Magic numbers in the discrete tomography of cyclotomic model sets

We report recent progress in the problem of distinguishing convex subsets of cyclotomic model sets $\varLambda$ by (discrete parallel) X-rays in prescribed $\varLambda$-directions. It turns out that for any of these model sets $\varLambda$ there exists a `magic number' $m_{\varLambda}$ such that any two convex subsets of $\varLambda$ can be distinguished by their X-rays in any set of $m_{\varLambda}$ prescribed $\varLambda$-directions. In particular, for pentagonal, octagonal, decagonal and dodecagonal model sets, the least possible numbers are in that very order 11, 9, 11 and 13.Comment: 6 pages, 1 figure; based on the results of arXiv:1101.4149 [math.MG]; presented at Aperiodic 2012 (Cairns, Australia

Gene-alcohol interactions identify several novel blood pressure loci including a promising locus near SLC16A9

Alcohol consumption is a known risk factor for hypertension, with recent candidate studies implicating gene-alcohol interactions in blood pressure (BP) regulation. We used 6,882 (predominantly) Caucasian participants aged 20 to 80 years from the Framingham SHARe (SNP Health Association Resource) to perform a genome-wide analysis of SNP-alcohol interactions on BP traits. We used a two-step approach in the ABEL suite to examine genetic interactions with three alcohol measures [ounces of alcohol consumed per week, drinks consumed per week, and the number of days drinking alcohol per week] on four BP traits [systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure]. In the first step, we fit a linear mixed model of each BP trait onto age, sex, BMI, and antihypertensive medication while accounting for the phenotypic correlation among relatives. In the second step, we conducted 1 degree-of-freedom (df) score tests of the SNP main effect, alcohol main effect, and SNP-alcohol interaction using the maximum likelihood estimates of the parameters from the first step. We then calculated the joint 2 df score test of the SNP main effect and SNP-alcohol interaction using MixABEL. The effect of SNP rs10826334 (near SLC16A9) on SBP was significantly modulated by both the number of alcoholic drinks and the ounces of alcohol consumed per week (p-values of 1.27E-08 and 3.92E-08, respectively). Each copy of the G-allele decreased SBP by 3.79 mmHg in those consuming 14 drinks per week versus a 0.461 mmHg decrease in non-drinkers. Index SNPs in 20 other loci exhibited suggestive (p-value≤1E-06) associations with BP traits by the 1 df interaction test or joint 2df test, including 3 rare variants, one low-frequency variant, and SNPs near/in genes ESRRG, FAM179A, CRIPT-SOCS5, KAT2B,ADCY2, GLI3, ZNF716, SLIT1, PDE3A, KERA-LUM, RNF219-AS1, CLEC3A , FBX015, and IGSF5. SNP -alcohol interactions may enhance discovery of novel variants with large effects that can be targete

Comparison of two methods for analysis of gene-environment interactions in longitudinal family data: The Framingham heart study

Gene–environment interaction (GEI) analysis can potentially enhance gene discovery for common complex traits. However, genome-wide interaction analysis is computationally intensive. Moreover, analysis of longitudinal data in families is much more challenging due to the two sources of correlations arising from longitudinal measurements and family relationships. GWIS of longitudinal family data can be a computational bottleneck. Therefore, we compared two methods for analysis of longitudinal family data: a methodologically sound but computationally demanding method using the Kronecker model (KRC) and a computationally more forgiving method using the hierarchical linear model (HLM). The KRC model uses a Kronecker product of an unstructured matrix for correlations among repeated measures (longitudinal) and a compound symmetry matrix for correlations within families at a given visit. The HLM uses an autoregressive covariance matrix for correlations among repeated measures and a random intercept for familial correlations. We compared the two methods using the longitudinal Framingham heart study (FHS) SHARe data. Specifically, we evaluated SNP–alcohol (amount of alcohol consumption) interaction effects on high density lipoprotein cholesterol (HDLC). Keeping the prohibitive computational burden of KRC in mind, we limited the analysis to chromosome 16, where preliminary cross-sectional analysis yielded some interesting results. Our first important finding was that the HLM provided very comparable results but was remarkably faster than the KRC, making HLM the method of choice. Our second finding was that longitudinal analysis provided smaller P-values, thus leading to more significant results, than cross-sectional analysis. This was particularly pronounced in identifying GEIs. We conclude that longitudinal analysis of GEIs is more powerful and that the HLM method is an optimal method of choice as compared to the computationally (prohibitively) intensive KRC method

Fundamental and realized feeding niche breadths of sexual and asexual stick insects.

