Emerging infectious disease: what are the relative roles of ecology and evolution?

The increasing threat of infectious diseases in humans has renewed interest in factors leading to the emergence of new diseases and the re-emergence of familiar diseases. Examples of seemingly novel diseases currently spreading in human populations include HIV, dengue hemorrhagic fever and Lyme disease; drug-resistant forms of well-known diseases such as tuberculosis are also increasing. The problem of disease emergence also extends to other animal and plant populations. In most current epidemics, ecological factors (e.g. migration, climate, agricultural practices) play a more significant role in disease emergence than evolutionary changes in pathogens or hosts. Evolutionary biologists and ecologists have much to offer to the development of strategies for the control of emerging diseases.     

Insurance and genetic testing: where are we now?

Basic research will spur development of genetic tests that are capable of presymptomatic prediction of disease, disability, and premature death in presently asymptomatic individuals. Concerns have been expressed about potential harms related to the use of genetic test results, especially loss of confidentiality, eugenics, and discrimination. Existing laws and administrative policies may not be sufficient to assure that genetic information is used fairly. To provide factual information and conceptual principles upon which sound social policy can be based, the Human Genome Initiative established an Ethical, Legal, and Social Issues Program. Among the first areas to be identified as a priority for study was insurance. This paper provides a review of life, health, and disability insurance systems, including basic principles, risk classification, and market and regulatory issues, and examines the potential impact of genetic information on the insurance industry.     

Revealing the genetic basis of multiple sclerosis: are we there yet?

For more than 30 years the only genetic factor associated with susceptibility to multiple sclerosis (MS) was the human leukocyte antigen (HLA) region. Recent advancements in genotyping platforms and the development of more effective statistical methods resulted in the identification of 16 more genes by genome-wide association studies (GWAS) in the last three years alone. While the effect of each of these genes is modest compared to that of HLA, this list is expected to grow significantly in the near future, thus defining a complex landscape in which susceptibility may be determined by a combination of allelic variants in different pathways according to ethnic background, disease sub-type, and specific environmental triggers. A considerable overlap of susceptibility genes among multiple autoimmune diseases is becoming evident and integration of these genetic variants with our current knowledge of affected biological pathways will greatly improve our understanding of mechanisms of general autoimmunity and of tissue specificity.     

Models of human genetic disease: how biased are the standard formulae?

Standard theory provides a simple prediction for the frequency of a recessive lethal allele conferring heterozygous protection against an infectious disease (the best-known example being sickle cell protection against malaria). This relationship allows historic disease mortality rates to be estimated. There are, however, hidden biases in this approach. Reproductively active human females in archaic societies normally produce children at intervals of around 4 years. If death of the fetus or young infant (less than around 3 years of age) occurs, then the mother re-enters oestrus and produces another child. This 'reproductive compensation' reduces selection against the agent causing early mortality (the recessive allele or infective agent) and biases our estimates of historic mortality rates. The magnitude of these biases is investigated. Re-conception also constitutes a demographic selective pressure acting alongside natural selection: lethal genetic diseases (or tightly linked loci) will be selected to become ever more virulent, killing at ever decreasing ages, to allow the mother to re-enter oestrus and re-conceive a (hopefully unaffected) sibling; this effect also invalidates statistical tests using the number of alleles to distinguish overdominance from drift as explanations for high allele frequency. The same bias affects calculations of mutation/selection balance: for any given mutation rate, syndromes which kill early in life will reach much higher frequencies than those killing at later ages. An intriguing consequence is that lethal recessive disorders in humans will increase in frequency by up to 45% as a consequence of the recent demographic transition to planned family size.     

Ancient vs. recent processes as factors shaping the genetic variation of the European wild boar: are the effects of the last glaciation still detectable?

