Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis

Exome sequencing has become a powerful and effective strategy for the discovery of genes underlying Mendelian disorders. However, use of exome sequencing to identify variants associated with complex traits has been more challenging, partly because the sample sizes needed for adequate power may be very large. One strategy to increase efficiency is to sequence individuals who are at both ends of a phenotype distribution (those with extreme phenotypes). Because the frequency of alleles that contribute to the trait are enriched in one or both phenotype extremes, a modest sample size can potentially be used to identify novel candidate genes and/or alleles. As part of the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), we used an extreme phenotype study design to discover that variants in DCTN4, encoding a dynactin protein, are associated with time to first P. aeruginosa airway infection, chronic P. aeruginosa infection and mucoid P. aeruginosa in individuals with cystic fibrosis.     

Forecast covariances in the linear multiregression dynamic model

The linear multiregression dynamic model (LMDM) is a Bayesian dynamic model which preserves any conditional independence and causal structure across a multivariate time series. The conditional independence structure is used to model the multivariate series by separate (conditional) univariate dynamic linear models, where each series has contemporaneous variables as regressors in its model. Calculating the forecast covariance matrix (which is required for calculating forecast variances in the LMDM) is not always straightforward in its current formulation. In this paper we introduce a simple algebraic form for calculating LMDM forecast covariances. Calculation of the covariance between model regression components can also be useful and we shall present a simple algebraic method for calculating these component covariances. In the LMDM formulation, certain pairs of series are constrained to have zero forecast covariance. We shall also introduce a possible method to relax this restriction. Copyright © 2008 John Wiley & Sons, Ltd.     

Complex zeolite structure solved by combining powder diffraction and electron microscopy

Many industrially important materials, ranging from ceramics to catalysts to pharmaceuticals, are polycrystalline and cannot be grown as single crystals. This means that non-conventional methods of structure analysis must be applied to obtain the structural information that is fundamental to the understanding of the properties of these materials. Electron microscopy might appear to be a natural approach, but only relatively simple structures have been solved by this route. Powder diffraction is another obvious option, but the overlap of reflections with similar diffraction angles causes an ambiguity in the relative intensities of those reflections. Various ways of overcoming or circumventing this problem have been developed, and several of these involve incorporating chemical information into the structure determination process. For complex zeolite structures, the FOCUS algorithm has proved to be effective. Because it operates in both real and reciprocal space, phase information obtained from high-resolution transmission electron microscopy images can be incorporated directly into this algorithm in a simple way. Here we show that by doing so, the complexity limit can be extended much further. The power of this approach has been demonstrated with the solution of the structure of the zeolite TNU-9 (|H9.3|[Al9.3Si182.7O384]; ref. 10) with 24 topologically distinct (Si,Al) atoms and 52 such O atoms. For comparison, ITQ-22 (ref. 11), the most complex zeolite known to date, has 16 topologically distinct (Si,Ge) atoms.     

Close genetic linkage between X-linked retinitis pigmentosa and a restriction fragment length polymorphism identified by recombinant DNA probe L1.28

Retinitis pigmentosa (RP) is a group of retinal degeneration characterized by progressive visual field loss, night blindness and pigmentary retinopathy. Its prevalence is in the region of 1-2 in 5,000 of the general population, making it one of the commoner causes of blindness in early and middle life. Although 36-48% of RP patients are isolated cases, the remainder show autosomal dominant, autosomal recessive or X-linked modes of inheritance. The X-linked variety ( XLRP ) is found in 14-22% of RP families in the UK. In the present study, X chromosome-specific recombinant DNA probes which can detect restriction fragment length polymorphisms have been used to localize the XLRP gene(s) to a subregion of the X chromosome using linkage analysis. One of the probes, L1.28, has been shown to be closely linked to XLRP in five kindreds, with 95% confidence limits of 0-15 centimorgans (maximum LOD score of 7.89 at a distance of 3 centimorgans). This suggests that the XLRP locus lies on the proximal part of the short arm of the X chromosome. This probe is potentially useful for carrier detection and early diagnosis in about 40% of cases, provided that genetic heterogeneity can be excluded by analysis of further families.     

Ocean circulation off east Antarctica affects ecosystem structure and sea-ice extent

Sea ice and oceanic boundaries have a dominant effect in structuring Antarctic marine ecosystems. Satellite imagery and historical data have identified the southern boundary of the Antarctic Circumpolar Current as a site of enhanced biological productivity. Meso-scale surveys off the Antarctic peninsula have related the abundances of Antarctic krill (Euphausia superba) and salps (Salpa thompsoni) to inter-annual variations in sea-ice extent. Here we have examined the ecosystem structure and oceanography spanning 3,500 km of the east Antarctic coastline, linking the scales of local surveys and global observations. Between 80 degrees and 150 degrees E there is a threefold variation in the extent of annual sea-ice cover, enabling us to examine the regional effects of sea ice and ocean circulation on biological productivity. Phytoplankton, primary productivity, Antarctic krill, whales and seabirds were concentrated where winter sea-ice extent is maximal, whereas salps were located where the sea-ice extent is minimal. We found enhanced biological activity south of the southern boundary of the Antarctic Circumpolar Current rather than in association with it. We propose that along this coastline ocean circulation determines both the sea-ice conditions and the level of biological productivity at all trophic levels.