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DIVERGE is a software system for phylogeny-based analyses of protein family evolution and functional divergence. It provides a suite of statistical tools for selection and prioritization of the amino acid sites that are responsible for the functional divergence of a gene family. The synergistic efforts of DIVERGE and other methods have convincingly demonstrated that the pattern of rate change at a particular amino acid site may contain insightful information about the underlying functional divergence following gene duplication. These predicted sites may be used as candidates for further experiments. We are now releasing an updated version of DIVERGE with the following improvements: 1) a feasible approach to examining functional divergence in nearly complete sequences by including deletions and insertions (indels); 2) the calculation of the false discovery rate of functionally diverging sites; 3) estimation of the effective number of functional divergence-related sites that is reliable and insensitive to cutoffs; 4) a statistical test for asymmetric functional divergence; and 5) a new method to infer functional divergence specific to a given duplicate cluster. In addition, we have made efforts to improve software design and produce a well-written software manual for the general user.

Background γ-glutamyltranspeptidase (GGT) is a bi-substrate enzyme conserved in all three domains of life. It catalyzes the cleavage and transfer of γ-glutamyl moiety of glutathione to either water (hydrolysis) or substrates like peptides (transpeptidation). GGTs exhibit great variability in their enzyme kinetics although the mechanism of catalysis is conserved. Recently, GGT has been shown to be a virulence factor in microbes like Helicobacter pylori and Bacillus anthracis . In mammalian cells also, GGT inhibition prior to chemotherapy has been shown to sensitize tumors to the therapy. Therefore, lately both bacterial and eukaryotic GGTs have emerged as potential drug targets, but the efforts directed towards finding suitable inhibitors have not yielded any significant results yet. We propose that delineating the residues responsible for the functional diversity associated with these proteins could help in design of species/clade specific inhibitors. Results In the present study, we have carried out phylogenetic analysis on a set of 47 GGT-like proteins to address the functional diversity. These proteins segregate into various subfamilies, forming separate clades on the tree. Sequence conservation and motif prediction studies show that even though most of the highly conserved residues have been characterized biochemically in previous studies, a significant number of novel putative sites and motifs are discovered that vary in a clade specific manner. Many of the putative sites predicted during the functional divergence type I and type II analysis, lie close to the known catalytic residues and line the walls of the substrate binding cavity, reinforcing their role in modulating the substrate specificity, catalytic rates and stability of this protein. Conclusion The study offers interesting insights into the evolution of GGT-like proteins in pathogenic vs. non-pathogenic bacteria, archaea and eukaryotes. Our analysis delineates residues that are highly specific to each GGT subfamily. We propose that these sites not only explain the differences in stability and catalytic variability of various GGTs but can also aid in design of specific inhibitors against particular GGTs. Thus, apart from the commonly used in-silico inhibitor screening approaches, evolutionary analysis identifying the functional divergence hotspots in GGT proteins could augment the structure based drug design approaches. Reviewers This article was reviewed by Andrei Osterman, Christine Orengo, and Srikrishna Subramanian. For complete reports, see the Reviewers’ reports section

