian organicist and experimental geneticist who worked with Drosophila. This paper suggests a further reason that can only be seen now. The former defined genes and their alleles by their selectable phenotypes, essentially the Mendelian view, while Waddington defined a gene through its functional role as determined by genetic analysis, a view that foresaw the modern view that a gene is a DNA sequence with some function. The former were interested in selection, while Waddington focused on variation. The differences between the two views of a gene are briefly considered in the context of systems biology.

Pathbase: a database of mutant mouse pathology.

Pathbase is a database that stores images of the abnormal histology associated with spontaneous and induced mutations of both embryonic and adult mice including those produced by transgenesis, targeted mutagenesis and chemical mutagenesis. Images of normal mouse histology and strain-dependent background lesions are also available. The database and the images are publicly accessible (http://www.pathbase.net) and linked by anatomical site, gene and other identifiers to relevant databases; there are also facilities for public comment and record annotation. The database is structured around a novel ontology of mouse disorders (MPATH) and provides high-resolution downloadable images of normal and diseased tissues that are searchable through orthogonal ontologies for pathology, developmental stage, anatomy and gene attributes (GO terms), together with controlled vocabularies for type of genetic manipulation or mutation, genotype and free text annotation for mouse strain and additional attributes. The database is actively curated and data records assessed by pathologists in the Pathbase Consortium before publication. The database interface is designed to have optimal browser and platform compatibility and to interact directly with other web-based mouse genetic resources.

EMAP and EMAGE: a framework for understanding spatially organized data.

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

Pathbase: a new reference resource and database for laboratory mouse pathology.

Pathbase (http://www.pathbase.net) is a web accessible database of histopathological images of laboratory mice, developed as a resource for the coding and archiving of data derived from the analysis of mutant or genetically engineered mice and their background strains. The metadata for the images, which allows retrieval and interoperability with other databases, is derived from a series of orthogonal ontologies and controlled vocabularies. One of these controlled vocabularies, MPATH, was developed by the Pathbase Consortium as a formal description of the content of mouse histopathological images. The database currently has over 1000 images on-line with 2000 more under curation and presents a paradigm for the development of future databases dedicated to aspects of experimental biology.

The AEO, an Ontology of Anatomical Entities for Classifying Animal Tissues and Organs.

This paper describes the AEO, an ontology of anatomical entities that expands the common anatomy reference ontology (CARO) and whose major novel feature is a type hierarchy of ~160 anatomical terms. The breadth of the AEO is wider than CARO as it includes both developmental and gender-specific classes, while the granularity of the AEO terms is at a level adequate to classify simple-tissues (~70 classes) characterized by their containing a predominantly single cell-type. For convenience and to facilitate interoperability, the AEO contains an abbreviated version of the ontology of cell-types (~100 classes) that is linked to these simple-tissue types. The AEO was initially based on an analysis of a broad range of animal anatomy ontologies and then upgraded as it was used to classify the ~2500 concepts in a new version of the ontology of human developmental anatomy (www.obofoundry.org/), a process that led to significant improvements in its structure and content, albeit with a possible focus on mammalian embryos. The AEO is intended to provide the formal classification expected in contemporary ontologies as well as capturing knowledge about anatomical structures not currently included in anatomical ontologies. The AEO may thus be useful in increasing the amount of tissue and cell-type knowledge in other anatomy ontologies, facilitating annotation of tissues that share common features, and enabling interoperability across anatomy ontologies. The AEO can be downloaded from http://www.obofoundry.org/.

A bioinformatics approach for identifying candidate transcriptional regulators of mesenchyme-to-epithelium transitions in mouse embryos.

This article reports a method for identifying groups of genes associated with tissues undergoing a particular process during mouse development. Given the Theiler stage at which each tissue starts the process, Boolean intersection analysis identifies genes expressed in some or all of these tissues both before the process starts and once it has started. This analysis is implemented in GXD-search; this tool downloads appropriate gene sets from GXD, the mouse gene expression database, and performs the calculations. Applied to mesenchyme-to-epithelium transitions (MET), GXD-search has identified Crabp1 and six transcriptional regulators (Cited1, Cited2, Meox1, Lhx1, Foxc1, and Foxc2) that are usually expressed in tissues about to undergo this process. Expression pattern analysis of these transcriptional regulators, mutations in each of which affect epithelial development, shows that this gene set is expressed in no other tissues and they are, thus, candidates for regulating MET. GXD-search is downloadable from http://www.aiai.ed.ac.uk/project/biosphere/GXD-search.html.

Anatomics: the intersection of anatomy and bioinformatics.

