Revising the global biogeography of plant life cycles

There are two main life cycles in plants, annual and perennial. These life cycles are associated with different traits, which determine ecosystem function. Although life cycles are textbook examples of plant adaptation to different environments, we lack comprehensive knowledge regarding global distributional patterns. Here, we assembled an extensive database of plant life cycle assignments of 235,000 plant species coupled with millions of georeferenced datapoints to map the worldwide biogeography of life cycles. We found that annuals are half as common as initially thought, accounting for only 6% of species. Our analyses indicate annuals are favored in hot and dry regions. However, a more accurate model shows annual species' prevalence is driven by temperature and precipitation in the driest quarter (rather than yearly means), explaining, for example, why some Mediterranean systems have more annuals than deserts. Furthermore, this pattern remains consistent among different families, indicating convergent evolution. Finally, we demonstrate that increasing climate variability and anthropogenic disturbance increase annual favorability. Considering future climate change, we predict an increase in annual prevalence for 81% of the world's ecoregions by 2100. Overall, our analyses raise concerns for ecosystem services provided by perennials as ongoing changes are leading to a more annuals-dominated world.Comment: 49 pages, 10 figures, 5 table

Epitopia: a web-server for predicting B-cell epitopes

<p>Abstract</p> <p>Background</p> <p>Detecting candidate B-cell epitopes in a protein is a basic and fundamental step in many immunological applications. Due to the impracticality of experimental approaches to systematically scan the entire protein, a computational tool that predicts the most probable epitope regions is desirable.</p> <p>Results</p> <p>The Epitopia server is a web-based tool that aims to predict immunogenic regions in either a protein three-dimensional structure or a linear sequence. Epitopia implements a machine-learning algorithm that was trained to discern antigenic features within a given protein. The Epitopia algorithm has been compared to other available epitope prediction tools and was found to have higher predictive power. A special emphasis was put on the development of a user-friendly graphical interface for displaying the results.</p> <p>Conclusion</p> <p>Epitopia is a user-friendly web-server that predicts immunogenic regions for both a protein structure and a protein sequence. Its accuracy and functionality make it a highly useful tool. Epitopia is available at <url>http://epitopia.tau.ac.il</url> and includes extensive explanations and example predictions.</p

A LASSO-based approach to sample sites for phylogenetic tree search

Motivation In recent years, full-genome sequences have become increasingly available and as a result many modern phylogenetic analyses are based on very long sequences, often with over 100 000 sites. Phylogenetic reconstructions of large-scale alignments are challenging for likelihood-based phylogenetic inference programs and usually require using a powerful computer cluster. Current tools for alignment trimming prior to phylogenetic analysis do not promise a significant reduction in the alignment size and are claimed to have a negative effect on the accuracy of the obtained tree. Results Here, we propose an artificial-intelligence-based approach, which provides means to select the optimal subset of sites and a formula by which one can compute the log-likelihood of the entire data based on this subset. Our approach is based on training a regularized Lasso-regression model that optimizes the log-likelihood prediction accuracy while putting a constraint on the number of sites used for the approximation. We show that computing the likelihood based on 5% of the sites already provides accurate approximation of the tree likelihood based on the entire data. Furthermore, we show that using this Lasso-based approximation during a tree search decreased running-time substantially while retaining the same tree-search performance

Sex determination, longevity, and the birth and death of reptilian species

Vertebrate sex-determining mechanisms (SDMs) are triggered by the genotype (GSD), by temperature (TSD), or occasionally, by both. The causes and consequences of SDM diversity remain enigmatic. Theory predicts SDM effects on species diversification, and life-span effects on SDM evolutionary turnover. Yet, evidence is conflicting in clades with labile SDMs, such as reptiles. Here, we investigate whether SDM is associated with diversification in turtles and lizards, and whether alterative factors, such as lifespan\u27s effect on transition rates, could explain the relative prevalence of SDMs in turtles and lizards (including and excluding snakes). We assembled a comprehensive dataset of SDM states for squamates and turtles and leveraged large phylogenies for these two groups. We found no evidence that SDMs affect turtle, squamate, or lizard diversification. However, SDM transition rates differ between groups. In lizards TSD-to-GSD surpass GSD-to-TSD transitions, explaining the predominance of GSD lizards in nature. SDM transitions are fewer in turtles and the rates are similar to each other (TSD-to-GSD equals GSD-to-TSD), which, coupled with TSD ancestry, could explain TSD\u27s predominance in turtles. These contrasting patterns can be explained by differences in life history. Namely, our data support the notion that in general, shorter lizard lifespan renders TSD detrimental favoring GSD evolution in squamates, whereas turtle longevity permits TSD retention. Thus, based on the macro-evolutionary evidence we uncovered, we hypothesize that turtles and lizards followed different evolutionary trajectories with respect to SDM, likely mediated by differences in lifespan. Combined, our findings revealed a complex evolutionary interplay between SDMs and life histories that warrants further research that should make use of expanded datasets on unexamined taxa to enable more conclusive analyses