Background Subtilisin-like serine proteases or Subtilases in fungi are important for penetration and colonization of host. In Hypocreales, these proteins share several properties with other fungal, bacterial, plant and mammalian homologs. However, adoption of specific roles in entomopathogenesis may be governed by attainment of unique biochemical and structural features during the evolutionary course. Due to such functional shifts Subtilases coded by different family members of Hypocreales acquire distinct features according to respective hosts and lifestyle. We conducted phylogenetic and DIVERGE analyses and identified important protein residues that putatively assign functional specificity to Subtilases in fungal families/species under the order Hypocreales. Results A total of 161 Subtilases coded by 10 species from five different families under the fungal order Hypocreales was included in the analysis. Based on the presence of conserved domains, the Subtilase genes were divided into three subfamilies, Subtilisin (S08.005), Proteinase K (S08.054) and Serine-carboxyl peptidases (S53.001). These subfamilies were investigated for phylogenetic associations, protein residues under positive selection and functional divergence among paralogous clades. The observations were co-related with the life-styles of the fungal families/species. Phylogenetic and Divergence analyses of Subtilisin (S08.005) and Proteinase K (S08.054) families of proteins revealed that the paralogous clades were clear-cut representation of familial origin of the protein sequences. We observed divergence between the paralogous clades of plant-pathogenic fungi (Nectriaceae), insect-pathogenic fungi (Cordycipitaceae/Clavicipitaceae) and nematophagous fungi (Ophiocordycipitaceae). In addition, Subtilase genes from the nematode-parasitic fungus Purpureocillium lilacinum made a unique cluster which putatively indicated that the fungus might have developed distinctive mechanisms for nematode-pathogenesis. Our evolutionary genetics analysis revealed evidence of positive selection on the Subtilisin (S08.005) and Proteinase K (S08.054) protein sequences of the entomopathogenic and nematophagous species belonging to Cordycipitaceae, Clavicipitaceae and Ophiocordycipitaceae families of Hypocreales. Conclusions Our study provided new insights into the evolution of Subtilisin like serine proteases in Hypocreales, a fungal order largely consisting of biological control species. Subtilisin (S08.005) and Proteinase K (S08.054) proteins seemed to play important roles during life style modifications among different families and species of Hypocreales. Protein residues found significant in functional divergence analysis in the present study may provide support for protein engineering in future.

A new framework for measuring functional diversity (FD) from multiple traits has recently been proposed. This framework was mostly limited to quantitative traits without missing values and to situations in which there are more species than traits, although the authors had suggested a way to extend their framework to other trait types. The main purpose of this note is to further develop this suggestion. We describe a highly flexible distance‐based framework to measure different facets of FD in multidimensional trait space from any distance or dissimilarity measure, any number of traits, and from different trait types (i.e., quantitative, semi‐quantitative, and qualitative). This new approach allows for missing trait values and the weighting of individual traits. We also present a new multidimensional FD index, called functional dispersion (FDis), which is closely related to Rao's quadratic entropy. FDis is the multivariate analogue of the weighted mean absolute deviation (MAD), in which the weights are species relative abundances. For unweighted presence–absence data, FDis can be used for a formal statistical test of differences in FD. We provide the “FD” R language package to easily implement our distance‐based FD framework.

Question: Which functional diversity indices have the power to reveal changes in community assembly processes along abiotic stress gradients? Is their power affected by stochastic processes and variations in species richness along stress gradients? Methods: We used a simple community assembly model to explore the power of functional diversity indices across a wide range of ecological contexts. The model assumes that with declining stress the influence of niche complementarity on species fitness increases while that of environmental filtering decreases. We separately incorporated two trait-independent stochastic processes — mass and priority effects — in simulating species occurrences and abundances along a hypothetical stress gradient. We ran simulations where species richness was constant along the gradient, or increased, decreased or varied randomly with declining stress. We compared observed values for two indices of functional richness — total functional dendrogram length (FD) and convex hull volume (FRic) — with a matrix-swap null model (yielding indices SESFD and SESFRic) to remove any trivial effects of species richness. We also compared two indices that measure both functional richness and functional divergence — Rao quadratic entropy (Rao) and functional dispersion (FDis) — with a null model that randomizes abundances across species but within communities. This converts them to pure measures of functional divergence (SESRao and SESFDis). Results: When mass effects operated, only SESRao and SESFDis gave reasonable power, irrespective of how species richness varied along the stress gradient. FD, FRic, Rao and FDis had low power when species richness was constant, and variation in species richness greatly influenced their power. SESFRic and SESFD were unaffected by variation in species richness. When priority effects operated, FRic, SESFRic, Rao and FDis had good power and were unaffected by variation in species richness. Variation in species richness greatly affected FD and SESFD. SESRao and SESFDis had low power in the priority effects model but were unaffected by variation in species richness. Conclusions: Our results demonstrate that a reliable test for changes in assembly processes along stress gradients requires functional diversity indices measuring either functional richness or functional divergence. We recommend using SESFRic as a measure of functional richness and either SESRao or SESFDis (which are very closely related mathematically) as a measure of functional divergence. Used together, these indices of functional richness and functional divergence provide good power to test for increasing niche complementarity with declining stress across a broad range of ecological contexts.

