The origin of subfunctions and modular gene regulation

Expression of defensin genes across house fly (Musca domestica) life history gives insight into immune system subfunctionalization

Animals encounter diverse microbial communities throughout their lifetime, which exert varying selection pressures. Antimicrobial peptides (AMPs), which lyse or inhibit microbial growth, are a first line of defense against some of these microbes. Here we examine how developmental variation in microbial exposure has affected the evolution of expression and amino acid sequences of Defensins (an ancient class of AMPs) in the house fly (Musca domestica). The house fly is a well-suited model for this work because it trophically associates with varying microbial communities throughout its life history and its genome contains expanded families of AMPs, including Defensins. We identified two subsets of house fly Defensins: one expressed in larvae or pupae, and the other expressed in adults. The amino acid sequences of these two Defensin subsets form distinct monophyletic clades, and they are located in separate gene clusters in the genome. The adult-expressed Defensins evolve faster than larval/pupal Defensins, consistent with different selection pressures across developmental stages. Our results therefore suggest that varied microbial communities encountered across life history can shape the evolutionary trajectories of immune genes.

Genome organization and botanical diversity

The rich diversity of angiosperms, both the planet's dominant flora and the cornerstone of agriculture, is integrally intertwined with a distinctive evolutionary history. Here, we explore the interplay between angiosperm genome organization and botanical diversity, empowered by genomic approaches ranging from genetic linkage mapping to analysis of gene regulation. Commonality in the genetic hardware of plants has enabled robust comparative genomics that has provided a broad picture of angiosperm evolution and implicated both general processes and specific elements in contributing to botanical diversity. We argue that the hardware of plant genomes-both in content and in dynamics-has been shaped by selection for rather substantial differences in gene regulation between plants and animals such as maize and human, organisms of comparable genome size and gene number. Their distinctive genome content and dynamics may reflect in part the indeterminate development of plants that puts strikingly different demands on gene regulation than in animals. Repeated polyploidization of plant genomes and multiplication of individual genes together with extensive rearrangement and differential retention provide rich raw material for selection of morphological and/or physiological variations conferring fitness in specific niches, whether natural or artificial. These findings exemplify the burgeoning information available to employ in increasing knowledge of plant biology and in modifying selected plants to better meet human needs.

The ensemble of gene regulatory networks at mutation-selection balance

The evolution of diverse phenotypes both involves and is constrained by molecular interaction networks. When these networks influence patterns of expression, we refer to them as gene regulatory networks (GRNs). Here, we develop a model of GRN evolution analogous to work from quasi-species theory, which is itself essentially the mutation-selection balance model from classical population genetics extended to multiple loci. With this GRN model, we prove that-across a broad spectrum of selection pressures-the dynamics converge to a stationary distribution over GRNs. Next, we show from first principles how the frequency of GRNs at equilibrium is related to the topology of the genotype network, in particular, via a specific network centrality measure termed the eigenvector centrality. Finally, we determine the structural characteristics of GRNs that are favoured in response to a range of selective environments and mutational constraints. Our work connects GRN evolution to quasi-species theory-and thus to classical populations genetics-providing a mechanistic explanation for the observed distribution of GRNs evolving in response to various evolutionary forces, and shows how complex fitness landscapes can emerge from simple evolutionary rules.

A synthetic synthesis to explore animal evolution and development

Identifying the general principles by which genotypes are converted into phenotypes remains a challenge in the post-genomic era. We still lack a predictive understanding of how genes shape interactions among cells and tissues in response to signalling and environmental cues, and hence how regulatory networks generate the phenotypic variation required for adaptive evolution. Here, we discuss how techniques borrowed from synthetic biology may facilitate a systematic exploration of evolvability across biological scales. Synthetic approaches permit controlled manipulation of both endogenous and fully engineered systems, providing a flexible platform for investigating causal mechanisms in vivo. Combining synthetic approaches with multi-level phenotyping (phenomics) will supply a detailed, quantitative characterization of how internal and external stimuli shape the morphology and behaviour of living organisms. We advocate integrating high-throughput experimental data with mathematical and computational techniques from a variety of disciplines in order to pursue a comprehensive theory of evolution.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Recent ecophysiological, biochemical and evolutional insights into plant carnivory

BACKGROUND

Carnivorous plants are an ecological group of approx. 810 vascular species which capture and digest animal prey, absorb prey-derived nutrients and utilize them to enhance their growth and development. Extant carnivorous plants have evolved in at least ten independent lineages, and their adaptive traits represent an example of structural and functional convergence. Plant carnivory is a result of complex adaptations to mostly nutrient-poor, wet and sunny habitats when the benefits of carnivory exceed the costs. With a boost in interest and extensive research in recent years, many aspects of these adaptations have been clarified (at least partly), but many remain unknown.

SCOPE

We provide some of the most recent insights into substantial ecophysiological, biochemical and evolutional particulars of plant carnivory from the functional viewpoint. We focus on those processes and traits in carnivorous plants associated with their ecological characterization, mineral nutrition, cost-benefit relationships, functioning of digestive enzymes and regulation of the hunting cycle in traps. We elucidate mechanisms by which uptake of prey-derived nutrients leads to stimulation of photosynthesis and root nutrient uptake.

CONCLUSIONS

Utilization of prey-derived mineral (mainly N and P) and organic nutrients is highly beneficial for plants and increases the photosynthetic rate in leaves as a prerequisite for faster plant growth. Whole-genome and tandem gene duplications brought gene material for diversification into carnivorous functions and enabled recruitment of defence-related genes. Possible mechanisms for the evolution of digestive enzymes are summarized, and a comprehensive picture on the biochemistry and regulation of prey decomposition and prey-derived nutrient uptake is provided.

Bridging the gap between theory and practice in elucidating modular gene regulatory sequence organisation within genomes

Changes to promoter regions probably have been responsible for many morphological evolutionary transitions, especially in animals. This idea is becoming testable, as data from genome projects amass and enable bioinformaticians to conduct comparative sequence analyses and test for correlations between genotypic similarities or differences and phenotypic likeness or disparity. Although such practical pursuits have initiated some theoretical considerations, a conceptual framework for understanding promoter region evolution, potentially effecting morphological evolution, is only starting to emerge, predominantly resulting from computational research. We contribute to this framework by specifying three big problems for promoter region research; reviewing computational research on promoter region evolution; and exemplifying a topic for future promoter region research - module evolution.

