Browsing by Issue Date, starting with "2009"
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- Genetic recombination and molecular evolutionPublication . Charlesworth, B.; Betancourt, A.J.; Kaiser, V.B.; Gordo, I.Reduced rates of genetic recombination are often associated with reduced genetic variability and levels of adaptation. Several different evolutionary processes, collectively known as Hill–Robertson (HR) effects, have been proposed as causes of these correlates of recombination. Here, we use DNA sequence polymorphism and divergence data from the noncrossing over dot chromosome of Drosophila to discriminate between two of the major forms of HR effects: selective sweeps and background selection. This chromosome shows reduced levels of silent variability and reduced effectiveness of selection. We show that neither model fits the data on variability. We propose that, in large genomic regions with restricted recombination, HR effects among nonsynonymous mutations undermine the effective strength of selection, so that their background selection effects are weakened. This modified model fits the data on variability and also explains why variability in very large nonrecombining genomes is not completely wiped out. We also show that HR effects of this type can produce an individual selection advantage to recombination, as well as greatly reduce the mean fitness of nonrecombining genomes and genomic regions
- Identification of Functional LsrB-Like Autoinducer-2 ReceptorsPublication . Pereira, C. S.; de Regt, A. K.; Brito, P. H.; Miller, S. T.; Xavier, K. B.Although a variety of bacterial species have been reported to use the interspecies communication signal autoinducer-2 (AI-2) to regulate multiple behaviors, the molecular mechanisms of AI-2 recognition and signal transduction remain poorly understood. To date, two types of AI-2 receptors have been identified: LuxP, present in Vibrio spp., and LsrB, first identified in Salmonella enterica serovar Typhimurium. In S. Typhimurium, LsrB is the ligand binding protein of a transport system that enables the internalization of AI-2. Here, using both sequence analysis and structure prediction, we establish a set of criteria for identifying functional AI-2 receptors. We test our predictions experimentally, assaying key species for their abilities to import AI-2 in vivo, and test their LsrB orthologs for AI-2 binding in vitro. Using these experimental approaches, we were able to identify AI-2 receptors in organisms belonging to phylogenetically distinct families such as the Enterobacteriaceae, Rhizobiaceae, and Bacillaceae. Phylogenetic analysis of LsrB orthologs indicates that this pattern could result from one single origin of the functional LsrB gene in a gammaproteobacterium, suggesting possible posterior independent events of lateral gene transfer to the Alphaproteobacteria and Firmicutes. Finally, we used mutagenesis to show that two AI-2-interacting residues are essential for the AI-2 binding ability. These two residues are conserved in the binding sites of all the functional AI-2 binding proteins but not in the non-AI-2-binding orthologs. Together, these results strongly support our ability to identify functional LsrB-type AI-2 receptors, an important step in investigations of this interspecies signal.
- On the Final Size of Epidemics with SeasonalityPublication . Bacäer, N.; Gomes, M.G.M.We first study an SIR system of differential equations with periodic coefficients describing an epidemic in a seasonal environment. Unlike in a constant environment, the final epidemic size may not be an increasing function of the basic reproduction number ℛ0 or of the initial fraction of infected people. Moreover, large epidemics can happen even if ℛ0<1. But like in a constant environment, the final epidemic size tends to 0 when ℛ0<1 and the initial fraction of infected people tends to 0. When ℛ0>1, the final epidemic size is bigger than the fraction 1−1/ℛ0 of the initially nonimmune population. In summary, the basic reproduction number ℛ0 keeps its classical threshold property but many other properties are no longer true in a seasonal environment. These theoretical results should be kept in mind when analyzing data for emerging vector-borne diseases (West-Nile, dengue, chikungunya) or air-borne diseases (SARS, pandemic influenza); all these diseases being influenced by seasonality.
- Irf4 is a positional and functional candidate gene for the control of serum IgM levels in the mousePublication . Côrte-Real, J; Rodo, Joana; Almeida, P; Coutinho, António; Demengeot, Jocelyne; Penha-Gonçalves, CarlosNatural IgM are involved in numerous immunological functions but the genetic factors that control the homeostasis of its secretion and upholding remain unknown. Prompted by the finding that C57BL/6 mice had significantly lower serum levels of IgM when compared with BALB/c mice, we performed a genome-wide screen and found that the level of serum IgM was controlled by a QTL on chromosome 13 reaching the highest level of association at marker D13Mit266 (LOD score¼3.54). This locus was named IgMSC1 and covered a region encompassing the interferon-regulatory factor 4 gene (Irf4). The number of splenic mature B cells in C57BL/6 did not differ from BALB/c mice but we found that low serum levels of IgM in C57BL/6 mice correlated with lower frequency of IgM-secreting cells in the spleen and in the peritoneal cavity. These results suggested that C57BL/6 mice have lower efficiency in late B-cell maturation, a process that is highly impaired in Irf4 knockout mice. In fact, we also found reduced Irf4 gene expression in B cells of C57BL/6 mice. Thus, we propose Irf4 as a candidate for the IgMSC1 locus, which controls IgM homeostatic levels at the level of B-cell terminal differentiation.
