800 research outputs found
Evidence for variation in the effective population size of animal mitochondrial DNA
Background: It has recently been shown that levels of diversity in mitochondrial DNA are remarkably constant across animals of diverse census population sizes and ecologies, which has led to the suggestion that the effective population of mitochondrial DNA may be relatively constant. Results: Here we present several lines of evidence that suggest, to the contrary, that the effective population size of mtDNA does vary, and that the variation can be substantial. First, we show that levels of mitochondrial and nuclear diversity are correlated within all groups of animals we surveyed. Second, we show that the effectiveness of selection on non-synonymous mutations, as measured by the ratio of the numbers of non-synonymous and synonymous polymorphisms, is negatively correlated to levels of mitochondrial diversity. Finally, we estimate the effective population size of mitochondrial DNA in selected mammalian groups and show that it varies by at least an order of magnitude. Conclusions: We conclude that there is variation in the effective population size of mitochondria. Furthermore we suggest that the relative constancy of DNA diversity may be due to a negative correlation between the effective population size and the mutation rate per generation
Apparent diffusion coefficient for molecular subtyping of non-gadolinium-enhancing WHO grade II/III glioma: volumetric segmentation versus two-dimensional region of interest analysis
OBJECTIVES: To investigate if quantitative apparent diffusion coefficient (ADC) measurements can predict genetic subtypes of non-gadolinium-enhancing gliomas, comparing whole tumour against single slice analysis. METHODS: Volumetric T2-derived masks of 44 gliomas were co-registered to ADC maps with ADC mean (ADCmean) calculated. For the slice analysis, two observers placed regions of interest in the largest tumour cross-section. The ratio (ADCratio) between ADCmeanin the tumour and normal appearing white matter was calculated for both methods. RESULTS: Isocitrate dehydrogenase (IDH) wild-type gliomas showed the lowest ADC values throughout (p < 0.001). ADCmeanin the IDH-mutant 1p19q intact group was significantly higher than in the IDH-mutant 1p19q co-deleted group (p < 0.01). A volumetric ADCmeanthreshold of 1201 × 10-6mm2/s identified IDH wild-type with a sensitivity of 83% and a specificity of 86%; a volumetric ADCratiocut-off value of 1.65 provided a sensitivity of 80% and a specificity of 92% (area under the curve (AUC) 0.9-0.94). A slice ADCratiothreshold for observer 1 (observer 2) of 1.76 (1.83) provided a sensitivity of 80% (86%), specificity of 91% (100%) and AUC of 0.95 (0.96). The intraclass correlation coefficient was excellent (0.98). CONCLUSIONS: ADC measurements can support the distinction of glioma subtypes. Volumetric and two-dimensional measurements yielded similar results in this study. KEY POINTS: • Diffusion-weighted MRI aids the identification of non-gadolinium-enhancing malignant gliomas • ADC measurements may permit non-gadolinium-enhancing glioma molecular subtyping • IDH wild-type gliomas have lower ADC values than IDH-mutant tumours • Single cross-section and volumetric ADC measurements yielded comparable results in this study
Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions
The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions
Differential Expression of Vegfr-2 and Its Soluble Form in Preeclampsia
Several studies have suggested that the main features of preeclampsia (PE) are consequences of endothelial dysfunction related to excess circulating anti-angiogenic factors, most notably, soluble sVEGFR-1 (also known as sFlt-1) and soluble endoglin (sEng), as well as to decreased PlGF. Recently, soluble VEGF type 2 receptor (sVEGFR-2) has emerged as a crucial regulator of lymphangiogenesis. To date, however, there is a paucity of information on the changes of VEGFR-2 that occur during the clinical onset of PE. Therefore, the aim of our study was to characterize the plasma levels of VEGFR-2 in PE patients and to perform VEGFR-2 immunolocalization in placenta.By ELISA, we observed that the VEGFR-2 plasma levels were reduced during PE compared with normal gestational age matched pregnancies, whereas the VEGFR-1 and Eng plasma levels were increased. The dramatic drop in the VEGFR-1 levels shortly after delivery confirmed its placental origin. In contrast, the plasma levels of Eng and VEGFR-2 decreased only moderately during the early postpartum period. An RT-PCR analysis showed that the relative levels of VEGFR-1, sVEGFR-1 and Eng mRNA were increased in the placentas of women with severe PE. The relative levels of VEGFR-2 mRNA as well as expressing cells, were similar in both groups. We also made the novel finding that a recently described alternatively spliced VEGFR-2 mRNA variant was present at lower relative levels in the preeclamptic placentas.Our results indicate that the plasma levels of anti-angiogenic factors, particularly VEGFR-1 and VEGFR-2, behave in different ways after delivery. The rapid decrease in plasma VEGFR-1 levels appears to be a consequence of the delivery of the placenta. The persistent circulating levels of VEGFR-2 suggest a maternal endothelial origin of this peptide. The decreased VEGFR-2 plasma levels in preeclamptic women may serve as a marker of endothelial dysfunction
Pervasive Adaptive Protein Evolution Apparent in Diversity Patterns around Amino Acid Substitutions in Drosophila simulans