1. Indices quantifying the functional aspect of biodiversity are essential in understanding relationships between biodiversity, ecosystem functioning and environmental constraints. Many indices of functional diversity have been published but we lack consensus about what indices quantify, how redundant they are and which ones are recommended. 2. This study aims to build a typology of functional diversity indices from artificial data sets encompassing various community structures (different assembly rules, various species richness levels) and to identify a set of independent indices able to discriminate community assembly rules. 3. Our results confirm that indices can be divided into three main categories, each of these corresponding to one aspect of functional diversity: functional richness, functional evenness and functional divergence. Most published indices are highly correlated and quantify functional richness while quadratic entropy (Q) represents a mix between functional richness and functional divergence. Conversely, two indices (FEve and FDiv respectively quantifying functional evenness and functional divergence) are rather independent to all the others. The power analysis revealed that some indices efficiently detect assembly rules while others performed poorly. 4. To accurately assess functional diversity and establish its relationships with ecosystem functioning and environmental constraints, we recommend investigating each functional component separately with the appropriate index. Guidelines are provided to help choosing appropriate indices given the issue being investigated. 5. This study demonstrates that functional diversity indices have the potential to reveal the processes that structure biological communities. Combined with complementary methods (phylogenetic and taxonomic diversity), the multifaceted framework of functional diversity will help improve our understanding of how biodiversity interacts with ecosystem processes and environmental constraints.

Understanding how ecosystem functioning is impacted by global change drivers is a central topic in ecology and conservation science. We need to assess not only how environmental change affects species richness, but also how the distribution of functional traits (i.e. functional diversity) mediate the relationship between species richness and ecosystem functioning. However, most evidence about the capacity of functional diversity to explain ecosystem functioning has been developed from studies conducted at a single spatial scale. Here, we explore theory, expectations and evidence for why and how species richness and functional diversity relationships vary with spatial scale. Despite the importance of accounting for spatial processes at multiple scales, we show that most studies of the species richness–functional diversity relationship focus on single scale analyses that ignore spatial context. Thus, we discuss the need to establish a spatially explicit, multi‐scale framework for understanding the relationship between species richness and functional diversity. As a starting point to developing such a framework, we detail some expected trajectories and mechanisms by which the diversity of species and functional traits may change across increasing spatial scales. We also explore what is known about two important gaps in the literature about this relationship: 1) the influence of spatial autocorrelation on community assembly processes and 2) the variation in the structure of species interactions across spatial extents. We present some key challenges that could be addressed by integrating approaches from community and landscape ecology. This information will help improve our understanding of the relative influence of local and large‐scale processes on community structure, while providing a foundation for improving biodiversity monitoring, policy and ecosystem function based conservation.