Arabidopsis NSE4 Proteins Act in Somatic Nuclei and Meiosis to Ensure Plant Viability and Fertility

The SMC 5/6 complex together with cohesin and condensin is a member of the structural maintenance of chromosome (SMC) protein family. In non-plant organisms SMC5/6 is engaged in DNA repair, meiotic synapsis, genome organization and stability. In plants, the function of SMC5/6 is still enigmatic. Therefore, we analyzed the crucial δ-kleisin component NSE4 of the SMC5/6 complex in the model plant Arabidopsis thaliana. Two functional conserved Nse4 paralogs (Nse4A and Nse4B) are present in A. thaliana, which may have evolved via gene subfunctionalization. Due to its high expression level, Nse4A seems to be the more essential gene, whereas Nse4B appears to be involved mainly in seed development. The morphological characterization of A. thaliana T-DNA mutants suggests that the NSE4 proteins are essential for plant growth and fertility. Detailed investigations in wild-type and the mutants based on live cell imaging of transgenic GFP lines, fluorescence in situ hybridization (FISH), immunolabeling and super-resolution microscopy suggest that NSE4A acts in several processes during plant development, such as mitosis, meiosis and chromatin organization of differentiated nuclei, and that NSE4A operates in a cell cycle-dependent manner. Differential response of NSE4A and NSE4B mutants after induced DNA double strand breaks (DSBs) suggests their involvement in DNA repair processes.

How transcription circuits explore alternative architectures while maintaining overall circuit output

This review by Dalal and Johnson focuses on the evolutionary rewiring of transcription regulators and the conservation of patterns of gene expression. They describe how preservation of gene expression patterns in the wake of extensive rewiring is a general feature of transcription circuit evolution.

Transcription regulators bind to cis-regulatory sequences and thereby control the expression of target genes. While transcription regulators and the target genes that they regulate are often deeply conserved across species, the connections between the two change extensively over evolutionary timescales. In this review, we discuss case studies where, despite this extensive evolutionary rewiring, the resulting patterns of gene expression are preserved. We also discuss in silico models that reach the same general conclusions and provide additional insights into how this process occurs. Together, these approaches make a strong case that the preservation of gene expression patterns in the wake of extensive rewiring is a general feature of transcription circuit evolution.

Subfunctionalization influences the expansion of bacterial multidrug antibiotic resistance

Background

Antibiotic resistance is a major problem for human health. Multidrug resistance efflux pumps, especially those of the Resistance-Nodulation-Cell Division (RND) family, are major contributors to high-level antibiotic resistance in Gram-negative bacteria. Most bacterial genomes contain several copies of the different classes of multidrug resistance efflux pumps. Gene duplication and gain of function by the duplicate copies of multidrug resistance efflux pump genes plays a key role in the expansion and diversification of drug-resistance mechanisms.

Results

We used two members of the Burkholderia RND superfamily as models to understand how duplication events affect the antibiotic resistance of these strains. First, we analyzed the conservation and distribution of these two RND systems and their regulators across the Burkholderia genus. Through genetic manipulations, we identified both the exact substrate range of these transporters and their eventual interchangeability. We also performed a directed evolution experiment, combined with next generation sequencing, to evaluate the role of antibiotics in the activation of the expression of these systems. Together, our results indicate that the first step to diversify the functions of these pumps arises from changes in their regulation (subfunctionalization) instead of functional mutations. Further, these pumps could rewire their regulation to respond to antibiotics, thus maintaining high genomic plasticity.

Conclusions

Studying the regulatory network that controls the expression of the RND pumps will help understand and eventually control the development and expansion of drug resistance.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4222-4) contains supplementary material, which is available to authorized users.

Evolution of new regulatory functions on biophysically realistic fitness landscapes

Gene expression is controlled by networks of regulatory proteins that interact specifically with external signals and DNA regulatory sequences. These interactions force the network components to co-evolve so as to continually maintain function. Yet, existing models of evolution mostly focus on isolated genetic elements. In contrast, we study the essential process by which regulatory networks grow: the duplication and subsequent specialization of network components. We synthesize a biophysical model of molecular interactions with the evolutionary framework to find the conditions and pathways by which new regulatory functions emerge. We show that specialization of new network components is usually slow, but can be drastically accelerated in the presence of regulatory crosstalk and mutations that promote promiscuous interactions between network components.Gene networks evolve by transcription factor (TF) duplication and divergence of their binding site specificities, but little is known about the global constraints at play. Here, the authors study the coevolution of TFs and binding sites using a biophysical-evolutionary approach, and show that the emerging complex fitness landscapes strongly influence regulatory evolution with a role for crosstalk.

Evolutionary diversification of retinoic acid receptor ligand-binding pocket structure by molecular tinkering

Whole genome duplications (WGDs) have been classically associated with the origin of evolutionary novelties and the so-called duplication-degeneration-complementation model describes the possible fates of genes after duplication. However, how sequence divergence effectively allows functional changes between gene duplicates is still unclear. In the vertebrate lineage, two rounds of WGDs took place, giving rise to paralogous gene copies observed for many gene families. For the retinoic acid receptors (RARs), for example, which are members of the nuclear hormone receptor (NR) superfamily, a unique ancestral gene has been duplicated resulting in three vertebrate paralogues: RARα, RARβ and RARγ. It has previously been shown that this single ancestral RAR was neofunctionalized to give rise to a larger substrate specificity range in the RARs of extant jawed vertebrates (also called gnathostomes). To understand RAR diversification, the members of the cyclostomes (lamprey and hagfish), jawless vertebrates representing the extant sister group of gnathostomes, provide an intermediate situation and thus allow the characterization of the evolutionary steps that shaped RAR ligand-binding properties following the WGDs. In this study, we assessed the ligand-binding specificity of cyclostome RARs and found that their ligand-binding pockets resemble those of gnathostome RARα and RARβ. In contrast, none of the cyclostome receptors studied showed any RARγ-like specificity. Together, our results suggest that cyclostome RARs cover only a portion of the specificity repertoire of the ancestral gnathostome RARs and indicate that the establishment of ligand-binding specificity was a stepwise event. This iterative process thus provides a rare example for the diversification of receptor-ligand interactions of NRs following WGDs.

