Predicting Phenotypic Diversity and the Underlying Quantitative Molecular Transitions

During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render ~500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus.     

Hypothesis testing in evolutionary developmental biology: a case study from insect wings

Developmental data have the potential to give novel insights into morphological evolution. Because developmental data are time-consuming to obtain, support for hypotheses often rests on data from only a few distantly related species. Similarities between these distantly related species are parsimoniously inferred to represent ancestral aspects of development. However, with limited taxon sampling, ancestral similarities in developmental patterning can be difficult to distinguish from similarities that result from convergent co-option of developmental networks, which appears to be common in developmental evolution. Using a case study from insect wings, we discuss how these competing explanations for similarity can be evaluated. Two kinds of developmental data have recently been used to support the hypothesis that insect wings evolved by modification of limb branches that were present in ancestral arthropods. This support rests on the assumption that aspects of wing development in Drosophila, including similarities to crustacean epipod patterning, are ancestral for winged insects. Testing this assumption requires comparisons of wing development in Drosophila and other winged insects. Here we review data that bear on this assumption, including new data on the functions of wingless and decapentaplegic during appendage allocation in the red flour beetle Tribolium castaneum.     

传粉网络的研究进展:网络的结构和动态

植物与传粉者之间相互作用,构成了复杂的传粉网络。近年来,社会网络分析技术的发展使得复杂生态网络的研究成为可能。从群落水平上研究植物与传粉者之间的互惠关系,为理解群落的结构和动态以及花部特征的演化提供了全新的视角。传粉网络的嵌套结构说明自然界的传粉服务存在冗余,而且是相对泛化的物种主导了传粉。在多年或者多季度的传粉网络中,虽然有很高的物种替换率,但是其网络结构仍然保持相对稳定,说明传粉网络对干扰有很强的抗性。尽管有关网络结构和动态的研究逐渐增多,但传粉网络维持的机制仍不清楚。网络结构可以部分由花部特征与传粉者的匹配来解释,也受到系统发生的制约,影响因素还包括群落构建的时间和物种多样性,以及物种在群落中的位置。开展大尺度群落动态的研究,为探索不同时间尺度、不同物种多样性水平上的传粉网络的生态学意义提供了条件。但已有的研究仍存在不足,比如基于访问观察的网络无法准确衡量传粉者的访问效率和植物间的花粉流动,以及结果受到调查精度区域研究不平衡的制约等。目前的研究只深入到传粉者携带花粉构成成分的水平,传粉者访问植物的网络不能代表植物的整个传粉过程。因此,研究应当更多地深入到物种之间关系对有性生殖的切实影响上。     

Bioclimatic transect networks: Powerful observatories of ecological change

Transects that traverse substantial climate gradients are important tools for climate change research and allow questions on the extent to which phenotypic variation associates with climate, the link between climate and species distributions, and variation in sensitivity to climate change among biomes to be addressed. However, the potential limitations of individual transect studies have recently been highlighted. Here, we argue that replicating and networking transects, along with the introduction of experimental treatments, addresses these concerns. Transect networks provide cost‐effective and robust insights into ecological and evolutionary adaptation and improve forecasting of ecosystem change. We draw on the experience and research facilitated by the Australian Transect Network to demonstrate our case, with examples, to clarify how population‐ and community‐level studies can be integrated with observations from multiple transects, manipulative experiments, genomics, and ecological modeling to gain novel insights into how species and systems respond to climate change. This integration can provide a spatiotemporal understanding of past and future climate‐induced changes, which will inform effective management actions for promoting biodiversity resilience.     

ModuleBlast: identifying activated sub-networks within and across species

Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFκB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein.     

Genome evolution in Oryza allopolyploids of various ages: Insights into the process of diploidization

The prevalence and recurrence of whole-genome duplication in plants and its major role in evolution have been well recognized. Despite great efforts, many aspects of genome evolution, particularly the temporal progression of genomic responses to allopolyploidy and the underlying mechanisms, remain poorly understood. The rice genus Oryza consists of both recently formed and older allopolyploid species, representing an attractive system for studying the genome evolution after allopolyploidy. In this study, through screening BAC libraries and sequencing and annotating the targeted BAC clones, we generated orthologous genomic sequences surrounding the DEP1 locus, a major grain yield QTL in cultivated rice, from four Oryza polyploids of various ages and their likely diploid genome donors or close relatives. Based on sequenced DEP1 region and published data from three other genomic regions, we investigated the temporal evolutionary dynamics of four polyploid genomes at both genetic and expression levels. In the recently formed BBCC polyploid, Oryza minuta, genome dominance was not observed and its short-term responses to allopolyploidy are mainly manifested as a high proportion of homoeologous gene pairs showing unequal expression. This could partly be explained by parental legacy, rewiring of divergent regulatory networks and epigenetic modulation. Moreover, we detected an ongoing diploidization process in this genus, and suggest that the expression divergence driven by changes of selective constraint probably plays a big role in the long-term diploidization. These findings add novel insights into our understanding of genome evolution after allopolyploidy, and could facilitate crop improvements through hybridization and polyploidization.     