1. Functional diversity (FD) metrics are widely used to assess invasion ecosystem impacts, but we have limited theory to predict how FD should respond to invasion. A key challenge to effectively using FD metrics is the complexity of conceptualizing alterations to multidimensional trait space, making it difficult to select a priori the most appropriate metric for specific ecological questions. 2. Here, we provide expectations on how invasion should change four commonly used FD metrics—functional richness (FRic), evenness (FEve), divergence (FDiv) and dispersion (FDis)—and then test these expectations in a laboratory decomposition experiment. We simulate invasion of a forest by understorey plants by adding leaf litter from 18 natives and non-natives to a representative canopy tree litter mixture to test changes in FD and decomposition. 3. All four metrics changed predictably with invasion. Species that were more functionally unique or when added at greater proportions had larger impacts on FD. Overall, FRic, FEve and FDiv were poor choices for understanding impacts of non-native species. FDis was the only metric that both changed predictably with addition of understorey litter and correlated intuitively with changes in carbon mineralization. Furthermore, ranking species based upon how much they changed FDis of the litter mixture provided a fair assessment of which species had the largest impact on decomposition. As such, functional dispersion may be a key tool for predicting a priori which non-natives will have the greatest impact on ecosystem processes. 4. Synthesis. We highlight the need to assess the suitability of each functional diversity metric for the specific ecological question at hand. Our work reveals the pitfalls of considering multiple metrics or randomly choosing a single metric without suitability assessments. At the same time, it suggests a framework for metric assessment that should help lead to selection of a metric or metrics that provide robust a priori insights into how invasion by non-native species can impact ecosystem processes.

The study of functional diversity (FD) provides ways to understand phenomena as complex as community assembly or the dynamics of biodiversity change under multiple pressures. Different frameworks are used to quantify FD, either based on dissimilarity matrices (e.g. Rao entropy, functional dendrograms) or multidimensional spaces (e.g. convex hulls, kernel‐density hypervolumes), each with their own strengths and limits. Frameworks based on dissimilarity matrices either do not enable the measurement of all components of FD (i.e. richness, divergence, and regularity), or result in the distortion of the functional space. Frameworks based on multidimensional spaces do not allow for comparisons with phylogenetic diversity (PD) measures and can be sensitive to outliers. We propose the use of neighbor‐joining trees (NJ) to represent and quantify FD in a way that combines the strengths of current frameworks without many of their weaknesses. Importantly, our approach is uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles. We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel‐density hypervolumes using both simulated and empirical datasets. Using NJ, we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree‐based representations. Moreover, the method is directly comparable with taxonomic diversity (TD) and PD measures, and enables quantification of the richness, divergence and regularity of the functional space.

1. Understanding how environmental factors drive plant community assembly remains a major challenge in community ecology. The strength of different assembly processes along environmental gradients, such as environmental filtering and functional niche differentiation, can be quantified by analysing trait distributions in communities. While environmental filtering affects species occurrence among communities, functional divergence or convergence is strongly related to species abundances within communities, which few studies have taken into account. We examine the trait-mediated effect of these two processes along a stress-resource gradient. 2. We measured species abundances and the distributions of eight traits related to vegetative and regenerative phases in plant communities along a gradient of soil depth and resource availability in Mediterranean rangelands. We quantified environmental filtering, defined as a local restriction of trait range, and trait divergence, based on abundance-weighted trait variance, using a two-step approach with specifically designed null models. 3. Communities presented a clear functional response to the soil gradient, as evidenced by strong trends in community-weighted trait means. We detected environmental filtering of different traits at both ends of the gradient, suggesting that, contrary to widespread expectations, trait filtering may not necessarily be the result of abiotic filtering under harsh conditions but could likely also result from biotic interactions in productive habitats. 4. We found marked shifts in trait abundance distributions within communities along the gradient. Vegetative traits (e.g. leaf dry matter content) diverged on shallow soils, reflecting the coexistence of distinct water- and nutrient-use strategies in these constrained habitats and converged with increasing soil resource availability. By contrast, regenerative traits (e.g. seed mass) tended to diverge towards deeper soils, while plant reproductive heights diverged all along the gradient. 5. Synthesis: Our study highlights how the combination of abundance data with traits capturing different functional niches is critical to the detection of complex functional responses of plant communities to environmental gradients. We demonstrate that patterns of trait divergence and filtering are strongly contingent on both trait and environment such that there can be no expectation of a simple trend of increasing or decreasing functional divergence along a gradient of resource availability.