The factors contributing to the maintenance of sex over asexuality in natural populations remain unclear. Ecological divergences between sexual and asexual lineages could help to maintain reproductive polymorphisms, at least transiently, but the consequences of asexuality for the evolution of ecological niches are unknown. Here, we investigated how niche breadths change in transitions from sexual reproduction to asexuality. We used host plant ranges as a proxy to compare the realized feeding niche breadths of five independently derived asexual Timema stick insect species and their sexual relatives at both the species and population levels. Asexual species had systematically narrower realized niches than sexual species, though this pattern was not apparent at the population level. To investigate how the narrower realized niches of asexual species arise, we performed feeding experiments to estimate fundamental niche breadths but found no systematic differences between reproductive modes. The narrow realized niches found in asexual species are therefore probably a consequence of biotic interactions such as predation or competition, that constrain realized niche size in asexuals more strongly than in sexuals

Mapping the conformations of biological assemblies

Mapping conformational heterogeneity of macromolecules presents a formidable challenge to X-ray crystallography and cryo-electron microscopy, which often presume its absence. This has severely limited our knowledge of the conformations assumed by biological systems and their role in biological function, even though they are known to be important. We propose a new approach to determining to high resolution the three-dimensional conformations of biological entities such as molecules, macromolecular assemblies, and ultimately cells, with existing and emerging experimental techniques. This approach may also enable one to circumvent current limits due to radiation damage and solution purification.Comment: 14 pages, 6 figure

Chlorine isotope composition in chlorofluorocarbons CFC-11, CFC-12 and CFC-113 in firn, stratospheric and tropospheric air

The stratospheric degradation of chlorofluorocarbons (CFCs) releases chlorine, which is a major contributor to the destruction of stratospheric ozone (O3). A recent study reported strong chlorine isotope fractionation during the breakdown of the most abundant CFC (CFC-12, CCl2F2, Laube et al., 2010a), similar to effects seen in nitrous oxide (N2O). Using air archives to obtain a long-term record of chlorine isotope ratios in CFCs could help to identify and quantify their sources and sinks. We analyse the three most abundant CFCs and show that CFC-11 (CCl3F) and CFC-113 (CClF2CCl2F) exhibit significant stratospheric chlorine isotope fractionation, in common with CFC-12. The apparent isotope fractionation (εapp) for mid- and high-latitude stratospheric samples are (-2.4±0.5) ‰ and (-2.3±0.4) ‰ for CFC-11, (-12.2±1.6) ‰ and (-6.8±0.8) ‰ for CFC-12 and (-3.5±1.5) ‰ and (-3.3±1.2) ‰ for CFC-113, respectively. Assuming a constant isotope composition of emissions, we calculate the expected trends in the tropospheric isotope signature of these gases based on their stratospheric 37Cl enrichment and stratosphere-troposphere exchange. We compare these projections to the long-term δ(37Cl) trends of all three CFCs, measured on background tropospheric samples from the Cape Grim air archive (Tasmania, 1978 – 2010) and tropospheric firn air samples from Greenland (NEEM site) and Antarctica (Fletcher Promontory site). From 1970 to the present-day, projected trends agree with tropospheric measurements, suggesting that within analytical uncertainties a constant average emission isotope delta is a compatible scenario. The measurement uncertainty is too high to determine whether the average emission isotope delta has been affected by changes in CFC manufacturing processes, or not. Our study increases the suite of trace gases amenable to direct isotope ratio measurements in small air volumes (approximately 200 ml), using a single-detector gas chromatography-mass spectrometry system