Metapopulation theory developed in terrestrial ecology provides applicable frameworks for interpreting the role of local and regional processes in shaping species distribution patterns. Yet, empirical testing of metapopulation models on microbial communities is essentially lacking. We determined regional bacterioplankton dynamics from monthly transect sampling in the Baltic Sea Proper using 16S rRNA gene sequencing. A strong positive trend was found between local relative abundance and occupancy of populations. Notably, the occupancy-frequency distributions were significantly bimodal with a satellite mode of rare endemic populations and a core mode of abundant cosmopolitan populations (e.g. Synechococcus, SAR11 and SAR86 clade members). Temporal changes in population distributions supported several theoretical frameworks. Still, bimodality was found among bacterioplankton communities across the entire Baltic Sea, and was also frequent in globally distributed datasets. Datasets spanning waters with widely different physicochemical characteristics or environmental gradients typically lacked significant bimodal patterns. When such datasets were divided into subsets with coherent environmental conditions, bimodal patterns emerged, highlighting the importance of positive feedbacks between local abundance and occupancy within specific biomes. Thus, metapopulation theory applied to microbial biogeography can provide novel insights into the mechanisms governing shifts in biodiversity resulting from natural or anthropogenically induced changes in the environment.

Using deep RNA sequencing, we have studied the expression of adenovirus-encoded small RNAs at different times after infection. Nineteen small RNAs which comprised more than 1% of the total pool of small RNAs at least one time point were identified. These small RNAs were between 25 and 35 nucleotides long and mapped in the region of the VA RNAI and RNAII genes. However, the overlap was incomplete and some contained a few extra nucleotides at the 3' end. This finding together with the observation that some of the small RNAs were detected before VA RNA expression had started might indicate that they are derived from other precursors than VA RNAI and II. Interestingly, the small RNAs displayed different expression profiles during the course of the infection suggesting that they have different functions. An effort was made to identify their mRNA targets by using computer prediction and deep cDNA sequencing. The most significant targets for the earliest small RNAs were genes involved in signaling pathways.

Transcontinental migration is a fascinating example of how animals can respond to climatic oscillation. Yet, quantitative data on fitness components are scarce, and the resulting population genetic consequences are poorly understood. Migratory divides, hybrid zones with a transition in migratory behaviour, provide a natural setting to investigate the micro-evolutionary dynamics induced by migration under sympatric conditions. Here, we studied the effects of migratory programme on survival, trait evolution and genome-wide patterns of population differentiation in a migratory divide of European barn swallows. We sampled a total of 824 individuals from both allopatric European populations wintering in central and southern Africa, respectively, along with two mixed populations from within the migratory divide. While most morphological characters varied by latitude consistent with Bergmann's rule, wing length co-varied with distance to wintering grounds. Survival data collected during a 5-year period provided strong evidence that this covariance is repeatedly generated by disruptive selection against intermediate phenotypes. Yet, selection-induced divergence did not translate into genome-wide genetic differentiation as assessed by microsatellites, mtDNA and >20 000 genome-wide SNP markers; nor did we find evidence of local genomic selection between migratory types. Among breeding populations, a single outlier locus mapped to the BUB1 gene with a role in mitotic and meiotic organization. Overall, this study provides evidence for an adaptive response to variation in migration behaviour continuously eroded by gene flow under current conditions of nonassortative mating. It supports the theoretical prediction that population differentiation is difficult to achieve under conditions of gene flow despite measurable disruptive selection.

Genetic differences among neoplastic cells within the same tumour have been proposed to drive cancer progression and treatment failure. Whether data on intratumoral diversity can be used to predict clinical outcome remains unclear. We here address this issue by quantifying genetic intratumoral diversity in a set of chemotherapy-treated childhood tumours. By analysis of multiple tumour samples from seven patients we demonstrate intratumoral diversity in all patients analysed after chemotherapy, typically presenting as multiple clones within a single millimetre-sized tumour sample (microdiversity). We show that microdiversity often acts as the foundation for further genome evolution in metastases. In addition, we find that microdiversity predicts poor cancer-specific survival (60%; P=0.009), independent of other risk factors, in a cohort of 44 patients with chemotherapy-treated childhood kidney cancer. Survival was 100% for patients lacking microdiversity. Thus, intratumoral genetic diversity is common in childhood cancers after chemotherapy and may be an important factor behind treatment failure.

The characterization of aberrant DNA methylation is emerging as a key part of the study of cancer development and phenotype. The technical advancements and decreasing costs of methods for high-throughput profiling of DNA methylation have brought about a high interest in the use of such methods in disease association studies. Here we discuss the principles for DNA methylation analysis using data from the Infinium DNA methylation BeadChip assays and describe the computational steps and statistical considerations going from processing of the raw array data to analysis of differential methylation. Moreover, we provide detailed guidelines on how to perform tumor subtype classification based on DNA methylation signatures.