The European wild boar is an important game species, subjected to local extinctions and translocations in the past, and currently enormously and worryingly expanding in some areas where management is urgently required. Understanding the relative roles of ancient and recent events in shaping the genetic structure of this species is therefore not only an interesting scientific issue, but it represents also the basis for addressing future management strategies. In addition, several pig breeds descend from the European wild boar, but the geographical location of the domestication area(s) and the possible introgression of pig genomes into wild populations are still open questions. Here, we analysed the genetic variation in different wild boar populations in Europe. Ten polymorphic microsatellites were typed in 252 wild boars and the mtDNA control region was sequenced in a subset of 145 individuals. Some samples from different pig breeds were also analysed. Our results, which were obtained considering also 612 published mtDNA sequences, suggest that (i) most populations are similarly differentiated, but the major discontinuity is found along the Alps; (ii) except for the Italian populations, European wild boars show the signature of a postglacial demographic expansion; (iii) Italian populations seem to preserve a high proportion of preglaciation diversity; (iv) the demographic decline which occurred in some areas in the last few centuries did not produce a noticeable reduction of genetic variation; (v) signs of human-mediated gene flow among populations are weak, although in some regions the effects of translocations are detectable and a low degree of pig introgression can be identified; (vi) the hypothesis of an independent domestication centre in Italy is not supported by our data, which in turn confirm that Central European wild boar might have represented an important source for domestic breeds. We can therefore conclude that recent human activities had a limited effect on the wild boar genetic structure. It follows that areas with high variation and differentiation represent natural reservoirs of genetic diversity to be protected avoiding translocations. In this context controlling some populations by hunting is not expected to affect significantly genetic variation in this species.     

Do genetic variations alter the effects of exercise training on cardiovascular disease and can we identify the candidate variants now or in the future?

Cardiovascular disease (CVD) and CVD risk factors are highly heritable, and numerous lines of evidence indicate they have a strong genetic basis. While there is nothing known about the interactive effects of genetics and exercise training on CVD itself, there is at least some literature addressing their interactive effect on CVD risk factors. There is some evidence indicating that CVD risk factor responses to exercise training are also heritable and, thus, may have a genetic basis. While roughly 100 studies have reported significant effects of genetic variants on CVD risk factor responses to exercise training, no definitive conclusions can be generated at the present time, because of the lack of consistent and replicated results and the small sample sizes evident in most studies. There is some evidence supporting "possible" candidate genes that may affect these responses to exercise training: APO E and CETP for plasma lipoprotein-lipid profiles; eNOS, ACE, EDN1, and GNB3 for blood pressure; PPARG for type 2 diabetes phenotypes; and FTO and BAR genes for obesity-related phenotypes. However, while genotyping technologies and statistical methods are advancing rapidly, the primary limitation in this field is the need to generate what in terms of exercise intervention studies would be almost incomprehensible sample sizes. Most recent diabetes, obesity, and blood pressure genetic studies have utilized populations of 10,000-250,000 subjects, which result in the necessary statistical power to detect the magnitude of effects that would probably be expected for the impact of an individual gene on CVD risk factor responses to exercise training. Thus at this time it is difficult to see how this field will advance in the future to the point where robust, consistent, and replicated data are available to address these issues. However, the results of recent large-scale genomewide association studies for baseline CVD risk factors may drive future hypothesis-driven exercise training intervention studies in smaller populations addressing the impact of specific genetic variants on well-defined physiological phenotypes.     

Candidate genes versus genome-wide associations: which are better for detecting genetic susceptibility to infectious disease?

Technological developments allow increasing numbers of markers to be deployed in case-control studies searching for genetic factors that influence disease susceptibility. However, with vast numbers of markers, true 'hits' may become lost in a sea of false positives. This problem may be particularly acute for infectious diseases, where the control group may contain unexposed individuals with susceptible genotypes. To explore this effect, we used a series of stochastic simulations to model a scenario based loosely on bovine tuberculosis. We find that a candidate gene approach tends to have greater statistical power than studies that use large numbers of single nucleotide polymorphisms (SNPs) in genome-wide association tests, almost regardless of the number of SNPs deployed. Both approaches struggle to detect genetic effects when these are either weak or if an appreciable proportion of individuals are unexposed to the disease when modest sample sizes (250 each of cases and controls) are used, but these issues are largely mitigated if sample sizes can be increased to 2000 or more of each class. We conclude that the power of any genotype-phenotype association test will be improved if the sampling strategy takes account of exposure heterogeneity, though this is not necessarily easy to do.     

Neurochemical dementia diagnostics in Alzheimer's disease: where are we now and where are we going?