The evolutionary dynamics of major regulators for sexual development among Hymenoptera species

All hymenopteran species, such as bees, wasps and ants, are characterized by the common principle of haplodiploid sex determination in which haploid males arise from unfertilized eggs and females from fertilized eggs. The underlying molecular mechanism has been studied in detail in the western honey bee Apis mellifera, in which the gene complementary sex determiner (csd) acts as primary signal of the sex determining pathway, initiating female development by csd-heterozygotes. Csd arose from gene duplication of the feminizer (fem) gene, a transformer (tra) ortholog, and mediates in conjunction with transformer2 (tra2) sex-specific splicing of fem. Comparative molecular analyses identified fem/tra and its downstream target doublesex (dsx) as conserved unit within the sex determining pathway of holometabolous insects. In this study, we aim to examine evolutionary differences among these key regulators. Our main hypothesis is that sex determining key regulators in Hymenoptera species show signs of coevolution within single phylogenetic lineages. We take advantage of several newly sequenced genomes of bee species to test this hypothesis using bioinformatic approaches. We found evidences that duplications of fem are restricted to certain bee lineages and notable amino acid differences of tra2 between Apis and non-Apis species propose structural changes in Tra2 protein affecting co-regulatory function on target genes. These findings may help to gain deeper insights into the ancestral mode of hymenopteran sex determination and support the common view of the remarkable evolutionary flexibility in this regulatory pathway.

Wiring for independence: positive feedback motifs facilitate individuation of traits in development and evolution

Independent selection response of a trait is contingent on the availability of genetic variation that is not entangled with other traits. Mechanistically, such variational individuation in spite of shared genome results from gene regulation. Changes that increase individuation of traits are likely caused by gene regulatory changes. Yet the effect of regulatory evolution on population variation is understudied. Trait individuation also occurs during development. Developmental differentiation involves two stages-induction of differentiation and the maintenance of differentiated fate. The corresponding gene regulatory transition involves the feed-forward and the regulated feedback motifs. Here we consider analogous transition pattern at the evolutionary scale, establishing an autonomous regulatory sub-network involved in the independent trait variation. A population genetic simulation of regulated feedback loop dynamics under small perturbations shows a decoupling of variation in gene expression between the upstream gene and the responding downstream gene. We furthermore observe that the ranges of dynamics that can be generated by feedback and feed-forward networks overlap. Such phenotypic overlap enables genetic accessibility of network-specific expression dynamics. We suggest that feedback topology may eventually confer selective advantage leading from a gradual process to threshold individuation, i.e., the emergence of a novel trait.

Nymphalid eyespots are co-opted to novel wing locations following a similar pattern in independent lineages

BACKGROUND

Variation in the number of repeated traits, or serial homologs, has contributed greatly to animal body plan diversity. Eyespot color patterns of nymphalid butterflies, like arthropod and vertebrate limbs, are an example of serial homologs. These eyespot color patterns originated in a small number of wing sectors on the ventral hindwing surface and later appeared in novel wing sectors, novel wings, and novel wing surfaces. However, the details of how eyespots were co-opted to these novel wing locations are currently unknown.

RESULTS

We used a large data matrix of eyespot/presence absence data, previously assembled from photographs of contemporary species, to perform a phylogenetic investigation of eyespot origins in nine independent nymphalid lineages. To determine how the eyespot gene regulatory network acquired novel positional information, we used phylogenetic correlation analyses to test for non-independence in the origination of eyespots. We found consistent patterns of eyespot gene network redeployment in the nine lineages, where eyespots first redeployed from the ventral hindwing to the ventral forewing, then to new sectors within the ventral wing surface, and finally to the dorsal wing surface. Eyespots that appeared in novel wing sectors modified the positional information of their serial homolog ancestors in one of two ways: by changing the wing or surface identity while retaining sector identity, or by changing the sector identity while retaining wing and surface identity.

CONCLUSIONS

Eyespot redeployment to novel sectors, wings, and surfaces happened multiple times in different nymphalid subfamilies following a similar pattern. This indicates that parallel mutations altering expression of the eyespot gene regulatory network led to its co-option to novel wing locations over time.

Evolutionary cell biology: two origins, one objective

All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.

Integrated phenotypes: understanding trait covariation in plants and animals

Integration and modularity refer to the patterns and processes of trait interaction and independence. Both terms have complex histories with respect to both conceptualization and quantification, resulting in a plethora of integration indices in use. We review briefly the divergent definitions, uses and measures of integration and modularity and make conceptual links to allometry. We also discuss how integration and modularity might evolve. Although integration is generally thought to be generated and maintained by correlational selection, theoretical considerations suggest the relationship is not straightforward. We caution here against uncontrolled comparisons of indices across studies. In the absence of controls for trait number, dimensionality, homology, development and function, it is difficult, or even impossible, to compare integration indices across organisms or traits. We suggest that care be invested in relating measurement to underlying theory or hypotheses, and that summative, theory-free descriptors of integration generally be avoided. The papers that follow in this Theme Issue illustrate the diversity of approaches to studying integration and modularity, highlighting strengths and pitfalls that await researchers investigating integration in plants and animals.

