Spatial processes and evolutionary models: a critical review

Evolution is a fundamentally population level process in which variation, drift and selection produce both temporal and spatial patterns of change. Statistical model fitting is now commonly used to estimate which kind of evolutionary process best explains patterns of change through time using models like Brownian motion, stabilizing selection (Ornstein–Uhlenbeck) and directional selection on traits measured from stratigraphic sequences or on phylogenetic trees. But these models assume that the traits possessed by a species are homogeneous. Spatial processes such as dispersal, gene flow and geographical range changes can produce patterns of trait evolution that do not fit the expectations of standard models, even when evolution at the local‐population level is governed by drift or a typical OU model of selection. The basic properties of population level processes (variation, drift, selection and population size) are reviewed and the relationship between their spatial and temporal dynamics is discussed. Typical evolutionary models used in palaeontology incorporate the temporal component of these dynamics, but not the spatial. Range expansions and contractions introduce rate variability into drift processes, range expansion under a drift model can drive directional change in trait evolution, and spatial selection gradients can create spatial variation in traits that can produce long‐term directional trends and punctuation events depending on the balance between selection strength, gene flow, extirpation probability and model of speciation. Using computational modelling that spatial processes can create evolutionary outcomes that depart from basic population‐level notions from these standard macroevolutionary models.     

Clustering of spatial gene expression patterns in the mouse brain and comparison with classical neuroanatomy

Spatial gene expression profiles provide a novel means of exploring the structural organization of the brain. Computational analysis of these patterns is made possible by genome-scale mapping of the C57BL/6J mouse brain in the Allen Brain Atlas. Here we describe methodology used to explore the spatial structure of gene expression patterns across a set of 3041 genes chosen on the basis of consistency across experimental observations (N = 2). The analysis was performed on smoothed, co-registered 3D expression volumes for each gene obtained by aggregating cellular resolution image data. Following dimensionality and noise reduction, voxels were clustered according to similarity of expression across the gene set. We illustrate the resulting parcellations of the mouse brain for different numbers of clusters (K) and quantitatively compare these parcellations with a classically-defined anatomical reference atlas at different levels of granularity, revealing a high degree of correspondence. These observations suggest that spatial localization of gene expression offers substantial promise in connecting knowledge at the molecular level with higher-level information about brain organization.     

From diversity indices to community assembly processes: a test with simulated data

Ecological theory suggests that spatial distribution of biodiversity is strongly driven by community assembly processes. Thus the study of diversity patterns combined with null model testing has become increasingly common to infer assembly processes from observed distributions of diversity indices. However, results in both empirical and simulation studies are inconsistent. The aim of our study is to determine with simulated data which facets of biodiversity, if any, may unravel the processes driving its spatial patterns, and to provide practical considerations about the combination of diversity indices that would produce significant and congruent signals when using null models. The study is based on simulated species’ assemblages that emerge under various landscape structures in a spatially explicit individual‐based model with contrasting, predefined assembly processes. We focus on four assembly processes (species‐sorting, mass effect, neutral dynamics and competition colonization trade‐off) and investigate the emerging species’ distributions with varied diversity indices (alpha, beta and gamma) measured at different spatial scales and for different diversity facets (taxonomic, functional and phylogenetic). We find that 1) the four assembly processes result in distinct spatial distributions of species under any landscape structure, 2) a broad range of diversity indices allows distinguishing between communities driven by different assembly processes, 3) null models provide congruent results only for a small fraction of diversity indices and 4) only a combination of these diversity indices allows identifying the correct assembly processes. Our study supports the inference of assembly processes from patterns of diversity only when different types of indices are combined. It highlights the need to combine phylogenetic, functional and taxonomic diversity indices at multiple spatial scales to effectively infer underlying assembly processes from diversity patterns by illustrating how combination of different indices might help disentangling the complex question of coexistence.     

