Maize centromeres: where sequence meets epigenetics

The centromere is a highly organized structure mainly composed of repeat sequences, which make this region extremely difficult for sequencing and other analyses. It plays a conserved role in equal division of chromosomes into daughter cells in both mitosis and meiosis. However, centromere sequences show notable plasticity. In a dicentric chromosome, one of the centromeres can become inactivated with the underlying DNA unchanged. Furthermore, formerly inactive centromeres can regain activity under certain conditions. In addition, neocentromeres without centromeric repeats have been found in a wide spectrum of species. This evidence indicates that epigenetic mechanisms together with centromeric sequences are associated with centromere specification.     

Somite formation: where left meets right

Somites are the bilaterally symmetric embryonic precursors of the vertebrate skeleton and axial muscle. Three recent studies reveal that somites form asymmetrically in the absence of retinoic acid signaling. These results uncover an unexpected relationship between somitogenesis and left-right patterning, and suggest that bilateral somite formation is regulated along the left-right axis.     

Cortical maps: where theory meets experiments

Primary visual cortex (V1) has remarkably systematic functional maps. One commonly used class of computational models proposes that such maps are generated by a mechanism that projects the multiple dimensions of neuronal responses smoothly onto the two dimensions of cortex. In this issue of Neuron, Mriganka Sur and colleagues find a close match between such model predictions and measurements from ferret V1.     

Plant transposable elements: where genetics meets genomics

Transposable elements are the single largest component of the genetic material of most eukaryotes. The recent availability of large quantities of genomic sequence has led to a shift from the genetic characterization of single elements to genome-wide analysis of enormous transposable-element populations. Nowhere is this shift more evident than in plants, in which transposable elements were first discovered and where they are still actively reshaping genomes.     

Hydrogen bonds in protein-DNA complexes: where geometry meets plasticity

Recognition of a DNA sequence by a protein is achieved by interface-coupled chemical and shape complementation. This complementation between the two molecules is clearly directional and is determined by the specific chemical contacts including mainly hydrogen bonds. Directionality is an instrumental property of hydrogen bonding as it influences molecular conformations, which also affects DNA-protein recognition. The prominent elements in the recognition of a particular DNA sequence by a protein are the hydrogen-bond donors and acceptors of the base pairs into the grooves of the DNA that must interact with complementary moieties of the protein partner. Protein side chains make most of the crucial contacts through bidentate and complex hydrogen-bonding interactions with DNA base edges hence conferring remarkable specificity.     