Neurochemical dementia diagnostics (NDD) is a routine laboratory tool used in the diagnostic process for patients with neurodegenerative disorders, such as Alzheimer's disease. Currently, two groups of biomarkers analyzed in the cerebrospinal fluid are considered - namely amyloid-β peptides and Tau proteins - along with the hyperphosphorylated forms of the latter (pTau). Current directions in the development of NDD include the following: search for novel biomarkers with improved analytical or diagnostic performance; optimization of the analysis of the biomarkers already available (e.g., by improved quality control and interlaboratory comparison of results); applications of novel technologies enabling better management of patient samples; and search for biomarkers in the blood. This article presents the state-of-the-art in the field of cerebrospinal fluid-based NDD, and also summarizes some of the hypotheses of how the future development of NDD tools might look.     

Indirect genetic effects and the lek paradox: inter-genotypic competition may strengthen genotype × environment interactions and conserve genetic variance

Understanding the evolutionary mechanisms that maintain genetic variation in natural populations is one of the fundamental goals of evolutionary biology. There is growing evidence that genotype-by-environment interaction (G × E) can maintain additive genetic variance (V _A), but we lack information on the relative performance of genotypes under the competitive situations encountered in the field. Competing genotypes may influence each other, and this interaction is also subject to selection through indirect genetic effects (IGE). Here, we explore how genotypes perform when interacting and evaluate IGE in order to understand its influence on V _A for sexually-selected traits in the lesser waxmoth, Achroia grisella. We found that inter-genotype differences and crossover interactions under joint rearing are equal to or greater than values when reared separately. A focal genotype exhibited different performances when jointly reared with various genotypes—suggesting that IGE may be responsible for the increased levels of crossover and differences in performance observed. We suggest that some genotypes are superior competitors for food acquisition in the larval stage, and that these differences influence the development and evolution of other genotypes through IGE. We reaffirm the role of G × E in maintaining V _A and note the general importance of IGE in studies of evolutionary mechanisms.     

Understanding the underlying mechanisms governing spindle orientation: How far are we from there?

Proper spindle orientation is essential for cell fate determination and tissue morphogenesis. Recently, accumulating studies have elucidated several factors that regulate spindle orientation, including geometric, internal and external cues. Abnormality in these factors generally leads to defects in the physiological functions of various organs and the development of severe diseases. Herein, we first review models that are commonly used for studying spindle orientation. We then review a conservative heterotrimeric complex critically involved in spindle orientation regulation in different models. Finally, we summarize some cues that affect spindle orientation and explore whether we can establish a model that precisely elucidates the effects of spindle orientation without interfusing other spindle functions. We aim to summarize current models used in spindle orientation studies and discuss whether we can build a model that disturbs spindle orientation alone. This can substantially improve our understanding of how spindle orientation is regulated and provide insights to investigate this complex event.     

How does the magnitude of genetic variation affect ecological and reproductive character displacement?

While previous studies on character displacement tended to focus on trait divergence and convergence as a result of long-term evolution, recent studies suggest that character displacement can be a special case of evolutionary rescue, where rapid evolution prevents species extinction by weakening interspecific competition. Here we analyzed a simple model to examine how the magnitude of genetic variation affects evolutionary rescue via ecological and reproductive character displacement that weakens interspecific competition in exploitation of shared resources (i.e., resource competition) and in the mating process caused by incomplete species recognition (i.e., reproductive interference), respectively. We found that slow trait divergence due to small genetic variance results in species extinction in reproductive character displacement but not in ecological character displacement. This is because one species becomes rare in slow character displacement, and this causes deterministic extinction due to minority disadvantage of reproductive interference. On the other hand, there is no deterministic extinction in the process of ecological character displacement. Furthermore, species extinction becomes less likely in the case of positive covariance between ecological and reproductive traits as divergence of the ecological trait (e.g., root depths) increases the divergence speed of the reproductive trait (e.g., flower colors) and vice versa. It will be interesting to compare intraspecific genetic (co)variance of ecological and reproductive traits in future studies for understanding how ecological and reproductive character displacement occur without extinction.     

Translational behaviour‐genetic studies of alcohol: are we there yet?

In biomedical research, one key stage of translating basic science knowledge to clinical practice is the reconciliation of phenotypes employed for laboratory animal studies with those important for the clinical condition. Alcohol dependence (AD) is a prototypic complex genetic trait. There is a long history of behaviour-genetic studies of AD in both human subjects and various genetic animal models. This review assesses the state of the art in our understanding of the genetic contributions to AD. In particular, it primarily focuses on the phenotypes studied in mouse genetic animal models, comparing them to the aspects of the human condition they are intended to target. It identifies several features of AD where genetic animal models have been particularly useful, and tries to identify understudied areas where there is good promise for further genetic animal model work.     

