512 research outputs found
Protein Structure Prediction Using Bee Colony Optimization Metaheuristic<em>: Extended Abstract</em>
Characterizing RNA ensembles from NMR data with kinematic models
International audienceFunctional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem-loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention
The Araguaia River as an Important Biogeographical Divide for Didelphid Marsupials in Central Brazil
The riverine barrier model suggests that rivers play a significant role in separating widespread organisms into isolated populations. In this study, we used a comparative approach to investigate the phylogeography of 6 didelphid marsupial species in central Brazil. Specifically, we evaluate the role of the mid-Araguaia River in differentiating populations and estimate divergence time among lineages to assess the timing of differentiation of these species, using mitochondrial DNA sequence data. The 6 didelphid marsupials revealed different intraspecific genetic patterns and structure. The 3 larger and more generalist species, Didelphis albiventris, Didelphis marsupialis, and Philander opossum, showed connectivity across the Araguaia River. In contrast the genetic structure of the 3 smaller and specialist species, Gracilinanus agilis, Marmosa (Marmosa) murina, and Marmosa (Micoureus) demerarae was shaped by the mid-Araguaia. Moreover, the split of eastern and western bank populations of the 2 latter species is consistent with the age of Araguaia River sediments formation. We hypothesize that the role of the Araguaia as a riverine barrier is linked to the level of ecological specialization among the 6 didelphid species and differences in their ability to cross rivers or disperse through the associated habitat types.FCT PhD grants: (SFRH/BD/24767/2005, SFRH/BD/23191/2005); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) PhD scholarship; Conselho Nacional de Desenvolvimento Científico e Tenológico (CNPq, Brazil) research grants; European Funds (COMPETE)
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Patterns of Positive Selection in Six Mammalian Genomes
Genome-wide scans for positively selected genes (PSGs) in mammals have provided insight into the dynamics of genome evolution, the genetic basis of differences between species, and the functions of individual genes. However, previous scans have been limited in power and accuracy owing to small numbers of available genomes. Here we present the most comprehensive examination of mammalian PSGs to date, using the six high-coverage genome assemblies now available for eutherian mammals. The increased phylogenetic depth of this dataset results in substantially improved statistical power, and permits several new lineage- and clade-specific tests to be applied. Of ∼16,500 human genes with high-confidence orthologs in at least two other species, 400 genes showed significant evidence of positive selection (FDR<0.05), according to a standard likelihood ratio test. An additional 144 genes showed evidence of positive selection on particular lineages or clades. As in previous studies, the identified PSGs were enriched for roles in defense/immunity, chemosensory perception, and reproduction, but enrichments were also evident for more specific functions, such as complement-mediated immunity and taste perception. Several pathways were strongly enriched for PSGs, suggesting possible co-evolution of interacting genes. A novel Bayesian analysis of the possible “selection histories” of each gene indicated that most PSGs have switched multiple times between positive selection and nonselection, suggesting that positive selection is often episodic. A detailed analysis of Affymetrix exon array data indicated that PSGs are expressed at significantly lower levels, and in a more tissue-specific manner, than non-PSGs. Genes that are specifically expressed in the spleen, testes, liver, and breast are significantly enriched for PSGs, but no evidence was found for an enrichment for PSGs among brain-specific genes. This study provides additional evidence for widespread positive selection in mammalian evolution and new genome-wide insights into the functional implications of positive selection.</p
Altered Metabolic Signature in Pre-Diabetic NOD Mice
Altered metabolism proceeding seroconversion in children progressing to Type 1 diabetes has previously been demonstrated. We tested the hypothesis that non-obese diabetic (NOD) mice show a similarly altered metabolic profile compared to C57BL/6 mice. Blood samples from NOD and C57BL/6 female mice was collected at 0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 13 and 15 weeks and the metabolite content was analyzed using GC-MS. Based on the data of 89 identified metabolites OPLS-DA analysis was employed to determine the most discriminative metabolites. In silico analysis of potential involved metabolic enzymes was performed using the dbSNP data base. Already at 0 weeks NOD mice displayed a unique metabolic signature compared to C57BL/6. A shift in the metabolism was observed for both strains the first weeks of life, a pattern that stabilized after 5 weeks of age. Multivariate analysis revealed the most discriminative metabolites, which included inosine and glutamic acid. In silico analysis of the genes in the involved metabolic pathways revealed several SNPs in either regulatory or coding regions, some in previously defined insulin dependent diabetes (Idd) regions. Our result shows that NOD mice display an altered metabolic profile that is partly resembling the previously observation made in children progressing to Type 1 diabetes. The level of glutamic acid was one of the most discriminative metabolites in addition to several metabolites in the TCA cycle and nucleic acid components. The in silico analysis indicated that the genes responsible for this reside within previously defined Idd regions
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