The evolution and functional divergence of the beta-carotene oxygenase gene family in teleost fish--exemplified by Atlantic salmon

In mammals, two carotenoid cleaving oxygenases are known; beta-carotene 15,15'-monooxygenase (BCMO1) and beta-carotene 9',10'-oxygenase (BCO2). BCMO1 is a key enzyme in vitamin A synthesis by symmetrically cleaving beta-carotene into 2 molecules of all-trans-retinal, while BCO2 is responsible for asymmetric cleavage of a broader range of carotenoids. Here, we show that the Atlantic salmon beta-carotene oxygenase (bco) gene family contains 5 members, three bco2 and two bcmo1 paralogs. Using public sequence databases, multiple bco genes were also found in several additional teleost species. Phylogenetic analysis indicates that bco2a and bco2b originate from the teleost fish specific genome duplication (FSGD or 3R), while the third and more distant paralog, bco2 like, might stem from a prior duplication event in the teleost lineage. The two bcmo1 paralogs (bcmo1 and bcmo1 like) appear to be the result of an ancient duplication event that took place before the divergence of ray-finned (Actinopterygii) and lobe-finned fish (Sarcopterygii), with subsequent nonfunctionalization and loss of one Sarcopterygii paralog. Gene expression analysis of the bcmo1 and bco2 paralogs in Atlantic salmon reveals regulatory divergence with tissue specific expression profiles, suggesting that the beta-carotene oxygenase subtypes have evolved functional divergences. We suggest that teleost fish have evolved and maintained an extended repertoire of beta-carotene oxygenases compared to the investigated Sarcopterygii species, and hypothesize that the main driver behind this functional divergence is the exposure to a diverse set of carotenoids in the aquatic environment.

Gene duplication as a major force in evolution

Gene duplication is an important mechanism for acquiring new genes and creating genetic novelty in organisms. Many new gene functions have evolved through gene duplication and it has contributed tremendously to the evolution of developmental programmes in various organisms. Gene duplication can result from unequal crossing over, retroposition or chromosomal (or genome) duplication. Understanding the mechanisms that generate duplicate gene copies and the subsequent dynamics among gene duplicates is vital because these investigations shed light on localized and genomewide aspects of evolutionary forces shaping intra-specific and inter-specific genome contents, evolutionary relationships, and interactions. Based on whole-genome analysis of Arabidopsis thaliana, there is compelling evidence that angiosperms underwent two whole-genome duplication events early during their evolutionary history. Recent studies have shown that these events were crucial for creation of many important developmental and regulatory genes found in extant angiosperm genomes. Recent studies also provide strong indications that even yeast (Saccharomyces cerevisiae), with its compact genome, is in fact an ancient tetraploid. Gene duplication can provide new genetic material for mutation, drift and selection to act upon, the result of which is specialized or new gene functions. Without gene duplication the plasticity of a genome or species in adapting to changing environments would be severely limited. Whether a duplicate is retained depends upon its function, its mode of duplication, (i.e. whether it was duplicated during a whole-genome duplication event), the species in which it occurs, and its expression rate. The exaptation of preexisting secondary functions is an important feature in gene evolution, just as it is in morphological evolution.

Mutation rules and the evolution of sparseness and modularity in biological systems

Biological systems exhibit two structural features on many levels of organization: sparseness, in which only a small fraction of possible interactions between components actually occur; and modularity – the near decomposability of the system into modules with distinct functionality. Recent work suggests that modularity can evolve in a variety of circumstances, including goals that vary in time such that they share the same subgoals (modularly varying goals), or when connections are costly. Here, we studied the origin of modularity and sparseness focusing on the nature of the mutation process, rather than on connection cost or variations in the goal. We use simulations of evolution with different mutation rules. We found that commonly used sum-rule mutations, in which interactions are mutated by adding random numbers, do not lead to modularity or sparseness except for in special situations. In contrast, product-rule mutations in which interactions are mutated by multiplying by random numbers – a better model for the effects of biological mutations – led to sparseness naturally. When the goals of evolution are modular, in the sense that specific groups of inputs affect specific groups of outputs, product-rule mutations also lead to modular structure; sum-rule mutations do not. Product-rule mutations generate sparseness and modularity because they tend to reduce interactions, and to keep small interaction terms small.

Comparative proteomics of the recently and recurrently formed natural allopolyploid Tragopogon mirus (Asteraceae) and its parents

• We examined the proteomes of the recently formed natural allopolyploid Tragopogon mirus and its diploid parents (T. dubius, T. porrifolius), as well as a diploid F(1) hybrid and synthetic T. mirus. • Analyses using iTRAQ LC-MS/MS technology identified 476 proteins produced by all three species. Of these, 408 proteins showed quantitative additivity of the two parental profiles in T. mirus (both natural and synthetic); 68 proteins were quantitatively differentially expressed. • Comparison of F(1) hybrid, and synthetic and natural polyploid T. mirus with the parental diploid species revealed 32 protein expression changes associated with hybridization, 22 with genome doubling and 14 that had occurred since the origin of T. mirus c. 80 yr ago. We found six proteins with novel expression; this phenomenon appears to start in the F(1) hybrid and results from post-translational modifications. • Our results indicate that the impact of hybridization on the proteome is more important than is polyploidization. Furthermore, two cases of homeolog-specific expression in T. mirus suggest that silencing in T. mirus was not associated with hybridization itself, but occurred subsequent to both hybridization and polyploidization. This study has shown the utility of proteomics in the analysis of the evolutionary consequences of polyploidy.

Expression of aromatase in radial glial cells in the brain of the Japanese eel provides insight into the evolution of the cyp191a gene in Actinopterygians

The cyp19a1 gene that encodes aromatase, the only enzyme permitting conversion of C19 aromatizable androgens into estrogens, is present as a single copy in the genome of most vertebrate species, except in teleosts in which it has been duplicated. This study aimed at investigating the brain expression of a cyp19a1 gene expressed in both gonad and brain of Japanese eel, a basal teleost. By means of immunohistochemistry and in situ hybridization, we show that cyp19a1 is expressed only in radial glial cells of the brain and in pituitary cells. Treatments with salmon pituitary homogenates (female) or human chorionic gonadotrophin (male), known to turn on steroid production in immature eels, strongly stimulated cyp19a1 messenger and protein expression in radial glial cells and pituitary cells. Using double staining studies, we also showed that aromatase-expressing radial glial cells exhibit proliferative activity in both the brain and the pituitary. Altogether, these data indicate that brain and pituitary expression of Japanese eel cyp19a1 exhibits characteristics similar to those reported for the brain specific cyp19a1b gene in teleosts having duplicated cyp19a1 genes. This supports the hypothesis that, despite the fact that eels also underwent the teleost specific genome duplication, they have a single cyp19a1 expressed in both brain and gonad. Such data also suggest that the intriguing features of brain aromatase expression in teleost fishes were not gained after the whole genome duplication and may reflect properties of the cyp19a1 gene of ancestral Actinopterygians.