- Bayesian analysis of allelic penetrance models for complex binary traitsPublication . Sepúlveda, Nuno; Paulino, Carlos Daniel; Penha-Gonçalves, CarlosComplex binary traits result from an intricate network of genetic and environmental factors. To aid their genetic dissection, several generalized linear models have been described to detect interaction between genes. However, it is recognized that these models have limited genetic interpretation. To overcome this problem, the allelic penetrance approach was proposed to model the action of a dominant or a recessive allele at a single locus, and to describe two-locus independent, inhibition, and cumulative actions. Classically, a recessive inheritance requires the expression of both recessive alleles in homozygotes to obtain the phenotype (type I recessiveness). In previous work, recessiveness was defined alternatively as a situation where a recessive allele is able to express the phenotype when the dominant allele is not active (type II recessiveness). Both definitions of recessiveness are then discussed under the allelic penetrance models. Bayesian methods are applied to analyze two data sets: one regarding the effect of the haplotype [HLA-B8, SC01, DR3] on the inheritance of IgD and IgG4 immunoglobulin deficiencies in humans, and other related to two-locus action in the control of Listeria infection susceptibility in mice.
- Genetic diversity in the SIR model of pathogen evolutionPublication . Gordo, I.; Gomes, M.G.M.; Reis, D.G.; Campos, P.R.A.We introduce a model for assessing the levels and patterns of genetic diversity in pathogen populations, whose epidemiology follows a susceptible-infected-recovered model (SIR). We model the population of pathogens as a metapopulation composed of subpopulations (infected hosts), where pathogens replicate and mutate. Hosts transmit pathogens to uninfected hosts. We show that the level of pathogen variation is well predicted by analytical expressions, such that pathogen neutral molecular variation is bounded by the level of infection and increases with the duration of infection. We then introduce selection in the model and study the invasion probability of a new pathogenic strain whose fitness (R0(1+s)) is higher than the fitness of the resident strain (R0). We show that this invasion probability is given by the relative increment in R0 of the new pathogen (s). By analyzing the patterns of genetic diversity in this framework, we identify the molecular signatures during the replacement and compare these with those observed in sequences of influenza A.
- A defined network of fast-spiking interneurons in orbitofrontal cortex: responses to behavioral contingencies and ketamine administrationPublication . Quirk, MC; Sosulski, DL; Feierstein, CE; Uchida, N; Mainen, ZFOrbitofrontal cortex (OFC) is a region of prefrontal cortex implicated in the motivational control of behavior and in related abnormalities seen in psychosis and depression. It has been hypothesized that a critical mechanism in these disorders is the dysfunction of GABAergic interneurons that normally regulate prefrontal information processing. Here, we studied a subclass of interneurons isolated in rat OFC using extracellular waveform and spike train analysis. During performance of a goal-directed behavioral task, the firing of this class of putative fast-spiking (FS) interneurons showed robust temporal correlations indicative of a functionally coherent network. FS cell activity also co-varied with behavioral response latency, a key indicator of motivational state. Systemic administration of ketamine, a drug that can mimic psychosis, preferentially inhibited this cell class. Together, these results support the idea that OFC-FS interneurons form a critical link in the regulation of motivation by prefrontal circuits during normal and abnormal brain and behavioral states.
- A Gene-Based Linkage Map for Bicyclus anynana Butterflies Allows for a Comprehensive Analysis of Synteny with the Lepidopteran Reference GenomePublication . Beldade, P.; Saenko, SV.; Pul, N.; Long, AD.Lepidopterans (butterflies and moths) are a rich and diverse order of insects, which, despite their economic impact and unusual biological properties, are relatively underrepresented in terms of genomic resources.We focus on Bicyclus anynana butterflies, a laboratory system for studying the diversification of novelties and serially repeated traits. With a panel of 12 small families and a biphasic mapping approach, we first assigned 508 expressed genes to segregation groups and then ordered 297 of them within individual linkage groups. We also coarsely mapped seven color pattern loci.
- Experimental evolution reveals natural selection on standing genetic variationPublication . Teotónio, H; Chelo, IM; Bradic, M; Rose, MR; Long, ADEvolution depends on genetic variation generated by mutation or recombination from standing genetic variation. In sexual organisms, little is known about the molecular population genetics of adaptation and reverse evolution(1-11). We carry out 50 generations of experimental reverse evolution in populations of Drosophila melanogaster, previously differentiated by forward evolution, and follow changes in the frequency of SNPs in both arms of the third chromosome. We characterize the effects of sampling finite population sizes and natural selection at the genotype level. We demonstrate that selection has occurred at several loci and further that there is no general loss or gain of allele diversity. We also observe that despite the complete convergence to ancestral levels of adaptation, allele frequencies only show partial return.
- Neural representation of behavioral outcomes in the orbitofrontal cortexPublication . Mainen, ZF; Kepecs, AThe orbitofrontal cortex (OFC) is important in processing rewards and other behavioral outcomes. Here, we review from a computational perspective recent progress in understanding this complex function. OFC neurons appear to represent abstract outcome values, which may facilitate the comparison of options, as well as concrete outcome attributes, such as flavor or location, which may enable predictive cues to access current outcome values in the face of dynamic modulation by internal state, context and learning. OFC can use reinforcement learning to generate outcome predictions; it can also generate outcome predictions using other mechanisms, including the evaluation of decision confidence or uncertainty. OFC neurons encode not only the mean expected outcome but also the variance, consistent with the idea that OFC uses a probabilistic population code to represent outcomes. We suggest that further attention to the nature of its representations and algorithms will be critical to further elucidating OFC function.
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