Identification of novel high-frequency DNA methylation changes in breast cancer

Recent data have revealed that epigenetic alterations, including DNA methylation and chromatin structure changes, are among the earliest molecular abnormalities to occur during tumorigenesis. The inherent thermodynamic stability of cytosine methylation and the apparent high specificity of the alterations for disease may accelerate the development of powerful molecular diagnostics for cancer. We report a genome-wide analysis of DNA methylation alterations in breast cancer. The approach efficiently identified a large collection of novel differentially DNA methylated loci (approximately 200), a subset of which was independently validated across a panel of over 230 clinical samples. The differential cytosine methylation events were independent of patient age, tumor stage, estrogen receptor status or family history of breast cancer. The power of the global approach for discovery is underscored by the identification of a single differentially methylated locus, associated with the GHSR gene, capable of distinguishing infiltrating ductal breast carcinoma from normal and benign breast tissues with a sensitivity and specificity of 90% and 96%, respectively. Notably, the frequency of these molecular abnormalities in breast tumors substantially exceeds the frequency of any other single genetic or epigenetic change reported to date. The discovery of over 50 novel DNA methylation-based biomarkers of breast cancer may provide new routes for development of DNA methylation-based diagnostics and prognostics, as well as reveal epigenetically regulated mechanism involved in breast tumorigenesis.     

Applications of a new subspace clustering algorithm (COSA) in medical systems biology

A novel clustering approach named Clustering Objects on Subsets of Attributes (COSA) has been proposed (Friedman and Meulman, (2004). Clustering objects on subsets of attributes. J. R. Statist. Soc. B 66, 1–25.) for unsupervised analysis of complex data sets. We demonstrate its usefulness in medical systems biology studies. Examples of metabolomics analyses are described as well as the unsupervised clustering based on the study of disease pathology and intervention effects in rats and humans. In comparison to principal components analysis and hierarchical clustering based on Euclidean distance, COSA shows an enhanced capability to trace partial similarities in groups of objects enabling a new discovery approach in systems biology as well as offering a unique approach to reveal common denominators of complex multi-factorial diseases in animal and human studies. Doris Damian, Matej Orešič, and Elwin Verheij contributed equally to this work.     

Characterization of an ethanol-inducible promoter system in Catharanthus roseus hairy roots

Efforts to engineer Catharanthus roseus hairy roots to produce commercially significant amounts of valuable compounds, such as the terpenoid indole alkaloids vinblastine and vincristine, require the development of tools to study the effects of overexpressing key metabolic and regulatory genes. The use of inducible promoters allows researchers to control the timing and level of expression of genes of interest. In addition, use of inducible promoters allows researchers to use a single transgenic line as both the control and experimental line, minimizing the problems associated with clonal variation. We have previously characterized the use of a glucocorticoid-inducible promoter system to study the effects of gene overexpression within the terpenoid indole alkaloid pathway on metabolite production. Here the feasibility of using an ethanol-inducible promoter within C. roseus hairy roots is reported. This ethanol-inducible promoter is highly sensitive to ethanol concentration with a concentration of 0.005% ethanol causing a 6-fold increase in CAT reporter activity after 24 h of induction. The ethanol-inducible CAT activity increased 24-fold over a 72-h induction period with 0.5% ethanol.     

Cross‐sex genetic covariances limit the evolvability of wing‐shape within and among species of Drosophila

The independent evolution of males and females is potentially constrained by both sexes inheriting the same alleles from their parents. This genetic constraint can limit the evolvability of complex traits; however, there are few studies of multivariate evolution that incorporate cross‐sex genetic covariances in their predictions. Drosophila wing‐shape has emerged as a model high‐dimensional phenotype; wing‐shape is highly evolvable in contemporary populations, and yet perplexingly stable across phylogenetic timescales. Here, we show that cross‐sex covariances in Drosophila melanogaster, given by the B ‐matrix, may considerably bias wing‐shape evolution. Using random skewers, we show that B would constrain the response to antagonistic selection by 90%, on average, but would double the response to concordant selection. Both cross‐sex within‐trait and cross‐sex cross‐trait covariances determined the predicted response to antagonistic selection, but only cross‐sex within‐trait covariances facilitated the predicted response to concordant selection. Similar patterns were observed in the direction of extant sexual dimorphism in D. melanogaster, and in directions of most and least dimorphic variation across the Drosophila phylogeny. Our results highlight the importance of considering between‐sex genetic covariances when making predictions about evolution on both macro‐ and microevolutionary timescales, and may provide one more explanatory piece in the puzzle of stasis.     

Mutation in a flexible linker modulates binding affinity for modular complexes

Tandem beta zippers are modular complexes formed between repeated linear motifs and tandemly arrayed domains of partner proteins in which β-strands form upon binding. Studies of such complexes, formed by LIM domain proteins and linear motifs in their intrinsically disordered partners, revealed spacer regions between the linear motifs that are relatively flexible but may affect the overall orientation of the binding modules. We demonstrate that mutation of a solvent exposed side chain in the spacer region of an LHX4–ISL2 complex has no significant effect on the structure of the complex, but decreases binding affinity, apparently by increasing flexibility of the linker.