Morphology of Aulacoseira filaments as indicator of the aquatic environment in a large subtropical river: The Pearl River,China

To identify new indicators of aquatic environmental parameters, both qualitative (the percentages of curved filaments and filaments with ending separation spines) and quantitative morphological parameters (filament and cell size) of a dominant chain colony-forming planktonic diatom (Aulacoseira granulata) were determined in the large, subtropical Pearl River, China. The qualitative parameters mainly exhibited a spatial pattern. The percentage of curved filaments was a good bioindicator of spatial patterns because it varied along the nutrient gradient. Furthermore, the percentage of filaments with ending separation spines was a good bioindicator of seasonal variation. Although the quantitative parameters exhibited a clear temporal pattern, no single parameter could be used as a bioindicator of either spatial or temporal patterns. The link between qualitative and quantitative parameters reflected the internal adaptation mechanism of filamentous diatoms to the external environment. The methods of the present study can also be applied to ecological indicators in other aquatic ecosystems dominated by chain colony-forming diatoms.     

The role of astrocyte-secreted matricellular proteins in central nervous system development and function

Matricellular proteins, such as thrombospondins (TSPs1-4), SPARC, SPARC-like1 (hevin) and tenascin C are expressed by astrocytes in the central nervous system (CNS) of rodents. The spatial and temporal expression patterns of these proteins suggest that they may be involved in important developmental processes such as cell proliferation and maturation, cell migration, axonal guidance and synapse formation. In addition, upon injury to the nervous system the expression of these proteins is upregulated, suggesting that they play a role in tissue remodeling and repair in the adult CNS. The genes encoding these proteins have been disrupted in mice. Interestingly, none of these proteins are required for survival, and furthermore, there are no evident abnormalities at the gross anatomical level in the CNS. However, detailed analyses of some of these mice in the recent years have revealed interesting CNS phenotypes. Here we will review the expression of these proteins in the CNS. We will discuss a newly described function for thrombospondins in synapse formation in the CNS in detail, and speculate whether other matricellular proteins could play similar roles in nervous system development and function.     

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.     

Spatial and molecular aspects of estrogen and progesterone receptor expression in human uteri and uterine carcinomas

The expression of steroid hormone receptors as molecules reflecting processes of development and differentiation in the human uterine tissue was analysed in a spatial distinct fashion: tissue samples were excised at the fundus and at different, spatially distinct positions of the uterus. They were analysed for concentrations of cytosolic estrogen and progesterone receptors in supernatants from frozen sections using an isoelectric focusing technique. The spatial and molecular distinct, qualitative and quantitative pattern of their expression in the human uterus and uterine adenocarcinomas were studied by sectioning tissue sample from the functionalis through the basalis of the endometrium until reaching deep myometrial parts of the tissue: (1) Specific spatial patterns of estrogen and progesterone receptor levels were detectable throughout the menstrual cycle. (2) For proliferative endometrium from the functionalis to the basalis of the endometrium, the content of both cytosolic receptor species increased up to 6-fold. (3) Differences detectable were less pronounced in the myometrial part of the tissue. (4) Differences of steroid receptor concentrations measured in the endometrium at different uterine positions were highest between fundus and corpus of the endometrium. (5) Maximal differences were detectable around ovulation. (6) After secretory transformation of the organ, specific patterns were still detectable, however quantitative differences were less pronounced. (7) Additionally, quantitative differences measurable were accompanied by variations of molecular properties of the progesterone receptor as demonstrated in an isoelectric focusing gel. (8) In endometrial adenocarcinomas, not only significant quantitative alterations in steroid receptor content were measured, but also a significantly changed spatial pattern of receptor concentrations, also a change of the molecular properties of the progesterone receptor was resolved if these tumor parameters were compared to those detected in the normal tissue of the same organ surrounding the tumor.     

