A galactic microquasar mimicking winged radio galaxies.

A subclass of extragalactic radio sources known as winged radio galaxies has puzzled astronomers for many years. The wing features are detected at radio wavelengths as low-surface-brightness radio lobes that are clearly misaligned with respect to the main lobe axis. Different models compete to account for these peculiar structures. Here, we report observational evidence that the parsec-scale radio jets in the Galactic microquasar GRS 1758-258 give rise to a Z-shaped radio emission strongly reminiscent of the X and Z-shaped morphologies found in winged radio galaxies. This is the first time that such extended emission features are observed in a microquasar, providing a new analogy for its extragalactic relatives. From our observations, we can clearly favour the hydrodynamic backflow interpretation against other possible wing formation scenarios. Assuming that physical processes are similar, we can extrapolate this conclusion and suggest that this mechanism could also be at work in many extragalactic cases.

Prediction of CpG-island function: CpG clustering vs. sliding-window methods.

BACKGROUND: Unmethylated stretches of CpG dinucleotides (CpG islands) are an outstanding property of mammal genomes. Conventionally, these regions are detected by sliding window approaches using %G + C, CpG observed/expected ratio and length thresholds as main parameters. Recently, clustering methods directly detect clusters of CpG dinucleotides as a statistical property of the genome sequence. RESULTS: We compare sliding-window to clustering (i.e. CpGcluster) predictions by applying new ways to detect putative functionality of CpG islands. Analyzing the co-localization with several genomic regions as a function of window size vs. statistical significance (p-value), CpGcluster shows a higher overlap with promoter regions and highly conserved elements, at the same time showing less overlap with Alu retrotransposons. The major difference in the prediction was found for short islands (CpG islets), often exclusively predicted by CpGcluster. Many of these islets seem to be functional, as they are unmethylated, highly conserved and/or located within the promoter region. Finally, we show that window-based islands can spuriously overlap several, differentially regulated promoters as well as different methylation domains, which might indicate a wrong merge of several CpG islands into a single, very long island. The shorter CpGcluster islands seem to be much more specific when concerning the overlap with alternative transcription start sites or the detection of homogenous methylation domains. CONCLUSIONS: The main difference between sliding-window approaches and clustering methods is the length of the predicted islands. Short islands, often differentially methylated, are almost exclusively predicted by CpGcluster. This suggests that CpGcluster may be the algorithm of choice to explore the function of these short, but putatively functional CpG islands.