Sperm biology pervades numerous research areas from clinical research to evolutionary biology and animal conservation. Integrating these fields for a better understanding of each is one of the main goals of the Biology of Spermatozoa meeting, a conference held biennially outside of Sheffield in the United Kingdom. This September, at the 11th meeting, scientists from around the globe presented their ongoing research on numerous aspects of reproductive biology, from assisted reproduction in humans and animal conservation through stem cell research and proteomics to sophisticated evolutionary adaptations of ejaculates and female reproductive traits in order to bias paternity toward one or the other male in situations of female promiscuity. Throughout the conference, ethical controversies with reproductive applications (e.g., sperm banking) found their place just as much as novel clinical technologies (e.g., sperm quality assays) or major advances in understanding the mechanisms underlying fundamental processes of postcopulatory sexual selection (e.g., using transgenic animals that produce fluorescently labeled sperm). Across a wide range of different taxa, this meeting has presented a fascinating synthesis of current research and emerging directions in the study of sperm biology.

All evolutionary biologists are familiar with evolutionary units that evolve by vertical descent in a tree-like fashion in single lineages. However, many other kinds of processes contribute to evolutionary diversity. In vertical descent, the genetic material of a particular evolutionary unit is propagated by replication inside its own lineage. In what we call introgressive descent, the genetic material of a particular evolutionary unit propagates into different host structures and is replicated within these host structures. Thus, introgressive descent generates a variety of evolutionary units and leaves recognizable patterns in resemblance networks. We characterize six kinds of evolutionary units, of which five involve mosaic lineages generated by introgressive descent. To facilitate detection of these units in resemblance networks, we introduce terminology based on two notions, P3s (subgraphs of three nodes: A, B, and C) and mosaic P3s, and suggest an apparatus for systematic detection of introgressive descent. Mosaic P3s correspond to a distinct type of evolutionary bond that is orthogonal to the bonds of kinship and genealogy usually examined by evolutionary biologists. We argue that recognition of these evolutionary bonds stimulates radical rethinking of key questions in evolutionary biology (e.g....

As part of BioMed Central’s open science mission, we are pleased to announce that two of our journals have integrated with the open data repository Dryad. Authors submitting their research to either BMC Ecology or BMC Evolutionary Biology will now have the opportunity to deposit their data directly into the Dryad archive and will receive a permanent, citable link to their dataset. Although this does not affect any of our current data deposition policies at these journals, we hope to encourage a more widespread adoption of open data sharing in the fields of ecology and evolutionary biology by facilitating this process for our authors. We also take this opportunity to discuss some of the wider issues that may concern researchers when making their data openly available. Although we offer a number of positive examples from different fields of biology, we also recognise that reticence to data sharing still exists, and that change must be driven from within research communities in order to create future science that is fit for purpose in the digital age.

As part of BioMed Central’s open science mission, we are pleased to announce that two of our journals have integrated with the open data repository Dryad. Authors submitting their research to either BMC Ecology or BMC Evolutionary Biology will now have the opportunity to deposit their data directly into the Dryad archive and will receive a permanent, citable link to their dataset. Although this does not affect any of our current data deposition policies at these journals, we hope to encourage a more widespread adoption of open data sharing in the fields of ecology and evolutionary biology by facilitating this process for our authors. We also take this opportunity to discuss some of the wider issues that may concern researchers when making their data openly available. Although we offer a number of positive examples from different fields of biology, we also recognise that reticence to data sharing still exists, and that change must be driven from within research communities in order to create future science that is fit for purpose in the digital age.

Well-studied innate immune systems exist throughout bacteria and archaea, but a more recently discovered genomic locus may offer prokaryotes surprising immunological adaptability. Mediated by a cassette-like genomic locus termed Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), the microbial adaptive immune system differs from its eukaryotic immune analogues by incorporating new immunities unidirectionally. CRISPR thus stores genomically recoverable timelines of virus-host coevolution in natural organisms refractory to laboratory cultivation. Here we combined a population genetic mathematical model of CRISPR-virus coevolution with six years of metagenomic sequencing to link the recoverable genomic dynamics of CRISPR loci to the unknown population dynamics of virus and host in natural communities. Metagenomic reconstructions in an acid-mine drainage system document CRISPR loci conserving ancestral immune elements to the base-pair across thousands of microbial generations. This ‘trailer-end conservation’ occurs despite rapid viral mutation and despite rapid prokaryotic genomic deletion. The trailer-ends of many reconstructed CRISPR loci are also largely identical across a population. ‘Trailer-end clonality’ occurs despite predictions of host immunological diversity due to negative frequency dependent selection (kill the winner dynamics). Statistical clustering and model simulations explain this lack of diversity by capturing rapid selective sweeps by highly immune CRISPR lineages. Potentially explaining ‘trailer-end conservation...

The Australo-Papuan fairy-wrens, emu-wrens and grasswrens comprise the passerine family Maluridae. They have long been known for their spectacular plumages, remarkable behavioural ecology and intriguing biogeography. The family has provided an ideal model with which to explore how phylogenetic and phylogeographic analyses of DNA-sequence data can inform understanding of evolutionary history and present-day biology. We review what has been learned of the phylogeny of the group and the phylogeographic history of individual species. We conclude that there is now a strong framework within which to pursue the remaining species-level taxonomic issues, and to extend ecological and behavioural studies into a new era of more detailed genetic questions such as the role of gene–environment interactions in adaptation. We highlight some remaining examples of such questions and discuss how they might be addressed.; Organismic and Evolutionary Biology

Understanding how complex organisms function as integrated units that constantly interact with their environment is a long-standing challenge in biology. To address this challenge, organismal biology reveals general organizing principles of physiological systems and behavior—in particular, in complex multicellular animals. Organismal biology also focuses on the role of individual variability in the evolutionary maintenance of diversity. To broadly advance these frontiers, cross-compatibility of experimental designs, methodological approaches, and data interpretation pipelines represents a key prerequisite. It is now possible to rapidly and systematically analyze complete genomes to elucidate genetic variation associated with traits and conditions that define individuals, populations, and species. However, genetic variation alone does not explain the varied individual physiology and behavior of complex organisms. We propose that such emergent properties of complex organisms can best be explained through a renewed emphasis on the context and life-history dependence of individual phenotypes to complement genetic data.; Organismic and Evolutionary Biology

Erythropoiesis is one of the best understood examples of cellular differentiation. Morphologically, erythroid differentiation proceeds in a nearly identical fashion between humans and mice, but recent evidence has shown that networks of gene expression governing this process are divergent between species. We undertook a systematic comparative analysis of six histone modifications and four transcriptional master regulators in primary proerythroblasts and erythroid cell lines to better understand the underlying basis of these transcriptional differences. Our analyses suggest that while chromatin structure across orthologous promoters is strongly conserved, subtle differences are associated with transcriptional divergence between species. Many transcription factor (TF) occupancy sites were poorly conserved across species (∼25% for GATA1, TAL1, and NFE2) but were more conserved between proerythroblasts and cell lines derived from the same species. We found that certain cis-regulatory modules co-occupied by GATA1, TAL1, and KLF1 are under strict evolutionary constraint and localize to genes necessary for erythroid cell identity. More generally, we show that conserved TF occupancy sites are indicative of active regulatory regions and strong gene expression that is sustained during maturation. Our results suggest that evolutionary turnover of TF binding sites associates with changes in the underlying chromatin structure...

Gene flow, or the exchange of genes between populations, is important because it determines the evolutionary trajectory of a species, including the relative influences of genetic drift and natural selection in the process of population differentiation. Gene flow differs among species because of variation in dispersal capability and abundances across taxa, and historical forces related to geological or lineage history. Both history and ecology influence gene flow in potentially complicated ways, and accounting for their effects remains an important problem in evolutionary biology. This research is a comparative study of gene flow and life-history in a monophyletic group of stream fishes, the darters. As a first step in disentangling historical and ecological effects, I reconstructed the phylogenetic relationships of the study species from nucleotide sequences in the mtDNA control region. I then used this phylogeny and regional glaciation history to infer historical effects on life-history evolution and gene flow in 15 species of darters. Gene flow was estimated indirectly, using information from 20 resolvable and polymorphic allozyme loci. When I accounted for historical effects, comparisons across taxa revealed that gene flow rates were closely associated with differences in clutch sizes and reproductive investment patterns. I hypothesized that differences in larval dispersal among taxa explained this relationship. Results from a field study of larval drift were consistent with this hypothesis. Finally...

The gecko genus Phyllopezus occurs across South America's open biomes: Cerrado, Seasonally Dry Tropical Forests (SDTF, including Caatinga), and Chaco. We generated a multi-gene dataset and estimated phylogenetic relationships among described Phyllopezus taxa and related species. We included exemplars from both described Phyllopezus pollicaris subspecies, P. p. pollicaris and P. p. przewalskii. Phylogenies from the concatenated data as well as species trees constructed from individual gene trees were largely congruent. All phylogeny reconstruction methods showed Bogertia lutzae as the sister species of Phyllopezus maranjonensis, rendering Phyllopezus paraphyletic. We synonymized the monotypic genus Bogertia with Phyllopezus to maintain a taxonomy that is isomorphic with phylogenetic history. We recovered multiple, deeply divergent, cryptic lineages within P. pollicaris. These cryptic lineages possessed mtDNA distances equivalent to distances among other gekkotan sister taxa. Described P. pollicaris subspecies are not reciprocally monophyletic and current subspecific taxonomy does not accurately reflect evolutionary relationships among cryptic lineages. We highlight the conservation significance of these results in light of the ongoing habitat loss in South America's open biomes. (C) 2011 Elsevier Inc. All rights reserved.; NSF [DEB 0515909]; NSF; Department of Fisheries...

The ability to estimate the evolutionary distance between extant genomes plays a crucial role in many phylogenomic studies. Often such estimation is based on the parsimony assumption, implying that the distance between two genomes can be estimated as the minimal number of genome rearrangements required to transform one genome into the other. However, in reality the parsimony assumption may not always hold, emphasizing the need for estimation that does not rely on the minimal number of genome rearrangements. While there exists a method for such estimation, it however assumes that genomes can be broken by rearrangements equally likely at any position in the course of evolution. This assumption, known as the random breakage model, has recently been refuted in favor of the more rigorous fragile breakage model postulating that only certain "fragile" genomic regions are prone to rearrangements. We propose a new method for estimating the evolutionary distance between two genomes with high accuracy under the fragile breakage model.

A tumor often consists of multiple cell subpopulations (clones). Current chemo-treatments often target one clone of a tumor. Although the drug kills that clone, other clones overtake it and the tumor reoccurs. Genome sequencing and computational analysis allows to computational dissection of clones from tumors, while singe-cell genome sequencing including RNA-Seq allows to profiling of these clones. This opens a new window for treating a tumor as a system in which clones are evolving. Future cancer systems biology studies should consider a tumor as an evolving system with multiple clones. Therefore, topics discussed in Part 2 of this review include evolutionary dynamics of clonal networks, early-warning signals for formation of fast-growing clones, dissecting tumor heterogeneity, and modeling of clone-clone-stroma interactions for drug resistance. The ultimate goal of the future systems biology analysis is to obtain a whole-system understanding of a tumor and therefore provides a more efficient and personalized management strategies for cancer patients.; Comment: 2 figs. Related papers can be found at http://www.cancer-systemsbiology.org, Seminar in Cancer Biology, 2013

Two giants of evolutionary theory, Sewall Wright and R. A. Fisher, fought bitterly for over thirty years. The Wright-Fisher controversy forms a cornerstone of the history and philosophy of biology. I argue that the standard interpretations of the Wright-Fisher controversy do not accurately represent the ideas and arguments of these two key historical figures. The usual account contrasts the major slogans attached to each name: Wright's adaptive landscape and shifting balance theory of evolution versus Fisher's fundamental theorem of natural selection. These alternative theories are in fact incommensurable. Wright's theory is a detailed dynamical model of evolutionary change in actual populations. Fisher's theory is an abstract invariance and conservation law that, like all physical laws, captures essential features of a system but does not account for all aspects of dynamics in real examples. This key contrast between embodied theories of real cases and abstract laws is missing from prior analyses of Wright versus Fisher. They never argued about this contrast. Instead, the issue at stake in their arguments concerned the actual dynamics of real populations. Both agreed that fluctuations of nonadditive (epistatic) gene combinations play a central role in evolution. Wright emphasized stochastic fluctuations of gene combinations in small...

Adaptation is a central topic in theoretical biology, of practical importance for analyzing drug resistance mutations. Several authors have used arguments based on extreme value theory in their work on adaptation. There are complications with these approaches if fitness is additive (meaning that fitness effects of mutations sum), or whenever there is more additivity than what one would expect in an uncorrelated fitness landscape. However, the approaches have been used in published work, even in situations with substantial amounts of additivity. In particular, extreme value theory has been used in discussions on evolutionary predictability. We say that evolution is predictable if the use of a particular drug at different locations tends lead to the same resistance mutations. Evolutionary predictability depends on the probabilities of mutational trajectories. Arguments about probabilities based on extreme value theory can be misleading. Additivity may cause errors in estimates of the probabilities of some mutational trajectories by a factor 20 even for rather small examples. We show that additivity gives systematic errors so as to exaggerate the differences between the most and the least likely trajectory. As a result of this bias, evolution may appear more predictable than it is. From a broader perspective...

We study a version of the Tangled Nature model of evolutionary ecology redefined in a phenotype space where mutants have properties correlated to their parents. The model has individual-based dynamics whilst incorporating species scale competitive constraints and a system scale resource constraint. Multiple species arise that coexist in a species interaction network with evolving global properties. Both the mean interaction strength and the network connectance increase relative to the null system as mutualism becomes more extensive. From a study of the dependence of average degree on the resource level we extract the diversity-connectance relationship which conforms to the hyperbolic form seen in field data. This is adjudged to arise as a consequence of the evolutionary pressure to achieve positive interactions. The network degree distributions conform more strongly to exponential than to the null binomial distributions in all cases. This effect is believed to be caused by correlations in the reproductive process. We also study how resource availability influences the phenotypical lifetime distribution which is approximately of power law form. We observe that the mean lifetime is inversely related to the resource level.; Comment: 18 pages and 9 figures

The evolution of cooperation has been a perennial problem in evolutionary biology because cooperation can be undermined by selfish cheaters who gain an advantage in the short run, while compromising the long-term viability of the population. Evolutionary game theory has shown that under certain conditions, cooperation nonetheless evolves stably, for example if players have the opportunity to punish cheaters that benefit from a public good yet refuse to pay into the common pool. However, punishment has remained enigmatic because it is costly, and difficult to maintain. On the other hand, cooperation emerges naturally in the Public Goods game if the synergy of the public good (the factor multiplying the public good investment) is sufficiently high. In terms of this synergy parameter, the transition from defection to cooperation can be viewed as a phase transition with the synergy as the critical parameter. We show here that punishment reduces the critical value at which cooperation occurs, but also creates the possibility of meta-stable phase transitions, where populations can "tunnel" into the cooperating phase below the critical value. At the same time, cooperating populations are unstable even above the critical value, because a group of defectors that are large enough can "nucleate" such a transition. We study the mean-field theoretical predictions via agent-based simulations of finite populations using an evolutionary approach where the decisions to cooperate or to punish are encoded genetically in terms of evolvable probabilities. We recover the theoretical predictions and demonstrate that the population shows hysteresis...

The prevalence of neutral mutations implies that biological systems typically have many more genotypes than phenotypes. But can the way that genotypes are distributed over phenotypes determine evolutionary outcomes? Answering such questions is difficult because the number of genotypes can be hyper-astronomically large. By solving the genotype-phenotype (GP) map for RNA secondary structure for systems up to length $L=126$ nucleotides (where the set of all possible RNA strands would weigh more than the mass of the visible universe) we show that the GP map strongly constrains the evolution of non-coding RNA (ncRNA). Simple random sampling over genotypes predicts the distribution of properties such as the mutational robustness or the number of stems per secondary structure found in naturally occurring ncRNA with surprising accuracy. Since we ignore natural selection, this strikingly close correspondence with the mapping suggests that structures allowing for functionality are easily discovered, despite the enormous size of the genetic spaces. The mapping is extremely biased: the majority of genotypes map to an exponentially small portion of the morphospace of all biophysically possible structures. Such strong constraints provide a non-adaptive explanation for the convergent evolution of structures such as the hammerhead ribozyme. These results presents a particularly clear example of bias in the arrival of variation strongly shaping evolutionary outcomes and may be relevant to Mayr's distinction between proximate and ultimate causes in evolutionary biology.; Comment: new version with some small tweaks to clarify the conclusions and some minor corrections

Evolutionary game dynamics describes not only frequency dependent genetical evolution, but also cultural evolution in humans. In this context, successful strategies spread by imitation. It has been shown that the details of strategy update rules can have a crucial impact on evolutionary dynamics in theoretical models and e.g. significantly alter the level of cooperation in social dilemmas. But what kind of strategy update rules can describe imitation dynamics in humans? Here, we present a way to measure such strategy update rules in a behavioral experiment. We use a setting in which individuals are virtually arranged on a spatial lattice. This produces a large number of different strategic situations from which we can assess strategy updating. Most importantly, spontaneous strategy changes corresponding to mutations or exploration behavior are more frequent than assumed in many models. Our experimental approach to measure properties of the update mechanisms used in theoretical models will be useful for mathematical models of cultural evolution.; Comment: PNAS, in press

The cellular theory on the nature of life has been one of the first major advancements in biology. Viruses, however, are the most abundant life forms, and their exclusion from mainstream biology and the Tree of Life (TOL) is a major paradox in biology. This article presents a broad, unifying scenario on the origin and evolution of cellular and viral domains that challenges the conventional views about the history of life and supports a TOL that includes viruses. Co-evolution of viruses and their host cells has led to some of the most remarkable developments and transitions in the evolution of life, including the origin of non-coding DNA as a genomic protective device against viral insertion damage. However, one of the major fundamental evolutionary developments driven by viruses was probably the origin of cellular domains - Bacteria, Archaea and Eukarya - from the Last Universal Common Ancestor (LUCA) lineage, by evolving anti-fusion mechanisms. Consistent with a novel fusion/fission model for the population mode of evolution of LUCA, this paper presents a “cell-like world” model for the origin of life. According to this model the evolution of coupled replication, transcription and translation system (RT&T) occurred within non-living cell-like compartments (CCs). In this model...