Quantitative biology: where modern biology meets physical sciences

Quantitative methods and approaches have been playing an increasingly important role in cell biology in recent years. They involve making accurate measurements to test a predefined hypothesis in order to compare experimental data with predictions generated by theoretical models, an approach that has benefited physicists for decades. Building quantitative models in experimental biology not only has led to discoveries of counterintuitive phenomena but has also opened up novel research directions. To make the biological sciences more quantitative, we believe a two-pronged approach needs to be taken. First, graduate training needs to be revamped to ensure biology students are adequately trained in physical and mathematical sciences and vice versa. Second, students of both the biological and the physical sciences need to be provided adequate opportunities for hands-on engagement with the methods and approaches necessary to be able to work at the intersection of the biological and physical sciences. We present the annual Physiology Course organized at the Marine Biological Laboratory (Woods Hole, MA) as a case study for a hands-on training program that gives young scientists the opportunity not only to acquire the tools of quantitative biology but also to develop the necessary thought processes that will enable them to bridge the gap between these disciplines.What does a mathematician looking at bacterial division under a microscope have in common with a biologist programming a stochastic simulation of microtubule growth? For one, both can be found at the Physiology Course at the Marine Biological Laboratory (MBL) in Woods Hole, MA, which brings together graduate students and young postdocs who have a passion for quantitative biology. Students enter the course with a wide array of scientific backgrounds, including chemistry, molecular biology, mathematics, and theoretical physics. Although at first hesitant to step outside their comfort zones, students leave the course confident and courageous in their abilities to work across traditional academic boundaries. Having experienced this transformation ourselves as participants in the 2014 Physiology Course, we wanted to share some of our insights and how they have influenced our perspectives on the present challenges and exciting future of quantitative cell biology.“When you cannot express [what you are speaking about] in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely, in your thoughts, advanced to the stage of science.” The need for quantification in the life sciences could not have been better worded than it is in this quote from Lord Kelvin. One of the key take-home messages from the course has been the crucial need for advancement of quantitative cell biology, which uses accurate measurements to refine a hypothesis, with the aim of comparing experimental data with predictions generated by theoretical models. We strongly believe that quantitative approaches not only aid in better addressing existing biological questions but also enable the formulation of new ones.The present time is particularly ripe for implementing quantitative approaches in cell biology, due to the wealth of data available and the depth of control we now have over many experimental systems. In the past 20 years, we have sequenced the human genome, broken the diffraction limit in microscopy, and begun to explore the possibilities of the micron-scaled experiments with microfluidics. With these tools in hand, the means to obtain quantitative data are not limited to a select few model systems; this level of experimental detail allows us to craft theoretical models that not only fit the data but have real predictive power. We can then return to our respective experimental systems with new hypotheses and interrogate them anew, reaping the benefits of an approach that has benefited physicists for decades.Building quantitative models in biology has been a powerful approach that has often revealed counterintuitive phenomena and insights while at the same time leading to novel research directions. This is of particular importance today, as experiments are becoming increasingly expensive and are rapidly accumulating vast amounts of data. It is now possible to perform “virtual” preliminary experiments in silico using quantitative models and pre-existing data and only then move to “real” laboratory experiments to test the developed hypotheses. Researchers trained this way can perform more focused experiments instead of adopting the traditional exploratory mode in the lab, saving both time and resources. However, we recognize that a majority of biology graduates have not been rigorously trained in the mathematical and physical sciences. Similarly, many physics graduates often remember their introductory biology classes simply for the rote memorization of protein names and signaling pathways, leading to the wrong assumption that biology is all about remembering three-letter abbreviations such as WNT, MYC, and so on. This can often create a misleading picture of biology.These challenges could be overcome by finding a common language between biologists, physicists, and mathematicians. A simple example of this is the word “model.” The same word can mean very different things to scientists depending upon their training: to a physicist it refers to quantitative visualization of a process via certain well-defined mathematical parameters; a biologist, on the other hand, might use the word to refer to a schematic depiction (also called a cartoon) of a biochemical reaction. We aim to reduce this gap between biological and physical sciences and bring these two communities together.One way to train young scientists in such an approach is to provide opportunities for hands-on engagement with the methods and thought processes necessary to partake in both fields. The MBL Physiology Course is an excellent case study for a training program that gives young scientists the building blocks and community necessary for success in bridging quantitative/physical sciences and biology. The course starts with a weeklong boot camp designed to bring students of different backgrounds up to speed on basic tools in quantitative biology. Students purify proteins, program in MATLAB, and build microscopes. The most important skill that biologists acquire is not simply learning how to write lines of MATLAB code, but rather phrasing biological phenomena in mathematical terms through equations and simulations. Building confocal microscopes and optical tweezers on a bare optical table creates trust in the tools we depend on to acquire quantitative data. Physicists, on the other hand, learn to purify motor proteins like kinesins