Reciprocal functions of the Drosophila yellow and ebony proteins in the development and evolution of pigment patterns

Body coloration affects how animals interact with the environment. In insects, the rapid evolution of black and brown melanin patterns suggests that these are adaptive traits. The developmental and molecular mechanisms that generate these pigment patterns are largely unknown. We demonstrate that the regulation and function of the yellow and ebony genes in Drosophila melanogaster play crucial roles in this process. The Yellow protein is required to produce black melanin, and is expressed in a pattern that correlates with the distribution of this pigment. Conversely, Ebony is required to suppress some melanin formation, and is expressed in cells that will produce both melanized and non-melanized cuticle. Ectopic expression of Ebony inhibits melanin formation, but increasing Yellow expression can overcome this effect. In addition, ectopic expression of Yellow is sufficient to induce melanin formation, but only in the absence of Ebony. These results suggest that the patterns and levels of Yellow and Ebony expression together determine the pattern and intensity of melanization. Based on their functions in Drosophila melanogaster, we propose that changes in the expression of Yellow and/or Ebony may have evolved with melanin patterns. Consistent with our hypothesis, we find that Yellow and Ebony are expressed in complementary spatial patterns that correlate with the formation of an evolutionary novel, male-specific pigment pattern in Drosophila biarmipes wings. These findings provide a developmental and genetic framework for understanding the evolution of melanin patterns.     

An inventory of the bacterial macromolecular components and their spatial organization

Formerly regarded as small 'bags' of nucleic acids with randomly diffusing enzymes, bacteria are organized by a sophisticated and tightly regulated molecular machinery. Here, we review qualitative and quantitative data on the intracellular organization of bacteria and provide a detailed inventory of macromolecular structures such as the divisome, the degradosome and the bacterial 'nucleolus'. We discuss how these metabolically active structures manage the spatial organization of the cell and how macromolecular crowding influences them. We present for the first time a visualization program, lifeexplorer, that can be used to study the interplay between metabolism and spatial organization of a prokaryotic cell.     

Dissecting the pleiotropic consequences of a quantitative trait nucleotide

The downstream consequences of a single quantitative trait polymorphism can provide important insight into the molecular basis of a trait. However, the molecular consequences of a polymorphism may be complex and only a subset of these may influence the trait of interest. In natural isolates of Saccharomyces cerevisiae , a nonsynonymous polymorphism in cystathione β-synthase ( CYS4 ) causes a deficiency in both cysteine and glutathione that results in rust-colored colonies and drug-dependent growth defects. Using a single-nucleotide allele replacement, we characterized the effects of this polymorphism on gene expression levels across the genome. To determine whether any of the differentially expressed genes are necessary for the production of rust-colored colonies, we screened the yeast deletion collection for genes that enhance or suppress rust coloration. We found that genes in the sulfur assimilation pathway are required for the production of rust color but not the drug-sensitivity phenotype. Our results show that a single quantitative trait polymorphism can generate a complex set of downstream changes, providing a molecular basis for pleiotropy.     

Modulatory effects of parallel fiber and molecular layer interneuron synaptic activity on purkinje cell responses to ascending segment input: a modeling study

Based on anatomical, physiological, and model-based studies, it has been proposed that synapses associated with the ascending segment of granule cell axons provide the principle excitatory drive on Purkinje cells which is then modulated by the more numerous parallel fiber synapses. In this study we have evaluated this idea using a detailed compartmental model of a cerebellar Purkinje cell by providing identical ascending segment synaptic inputs during different levels of random parallel fiber and molecular interneuron input. Results suggest that background inputs from parallel fibers and molecular layer interneurons can have a substantial effect on the response of Purkinje cells to ascending segment inputs. Interestingly, these effects are not reflected in the average firing rate of the Purkinje cell and are thus entirely dendritic in effect. These results are considered in the context of the known segregated spatial distribution of the parallel fibers and ascending segment synapses and a new hypothesis concerning the functional organization of cerebellar cortical circuitry.     

C(4) photosynthesis in terrestrial plants does not require Kranz anatomy

C(4) photosynthesis in terrestrial plants was thought to require Kranz anatomy because the cell wall between mesophyll and bundle sheath cells restricts leakage of CO(2). Recent work with the central Asian chenopods Borszczowia aralocaspica and Bienertia cycloptera show that C(4) photosynthesis functions efficiently in individual cells containing both the C(4) and C(3) cycles. These discoveries provide new inspiration for efforts to convert C(3) crops into C(4) plants because the anatomical changes required for C(4) photosynthesis might be less stringent than previously thought.     

