The October issue of Genome Medicine features articles covering a range of topics across our broad scope. The issue starts with Michael Wigler’s musings on the future applications of single-cell technologies for basic cell biology and biomedical research beyond cancer. Two reviews were also published in October; one by Tamim Shaikh and colleagues discussing the advantages and limitations of copy number variation analysis in clinical diagnostics as well as the impact of this on clinicians and patients. Another review, by Nicolai Bonne and David Wong, explains why saliva is a promising diagnostic sample and provides an overview of the recent technical innovation in this area, such as analyte stabilization, nucleic-acid pre-amplification and direct transcriptomics.
The issue also includes a study from the laboratory of Paul Bertone and colleagues. This study describes transcriptome profiling of glioblastoma-derived neural stem cells and normal neural stem cells to identify a gene expression signature with prognostic value that differentiates the two cell types. Another research article, by the teams of Julia Segre and Heidi Kong, compared the microbiome of the skin and nares of healthy children and adults, demonstrating that substantial changes occur during puberty in the composition of these microbial communities. This study has important clinical implications for the management of pediatric skin disorders that have a microbial origin.
Two research highlights were published in October; the first, by Miguel Andrade-Navarro, discusses the wider implications of two recent research articles published in BMC Bioinformatics and Genome Medicine. These research articles describe how to build a keyword profile from a collection of PubMed references and apply this to establish comparisons between genes and inherited diseases, respectively. In the second research highlight, Jeffrey Craig and colleagues highlight a recent study demonstrating that epigenome-wide association studies can be performed on neonatal blood spot cards, and explain how this type of study can break the chicken-and-egg association between epigenetic markers and disease.