and dyneins from native sources (squid), in the process coming face-to-face with the natural context of the biological questions that they are addressing.This interdisciplinary approach helps students from diverse backgrounds develop a common language. After the boot camp, students work together on three 2-week-long research projects under the guidance of leading scientists. Projects range from studying the spatial organization of the human oral microbiome and observing the development of the Caenorhabditis elegans embryo all the way to performing computational simulations of cytoskeletal polymers. By working together in a highly informal and stimulating environment, physicists learn to appreciate biological problems and biologists begin to see biological phenomena in a new light as a result of the novel physical tools and methodologies they learn from their peers. As an example, course participants Rikki Garner and Daniel Feliciano successfully collaborated to study how competition between two highly processive microtubule motors that work in opposition controls microtubule length. While Rikki (mentored by Jané Kondev) tackled the question theoretically using a random walk model, Daniel, under the mentorship of Joe Howard, carried out the experimental measurements via an in vitro assay to test Rikki''s predictions. Other examples of quantitative and biological expertise coming together to address biological questions include studying the displacement and transport of proteins at the interface between cells and synthetic supported lipid bilayers (Figure 1), observing and quantifying the cytoplasmic streaming as well as the filter-feeding flow vortices in the giant single-celled organism Stentor coeruleus (Figure 2), and imaging the spatial organization of complex oral microbial communities (Figure 3).Open in a separate windowFIGURE 1:Proteins are organized based on size at the membrane interface. The membrane interface between a cell and a supported lipid bilayer (SLB) was formed by the interaction of synthetic adhesion molecules, one protein (bound to the membrane via a His-tag) and another protein that interacts and binds with the membrane-bound protein (expressed in the S2 cells). Note that the long noninteracting protein (21 nm, magenta colored) but not the shorter noninteracting protein (8 nm, magenta colored), which is bigger than the synthetic interacting dimer (16 nm, red–green colored) is excluded from the cell–SLB interface. Both of these noninteracting proteins are bound to the SLB and do not interact with the cell. Scale bar: 10 μm. (Prepared by L.Z. and Nan Hyung Hong under the guidance of Matt Bakalar, Eva Schmid, and Dan Fletcher.)Open in a separate windowFIGURE 2:Stentor coeruleus is a giant single-celled organism that feeds by creating flow vortices in water and directing prey into its oral opening using this flow. (A) Maximum intensity projection of time-lapse images showing flow fields in the feeding flow generated by S. coeruleus. The flow is generated by the coordinated ciliary beating of the mouth cilia. (B) Flow velocity and flow directions were quantified by the particle image velocimetry method. The circularity of flow has also been indicated—the blue cloud around the oral cilia indicates clockwise flow, and red indicates anticlockwise flow. Scale bar: 100 μm. (Prepared by S.S. under the guidance of Mark Slabodnick, Tatyana Makushok, and Wallace Marshall in collaboration with Jack Costello, Providence College.)Open in a separate windowFIGURE 3:Spatial organization of complex microbial communities in an oral plaque sample taken from a volunteer as seen by combinatorial labeling and spectral imaging–fluorescent in situ hybridization (CLASI-FISH). Microbes seen here are Corynebacterium (pink), Neisseriaceae (blue), Fusobacterium (green), Pasteurellaceae (yellow), Streptococcus (cyan), and Actinomyces (red). (Prepared by Bryan Weinstein, Lishibanya Mohapatra, and Matti Gralka under the guidance of Blair Rossetti, Jessica Mark Welch, and Gary Borisy.)An invaluable aspect of the course is the informal nature of the interaction. There are a wide variety of morning seminar speakers, and in the question-and-answer sessions following the talks, the speakers discuss not only science but also the successes and failures they experienced while moving across the boundaries of biological and physical sciences. The interactive and collaborative nature of the course encourages students to not just learn from one another but to actually teach one another. “Chalk talks” and interactions happen spontaneously and are the strongest indication of the richness of the intellectual exchange among members of the community. Prime examples in the 2014 course are the chalk talks on Python (Bryan Weinstein), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) cloning (Dan Dickinson), and the basics of microfluidics (Sindy Tang).Although we have benefited immensely from this interdisciplinary course, we understand that it might not be feasible for all graduate students to participate in such courses. Nevertheless, we believe that the scientific community should work together to replicate elsewhere, at least partially, the strengths of this course to allow students to benefit from this approach. Students should be encouraged to host and attend seminars from speakers with diverse backgrounds, which will expose them to research areas different from their own. Biology students should also be exposed to mathematical and statistical instruction early in their research careers, preferably at the undergraduate level, to enable them to build strong foundations. Students should also be encouraged to participate in short-term, low-pressure interdisciplinary collaborations to broaden their understanding and initiate interactions with other fields. Short summer/winter schools—for example, the physical biology of the cell courses at Cold Spring Harbor and the International Centre for Theoretical Physics (Italy)–International Centre for Theoretical Sciences (India) Winter School on Quantitative Systems Biology, 2013, in Bangalore, India—can serve as the perfect stage for this.In conclusion, we expect that quantitative approaches will be indispensable for better addressing biological questions in the future. Our experience is that combining traditional experimental cell biology with quantitative thinking leads to hitherto unknown scientifically rich domains, and we ourselves have found this exploratory journey to be both achievable and rewarding. Although bridging the gap may appear to be difficult at times, it is extremely satisfying when accomplished, and doing it within a highly motivated and supportive community is what makes the connection possible and extremely useful.     