Computational resources are now using the tissue names of the major model organisms so that tissue-associated data can be archived in and retrieved from databases on the basis of developing and adult anatomy. For this to be done, the set of tissues in that organism (its anatome) has to be organized in a way that is computer-comprehensible. Indeed, such formalization is a necessary part of what is becoming known as systems biology, in which explanations of high-level biological phenomena are not only sought in terms of lower-level events, but are articulated within a computational framework. Lists of tissue names alone, however, turn out to be inadequate for this formalization because tissue organization is essentially hierarchical and thus cannot easily be put into tables, the natural format of relational databases. The solution now adopted is to organize the anatomy of each organism as a hierarchy of tissue names and linking relationships (e.g. the tibia is PART OF the leg, the tibia IS-A bone) within what are known as ontologies. In these, a unique ID is assigned to each tissue and this can be used within, for example, gene-expression databases to link data to tissue organization, and also used to query other data sources (interoperability), while inferences about the anatomy can be made within the ontology on the basis of the relationships. There are now about 15 such anatomical ontologies, many of which are linked to organism databases; these ontologies are now publicly available at the Open Biological Ontologies website (http://obo.sourceforge.net) from where they can be freely downloaded and viewed using standard tools. This review considers how anatomy is formalized within ontologies, together with the problems that have had to be solved for this to be done. It is suggested that the appropriate term for the analysis, computer formulation and use of the anatome is anatomics.

A traction-based mechanism for somitogenesis in the chick.

This paper suggests that chick somites form because presomitic cells exert tractional forces on one another. These forces derive from the increase in cell adhesion and density that occurs as N-CAM and N-cadherin are laid down by the motile cells of the presomitic mesoderm, well before the somites form. Harris et al. (1984) have shown that adhesive and motile cells in an appropriate environment in vitro can spontaneously form aggregates under the influence of the tractional forces that they exert. Presomitic mesodermal cells may behave similarly: as CAM production increases local adhesivity, the tractional forces between the cells should become sufficiently strong for groups of cells to segment off the mesenchyme as somites. The successive expression of CAMs down the presomitic mesoderm will thus lead to the formation of an anterior-posterior sequence of somites. This mechanism can explain several aspects of somitogenesis that models generating a repetitive pre-pattern through gating cohorts of cells find hard to explain: first, mesodermal segregation occurs among highly adherent cells; second, that multiple rows of somites can form in embryos cultured on highly adherent substrata; third, that stirred mesoderm will still form normal somites; and, fourth, how somite size can be altered in heat-shocked embryos and elsewhere. Suggestions are given as to how the mechanism may be tested and where else in the embryo it could apply.

Using bioinformatics to identify kidney genes.

Online knowledge of genes involved in mouse kidney development is available from the literature (PubMed) and text-based (Kidney Development and Mouse Gene Expression-GXD) databases. Further information is in gene databases of other organisms having tissues homologous to the metanephros (e.g. Drosophila Malpighian tubules; tools are available for identifying mouse homologues of non-mouse genes) and from tissues homologous to those in the developing kidney (e.g. mesothelium that, like nephrons, arises from a mesenchyme to epithelial transition). Future databases will also include graphical data, and this knowledge will provide a further level of insight. These databases and tools are discussed here.

Growth and death in the developing mammalian kidney: signals, receptors and conversations.

Because the kidney (metanephros) starts to function before completing development, its patterning and morphogenesis need to be closely integrated with its growth. This is achieved by blast cells at the kidney periphery generating new nephrons that link up to the extending collecting-duct arborisation, while earlier-formed and more internal nephrons are maturing and beginning to filter serum. This pattern of development requires that cell division and apoptosis be co-ordinated in the various kidney compartments (collecting-ducts, blast cells, metanephric mesenchyme, nephrons and vascular system). The underlying regulatory networks for cell proliferation are beginning to be unravelled, mainly through expression studies, mutation analysis and experimentation in vitro. This article summarises current knowledge of kidney growth and apoptosis, and analyses some of the 80 or so ligand-receptor pairings that seem to sustain development and growth. It also points to some unanswered questions, the most intriguing being what role does apoptosis play during normal kidney development?

The growth and morphogenesis of the early mouse mandible: a quantitative analysis.

Three-dimensional reconstruction and BrdU incorporation have been used to quantify the development and growth of the mouse mandible and to analyse its relationship to Meckel's cartilage and the molar teeth. The mandible anlage is first histologically detectable at E13.5 as paired plates of osteoid tissue within condensed mesenchyme (approximately 0.9 mm long and approximately 0.36 mm deep) that are lateral to the two arms of Meckel's cartilage. Over the next 3 days, each plate lengthens to approximately 3.6 mm, and extends medially at its superior and inferior edges, folding over to enclose the alveolar nerve and Meckel's cartilage and producing additional processes that form the molar tooth sockets (E15.5). At around E15.5, the first molar tooth socket forms from two processes that extend from the medial and distal parts of the mandible to surround the tooth. By E16.5, this process is complete in the distal region where Meckel's cartilage is beginning to degenerate. Mandible ossification begins at E14 with proliferation restricted to the outer surface. BrdU incorporation rates are particularly high at the proximal and distal ends where lengthening occurs, and at the superior and inferior edges as they extend medially to surround Meckel's cartilage. Incorporation rates slow at the distal ends of each mandible at E16.5 as they approach each other at the symphysis. The results indicate that the mandible mainly grows at its periphery, and the pattern of mandibular growth and morphogenesis suggests that these processes are mainly directed and constrained by paracrine signalling from Meckel's cartilage and the tooth buds.