Large scale of human duplicate genes divergence

Proteome complexity increases in the evolution mostly by means of gene duplication followed by divergence. In this genome-scale study of human genome I show that density distribution of duplicate gene pairs along the axis of protein divergence between pair members forms two main peaks with a small peak and plateau before the first main peak. This picture indicates the existence of three evolutionary stages of duplicate gene evolution. The analysis of various functional parameters (gene expression level and breadth, transcription factor targets, protein interaction networks) suggests that subfunctionalization (partition of function) is a predominant mode of divergence in the first main peak, whereas neofunctionalization (acquiring of novel functions) prevails in the second main peak. The young duplicate pairs show a much higher expression level compared with singleton genes and more diverged duplicates, which indicates that requirement for high gene dosage is important for retention of duplicates just after the duplication event. Thus, a prevailing route of duplicate evolution seems to be the high gene dosage-subfunctionalization-neofunctionalization. This adaptationist model suggests that an organism is evolving in the direction of its most intensively used functions.

Quantifying protein modularity and evolvability: a comparison of different techniques

Modularity increases evolvability by reducing constraints on adaptation and by allowing preexisting parts to function in new contexts for novel uses. Protein evolution provides an excellent context to study the causes and consequences of biological modularity. In order to address such questions, however, an index for protein modularity is necessary. This paper proposes a simple index for protein modularity-"module density"-which is the number of evolutionarily independent modules that compose a protein divided by the number of amino acids in the protein. The decomposition of proteins into constituent modules can be accomplished by either of two classes of methods. The first class of methods relies on "suppositional" criteria to assign amino acids to modules, whereas the second class of methods relies on "coevolutionary" criteria for this task. One simple and practical method from the first class consists of approximating the number of modules in a protein as the number of regular secondary structure elements (i.e., helices and sheets). Methods based on coevolutionary criteria require more elaborate data, but they have the advantage of being able to specify modules without prior assumptions about why they exist. Given the increasing availability of datasets sampling protein mutational spectra (e.g., from comparative genomics, experimental evolution, and computational prediction), methods based on coevolutionary criteria will likely become more promising in the near future. The ability to meaningfully quantify protein modularity via simple indices has the potential to aid future efforts to understand protein evolutionary rate determinants, improve molecular evolution models and engineer novel proteins.

Biological robustness: paradigms, mechanisms, and systems principles

Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g., mutational, environmental) are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior.

Evolutionary principles underlying structure and response dynamics of cellular networks

The network view in systems biology, in conjunction with the continuing development of experimental technologies, is providing us with the key structural and dynamical features of both cell-wide and pathway-level regulatory, signaling and metabolic systems. These include for example modularity and presence of hub proteins at the structural level and ultrasensitivity and feedback control at the level of dynamics. The uncovering of such features, and the seeming commonality of some of them, makes many systems biologists believe that these could represent design principles that underpin cellular systems across organisms. Here, we argue that such claims on any observed feature requires an understanding of how it has emerged in evolution and how it can shape subsequent evolution. We review recent and past studies that aim to achieve such evolutionary understanding for observed features of cellular networks. We argue that this evolutionary framework could lead to deciphering evolutionary origin and relevance of proposed design principles, thereby allowing to predict their presence or absence in an organism based on its environment and biochemistry and their effect on its future evolution.

Multiple routes to subfunctionalization and gene duplicate specialization

Gene duplication is arguably the most significant source of new functional genetic material. A better understanding of the processes that lead to the stable incorporation of gene duplications into the genome is important both because it relates to interspecific differences in genome composition and because it can shed light on why some classes of gene are more prone to duplication than others. Typically, models of gene duplication consider the periods before duplication, during the spread and fixation of a new duplicate, and following duplication as distinct phases without a common underlying selective environment. I consider a scenario where a gene that is initially expressed in multiple contexts can undergo mutations that alter its expression profile or its functional coding sequence. The selective regime that acts on the functional output of the allele copies carried by an individual is constant. If there is a potential selective benefit to having different coding sequences expressed in each context, then, regardless of the constraints on functional variation at the single-locus gene, the waiting time until a gene duplication is incorporated goes down as population size increases.

Protein structural modularity and robustness are associated with evolvability

Theory suggests that biological modularity and robustness allow for maintenance of fitness under mutational change, and when this change is adaptive, for evolvability. Empirical demonstrations that these traits promote evolvability in nature remain scant however. This is in part because modularity, robustness, and evolvability are difficult to define and measure in real biological systems. Here, we address whether structural modularity and/or robustness confer evolvability at the level of proteins by looking for associations between indices of protein structural modularity, structural robustness, and evolvability. We propose a novel index for protein structural modularity: the number of regular secondary structure elements (helices and strands) divided by the number of residues in the structure. We index protein evolvability as the proportion of sites with evidence of being under positive selection multiplied by the average rate of adaptive evolution at these sites, and we measure this as an average over a phylogeny of 25 mammalian species. We use contact density as an index of protein designability, and thus, structural robustness. We find that protein evolvability is positively associated with structural modularity as well as structural robustness and that the effect of structural modularity on evolvability is independent of the structural robustness index. We interpret these associations to be the result of reduced constraints on amino acid substitutions in highly modular and robust protein structures, which results in faster adaptation through natural selection.

Emergence of switch-like behavior in a large family of simple biochemical networks

Bistability plays a central role in the gene regulatory networks (GRNs) controlling many essential biological functions, including cellular differentiation and cell cycle control. However, establishing the network topologies that can exhibit bistability remains a challenge, in part due to the exceedingly large variety of GRNs that exist for even a small number of components. We begin to address this problem by employing chemical reaction network theory in a comprehensive in silico survey to determine the capacity for bistability of more than 40,000 simple networks that can be formed by two transcription factor-coding genes and their associated proteins (assuming only the most elementary biochemical processes). We find that there exist reaction rate constants leading to bistability in ∼90% of these GRN models, including several circuits that do not contain any of the TF cooperativity commonly associated with bistable systems, and the majority of which could only be identified as bistable through an original subnetwork-based analysis. A topological sorting of the two-gene family of networks based on the presence or absence of biochemical reactions reveals eleven minimal bistable networks (i.e., bistable networks that do not contain within them a smaller bistable subnetwork). The large number of previously unknown bistable network topologies suggests that the capacity for switch-like behavior in GRNs arises with relative ease and is not easily lost through network evolution. To highlight the relevance of the systematic application of CRNT to bistable network identification in real biological systems, we integrated publicly available protein-protein interaction, protein-DNA interaction, and gene expression data from Saccharomyces cerevisiae, and identified several GRNs predicted to behave in a bistable fashion.