Phylogenetic Analysis of Metabolic Pathways

The information provided by completely sequenced genomes can yield insights into the multi-level organization of organisms and their evolution. At the lowest level of molecular organization individual enzymes are formed, often through assembly of multiple polypeptides. At a higher level, sets of enzymes group into metabolic networks. Much has been learned about the relationship of species from phylogenetic trees comparing individual enzymes. In this article we extend conventional phylogenetic analysis of individual enzymes in different organisms to the organisms' metabolic networks. For this purpose we suggest a method that combines sequence information with information about the underlying reaction networks. A distance between pathways is defined as incorporating distances between substrates and distances between corresponding enzymes. The new analysis is applied to electron-transfer and amino acid biosynthesis networks yielding a more comprehensive understanding of similarities and differences between organisms. Received: 14 August 2000 / Accepted: 4 January 2001     

Synthetic genetic circuits for programmable biological functionalities

Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.     

Evolution of multiple phosphodiesterase isoforms in stickleback involved in cAMP signal transduction pathway

Background  

Duplicate genes are considered to have evolved through the partitioning of ancestral functions among duplicates (subfunctionalization) and/or the acquisition of novel functions from a beneficial mutation (neofunctionalization). Additionally, an increase in gene dosage resulting from duplication may also confer an advantageous effect, as has been suggested for histone, tRNA, and rRNA genes. Currently, there is little understanding of the effect of increased gene dosage on subcellular networks like signal transduction pathways. Addressing this issue may provide further insights into the evolution by gene duplication.     

Mechanisms of bacterial morphogenesis: Evolutionary cell biology approaches provide new insights

How Darwin's “endless forms most beautiful” have evolved remains one of the most exciting questions in biology. The significant variety of bacterial shapes is most likely due to the specific advantages they confer with respect to the diverse environments they occupy. While our understanding of the mechanisms generating relatively simple shapes has improved tremendously in the last few years, the molecular mechanisms underlying the generation of complex shapes and the evolution of shape diversity are largely unknown. The emerging field of bacterial evolutionary cell biology provides a novel strategy to answer this question in a comparative phylogenetic framework. This relatively novel approach provides hypotheses and insights into cell biological mechanisms, such as morphogenesis, and their evolution that would have been difficult to obtain by studying only model organisms. We discuss the necessary steps, challenges, and impact of integrating “evolutionary thinking” into bacterial cell biology in the genomic era.     

Natural history collections as windows on evolutionary processes

Natural history collections provide an immense record of biodiversity on Earth. These repositories have traditionally been used to address fundamental questions in biogeography, systematics and conservation. However, they also hold the potential for studying evolution directly. While some of the best direct observations of evolution have come from long‐term field studies or from experimental studies in the laboratory, natural history collections are providing new insights into evolutionary change in natural populations. By comparing phenotypic and genotypic changes in populations through time, natural history collections provide a window into evolutionary processes. Recent studies utilizing this approach have revealed some dramatic instances of phenotypic change over short timescales in response to presumably strong selective pressures. In some instances, evolutionary change can be paired with environmental change, providing a context for potential selective forces. Moreover, in a few cases, the genetic basis of phenotypic change is well understood, allowing for insight into adaptive change at multiple levels. These kinds of studies open the door to a wide range of previously intractable questions by enabling the study of evolution through time, analogous to experimental studies in the laboratory, but amenable to a diversity of species over longer timescales in natural populations.     

Delineating the longitudinal tumor evolution using organoid models

Cancer is an evolutionary process fueled by genetic or epigenetic alterations in the genome. Understanding the evolutionary dynamics that are operative at different stages of tumor progression might inform effective strategies in early detection, diagnosis, and treatment of cancer. However, our understanding on the dynamics of tumor evolution through time is very limited since it is usually impossible to sample patient tumors repeatedly. The recent advances in in vitro 3D organoid culture technologies have opened new avenues for the development of more realistic human cancer models that mimic many in vivo biological characteristics in human tumors. Here, we review recent progresses and challenges in cancer genomic evolution studies and advantages of using tumor organoids to study cancer evolution. We propose to establish an experimental evolution model based on continuous passages of patient-derived organoids and longitudinal sampling to study clonal dynamics and evolutionary patterns over time. Development and integration of population genetic theories and computational models into time-course genomic data in tumor organoids will help to pinpoint the key cellular mechanisms underlying cancer evolutionary dynamics, thus providing novel insights on therapeutic strategies for highly dynamic and heterogeneous tumors.     