The role of amplifiers in sexual selection: An integration of the amplifying and the Fisherian mechanisms

Summary In a non-Fisherian genetic model I have shown that sexual displays can evolve even if displays are not directly and unconditionally preferred by females (a basic requirement in any Fisherian model), provided that they amplify previously recognized differences in male quality. Here I show how this amplifying mechanism interacts with the traditional Fisherian mechanism of sexual selection. The theory that integrates these two mechanisms provides a more robust, entirely selective scenario of the evolution of mating preferences and sexual displays.     

Retinoblastoma tumor suppressor: where cancer meets the cell cycle

The retinoblastoma tumor suppressor gene, Rb, was the first tumor suppressor identified and plays a fundamental role in regulation of progression through the cell cycle. This review details facets of RB protein function in cell cycle control and focuses on specific questions that remain intensive areas of investigation.     

Developmental phenotypic plasticity: where internal programming meets the external environment

Developmental plasticity has long been the focus of research in both evolutionary ecology and molecular genetics. Recently, the concept of ontogenetic contingency has been proposed to indicate the dependence of plastic responses on the timing and sequence of developmental events. Also, the idea of the developmental reaction norm has been put forward to indicate the complex interactions among development, phenotypic plasticity, and allometry of different structures. Finally, for the first time, studies ranging from the ecological to the molecular aspects of the same plastic response are available on insect and flowering plant model systems.     