Switch-like behavior is found across a wide range of biological systems, and as a result there is significant interest in identifying the various ways in which biochemical reactions can be combined to yield a switch-like response. In this work we use a set of mathematical tools from chemical reaction network theory that provide information about the steady-states of a reaction network irrespective of the values of network rate constants, to conduct a large computational study of a family of model networks consisting of only two protein-coding genes. We find that a large majority of these networks (∼90%) have (for some set of parameters) the mathematical property known as bistability and can behave in a switch-like manner. Interestingly, the capacity for switch-like behavior is often maintained as networks increase in size through the introduction of new reactions. We then demonstrate using published yeast data how theoretical parameter-free surveys such as this one can be used to discover possible switch-like circuits in real biological systems. Our results highlight the potential usefulness of parameter-free modeling for the characterization of complex networks and to the study of network evolution, and are suggestive of a role for it in the development of novel synthetic biological switches.

The emergence of modularity in biological systems

In this review, we discuss modularity and hierarchy in biological systems. We review examples from protein structure, genetics, and biological networks of modular partitioning of the geometry of biological space. We review theories to explain modular organization of biology, with a focus on explaining how biology may spontaneously organize to a structured form. That is, we seek to explain how biology nucleated from among the many possibilities in chemistry. The emergence of modular organization of biological structure will be described as a symmetry-breaking phase transition, with modularity as the order parameter. Experimental support for this description will be reviewed. Examples will be presented from pathogen structure, metabolic networks, gene networks, and protein-protein interaction networks. Additional examples will be presented from ecological food networks, developmental pathways, physiology, and social networks.

Predicting genome-wide redundancy using machine learning

BACKGROUND

Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the test case used here.

RESULTS

Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in Arabidopsis showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1), suggesting that redundancy is stable over long evolutionary periods.

CONCLUSIONS

Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for Arabidopsis provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.

Surprising flexibility in a conserved Hox transcription factor over 550 million years of evolution

Although metazoan body plans are remarkably diverse, the structure and function of many embryonic regulatory genes are conserved because large changes would be detrimental to development. However, the fushi tarazu (ftz) gene has changed dramatically during arthropod evolution from Hox-like to a pair-rule segmentation gene in Drosophila. Changes in both expression and protein sequence contributed to this new function: ftz expression switched from Hox-like to stripes and changes in Ftz cofactor interaction motifs led to loss of homeotic and gain of segmentation potential. Here, we reconstructed ftz changes in a rigorous phylogenetic context. We found that ftz did not simply switch from Hox-like to segmentation function; rather, ftz is remarkably labile, having undergone multiple changes in sequence and expression. The segmentation LXXLL motif was stably acquired in holometabolous insects after the appearance of striped expression in early insect lineages. The homeotic YPWM motif independently degenerated multiple times. These "degen-YPWMs" showed varying degrees of homeotic potential when expressed in Drosophila, suggesting variable loss of Hox function in different arthropods. Finally, the intensity of ftz Hox-like expression decreased to marginal levels in some crustaceans. We propose that decreased expression levels permitted ftz variants to arise and persist in populations without disadvantaging organismal development. This process, in turn, allowed evolutionary transitions in protein function, as weakly expressed "hopeful gene variants" were coopted into alternative developmental pathways. Our findings show that variation of a pleiotropic transcription factor is more extensive than previously imagined, suggesting that evolutionary plasticity may be widespread among regulatory genes.

Evolution under fluctuating environments explains observed robustness in metabolic networks

A high level of robustness against gene deletion is observed in many organisms. However, it is still not clear which biochemical features underline this robustness and how these are acquired during evolution. One hypothesis, specific to metabolic networks, is that robustness emerges as a byproduct of selection for biomass production in different environments. To test this hypothesis we performed evolutionary simulations of metabolic networks under stable and fluctuating environments. We find that networks evolved under the latter scenario can better tolerate single gene deletion in specific environments. Such robustness is underlined by an increased number of independent fluxes and multifunctional enzymes in the evolved networks. Observed robustness in networks evolved under fluctuating environments was “apparent,” in the sense that it decreased significantly as we tested effects of gene deletions under all environments experienced during evolution. Furthermore, when we continued evolution of these networks under a stable environment, we found that any robustness they had acquired was completely lost. These findings provide evidence that evolution under fluctuating environments can account for the observed robustness in metabolic networks. Further, they suggest that organisms living under stable environments should display lower robustness in their metabolic networks, and that robustness should decrease upon switching to more stable environments.

One of the most surprising recent biological findings is the high level of tolerance organisms show towards loss of single genes. This observation suggests that there are certain features of biological systems that give them a high tolerance (i.e. robustness) towards gene loss. We still lack an exact understanding of what these features might be and how they could have been acquired during evolution. Here, we offer a possible answer for these questions in the context of metabolic networks. Using mathematical models capturing the structure and dynamics of metabolic networks, we simulate their evolution under stable and fluctuating environments (i.e., available metabolites). We find that the latter scenario leads to evolution of metabolic networks that display high robustness against gene loss. This robustness of in silico evolved networks is underlined by an increased number of multifunctional enzymes and independent paths leading from initial metabolites to biomass. These findings provide evidence that fluctuating environments can be a major evolutionary force leading to the emergence of robustness as a side effect. A direct prediction resulting from this study is that organisms living in stable and fluctuating environments should display differing levels of robustness against gene loss.