Patterns and causes of species richness: a general simulation model for macroecology

Understanding the causes of spatial variation in species richness is a major research focus of biogeography and macroecology. Gridded environmental data and species richness maps have been used in increasingly sophisticated curve‐fitting analyses, but these methods have not brought us much closer to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non‐linearity. However, curve‐fitting approaches are problematic because most theoretical models in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species’ geographical ranges in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell of the domain. In contrast to curve‐fitting analysis, simulation modelling explicitly incorporates the processes believed to be affecting the geographical ranges of species and generates a number of quantitative predictions that can be compared to empirical patterns. We describe three of the ‘control knobs’ for a GSM that specify simple rules for dispersal, evolutionary origins and environmental gradients. Binary combinations of different knob settings correspond to eight distinct simulation models, five of which are already represented in the literature of macroecology. The output from such a GSM will include the predicted species richness per grid cell, the range size frequency distribution, the simulated phylogeny and simulated geographical ranges of the component species, all of which can be compared to empirical patterns. Challenges to the development of the GSM include the measurement of goodness of fit (GOF) between observed data and model predictions, as well as the estimation, optimization and interpretation of the model parameters. The simulation approach offers new insights into the origin and maintenance of species richness patterns, and may provide a common framework for investigating the effects of contemporary climate, evolutionary history and geometric constraints on global biodiversity gradients. With further development, the GSM has the potential to provide a conceptual bridge between macroecology and historical biogeography.     

Systematic spatial mapping of proteins at exocytic and endocytic structures

Vesicular secretion (exocytosis) involves the release and then compensatory recycling of vesicle components through endocytosis. This fundamental cellular process is controlled by the coordinated assembly and interactions of dozens of proteins at the plasma membrane. Understanding the molecular composition of individual exocytic and endocytic structures and their organization across the plasma membrane is critical to understanding the behavior and regulation of these two cellular processes. Here we develop a high-resolution and high-throughput fluorescence imaging–based approach for the unbiased mapping of 78 proteins at single exocytic vesicles and endocytic structures in neuroendocrine PC12 cells. This analysis uses two-color single-frame images to provide a systems-level map of the steady-state distributions of proteins at individual exocytic and endocytic structures in the cell. Along with this quantitative map, we find that both calcium-regulated exocytic vesicles (dense core vesicles) and endocytic structures (clathrin-coated structures) and the proteins associated with these structures exhibit a random spatial distribution in unstimulated neuroendocrine PC12 cells. This approach is broadly applicable for quantitatively mapping the molecular composition and spatial organization of discrete cellular processes with central molecular hubs.     

Three-color versus four-color multiparameter cell cycle analyses of primary acute myeloid leukemia samples