Morphological and genetic variation in the endangered Sulawesi tortoise Indotestudo forstenii: evidence of distinct lineages?

Limited fieldwork and anecdotal evidence indicate that allopatric populations of the endangered Sulawesi tortoise (Indotestudo forstenii) differ in size and presence/absence of a nuchal scute, suggesting that these may constitute separate evolutionary lineages. We examined morphological and genetic variation to determine if the nuchal scute is correlated with size or genetic divergence. Our results indicate a strong correlation between size and nuchal scute such that turtles lacking a nuchal scute were larger than those possessing a nuchal scute. However, we found no correlation between genetic divergence and presence/absence of nuchal scutes, and thus no evidence of genetically differentiated lineages.     

Glucose-induced effects and joker function of glucose: endocrine or genotoxic prevalence?

The steady increase in chronic "glycemic load" is characteristic for modern times. Among myriad of glucose functions, two principals can be emphasized: first, endocrine (in particular, ability to induce insulin secretion) and second, DNA-damaging related to formation of reactive oxygen species (ROS). It was suggested by us earlier that a shift in the ratio of mentioned functions reflects a possible "joker" role of glucose as an important modifier of human pathology. Therefore, we embarked on a study to investigate an individual effect of peroral glucose challenge on serum insulin level and ROS generation by mononuclears (luminol-dependent/latex-induced chemiluminescence) in 20 healthy people aged between 28-75. Concentrations of glucose, blood lipids, carbonylated proteins, malondialdehyde, leptin and TNF-alpha were determined as well. On the basis of received data two separate groups could be distinguished: one (n=8), in which glucose stimulation of ROS generation by mononuclears was increased and relatively prevailed over induction of insulin secretion (state of the so called glucose-induced genotoxicity, GIGT), and another (n=12), in which signs of GIGT were not revealed. People who belonged to the first group were characterized with a tendency to lower body mass index, blood leptin and cholesterol and to higher TNF-alpha concentration. Thus, if joker function of glucose is realized in "genotoxic mode", the phenotype (and probably genotype) of subjects may be rather distinctive to the one discovered in glucose-induced "endocrine prevalence". Whether such changes may serve as a pro-mutagenic or pro-endocrine basis for the rise of different chronic diseases or, rather, different features/aggressiveness of the same disease warrants further study.     

Visualization of the interactome: What are we looking at?

Network visualization of the interactome has been become routine in systems biology research. Not only does it serve as an illustration on the cellular organization of protein-protein interactions, it also serves as a biological context for gaining insights from high-throughput data. However, the challenges to produce an effective visualization have been great owing to the fact that the scale, biological context and dynamics of any given interactome are too large and complex to be captured by a single visualization. Visualization design therefore requires a pragmatic trade-off between capturing biological concept and being comprehensible. In this review, we focus on the biological interpretation of different network visualizations. We will draw on examples predominantly from our experiences but elaborate them in the context of the broader field. A rich variety of networks will be introduced including interactomes and the complexome in 2D, interactomes in 2.5D and 3D and dynamic networks.     

How accurate is the current picture of human genetic variation?

Our understanding of the distribution of worldwide human genomic diversity has greatly increased over recent years thanks to the availability of large data sets derived from short tandem repeats (STRs), insertion deletion polymorphisms (indels) and single nucleotide polymorphisms (SNPs). A concern, however, is that the current picture of worldwide human genomic diversity may be inaccurate because of biases in the selection process of genetic markers (so-called 'ascertainment bias'). To evaluate this problem, we first compared the distribution of genomic diversity between these three types of genetic markers in the populations from the HGDP-CEPH panel for evidence of bias or incongruities. In a second step, using a very relaxed set of criteria to prevent the intrusion of bias, we developed a new set of unbiased STR markers and compared the results against those from available panels. Contrarily to recent claims, our results show that the STR markers suffer from no discernible bias, and can thus be used as a baseline reference for human genetic diversity and population differentiation. The bias on SNPs is moderate compared to that on the set of indels analysed, which we recommend should be avoided for work describing the distribution of human genetic diversity or making inference on human settlement history.