Spatial gene expression quantification: a tool for analysis of <it>in situ </it>hybridizations in sea anemone <it>Nematostella vectensis</it>

<p>Abstract</p> <p>Background</p> <p>Spatial gene expression quantification is required for modeling gene regulation in developing organisms. The fruit fly <it>Drosophila melanogaster</it> is the model system most widely applied for spatial gene expression analysis due to its unique embryonic properties: the shape does not change significantly during its early cleavage cycles and most genes are differentially expressed along a straight axis. This system of development is quite exceptional in the animal kingdom.</p> <p>In the sea anemone <it>Nematostella vectensis</it> the embryo changes its shape during early development; there are cell divisions and cell movement, like in most other metazoans. <it>Nematostella</it> is an attractive case study for spatial gene expression since its transparent body wall makes it accessible to various imaging techniques.</p> <p>Findings</p> <p>Our new quantification method produces standardized gene expression profiles from raw or annotated <it>Nematostella in situ</it> hybridizations by measuring the expression intensity along its cell layer. The procedure is based on digital morphologies derived from high-resolution fluorescence pictures. Additionally, complete descriptions of nonsymmetric expression patterns have been constructed by transforming the gene expression images into a three-dimensional representation.</p> <p>Conclusions</p> <p>We created a standard format for gene expression data, which enables quantitative analysis of <it>in situ</it> hybridizations from embryos with various shapes in different developmental stages. The obtained expression profiles are suitable as input for optimization of gene regulatory network models, and for correlation analysis of genes from dissimilar <it>Nematostella</it> morphologies. This approach is potentially applicable to many other metazoan model organisms and may also be suitable for processing data from three-dimensional imaging techniques.</p

Genome-Wide Association Study of Gene by Smoking Interactions in Coronary Artery Calcification

Many GWAS have identified novel loci associated with common diseases, but have focused only on main effects of individual genetic variants rather than interactions with environmental factors (GxE). Identification of GxE interactions is particularly important for coronary heart disease (CHD), a major preventable source of morbidity and mortality with strong non-genetic risk factors. Atherosclerosis is the major cause of CHD, and coronary artery calcification (CAC) is directly correlated with quantity of coronary atherosclerotic plaque. In the current study, we tested for genetic variants influencing extent of CAC via interaction with smoking (GxS), by conducting a GxS discovery GWAS in Genetic Epidemiology Network of Arteriopathy (GENOA) sibships (N = 915 European Americans) followed by replication in Framingham Heart Study (FHS) sibships (N = 1025 European Americans). Generalized estimating equations accounted for the correlation within sibships in strata-specific groups of smokers and nonsmokers, as well as GxS interaction. Primary analysis found SNPs that showed suggestive associations (p≤10(−5)) in GENOA GWAS, but these index SNPs did not replicate in FHS. However, secondary analysis was able to replicate candidate gene regions in FHS using other SNPs (+/−250 kb of GENOA index SNP). In smoker and nonsmoker groups, replicated genes included TCF7L2 (p = 6.0×10(−5)) and WWOX (p = 4.5×10(−6)); and TNFRSF8 (p = 7.8×10(−5)), respectively. For GxS interactions, replicated genes included TBC1D4 (p = 6.9×10(−5)) and ADAMTS9 (P = 7.1×10(−5)). Interestingly, these genes are involved in inflammatory pathways mediated by the NF-κB axis. Since smoking is known to induce chronic and systemic inflammation, association of these genes likely reflects roles in CAC development via inflammatory pathways. Furthermore, the NF-κB axis regulates bone remodeling, a key physiological process in CAC development. In conclusion, GxS GWAS has yielded evidence for novel loci that are associated with CAC via interaction with smoking, providing promising new targets for future population-based and functional studies of CAC development