Central B-cell tolerance: where selection begins

The development of an adaptive immune system based on the random generation of antigen receptors requires a stringent selection process that sifts through receptor specificities to remove those reacting with self-antigens. In the B-cell lineage, this selection process is first applied to IgM⁺ immature B cells. By using increasingly sophisticated mouse models, investigators have identified the central tolerance mechanisms that negatively select autoreactive immature B cells and prevent inclusion of their antigen receptors into the peripheral B-cell pool. Additional studies have uncovered mechanisms that promote the differentiation of nonautoreactive immature B cells and their positive selection into the peripheral B-cell population. These mechanisms of central selection are fundamental to the generation of a naïve B-cell repertoire that is largely devoid of self-reactivity while capable of reacting with any foreign insult.B-cell generation in the bone marrow of adult mammals occurs through a tightly controlled developmental process (Fig. 1). Productive rearrangement of immunoglobulin heavy (IgH) and light (IgL) chain gene segments in B lymphocyte precursor cells, in addition to the expression of Ig-α (CD79a) and Ig-β (CD79b), result in the generation and expression on the cell surface of a mature B-cell antigen receptor (BCR). Whereas the combination of Ig H and L chains determines the antigenic specificity of the newly formed BCR, their association with Ig-α and Ig-β allows transduction of a signal inside the cell that directs cell fate. Developing B cells first express a mature BCR on the cell surface in the form of IgM and as such are classified as immature B cells (Fig. 1) (Hardy et al. 1991; Pelanda et al. 1996). It is at the immature B-cell stage that the BCR is tested for the first time for reactivity against autoantigens. This test determines whether the immature B cell and the antibody it expresses on the surface will be selected into the peripheral B-cell repertoire. Central B-cell tolerance, in fact, refers to the process that negatively selects newly generated immature B cells that react with a self-antigen in the bone marrow environment. This is considered the first checkpoint of B-cell tolerance, and the results of this checkpoint are fundamental to the generation of a naïve repertoire that contains foreign reactive antibodies and is largely devoid of self-reactive specificities.Open in a separate windowFigure 1.Schematic representation of B-cell development and Ig loci in mice. Large pro-B cells initiate Ig gene rearrangement at the IgH locus. Expression of a H chain following a productive V_HD_HJ_H recombination event promotes the differentiation of large pre-B cells in which the expression of pre-BCR (H chain pairing with surrogate light chains) results in the clonal expansion of H chain-positive pre-B cells and the development of small pre-B cells. Expression of conventional L chains following productive rearrangements at the IgL chain loci in small pre-B cells promotes the development of a diverse population of IgM⁺ immature B cells, which then differentiate into IgM⁺IgD⁺ transitional B cells. The scheme of mouse Ig H, κ, and λ loci (not to scale) indicate the presence of V (white rectangles), D (black vertical lines), J (brown vertical lines; a dashed line indicates a nonfunctional element), and C (black rectangles; a gray rectangle indicates a nonfunctional element) gene segments. The scheme does not represent the number of V_H, D_H, and Vκ gene segments in the actual Ig loci.On passing this central checkpoint, immature B cells continue to differentiate into transitional and mature B cells before and after they travel to the spleen (Loder et al. 1999; Allman et al. 2001; Su and Rawlings 2002; Tarlinton et al. 2003). Analysis of the bone marrow early immature B-cell repertoire indicates that a staggering 50%–75% of these cells express BCRs that are specific for self-antigens, both in mice and humans (Grandien et al. 1994; Wardemann et al. 2003). Similar studies performed on cell populations at the other end of this central checkpoint, namely, transitional and naïve mature B cells in spleen and blood, show a much lower frequency (20%–40%) of cells expressing autoreactive antibodies (Grandien et al. 1994; Wardemann et al. 2003), demonstrating the stringency and limitation of this initial selection step. Moreover, individuals affected by autoimmune disease such as lupus erythematosus or rheumatoid arthritis bear many more autoreactive cells in their new emigrant and naïve B-cell populations (Samuels et al. 2005; Yurasov et al. 2005), indicating a defect in central (and/or peripheral) B-cell selection. Thus, it seems important that the development of autoreactive immature B cells be constrained to prevent the potential occurrence of autoimmunity. However, there are also reasons to believe that the high frequency of autoreactive specificities generated during primary Ig gene rearrangements may be necessary for the generation of the peripheral B-cell repertoire (Pelanda et al. 1997; Kohler et al. 2008). Indeed, a fraction of autoreactive immature B cells, those manifesting a low level of self-reactivity, do bypass the central checkpoint of tolerance and differentiate into mature B cells (Hayakawa et al. 2003; Wardemann et al. 2003; Wen et al. 2005). The inclusion of these weakly self-reactive B cells in the peripheral B-cell repertoire may allow recognition of a broader spectrum of foreign molecules, potentially decreasing the negative impact of infections, especially at early stages (Mouquet et al. 2010).What are the rules that govern the selection of immature B cells? Most studies of central tolerance have been conducted by following the selection of B cells expressing BCRs displaying well-defined reactivity for natural or synthetic self-antigens. This has been accomplished through the use of Ig transgenic mice in which developing B cells have been altered to carry prerearranged Ig H and L chain genes encoding antibodies of defined antigen specificity and reactivity. Here we review some of these studies, what we have learned from them, and open questions that still await answers.     

Evolution: radiotracking sexual selection

Why are members of one sex bigger than those of the other? A new study in which male giant weta were radiotracked found that smaller, longer legged males win the race to inseminate females.     

