Variation in DNA Methylation Is Not Consistently Reflected by Sociality in Hymenoptera

Changes in gene regulation that underlie phenotypic evolution can be encoded directly in the DNA sequence or mediated by chromatin modifications such as DNA methylation. It has been hypothesized that the evolution of eusocial division of labor is associated with enhanced gene regulatory potential, which may include expansions in DNA methylation in the genomes of Hymenoptera (bees, ants, wasps, and sawflies). Recently, this hypothesis garnered support from analyses of a commonly used metric to estimate DNA methylation in silico, CpG content. Here, we test this hypothesis using direct, nucleotide-level measures of DNA methylation across nine species of Hymenoptera. In doing so, we generated new DNA methylomes for three species of interest, including one solitary and one facultatively eusocial halictid bee and a sawfly. We demonstrate that the strength of correlation between CpG content and DNA methylation varies widely among hymenopteran taxa, highlighting shortcomings in the utility of CpG content as a proxy for DNA methylation in comparative studies of taxa with sparse DNA methylomes. We observed strikingly high levels of DNA methylation in the sawfly relative to other investigated hymenopterans. Analyses of molecular evolution suggest the relatively distinct sawfly DNA methylome may be associated with positive selection on functional DNMT3 domains. Sawflies are an outgroup to all ants, bees, and wasps, and no sawfly species are eusocial. We find no evidence that either global expansions or variation within individual ortholog groups in DNA methylation are consistently associated with the evolution of social behavior

Benchmarking homogenization algorithms for monthly data

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies. The algorithms were validated against a realistic benchmark dataset. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including i) the centered root mean square error relative to the true homogeneous values at various averaging scales, ii) the error in linear trend estimates and iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones

The Individualised versus the Public Health Approach to Treating Ebola.

Tom Boyles reflects on differing approaches taken for treating patients with Ebola virus disease in low- and high-resource settings