Apoptosis in the cortex of the developing mouse kidney.

Published levels of apoptosis in developing rat kidney (approximately 2.5%) seem large for a tissue with no obvious need for continual cell death. This paper examines the levels and patterns of apoptosis and mitosis in the cortical region of the developing metanephros of the mouse, the standard mammalian model embryo. Using confocal microscopy on specimens stained with propidium iodide to highlight nuclear morphology, optical sections of wholemount kidneys to a depth of approximately 50 microm were analysed and mitotic, apoptotic and interphase nuclei counted in the various compartments. Of the approximately 200 000 cells examined over E11.5-16.5, 2-3% were mitotic, confirming observations based on cryosections; the mitotic index peaked at E14.5, dropping to approximately 0.5% by P14. The mean apoptotic index during this period was 0.28%; this figure from wholemounts was approximately 10% of that earlier reported in cryosectioned rat kidneys. One possible explanation for the difference is that cryosectioning turns out to create small nuclear fragments that can stain strongly with propidium. Such fragments are not seen in wholemounts and do not stain with TUNEL. Wholemount mouse E11.5 tails and E16.5 lungs were also analysed and both their mitotic and their apoptotic indexes were similar to those in wholemount developing kidneys. These results show that the level of apoptosis in wholemount embryonic mouse kidney cortex is far less than previously reported in cryosectioned rat embryonic kidneys, and typical of that in other mouse embryonic tissues whose development seems not to require apoptosis.

An ontology of human developmental anatomy.

Human developmental anatomy has been organized as structured lists of the major constituent tissues present during each of Carnegie stages 1-20 (E1-E50, approximately 8500 anatomically defined tissue items). For each of these stages, the tissues have been organized as a hierarchy in which an individual tissue is catalogued as part of a larger tissue. Such a formal representation of knowledge is known as an ontology and this anatomical ontology can be used in databases to store, organize and search for data associated with the tissues present at each developmental stage. The anatomical data for compiling these hierarchies comes from the literature, from observations on embryos in the Patten Collection (Ann Arbor, MI, USA) and from comparisons with mouse tissues at similar stages of development. The ontology is available in three versions. The first gives hierarchies of the named tissues present at each Carnegie stage (http://www.ana.ed.ac.uk/anatomy/database/humat/) and is intended to help analyse both normal and abnormal human embryos; it carries hyperlinked notes on some ambiguities in the literature that have been clarified through analysing sectioned material. The second contains many additional subsidiary tissue domains and is intended for handling tissue-associated data (e.g. gene-expression) in a database. This version is available at the humat site and at http://genex.hgu.mrc.ac.uk/Resources/intro.html/), and has been designed to be interoperable with the ontology for mouse developmental anatomy, also available at the genex site. The third gives the second version in GO ontology syntax (with standard IDs for each tissue) and can be downloaded from both the genex and the Open Biological Ontology sites (http://obo.sourceforge.net/).

The SOFG Anatomy Entry List (SAEL): an annotation tool for functional genomics data.

A great deal of data in functional genomics studies needs to be annotated with low-resolution anatomical terms. For example, gene expression assays based on manually dissected samples (microarray, SAGE, etc.) need high-level anatomical terms to describe sample origin. First-pass annotation in high-throughput assays (e.g. large-scale in situ gene expression screens or phenotype screens) and bibliographic applications, such as selection of keywords, would also benefit from a minimum set of standard anatomical terms. Although only simple terms are required, the researcher faces serious practical problems of inconsistency and confusion, given the different aims and the range of complexity of existing anatomy ontologies. A Standards and Ontologies for Functional Genomics (SOFG) group therefore initiated discussions between several of the major anatomical ontologies for higher vertebrates. As we report here, one result of these discussions is a simple, accessible, controlled vocabulary of gross anatomical terms, the SOFG Anatomy Entry List (SAEL). The SAEL is available from http://www.sofg.org and is intended as a resource for biologists, curators, bioinformaticians and developers of software supporting functional genomics. It can be used directly for annotation in the contexts described above. Importantly, each term is linked to the corresponding term in each of the major anatomy ontologies. Where the simple list does not provide enough detail or sophistication, therefore, the researcher can use the SAEL to choose the appropriate ontology and move directly to the relevant term as an entry point. The SAEL links will also be used to support computational access to the respective ontologies.