89 research outputs found

    A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

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    Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

    Association of hypoxia inducible factor-1 alpha gene polymorphism with both type 1 and type 2 diabetes in a Caucasian (Hungarian) sample

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    BACKGROUND: Hypoxia inducible factor-1 alpha (HIF-1alpha) is a transcription factor that plays an important role in neo-vascularisation, embryonic pancreas beta-cell mass development, and beta cell protection. Recently a non synonymous single nucleotide polymorphism (g.C45035T SNP, rs11549465) of HIF-1alpha gene, resulting in the p.P582S amino acid change has been shown to be associated with type 2 diabetes (T2DM) in a Japanese population. Our aim was to replicate these findings on a Caucasian (Hungarian) population, as well as to study whether this genetic effect is restricted to T2DM or can be expanded to diabetes in general. METHODS: A large Caucasian sample (N = 890) was recruited including 370 T2DM, 166 T1DM and 354 healthy subjects. Genotyping was validated by two independent methods: a restriction fragment analysis (RFLP) and a real time PCR using TaqMan probes. An overestimation of heterozygotes by RFLP was observed as a consequence of a nearby SNP (rs34005929). Therefore genotyping results of the justified TaqMan system were accepted. The measured genotype distribution corresponded to Hardy-Weinberg equilibrium (P = 0.740) RESULTS: As the TT genotype was extremely rare in the population (0.6% in clinical sample and 2.5% in controls), the genotypes were grouped as T absent (CC) and T present (CT and TT). Genotype-wise analysis showed a significant increase of T present group in controls (24.0%) as compared to patients (16.8%, P = 0.008). This genetic effect was demonstrated in the separated samples of type 1 (15.1%, P = 0.020), and also in type 2 (17.6%, P = 0.032) diabetes. Allele-wise analysis gave identical results showing a higher frequency of the T allele in the control sample (13.3%) than in the clinical sample (8.7%, P = 0.002) with similar results in type 1 (7.8%, P = 0.010) and type 2 (9.1%, P = 0.011) diabetes. The odds ratio for diabetes (either type 1 or 2) was 1.56 in the presence of the C allele. CONCLUSION: We confirmed the protective effect of a rare genetic variant of HIF-1alpha gene against type 2 diabetes in a Caucasian sample. Moreover we demonstrated a genetic contribution of the same polymorphism in type 1 diabetes as well, supporting a possible overlap in pathomechanism for T2DM and a T1DM

    New evidence for habitat specific selection in Wadden Sea Zostera marina populations revealed by genome scanning using SNP and microsatellite markers

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    Eelgrass Zostera marina is an ecosystem-engineering species of outstanding importance for coastal soft sediment habitats that lives in widely diverging habitats. Our first goal was to detect divergent selection and habitat adaptation at the molecular genetic level; hence, we compared three pairs of permanently submerged versus intertidal populations using genome scans, a genetic marker-based approach. Three different statistical approaches for outlier identification revealed divergent selection at 6 loci among 46 markers (6 SNPs, 29 EST microsatellites and 11 anonymous microsatellites). These outlier loci were repeatedly detected in parallel habitat comparisons, suggesting the influence of habitat-specific selection. A second goal was to test the consistency of the general genome scan approach by doubling the number of gene-linked microsatellites and adding single nucleotide polymorphism (SNP) loci, a novel marker type for seagrasses, compared to a previous study. Reassuringly, results with respect to selection were consistent among most marker loci. Functionally interesting marker loci were linked to genes involved in osmoregulation and water balance, suggesting different osmotic stress, and reproductive processes (seed maturation), pointing to different life history strategies. The identified outlier loci are valuable candidates for further investigation into the genetic basis of natural selection

    Heterogeneous Adaptive Trajectories of Small Populations on Complex Fitness Landscapes

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    Background Small populations are thought to be adaptively handicapped, not only because they suffer more from deleterious mutations but also because they have limited access to new beneficial mutations, particularly those conferring large benefits. Methodology/Principal Findings Here, we test this widely held conjecture using both simulations and experiments with small and large bacterial populations evolving in either a simple or a complex nutrient environment. Consistent with expectations, we find that small populations are adaptively constrained in the simple environment; however, in the complex environment small populations not only follow more heterogeneous adaptive trajectories, but can also attain higher fitness than the large populations. Large populations are constrained to near deterministic fixation of rare large-benefit mutations. While such determinism speeds adaptation on the smooth adaptive landscape represented by the simple environment, it can limit the ability of large populations from effectively exploring the underlying topography of rugged adaptive landscapes characterized by complex environments. Conclusions Our results show that adaptive constraints often faced by small populations can be circumvented during evolution on rugged adaptive landscapes

    A framework for evolutionary systems biology

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    <p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

    Experimental biogeography: the role of environmental gradients in high geographic diversity in Cape Proteaceae

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    One of the fundamental dimensions of biodiversity is the rate of species turnover across geographic distance. The Cape Floristic Region of South Africa has exceptionally high geographic species turnover, much of which is associated with groups of closely related species with mostly or completely non-overlapping distributions. A basic unresolved question about biodiversity in this global hotspot is the relative importance of ecological gradients in generating and maintaining high geographic turnover in the region. We used reciprocal transplant experiments to test the extent to which abiotic environmental factors may limit the distributions of a group of closely related species in the genus Protea (Proteaceae), and thus elevate species turnover in this diverse, iconic family. We tested whether these species have a “home site advantage” in demographic rates (germination, growth, mortality), and also parameterized stage-structured demographic models for the species. Two of the three native species were predicted to have a demographic advantage at their home sites. The models also predicted, however, that species could maintain positive population growth rates at sites beyond their current distribution limits. Thus the experiment suggests that abiotic limitation under current environmental conditions does not fully explain the observed distribution limits or resulting biogeographic pattern. One potentially important mechanism is dispersal limitation, which is consistent with estimates based on genetic data and mechanistic dispersal models, though other mechanisms including competition may also play a role

    Common variants in WFS1 confer risk of type 2 diabetes

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    We studied genes involved in pancreatic beta cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes
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