New insights into bacterial adaptation through in vivo and in silico experimental evolution

Microbiology research has recently undergone major developments that have led to great progress towards obtaining an integrated view of microbial cell function. Microbial genetics, high-throughput technologies and systems biology have all provided an improved understanding of the structure and function of bacterial genomes and cellular networks. However, integrated evolutionary perspectives are needed to relate the dynamics of adaptive changes to the phenotypic and genotypic landscapes of living organisms. Here, we review evolution experiments, carried out both in vivo with microorganisms and in silico with artificial organisms, that have provided insights into bacterial adaptation and emphasize the potential of bacterial regulatory networks to evolve.     

Directed evolution of novel protein functions

Directed evolution has been successfully used to engineer proteins for basic and applied biological research. However, engineering of novel protein functions by directed evolution remains an overwhelming challenge. This challenge may come from the fact that multiple simultaneously or synergistic mutations are required for the creation of a novel protein function. Here we review the key developments in engineering of novel protein functions by using either directed evolution or a combined directed evolution and rational or computational design approach. Specific attention will be paid to a molecular evolution model for generation of novel proteins. The engineered novel proteins should not only broaden the range of applications of proteins but also provide new insights into protein structure-function relationship and protein evolution.     

Gene regulatory landscape of the sonic hedgehog locus in embryonic development

The organs of vertebrate species display a wide variety of morphology. A remaining challenge in evolutionary developmental biology is to elucidate how vertebrate lineages acquire distinct morphological features. Developmental programs are driven by spatiotemporal regulation of gene expression controlled by hundreds of thousands of cis-regulatory elements. Changes in the regulatory elements caused by the introduction of genetic variants can confer regulatory innovation that may underlie morphological novelties. Recent advances in sequencing technology have revealed a number of potential regulatory variants that can alter gene expression patterns. However, a limited number of studies demonstrate causal dependence between genetic and morphological changes. Regulation of Shh expression is a good model to understand how multiple regulatory elements organize tissue-specific gene expression patterns. This model also provides insights into how evolution of molecular traits, such as gene regulatory networks, lead to phenotypic novelty.     

Do major host shifts spark diversification in butterflies?

The Escape and Radiate Hypothesis posits that herbivorous insects and their host plants diversify through antagonistic coevolutionary adaptive radiation. For more than 50 years, it has inspired predictions about herbivorous insect macro‐evolution, but only recently have the resources begun to fall into place for rigorous testing of those predictions. Here, with comparative phylogenetic analyses of nymphalid butterflies, we test two of these predictions: that major host switches tend to increase species diversification and that such increases will be proportional to the scope of ecological opportunity afforded by a particular novel host association. We find that by and large the effect of major host‐use changes on butterfly diversity is the opposite of what was predicted; although it appears that the evolution of a few novel host associations can cause short‐term bursts of speciation, in general, major changes in host use tend to be linked to significant long‐term decreases in butterfly species richness.     

Flavonoids: a colorful model for the regulation and evolution of biochemical pathways

For more than a century, the biosynthesis of flavonoid pigments has been a favorite of scientists to study a wide variety of biological processes, such as inheritance and transposition, and has become one of the best-studied pathways in nature. The analysis of pigmentation continues to provide insights into new areas, such as the channeling and intracellular transport of metabolites, regulation of gene expression and RNA interference. Moreover, because pigmentation is studied in a variety of species, it provides unique molecular insights into the evolution of biochemical pathways and regulatory networks.     

Body size evolution in Mesozoic birds: little evidence for Cope's rule

Cope's rule, the tendency towards evolutionary increases in body size, is a long-standing macroevolutionary generalization that has the potential to provide insights into directionality in evolution; however, both the definition and identification of Cope's rule are controversial and problematic. A recent study [J. Evol. Biol. 21 (2008) 618] examined body size evolution in Mesozoic birds, and claimed to have identified evidence of Cope's rule occurring as a result of among-lineage species sorting. We here reassess the results of this study, and additionally carry out novel analyses testing for within-lineage patterns in body size evolution in Mesozoic birds. We demonstrate that the nonphylogenetic methods used by this previous study cannot distinguish between among- and within-lineage processes, and that statistical support for their results and conclusions is extremely weak. Our ancestor-descendant within-lineage analyses explicitly incorporate recent phylogenetic hypotheses and find little compelling evidence for Cope's rule. Cope's rule is not supported in Mesozoic birds by the available data, and body size evolution currently provides no insights into avian survivorship through the Cretaceous-Paleogene mass extinction.     

Dispatch. Sperm biology: size indeed matters

Sperm length is highly variable within and across species, but relatively little attention has been paid to this variation. Two recent studies employing laboratory selection experiments have provided novel insights into the evolution of sperm size.