We present a fast mapping-based algorithm to compute the mappability of each region of a reference genome up to a specified number of mismatches. Knowing the mappability of a genome is crucial for the interpretation of massively parallel sequencing experiments. We investigate the properties of the mappability of eukaryotic DNA/RNA both as a whole and at the level of the gene family, providing for various organisms tracks which allow the mappability information to be visually explored. In addition, we show that mappability varies greatly between species and gene classes. Finally, we suggest several practical applications where mappability can be used to refine the analysis of high-throughput sequencing data (SNP calling, gene expression quantification and paired-end experiments). This work highlights mappability as an important concept which deserves to be taken into full account, in particular when massively parallel sequencing technologies are employed. The GEM mappability program belongs to the GEM (GEnome Multitool) suite of programs, which can be freely downloaded for any use from its website (http://gemlibrary.sourceforge.net).

To understand basic principles of bacterial metabolism organization and regulation, but also the impact of genome size, we systematically studied one of the smallest bacteria, Mycoplasma pneumoniae. A manually curated metabolic network of 189 reactions catalyzed by 129 enzymes allowed the design of a defined, minimal medium with 19 essential nutrients. More than 1300 growth curves were recorded in the presence of various nutrient concentrations. Measurements of biomass indicators, metabolites, and 13C-glucose experiments provided information on directionality, fluxes, and energetics; integration with transcription profiling enabled the global analysis of metabolic regulation. Compared with more complex bacteria, the M. pneumoniae metabolic network has a more linear topology and contains a higher fraction of multifunctional enzymes; general features such as metabolite concentrations, cellular energetics, adaptability, and global gene expression responses are similar, however.

We analyzed the DNA methylome of ten subpopulations spanning the entire B cell differentiation program by whole-genome bisulfite sequencing and high-density microarrays. We observed that non-CpG methylation disappeared upon B cell commitment, whereas CpG methylation changed extensively during B cell maturation, showing an accumulative pattern and affecting around 30% of all measured CpG sites. Early differentiation stages mainly displayed enhancer demethylation, which was associated with upregulation of key B cell transcription factors and affected multiple genes involved in B cell biology. Late differentiation stages, in contrast, showed extensive demethylation of heterochromatin and methylation gain at Polycomb-repressed areas, and genes with apparent functional impact in B cells were not affected. This signature, which has previously been linked to aging and cancer, was particularly widespread in mature cells with an extended lifespan. Comparing B cell neoplasms with their normal counterparts, we determined that they frequently acquire methylation changes in regions already undergoing dynamic methylation during normal B cell differentiation.

The combined application of next-generation sequencing platforms has provided an economical approach to unlocking the potential of the turkey genome.