Natural selection on fecundity variance in subdivided populations: kin selection meets bet hedging

In a series of seminal articles in 1974, 1975, and 1977, J. H. Gillespie challenged the notion that the "fittest" individuals are those that produce on average the highest number of offspring. He showed that in small populations, the variance in fecundity can determine fitness as much as mean fecundity. One likely reason why Gillespie's concept of within-generation bet hedging has been largely ignored is the general consensus that natural populations are of large size. As a consequence, essentially no work has investigated the role of the fecundity variance on the evolutionary stable state of life-history strategies. While typically large, natural populations also tend to be subdivided in local demes connected by migration. Here, we integrate Gillespie's measure of selection for within-generation bet hedging into the inclusive fitness and game theoretic measure of selection for structured populations. The resulting framework demonstrates that selection against high variance in offspring number is a potent force in large, but structured populations. More generally, the results highlight that variance in offspring number will directly affect various life-history strategies, especially those involving kin interaction. The selective pressures on three key traits are directly investigated here, namely within-generation bet hedging, helping behaviors, and the evolutionary stable dispersal rate. The evolutionary dynamics of all three traits are markedly affected by variance in offspring number, although to a different extent and under different demographic conditions.     

Apis mellifera evolutionary lineages in Northern Africa: Libya, where orient meets occident

Abstract  The distribution of various evolutionary lineages of Apis mellifera subspecies in Africa is still controversial. We sampled honeybees from eight coastal locations and three Saharan oases in Libya and analyzed mtDNA variability with restriction fragment length polymorphisms and the sequence of the tRNAleu-cox2 intergenic region. Haplotypes belonging to the oriental O evolutionary lineage, including four which are newly described, were detected in all investigated locations. Haplotypes belonging to the European M lineage were rarely detected, probably reflecting the effect of sporadic importations. Honeybees belonging to the A lineage were detected in Al Aziziyah and Zlitan close to the Tunisian border. The distribution of the O lineage extends westward up to the border between Libya and Tunisia, a contact area between the O and A lineages. Various Libyan honeybee populations in Saharan oases are characterized by novel and unique haplotypes (O4, O5, O5′ and O5″). These might be natural relic populations that became isolated when the North African Sahara desert was still grassland (0.126–0.168 Myr ago).     

Adaptations to sexual selection and sexual conflict: insights from experimental evolution and artificial selection

Artificial selection and experimental evolution document natural selection under controlled conditions. Collectively, these techniques are continuing to provide fresh and important insights into the genetic basis of evolutionary change, and are now being employed to investigate mating behaviour. Here, we focus on how selection techniques can reveal the genetic basis of post-mating adaptations to sexual selection and sexual conflict. Alteration of the operational sex ratio of adult Drosophila over just a few tens of generations can lead to altered ejaculate allocation patterns and the evolution of resistance in females to the costly effects of elevated mating rates. We provide new data to show how male responses to the presence of rivals can evolve. For several traits, the way in which males responded to rivals was opposite in lines selected for male-biased, as opposed to female-biased, adult sex ratio. This shows that the manipulation of the relative intensity of intra- and inter-sexual selection can lead to replicable and repeatable effects on mating systems, and reveals the potential for significant contemporary evolutionary change. Such studies, with important safeguards, have potential utility for understanding sexual selection and sexual conflict across many taxa. We discuss how artificial selection studies combined with genomics will continue to deepen our knowledge of the evolutionary principles first laid down by Darwin 150 years ago.     

Good-genes effects in sexual selection

The magnitude of the effect of good genes as a viability benefit accruing to choosy females remains a controversial theoretical and empirical issue. We collected all available data from the literature to estimate the magnitude of good-genes viability effects, while adjusting for sample size. The average correlation coefficient between male traits and offspring survival in 22 studies was 0.122, which differed highly significantly from zero. This implies that male characters chosen by females reveal on average 1.5% of the variance in viability. The studies demonstrated considerable heterogeneity in effect size; some of this heterogeneity could be accounted for by differences among taxa (birds demonstrating stronger effects), and by differences in the degree of mating skew in the species (high skew reflecting stronger effects). Although these results suggest that viability-based sexual selection is widespread across taxa, they indicate that the effect is relatively minor. Finally, there was also an effect of publication year in that the more recent studies reported reduced effects. This may reflect publication biases during paradigm shifts of this debated issue, but it should also be recalled that the studies have only partly estimated the full fitness consequences of mate choice for offspring.     