Synonymous site conservation in the HIV-1 genome

Background: Synonymous or silent mutations are usually thought to evolve neutrally. However, accumulating recent evidence has demonstrated that silent mutations may destabilize RNA structures or disrupt cis regulatory motifs superimposed on coding sequences. Such observations suggest the existence of stretches of codon sites that are evolutionary conserved at both DNA-RNA and protein levels. Such stretches may point to functionally important regions within protein coding sequences not necessarily reflecting functional constraints on the amino-acid sequence. The HIV-1 genome is highly compact, and often harbors overlapping functional elements at the protein, RNA, and DNA levels. This superimposition of functions leads to complex selective forces acting on all levels of the genome and proteome. Considering the constraints on HIV-1 to maintain such a highly compact genome, we hypothesized that stretches of synonymous conservation would be common within its genome. Results: We used a combined computational-experimental approach to detect and characterize regions exhibiting strong purifying selection against synonymous substitutions along the HIV-1 genome. Our methodology is based on advanced probabilistic evolutionary models that explicitly account for synonymous rate variation among sites and rate dependencies among adjacent sites. These models are combined with a randomization procedure to automatically identify the most statistically significant regions of conserved synonymous sites along the genome. Using this procedure we identified 21 conserved regions. Twelve of these are mapped to regions within overlapping genes, seven correlate with known functional elements, while the functions of the remaining four are yet unknown. Among these four regions, we chose the one that deviates most from synonymous rate homogeneity for in-depth computational and experimental characterization. In our assays aiming to quantify viral fitness in both early and late stages of the replication cycle, no differences were observed between the mutated and the wild type virus following the introduction of synonymous mutations. Conclusions: The contradiction between the inferred purifying selective forces and the lack of effect of these mutations on viral replication may be explained by the fact that the phenotype was measured in single-cycle infection assays in cell culture. Such a system does not account for the complexity of HIV-1 infections in vivo, which involves multiple infection cycles and interaction with the host immune system

Tree of Sex: A database of sexual systems

The vast majority of eukaryotic organisms reproduce sexually, yet the nature of the sexual system and the mechanism of sex determination often vary remarkably, even among closely related species. Some species of animals and plants change sex across their lifespan, some contain hermaphrodites as well as males and females, some determine sex with highly differentiated chromosomes, while others determine sex according to their environment. Testing evolutionary hypotheses regarding the causes and consequences of this diversity requires interspecific data placed in a phylogenetic context. Such comparative studies have been hampered by the lack of accessible data listing sexual systems and sex determination mechanisms across the eukaryotic tree of life. Here, we describe a database developed to facilitate access to sexual system and sex chromosome information, with data on sexual systems from 11,038 plant, 705 fish, 173 amphibian, 593 non-avian reptilian, 195 avian, 479 mammalian, and 11,556 invertebrate species

Epitope mapping using combinatorial phage-display libraries: a graph-based algorithm

A phage-display library of random peptides is a combinatorial experimental technique that can be harnessed for studying antibody–antigen interactions. In this technique, a phage peptide library is scanned against an antibody molecule to obtain a set of peptides that are bound by the antibody with high affinity. This set of peptides is regarded as mimicking the genuine epitope of the antibody's interacting antigen and can be used to define it. Here we present PepSurf, an algorithm for mapping a set of affinity-selected peptides onto the solved structure of the antigen. The problem of epitope mapping is converted into the task of aligning a set of query peptides to a graph representing the surface of the antigen. The best match of each peptide is found by aligning it against virtually all possible paths in the graph. Following a clustering step, which combines the most significant matches, a predicted epitope is inferred. We show that PepSurf accurately predicts the epitope in four cases for which the epitope is known from a solved antibody–antigen co-crystal complex. We further examine the capabilities of PepSurf for predicting other types of protein–protein interfaces. The performance of PepSurf is compared to other available epitope mapping programs

An Evolutionary Analysis of Lateral Gene Transfer in Thymidylate Synthase Enzymes

Thymidylate synthases (Thy) are key enzymes in the synthesis of deoxythymidylate, 1 of the 4 building blocks of DNA. As such, they are essential for all DNA-based forms of life and therefore implicated in the hypothesized transition from RNA genomes to DNA genomes. Two evolutionally unrelated Thy enzymes, ThyA and ThyX, are known to catalyze the same biochemical reaction. Both enzymes are sporadically distributed within each of the 3 domains of life in a pattern that suggests multiple nonhomologous lateral gene transfer (LGT) events. We present a phylogenetic analysis of the evolution of the 2 enzymes, aimed at unraveling their entangled evolutionary history and tracing their origin back to early life. A novel probabilistic evolutionary model was developed, which allowed us to compute the posterior probabilities and the posterior expectation of the number of LGT events. Simulation studies were performed to validate the model's ability to accurately detect LGT events, which have occurred throughout a large phylogeny. Applying the model to the Thy data revealed widespread nonhomologous LGT between and within all 3 domains of life. By reconstructing the ThyA and ThyX gene trees, the most likely donor of each LGT event was inferred. The role of viruses in LGT of Thy is finally discussed

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Sex Determination:Why So Many Ways of Doing It?

Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination