Evolution and medicine in undergraduate education: a prescription for all biology students

The interface between evolutionary biology and the biomedical sciences promises to advance understanding of the origins of genetic and infectious diseases in humans, potentially leading to improved medical diagnostics, therapies, and public health practices. The biomedical sciences also provide unparalleled examples for evolutionary biologists to explore. However, gaps persist between evolution and medicine, for historical reasons and because they are often perceived as having disparate goals. Evolutionary biologists have a role in building a bridge between the disciplines by presenting evolutionary biology in the context of human health and medical practice to undergraduates, including premedical and preprofessional students. We suggest that students will find medical examples of evolution engaging. By making the connections between evolution and medicine clear at the undergraduate level, the stage is set for future health providers and biomedical scientists to work productively in this synthetic area. Here, we frame key evolutionary concepts in terms of human health, so that biomedical examples may be more easily incorporated into evolution courses or more specialized courses on evolutionary medicine. Our goal is to aid in building the scientific foundation in evolutionary biology for all students, and to encourage evolutionary biologists to join in the integration of evolution and medicine.     

Spatial and Temporal Simulation of Human Evolution. Methods,Frameworks and Applications

Analyses of human evolution are fundamental to understand the current gradients of human diversity. In this concern, genetic samples collected from current populations together with archaeological data are the most important resources to study human evolution. However, they are often insufficient to properly evaluate a variety of evolutionary scenarios, leading to continuous debates and discussions. A commonly applied strategy consists of the use of computer simulations based on, as realistic as possible, evolutionary models, to evaluate alternative evolutionary scenarios through statistical correlations with the real data. Computer simulations can also be applied to estimate evolutionary parameters or to study the role of each parameter on the evolutionary process. Here we review the mainly used methods and evolutionary frameworks to perform realistic spatially explicit computer simulations of human evolution. Although we focus on human evolution, most of the methods and software we describe can also be used to study other species. We also describe the importance of considering spatially explicit models to better mimic human evolutionary scenarios based on a variety of phenomena such as range expansions, range shifts, range contractions, sex-biased dispersal, long-distance dispersal or admixtures of populations. We finally discuss future implementations to improve current spatially explicit simulations and their derived applications in human evolution.     

Network thinking in ecology and evolution

Although pairwise interactions have always had a key role in ecology and evolutionary biology, the recent increase in the amount and availability of biological data has placed a new focus on the complex networks embedded in biological systems. The increased availability of computational tools to store and retrieve biological data has facilitated wide access to these data, not just by biologists but also by specialists from the social sciences, computer science, physics and mathematics. This fusion of interests has led to a burst of research on the properties and consequences of network structure in biological systems. Although traditional measures of network structure and function have started us off on the right foot, an important next step is to create biologically realistic models of network formation, evolution, and function. Here, we review recent applications of network thinking to the evolution of networks at the gene and protein level and to the dynamics and stability of communities. These studies have provided new insights into the organization and function of biological systems by applying existing techniques of network analysis. The current challenge is to recognize the commonalities in evolutionary and ecological applications of network thinking to create a predictive science of biological networks.     

BIOCOMPUTATION: Some history and prospects

At first glance, biology and computer science are diametrically opposed sciences. Biology deals with carbon based life forms shaped by evolution and natural selection. Computer Science deals with electronic machines designed by engineers and guided by mathematical algorithms. In this brief paper, we review biologically inspired computing. We discuss several models of computation which have arisen from various biological studies. We show what these have in common, and conjecture how biology can still suggest answers and models for the next generation of computing problems. We discuss computation and argue that these biologically inspired models do not extend the theoretical limits on computation. We suggest that, in practice, biological models may give more succinct representations of various problems, and we mention a few cases in which biological models have proved useful. We also discuss the reciprocal impact of computer science on biology and cite a few significant contributions to biological science.     

Guidelines: From artificial evolution to computational evolution: a research agenda

Computational scientists have developed algorithms inspired by natural evolution for at least 50 years. These algorithms solve optimization and design problems by building solutions that are 'more fit' relative to desired properties. However, the basic assumptions of this approach are outdated. We propose a research programme to develop a new field: computational evolution. This approach will produce algorithms that are based on current understanding of molecular and evolutionary biology and could solve previously unimaginable or intractable computational and biological problems.     

Developing a Curriculum for Evolutionary Medicine: Case Studies of Scurvy and Female Reproductive Tract Cancers

Most early evolutionary thinkers came from medicine, yet evolution has had a checkered history in medical education. It is only in the last few decades that serious efforts have begun to be made to integrate evolutionary biology into the medical curriculum. However, it is not clear when, where (independently or as part of preclinical or clinical teaching courses) and, most importantly, how should medical students learn the basic principles of evolutionary biology applied to medicine, known today as evolutionary or Darwinian medicine. Most clinicians are ill-prepared to teach evolutionary biology and most evolutionary biologists ill-equipped to formulate clinical examples. Yet, if evolutionary science is to have impact on clinical thought, then teaching material that embeds evolution within the clinical framework must be developed. In this paper, we use two clinical case studies to demonstrate how such may be used to teach evolutionary medicine to medical students in a way that is approachable as well as informative and relevant.     

Acceptance of Evolution Increases with Student Academic Level: A Comparison Between a Secular and a Religious College

Acceptance of evolution among the general public, high schools, teachers, and scientists has been documented in the USA; little is known about college students’ views on evolution; this population is relevant since it transits from a high-school/parent-protective environment to an independent role in societal decisions. Here we compare perspectives about evolution, creationism, and intelligent design (ID) between a secular (S) and a religious (R) college in the Northeastern USA. Interinstitutional comparisons showed that 64% (mean S + R) biology majors vs. 42/62% (S/R) nonmajors supported the exclusive teaching of evolution in science classes; 24/29% (S/R) biology majors vs. 26/38% (S/R) nonmajors perceived ID as both alternative to evolution and/or scientific theory about the origin of life; 76% (mean S + R) biology majors and nonmajors accepted evolutionary explanations about the origin of life; 86% (mean S + R) biology majors vs. 79% (mean S + R) nonmajors preferred science courses where human evolution is discussed; 76% (mean S+R) biology majors vs. 79% (mean S + R) nonmajors welcomed questions about evolution in exams and/or thought that such questions should always be in exams; and 66% (mean S + R) biology majors vs. 46% (mean S + R) nonmajors admitted they accept evolution openly and/or privately. Intrainstitutional comparisons showed that overall acceptance of evolution among biologists (S or R) increased gradually from the freshman to the senior year, due to exposure to upper-division courses with evolutionary content. College curricular/pedagogical reform should fortify evolution literacy at all education levels, particularly among nonbiologists.     

Orchid diversity: an evolutionary consequence of deception?

The Orchidaceae are one of the most species-rich plant families and their floral diversity and pollination biology have long intrigued evolutionary biologists. About one-third of the estimated 18,500 species are thought to be pollinated by deceit. To date, the focus has been on how such pollination evolved, how the different types of deception work, and how it is maintained, but little progress has been made in understanding its evolutionary consequences. To address this issue, we discuss here how deception affects orchid mating systems, the evolution of reproductive isolation, speciation processes and neutral genetic divergence among species. We argue that pollination by deceit is one of the keys to orchid floral and species diversity. A better understanding of its evolutionary consequences could help evolutionary biologists to unravel the reasons for the evolutionary success of orchids.     

A database of vertebrate longevity records and their relation to other life‐history traits

Longevity is a major characteristic of animals that has long fascinated scientists. In this work, we present a comprehensive database of animal longevity records and related life‐history traits entitled AnAge, which we compiled and manually curated from an extensive literature. AnAge started as a collection of longevity records, but has since been expanded to include quantitative data for numerous other life‐history traits, including body masses at different developmental stages, reproductive data such as age at sexual maturity and measurements of reproductive output, and physiological traits related to metabolism. AnAge features over 4000 vertebrate species and is a central resource for applying the comparative method to studies of longevity and life‐history evolution across the tree of life. Moreover, by providing a reference value for longevity and other life‐history traits, AnAge can prove valuable to a broad range of biologists working in evolutionary biology, ecology, zoology, physiology and conservation biology. AnAge is freely available online ( http://genomics.senescence.info/species/ ).     

Phylogenetic systematics turns over a new leaf

Long restricted to the domain of molecular systematics and studies of molecular evolution, likelihood methods are now being used in analyses of discrete morphological data, specifically to estimate ancestral character states and for tests of character correlation. Biologists are beginning to apply likelihood models within a Bayesian statistical framework, which promises not only to provide answers that evolutionary biologists desire, but also to make practical the application of more realistic evolutionary models.     

Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.     

INTEGRATING FOSSILS WITH MOLECULAR PHYLOGENIES IMPROVES INFERENCE OF TRAIT EVOLUTION

Comparative biologists often attempt to draw inferences about tempo and mode in evolution by comparing the fit of evolutionary models to phylogenetic comparative data consisting of a molecular phylogeny with branch lengths and trait measurements from extant taxa. These kinds of approaches ignore historical evidence for evolutionary pattern and process contained in the fossil record. In this article, we show through simulation that incorporation of fossil information dramatically improves our ability to distinguish among models of quantitative trait evolution using comparative data. We further suggest a novel Bayesian approach that allows fossil information to be integrated even when explicit phylogenetic hypotheses are lacking for extinct representatives of extant clades. By applying this approach to a comparative dataset comprising body sizes for caniform carnivorans, we show that incorporation of fossil information not only improves ancestral state estimates relative to those derived from extant taxa alone, but also results in preference of a model of evolution with trend toward large body size over alternative models such as Brownian motion or Ornstein–Uhlenbeck processes. Our approach highlights the importance of considering fossil information when making macroevolutionary inference, and provides a way to integrate the kind of sparse fossil information that is available to most evolutionary biologists.     

An emerging synthesis between community ecology and evolutionary biology

A synthesis between community ecology and evolutionary biology is emerging that identifies how genetic variation and evolution within one species can shape the ecological properties of entire communities and, in turn, how community context can govern evolutionary processes and patterns. This synthesis incorporates research on the ecology and evolution within communities over short timescales (community genetics and diffuse coevolution), as well as macroevolutionary timescales (community phylogenetics and co-diversification of communities). As we discuss here, preliminary evidence supports the hypothesis that there is a dynamic interplay between ecology and evolution within communities, yet researchers have not yet demonstrated convincingly whether, and under what circumstances, it is important for biologists to bridge community ecology and evolutionary biology. Answering this question will have important implications for both basic and applied problems in biology.     

Modeling planarian regeneration: a primer for reverse-engineering the worm

A mechanistic understanding of robust self-assembly and repair capabilities of complex systems would have enormous implications for basic evolutionary developmental biology as well as for transformative applications in regenerative biomedicine and the engineering of highly fault-tolerant cybernetic systems. Molecular biologists are working to identify the pathways underlying the remarkable regenerative abilities of model species that perfectly regenerate limbs, brains, and other complex body parts. However, a profound disconnect remains between the deluge of high-resolution genetic and protein data on pathways required for regeneration, and the desired spatial, algorithmic models that show how self-monitoring and growth control arise from the synthesis of cellular activities. This barrier to progress in the understanding of morphogenetic controls may be breached by powerful techniques from the computational sciences-using non-traditional modeling approaches to reverse-engineer systems such as planaria: flatworms with a complex bodyplan and nervous system that are able to regenerate any body part after traumatic injury. Currently, the involvement of experts from outside of molecular genetics is hampered by the specialist literature of molecular developmental biology: impactful collaborations across such different fields require that review literature be available that presents the key functional capabilities of important biological model systems while abstracting away from the often irrelevant and confusing details of specific genes and proteins. To facilitate modeling efforts by computer scientists, physicists, engineers, and mathematicians, we present a different kind of review of planarian regeneration. Focusing on the main patterning properties of this system, we review what is known about the signal exchanges that occur during regenerative repair in planaria and the cellular mechanisms that are thought to underlie them. By establishing an engineering-like style for reviews of the molecular developmental biology of biomedically important model systems, significant fresh insights and quantitative computational models will be developed by new collaborations between biology and the information sciences.     

Bridging the gap between developmental systems theory and evolutionary developmental biology

Many scientists and philosophers of science are troubled by the relative isolation of developmental from evolutionary biology. Reconciling the science of development with the science of heredity preoccupied a minority of biologists for much of the twentieth century, but these efforts were not corporately successful. Mainly in the past fifteen years, however, these previously dispersed integrating programmes have been themselves synthesized and so reinvigorated. Two of these more recent synthesizing endeavours are evolutionary developmental biology (EDB, or "evo-devo") and developmental systems theory (DST). While the former is a bourgeoning and scientifically well-respected biological discipline, the same cannot be said of DST, which is virtually unknown among biologists. In this review, we provide overviews of DST and EDB, summarize their key tenets, examine how they relate to one another and to the study of epigenetics, and survey the impact that DST and EDB have had (and in future should have) on biological theory and practice.     

The genetic equidistance result: misreading by the molecular clock and neutral theory and reinterpretation nearly half of a century later

In 1963,Margoliash discovered the unexpected genetic equidistance result after comparing cytochrome c sequences from different species.This finding,together with the hemoglobin analyses of Zuckerkandl and Pauling in 1962,directly inspired the ad hoc molecular clock hypothesis.Unfortunately,however,many biologists have since mistakenly viewed the molecular clock as a genuine reality,which in turn inspired Kimura,King,and Jukes to propose the neutral theory of molecular evolution.Many years of studies have found numerous contradictions to the theory,and few today believe in a universal constant clock.What is being neglected,however,is that the failure of the molecular clock hypothesis has left the original equidistance result an unsolved mystery.In recent years,we fortuitously rediscovered the equidistance result,which remains unknown to nearly all researchers.Incorporating the proven virtues of existing evolutionary theories and introducing the novel concept of maximum genetic diversity,we proposed a more complete hypothesis of evolutionary genetics and reinterpreted the equidistance result and other major evolutionary phenomena.The hypothesis may rewrite molecular phylogeny and population genetics and solve major biomedical problems that challenge the existing framework of evolutionary biology.     

Historic and functional biology: the inadequacy of a system theory of evolution

In the first half of the 20th century neo-Kantianism in a broad sense proved itself the main conceptual and methodological background of the central European biology. As such it contributed much to the victory on the typological, idealistic-morphological and psycho-vitalistic interpretations of life. On the other hand it could not give tools to the biologists for working out a strictly darwinian evolution theory. Kant's theory of organism was conceived without evolution as a theory of the internal functionality of the organism. There was only some 'play' with the evolutionary differentiation of the species. Since then the disputes around the work of August Weismann, a synthetical evolution theory which is now behind time, arose. This theory developed from coinciding claims, elaborated by geneticists, mathematicians, and by biologists studying development, natural history and systematics. This was done under a strong influence of marxist ideas. Through the interweaving of such different approaches it was possible for this evolutionary synthesis to influence successfully the development of evolution research during more than 40 years. Philosophically speaking modern evolution theory means therefore an aversion, even a positive abolition of Kantian positions. A number of biologists however--as L. von Bertalanffy--refused to adhere to a misinterpreted Kantian methodology and oriented themselves to an approach via system theory, which obtained a place in evolution research. In fact this is a Kantian approach as well. They only repeated the Kantian dilemma of the evolution which can also be found in Lamarck and Hegel. The system theory of the functionality of the organism never reaches to the level of the evolving species, but remains always on the level of epigenetic thinking, because of its philosophical origin. This paper points out the consequences of this still current dilemma. At the same time an all-enclosing reflection on the methodological, epistemological and the important historical questions of evolutionary biology in its scientific context is recommended.     

Pollen—Tiny and ephemeral but not forgotten: New ideas on their ecology and evolution

Ecologists and evolutionary biologists have been interested in the functional biology of pollen since the discovery in the 1800s that pollen grains encompass tiny plants (male gametophytes) that develop and produce sperm cells. After the discovery of double fertilization in flowering plants, botanists in the early 1900s were quick to explore the effects of temperature and maternal nutrients on pollen performance, while evolutionary biologists began studying the nature of haploid selection and pollen competition. A series of technical and theoretic developments have subsequently, but usually separately, expanded our knowledge of the nature of pollen performance and how it evolves. Today, there is a tremendous diversity of interests that touch on pollen performance, ranging from the ecological setting on the stigma, structural and physiological aspects of pollen germination and tube growth, the form of pollen competition and its role in sexual selection in plants, virus transmission, mating system evolution, and inbreeding depression. Given the explosion of technical knowledge of pollen cell biology, computer modeling, and new methods to deal with diversity in a phylogenetic context, we are now more than ever poised for a new era of research that includes complex functional traits that limit or enhance the evolution of these deceptively simple organisms.     

Opening Darwin's black box: teaching evolution through developmental genetics

When biologists are asked to discuss the evidence for evolution at public forums, they usually use well-established microevolutionary examples. Although these examples show the efficacy of evolution within species, they often leave audiences susceptable to the arguments of creationists who deny that evolution can create new structures and species. Recent studies from evolutionary developmental biology are beginning to provide case studies that specifically address these concerns. This perspective presents some of this new evidence and provides a framework in which to explain homology and phylogeny to such audiences.     

Flexible ligand docking using evolutionary algorithms: investigating the effects of variation operators and local search hybrids

The docking of ligands to proteins can be formulated as a computational problem where the task is to find the most favorable energetic conformation among the large space of possible protein-ligand complexes. Stochastic search methods such as evolutionary algorithms (EAs) can be used to sample large search spaces effectively and is one of the commonly used methods for flexible ligand docking. During the last decade, several EAs using different variation operators have been introduced, such as the ones provided with the AutoDock program. In this paper we evaluate the performance of different EA settings such as choice of variation operators, population size, and usage of local search. The comparison is performed on a suite of six docking problems previously used to evaluate the performance of search algorithms provided with the AutoDock program package. The results from our investigation confirm that the choice of variation operators has an impact on the search-capabilities of EAs. The introduced DockEA using the best settings found obtained the overall best docking solutions compared to the Lamarckian GA (LGA) provided with AutoDock. Furthermore, the DockEA proved to be more robust than the LGA (in terms of reproducing the results in several runs) on the more difficult problems with a high number of flexible torsion angles.