Experimental sexual selection in Chlamydomonas

Sexual and asexual lines of the unicellular chlorophyte Chlamydomonas reinhardtii were propagated for about 100 sexual cycles and 1000 vegetative cycles in contrasted environments, liquid and solid growth media, in order to generate divergent natural and sexual selection. Sexual lines were transferred by many zygotes or by a single zygote in each sexual generation. By the end of the experiment zygote production was in the order sexual mass-transfer>sexual single-zygote>asexual>ancestor. The direct response to sexual selection was large, with zygote production increasing by about two orders of magnitude, mainly because mating had become spontaneous instead of being invoked by nitrogen starvation. Asexual lines became sexually sterilized by the fixation of a single mating type. Sexual selection caused a radical shift in the gender system, with homothallism spreading to high frequency in all sexual lines of this normally heterothallic species. This may have been caused by the transposition of a mating-type gene to an autosome. No substantial degree of environment-specific mating evolved, however, and thus no sexual isolation indicative of incipient speciation. It is possible that selection experiments of this kind are unlikely to induce sexual isolation because mating-type genes evolve in a saltatory fashion.     

The evolution of trans-generational altruism: kin selection meets niche construction

A cornerstone result of sociobiology states that limited dispersal can induce kin competition to offset the kin selected benefits of altruism. Several mechanisms have been proposed to circumvent this dilemma but all assume that actors and recipients of altruism interact during the same time period. Here, this assumption is relaxed and a model is developed where individuals express an altruistic act, which results in posthumously helping relatives living in the future. The analysis of this model suggests that kin selected benefits can then feedback on the evolution of the trait in a way that promotes altruistic helping at high rates under limited dispersal. The decoupling of kin competition and kin selected benefits results from the fact that by helping relatives living in the future, an actor is helping individuals that are not in direct competition with itself. A direct consequence is that behaviours which actors gain by reducing the common good of present and future generations can be opposed by kin selection. The present model integrates niche-constructing traits with kin selection theory and delineates demographic and ecological conditions under which altruism can be selected for; and conditions where the 'tragedy of the commons' can be reduced.     

Hamilton's rule meets the Hamiltonian: kin selection on dynamic characters

Many biological characters of interest are temporal sequences of decisions. The evolution of such characters is often modelled using dynamic optimization methods such as the maximum principle. A quantity central to these analyses is the ''Hamiltonian'' function, named after the mathematician William R. Hamilton. On the other hand, evolutionary models in which individuals interact with relatives are usually based on Hamilton''s rule, named after the evolutionary biologist William D. Hamilton. In this article we present a generalized maximum principle that includes the effects of interactions among relatives and we show that a time-dependent (dynamic) version of Hamilton''s rule holds involving the Hamiltonian. This result brings together the power and generality of both the maximum principle and Hamilton''s rule thereby providing a natural framework for understanding the evolution of ''dynamic'' characters under kin selection.     

Sexual dichromatism in frogs: natural selection, sexual selection and unexpected diversity

Sexual dichromatism, a form of sexual dimorphism in which males and females differ in colour, is widespread in animals but has been predominantly studied in birds, fishes and butterflies. Moreover, although there are several proposed evolutionary mechanisms for sexual dichromatism in vertebrates, few studies have examined this phenomenon outside the context of sexual selection. Here, we describe unexpectedly high diversity of sexual dichromatism in frogs and create a comparative framework to guide future analyses of the evolution of these sexual colour differences. We review what is known about evolution of colour dimorphism in frogs, highlight alternative mechanisms that may contribute to the evolution of sexual colour differences, and compare them to mechanisms active in other major groups of vertebrates. In frogs, sexual dichromatism can be dynamic (temporary colour change in males) or ontogenetic (permanent colour change in males or females). The degree and the duration of sexual colour differences vary greatly across lineages, and we do not detect phylogenetic signal in the distribution of this trait, therefore frogs provide an opportunity to investigate the roles of natural and sexual selection across multiple independent derivations of sexual dichromatism.