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

Characterization of the shsp genes in Drosophila buzzatii and association between the frequency of Valine mutations in hsp23 and climatic variables along a longitudinal gradient in Australia

The small heat shock gene (shsp) cluster of Drosophila buzzatii was sequenced and the gene order and DNA sequence were compared with those of the shsps in Drosophila melanogaster. The D. buzzatii shsp cluster contains an inversion and a duplication of hsp26. A phylogenetic tree was constructed based on hsp26 genes from several Drosophila species of the Sophophora and Drosophila subgenera. The tree shows first a separation of the Sophophora and the Drosophila subgenera and then the Drosophila subgenus is divided into the Hawaiian Drosophila and the repleta/virilis groups. Only the latter contain a duplicated hsp26. Comparing the gene organisation of the shsp cluster shows that all the Drosophila subgenus species contain the inversion. Putative heat shock elements (HSE) were found in the promoters of all the shsp and putative regulator elements for tissue specific expression were found in the promoter of hsp23, hsp27 and one of the hsp26 genes. hsp23 was found to be polymorphic for four non-synonymous changes that all lead to exchange of a Valine. The duplicated hsp26 gene in D. buzzatii (phsp26) was polymorphic for two non-synonymous changes. The allele frequencies of these variants were determined in nine D. buzzatii populations covering most of its distribution in Australia using high-resolution melting curves. The allele frequencies of one of the hsp23 variants showed a significant linear regression with longitude and the pooled frequency of the four Valine changes of hsp23 in the nine populations showed a significant linear regression with longitude and with a composite measure of climatic variables.

Nuclear glutamine synthetase evolution in Nicotiana: phylogenetics and the origins of allotetraploid and homoploid (diploid) hybrids

Interspecies relationships in Nicotiana (Solanaceae) are complex because 40 species are diploid (two sets of chromosomes) and 35 species are allotetraploid (four sets of chromosomes, two from each progenitor diploid species). We sequenced a fragment (containing four introns) of the nuclear gene 'chloroplast-expressed glutamine synthetase' (ncpGS) in 65 species of Nicotiana. Here we present the first phylogenetic analysis based on a low-copy nuclear gene for this well studied and important genus. Diploid species have a single-copy of ncpGS, and allotetraploids as expected have two homeologous copies, each derived from their progenitor diploid. Results were particularly useful for determining the paternal lineage of previously enigmatic taxa (for which our previous analyses had revealed only the maternal progenitors). In particular, we were able to shed light on the origins of the two oldest and largest allotetraploid sections, N. sects. Suaveolentes and Repandae. All homeologues have an intact reading frame and apparently similar rates of divergence, suggesting both remain functional. Difficulties in fitting certain diploid species into the sectional classification of Nicotiana on morphological grounds, coupled with discordance between the ncpGS data and previous trees (i.e. plastid, nuclear ribosomal DNA), indicate a number of homoploid (diploid) hybrids in the genus. We have evidence for Nicotiana glutinosa and Nicotiana linearis being of hybrid origin and patterns of intra-allelic recombination also indicate the possibility of reticulate origins for other diploid species.

Making a functional diploid: from polysomic to disomic inheritance

One little understood feature of polyploid speciation is the transition from polysomic to disomic inheritance, and much recent attention has focused on the role of pairing genes in this process. Using computer simulations we studied the effects of mutations, chromosomal inversions, chiasma, neofunctionalization, subfunctionalization and selection on the evolution of disomic inheritance in a polyploid over 10 000 generations. We show that: the evolution of pairing genes is not essential for the establishment of disomic inheritance, as genetic drift, coupled with a threshold for homologue pairing fidelity, is sufficient to explain the transition from polysomic to disomic inheritance; high rates of recombination increase the number of generations required for disomic inheritance to become established; both neofunctionalization and subfunctionalization speed up the transition to disomic inheritance. The data suggest that during polyploid species establishment, selection will favour reduced chiasma number and/or more focused distribution. The data also suggest a new role for subfunctionalization in that it can drive disomic inheritance. The evolution of subfunctionalization in genes across the genome will then act to maintain genes in syntenic blocks and may explain why such regions are so highly conserved.

Insights from the comparison of plant genome sequences

The next decade will see essentially completed sequences for multiple branches of virtually all angiosperm clades that include major crops and/or botanical models. These sequences will provide a powerful framework for relating genome-level events to aspects of morphological and physiological variation that have contributed to the colonization of much of the planet by angiosperms. Clarification of the fundamental angiosperm gene set, its arrangement, lineage-specific variations in gene repertoire and arrangement, and the fates of duplicated gene pairs will advance knowledge of functional and regulatory diversity and perhaps shed light on adaptation by lineages to whole-genome duplication, which is a distinguishing feature of angiosperm evolution. Better understanding of the relationships among angiosperm genomes promises to provide a firm foundation upon which to base translational genomics: the leveraging of hard-won structural and functional genomic information from crown botanical models to dissect novel and, in some cases, economically important features in many additional organisms.

Gene and genome duplications: the impact of dosage-sensitivity on the fate of nuclear genes

Whole genome duplications (WGDs) followed by diploidization, which includes gene loss, have been an important recurrent process in the evolution of higher eukaryotes. Gene retention is biased to specific functional gene categories during diploidization. Dosage-sensitive genes, which include transcription factors, are significantly over-retained following WGDs. By contrast, these same functional gene categories exhibit lower retention rates following smaller scale duplications (e.g., local and tandem duplicates, segmental duplicates, aneuploidy). In light of these recent observations, we review current theories that address the fate of nuclear genes following duplication events (i.e., Gain of Function Hypothesis, Subfunctionalization Hypothesis, Increased Gene Dosage Hypothesis, Functional Buffering Model, and the Gene Balance Hypothesis). We broadly review different mechanisms of dosage-compensation that have evolved to alleviate harmful dosage-imbalances. In addition, we examine a recently proposed extension of the Gene Balance Hypothesis to explain the shared single copy status for a specific functional class of genes across the flowering plants. We speculate that the preferential retention of dosage-sensitive genes (e.g., regulatory genes such as transcription factors) and gene loss following WGDs has played a significant role in the development of morphological complexity in eukaryotes and facilitating speciation, respectively. Lastly, we will review recent findings that suggest polyploid lineages had increased rates of survival and speciation following mass extinction events, including the Cretaceous-Tertiary (KT) extinction.

On theoretical models of gene expression evolution with random genetic drift and natural selection

BACKGROUND

The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.

METHODOLOGY/PRINCIPAL FINDINGS

In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1) our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2) cytological constraints can be explicitly formulated to describe long-term evolution; (3) the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.

CONCLUSIONS/SIGNIFICANCE

The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

Segmental duplications contribute to gene expression differences between humans and chimpanzees

In addition to specific changes in cis- and trans-regulatory elements, structural changes in the genome are hypothesized to underlie a large number of differences in gene expression between species. Accordingly, we show that species-specific segmental duplications are enriched with genes that are differentially expressed between humans and chimpanzees.

Extinctions in heterogeneous environments and the evolution of modularity

Extinctions of local subpopulations are common events in nature. Here, we ask whether such extinctions can affect the design of biological networks within organisms over evolutionary timescales. We study the impact of extinction events on modularity of biological systems, a common architectural principle found on multiple scales in biology. As a model system, we use networks that evolve toward goals specified as desired input–output relationships. We use an extinction–recolonization model, in which metapopulations occupy and migrate between different localities. Each locality displays a different environmental condition (goal), but shares the same set of subgoals with other localities. We find that in the absence of extinction events, the evolved computational networks are typically highly optimal for their localities with a nonmodular structure. In contrast, when local populations go extinct from time to time, we find that the evolved networks are modular in structure. Modular circuitry is selected because of its ability to adapt rapidly to the conditions of the free niche following an extinction event. This rapid adaptation is mainly achieved through genetic recombination of modules between immigrants from neighboring local populations. This study suggests, therefore, that extinctions in heterogeneous environments promote the evolution of modular biological network structure, allowing local populations to effectively recombine their modules to recolonize niches.

Loss of protein interactions and regulatory divergence in yeast whole-genome duplicates

Whole-genome duplications are important for the growth of genome complexity. We investigated various factors involved in the evolution of yeast whole-genome duplicates (ohnologs) making emphasis on the analysis of protein interactions. We found that ohnologs have a lower number of protein interactions compared with small-scale duplicates and singletons (by about -40%). The loss of interactions was proportional to their initial number and independent of ohnolog position in the protein interaction network. A faster evolving member of an ohnolog pair has a lower number of interactions compared to its counterpart. The Gene Ontology mapping of non-overlapping and overlapping interactants of paired ohnologs reveals a sharp asymmetry in GO terms related to regulation. The fraction of these terms is much higher in non-overlapping interactants (compared to overlapping interactants and total dataset). Network clustering coefficient is lower in ohnologs, yet they show an increased density of protein interactions restricted within the whole ohnologs set. These facts suggest that subfunctionalization (or subneofunctionalization) reflected in the loss of protein interactions was a prevailing process in the divergence of ohnologs, which distinguishes them from small-scale duplicates. The loss of protein interactions was associated with the regulatory divergence between the members of an ohnolog pair. A small-scale modularity (reflected in clustering coefficient) probably was not important for ohnologs retention, yet a larger-scale modularity could be involved in their evolution.

Forward and reverse genetics of rapid-cycling Brassica oleracea

Seeds of rapid-cycling Brassica oleracea were mutagenized with the chemical mutagen, ethylmethane sulfonate. The reverse genetics technique, TILLING, was used on a sample population of 1,000 plants, to determine the mutation profile. The spectrum and frequency of mutations induced by ethylmethane sulfonate was similar to that seen in other diploid species such as Arabidopsis thaliana. These data indicate that the mutagenesis was effective and demonstrate that TILLING represents an efficient reverse genetic technique in B. oleracea that will become more valuable as increasing genomic sequence data become available for this species. The extensive duplication in the B. oleracea genome is believed to result in the genetic redundancy that has been important for the evolution of morphological diversity seen in today's B. oleracea crops (broccoli, Brussels sprouts, cauliflower, cabbage, kale and kohlrabi). However, our forward genetic screens identified 120 mutants in which some aspect of development was affected. Some of these lines have been characterized genetically and in the majority of these, the mutant trait segregates as a recessive allele affecting a single locus. One dominant mutation (curly leaves) and one semi-dominant mutation (dwarf-like) were also identified. Allelism tests of two groups of mutants (glossy and dwarf) revealed that for some loci, multiple independent alleles have been identified. These data indicate that, despite genetic redundancy, mutation of many individual loci in B. oleracea results in distinct phenotypes.

Domain duplication, divergence, and loss events in vertebrate Msx paralogs reveal phylogenomically informed disease markers

Background

Msx originated early in animal evolution and is implicated in human genetic disorders. To reconstruct the functional evolution of Msx and inform the study of human mutations, we analyzed the phylogeny and synteny of 46 metazoan Msx proteins and tracked the duplication, diversification and loss of conserved motifs.

Results

Vertebrate Msx sequences sort into distinct Msx1, Msx2 and Msx3 clades. The sister-group relationship between MSX1 and MSX2 reflects their derivation from the 4p/5q chromosomal paralogon, a derivative of the original "MetaHox" cluster. We demonstrate physical linkage between Msx and other MetaHox genes (Hmx, NK1, Emx) in a cnidarian. Seven conserved domains, including two Groucho repression domains (N- and C-terminal), were present in the ancestral Msx. In cnidarians, the Groucho domains are highly similar. In vertebrate Msx1, the N-terminal Groucho domain is conserved, while the C-terminal domain diverged substantially, implying a novel function. In vertebrate Msx2 and Msx3, the C-terminal domain was lost. MSX1 mutations associated with ectodermal dysplasia or orofacial clefting disorders map to conserved domains in a non-random fashion.

Conclusion

Msx originated from a MetaHox ancestor that also gave rise to Tlx, Demox, NK, and possibly EHGbox, Hox and ParaHox genes. Duplication, divergence or loss of domains played a central role in the functional evolution of Msx. Duplicated domains allow pleiotropically expressed proteins to evolve new functions without disrupting existing interaction networks. Human missense sequence variants reside within evolutionarily conserved domains, likely disrupting protein function. This phylogenomic evaluation of candidate disease markers will inform clinical and functional studies.