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The painting Histone Subunit Exchange portrays the dynamic nature of nucleosome structure. This issue focuses on the role of epigenetics in health and disease and discusses the therapeutic prospects of targeting the epigenetic machinery. Credit: David Sweatt.
Researchers are testing a slew of targeted therapeutic strategies in lung cancer. Signs are emerging that these therapies are gaining increasing traction in what has long been one of oncology's minefields. Malorye Allison investigates.
Genetic testing for rare heart conditions might someday expand to more common cardiac ailments. Already there are signs testing is dramatically changing how some conditions are treated and doctors' definition of who a patient is. Stephen Strauss reports.
When faced with a competitive threat, two companies took diametrically opposite approaches. Both were ultimately successful, but Genzyme's decision proved to be the cleaner and cheaper option.
A recent Australian legal decision means that, unless faculty members are bound by an assignment or intellectual property policy, they may own inventions resulting from their research.
Two comparative studies from the International Human Epigenome Project find high concordance between different methods for measuring genomic methylation.
High-throughput technologies are enabling epigenetic modifications to be mapped on a genome-wide scale, but whether such knowledge can be rapidly translated into biomedical applications remains unclear.
One of the biggest gaps in our knowledge about epigenomes is how their interplay with cellular signaling influences development, adult cellular differentiation and disease.
The NIH Roadmap Epigenomics Mapping Consortium aims to produce a public resource of epigenomic maps for stem cells and primary ex vivo tissues selected to represent the normal counterparts of tissues and organ systems frequently involved in human disease.
Epigenomics provides the context for understanding the function of genome sequence, analogous to the functional anatomy of the human body provided by Vesalius a half-millennium ago. Much of the seemingly inconclusive genetic data related to common diseases could therefore become meaningful in an epigenomic context.
Comparative analysis of epigenomes offers new opportunities to understand cellular differentiation, mutation effects and disease processes. But the scale and heterogeneity of epigenetic data present numerous computational challenges.
Methods for profiling DNA methylation differ in the physical principles used to detect modified cytosines. Harris et al. compare the performances of four sequencing-based technologies for genome-wide analysis of DNA methylation and combine two methods to enable detection of allelic differences in epigenetic marks.
Comparison of the methylation patterns of cells in different developmental or disease states can help to elucidate both normal and pathological regulatory mechanisms. Bock et al. evaluate the ability of three sequencing-based methods and one microarray-based technology to detect differentially methylated regions on a genome-wide scale.
The grading systems used by in vitro fertilization clinics cannot determine reliably whether a given embryo will lead to a successful pregnancy. Wong et al. address one part of this problem by showing that development of an embryo to the blastocyst stage can be predicted with high confidence at day 2 post fertilization.
Biomechanical forces may be an effective approach for controlling the behavior of stem cells in vitro. Holst et al. show that the elasticity of a tropoelastin matrix expands hematopoietic stem and progenitor cells.
Recent years have seen an explosive increase in our knowledge of such epigenetic mechanisms as chromatin remodeling and DNA methylation in development and disease. This focus issue discusses the current state of the field and how current insights can be translated into practical applications.
Articles from Nature Biotechnology and The Pharmacogenomics Journal that explore best practices for developing and validating predictive models based on data from gene expression and genotyping microarrays. These report the second phase of a collaboration between industry, academic and government researchers as part of the MicroArray Quality Control (MAQC) consortium.