In Drosophila, multiple lines of evidence converge in suggesting that beneficial substitutions to the genome may be common. All suffer from confounding factors, however, such that the interpretation of the evidence—in particular, conclusions about the rate and strength of beneficial substitutions—remains tentative. Here, we use genome-wide polymorphism data in D. simulans and sequenced genomes of its close relatives to construct a readily interpretable characterization of the effects of positive selection: the shape of average neutral diversity around amino acid substitutions. As expected under recurrent selective sweeps, we find a trough in diversity levels around amino acid but not around synonymous substitutions, a distinctive pattern that is not expected under alternative models. This characterization is richer than previous approaches, which relied on limited summaries of the data (e.g., the slope of a scatter plot), and relates to underlying selection parameters in a straightforward way, allowing us to make more reliable inferences about the prevalence and strength of adaptation. Specifically, we develop a coalescent-based model for the shape of the entire curve and use it to infer adaptive parameters by maximum likelihood. Our inference suggests that ∼13% of amino acid substitutions cause selective sweeps. Interestingly, it reveals two classes of beneficial fixations: a minority (approximately 3%) that appears to have had large selective effects and accounts for most of the reduction in diversity, and the remaining 10%, which seem to have had very weak selective effects. These estimates therefore help to reconcile the apparent conflict among previously published estimates of the strength of selection. More generally, our findings provide unequivocal evidence for strongly beneficial substitutions in Drosophila and illustrate how the rapidly accumulating genome-wide data can be leveraged to address enduring questions about the genetic basis of adaptation
The genomes of two key bumblebee species with primitive eusocial organization
Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation
Modeling complex ecological economic systems: toward an evolutionary, dynamic understanding of people and nature
Recent understanding about system dynamics and predictability that has emerged from the study of complex systems is creating new tools for modeling interactions between anthropogenic and natural systems. A range of techniques has become available through advances in computer speed and accessibility and by implementing a broad, interdisciplinary systems view
Estimation of Isolation Times of the Island Species in the Drosophila simulans Complex from Multilocus DNA Sequence Data
Background: The Drosophila simulans species complex continues to serve as an important model system for the study of new species formation. The complex is comprised of the cosmopolitan species, D. simulans, and two island endemics, D. mauritiana and D. sechellia. A substantial amount of effort has gone into reconstructing the natural history of the complex, in part to infer the context in which functional divergence among the species has arisen. In this regard, a key parameter to be estimated is the initial isolation time (t) of each island species. Loci in regions of low recombination have lower divergence within the complex than do other loci, yet divergence from D. melanogaster is similar for both classes. This might reflect gene flow of the lowrecombination loci subsequent to initial isolation, but it might also reflect differential effects of changing population size on the two recombination classes of loci when the low-recombination loci are subject to genetic hitchhiking or pseudohitchhiking Methodology/Principal Findings: New DNA sequence variation data for 17 loci corroborate the prior observation from 13 loci that DNA sequence divergence is reduced in genes of low recombination. Two models are presented to estimate t and other relevant parameters (substitution rate correction factors in lineages leading to the island species and, in the case of the 4-parameter model, the ratio of ancestral to extant effective population size) from the multilocus DNA sequence data. Conclusions/Significance: In general, it appears that both island species were isolated at about the same time, here estimated at,250,000 years ago. It also appears that the difference in divergence patterns of genes in regions of low an
The Genetics of Adaptation for Eight Microvirid Bacteriophages
Theories of adaptive molecular evolution have recently experienced significant expansion, and their predictions and assumptions have begun to be subjected to rigorous empirical testing. However, these theories focus largely on predicting the first event in adaptive evolution, the fixation of a single beneficial mutation. To address long-term adaptation it is necessary to include new assumptions, but empirical data are needed for guidance. To empirically characterize the general properties of adaptive walks, eight recently isolated relatives of the single-stranded DNA (ssDNA) bacteriophage φX174 (family Microviridae) were adapted to identical selective conditions. Three of the eight genotypes were adapted in replicate, for a total of 11 adaptive walks. We measured fitness improvement and identified the genetic changes underlying the observed adaptation. Nearly all phages were evolvable; nine of the 11 lineages showed a significant increase in fitness. However, fitness plateaued quickly, and adaptation was achieved through only three substitutions on average. Parallel evolution was rampant, both across replicates of the same genotype as well as across different genotypes, yet adaptation of replicates never proceeded through the exact same set of mutations. Despite this, final fitnesses did not vary significantly among replicates. Final fitnesses did vary significantly across genotypes but not across phylogenetic groupings of genotypes. A positive correlation was found between the number of substitutions in an adaptive walk and the magnitude of fitness improvement, but no correlation was found between starting and ending fitness. These results provide an empirical framework for future adaptation theory
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