Checkpoint alterations that impact cell cycle and apoptosis responses to therapeutic treatments may produce drug resistance in acute myeloid leukemia (AML). To study these, we have developed flow cytometry assays of checkpoint function that also allow quantitation of key molecular regulators of apoptosis and cell cycle. We have used three-color (3C) assays, with FITC-labeled anti-BCL-2 and PE-labeled anti-proliferating cell nuclear antigen (PCNA) antibodies, and the DNA dye 7-aminoactinomycin, to characterize primary leukemia cells identified in DNA x side light scatter (SSC) histograms. We showed that 3C assays are accurate and reproducible in analyses of leukemia cell lines and of primary AML and normal bone marrow samples (Banker et al.: Blood 89: 243-255, 1997; Banker et al.: Leukemia Res 22: 221-239, 1998; Banker et al.: Clin Cancer Res 4: 3051-3062, 1998). To further confirm the validity of our SSC leukemia cell gating and to address whether immunophenotypic AML subsets might have different biologic properties, we have now designed four-color (4C) flow assays to characterize checkpoint status in leukemic blasts specifically identified by surface immunostaining. In modeling this assay strategy, PE/Cy5-labeled anti-CD34 antibody was used to detect blasts, with FITC-labeled anti-BCL-2, PE-labeled anti-PCNA antibodies, and Hoechst 33342 (H33342) DNA dye. Four-color CD34-gated data was concordant with 3C, SSC-gated data for leukemia cell lines and for most primary AML samples with high and intermediate blast counts. BCL-2 and PCNA immunopositivity and sub-G1 apoptosis determinations were different in the CD34-gated versus SSC-gated blasts in particular samples with smaller CD34(+) subsets, suggesting that leukemia samples can contain blast subsets with different biologic properties. On the other hand, PCNA-gated cell-cycle distributions in untreated cells and G1 versus S phase cell-cycle arrests after cytosine arabinoside treatments were completely concordant in 4C and 3C assays. We conclude that both 3C and 4C assays can be used to characterize protein expression and cell-cycle drug response patterns in leukemia blasts, but that 4C assays may additionally allow discrimination of these properties in immunophenotypic leukemia subsets.     

Kolmogorov complexity of epithelial pattern formation: The role of regulatory network configuration

The tissues of multicellular organisms are made of differentiated cells arranged in organized patterns. This organization emerges during development from the coupling of dynamic intra- and intercellular regulatory networks. This work applies the methods of information theory to understand how regulatory network structure both within and between cells relates to the complexity of spatial patterns that emerge as a consequence of network operation. A computational study was performed in which undifferentiated cells were arranged in a two dimensional lattice, with gene expression in each cell regulated by identical intracellular randomly generated Boolean networks. Cell–cell contact signalling between embryonic cells is modeled as coupling among intracellular networks so that gene expression in one cell can influence the expression of genes in adjacent cells. In this system, the initially identical cells differentiate and form patterns of different cell types. The complexity of network structure, temporal dynamics and spatial organization is quantified through the Kolmogorov-based measures of normalized compression distance and set complexity. Results over sets of random networks that operate in the ordered, critical and chaotic domains demonstrate that: (1) ordered and critical networks tend to create the most information-rich patterns; (2) signalling configurations in which cell-to-cell communication is non-directional mostly produce simple patterns irrespective of the internal network domain; and (3) directional signalling configurations, similar to those that function in planar cell polarity, produce the most complex patterns, but only when the intracellular networks function in non-chaotic domains.     

Latitudinal divergence of common frog (Rana temporaria) life history traits by natural selection: evidence from a comparison of molecular and quantitative genetic data

The relative roles of natural selection and direct environmental induction, as well as of natural selection and genetic drift, in creating clinal latitudinal variation in quantitative traits have seldom been assessed in vertebrates. To address these issues, we compared molecular and quantitative genetic differentiation between six common frog (Rana temporaria) populations along an approximately 1600 km long latitudinal gradient across Scandinavia. The degree of population differentiation (QST approximately 0.81) in three heritable quantitative traits (age and size at metamorphosis, growth rate) exceeded that in eight (neutral) microsatellite loci (FST = 0.24). Isolation by distance was clear for both neutral markers and quantitative traits, but considerably stronger for one of the three quantitative traits than for neutral markers. QST estimates obtained using animals subjected to different rearing conditions (temperature and food treatments) revealed some environmental dependency in patterns of population divergence in quantitative traits, but in general, these effects were weak in comparison to overall patterns. Pairwise comparisons of FST and QST estimates across populations and treatments revealed that the degree of quantitative trait differentiation was not generally predictable from knowledge of that in molecular markers. In fact, both positive and negative correlations were observed depending on conditions where the quantitative genetic variability had been measured. All in all, the results suggest a very high degree of genetic subdivision both in neutral marker genes and genes coding quantitative traits across a relatively recently (< 9000 years) colonized environmental gradient. In particular, they give evidence for natural selection being the primary agent behind the observed latitudinal differentiation in quantitative traits.