DNMT3L Modulates Significant and Distinct Flanking Sequence Preference for DNA Methylation by DNMT3A and DNMT3B In Vivo

The DNTM3A and DNMT3B de novo DNA methyltransferases (DNMTs) are responsible for setting genomic DNA methylation patterns, a key layer of epigenetic information. Here, using an in vivo episomal methylation assay and extensive bisulfite methylation sequencing, we show that human DNMT3A and DNMT3B possess significant and distinct flanking sequence preferences for target CpG sites. Selection for high or low efficiency sites is mediated by the base composition at the −2 and +2 positions flanking the CpG site for DNMT3A, and at the −1 and +1 positions for DNMT3B. This intrinsic preference reproducibly leads to the formation of specific de novo methylation patterns characterized by up to 34-fold variations in the efficiency of DNA methylation at individual sites. Furthermore, analysis of the distribution of signature methylation hotspot and coldspot motifs suggests that DNMT flanking sequence preference has contributed to shaping the composition of CpG islands in the human genome. Our results also show that the DNMT3L stimulatory factor modulates the formation of de novo methylation patterns in two ways. First, DNMT3L selectively focuses the DNA methylation machinery on properly chromatinized DNA templates. Second, DNMT3L attenuates the impact of the intrinsic DNMT flanking sequence preference by providing a much greater boost to the methylation of poorly methylated sites, thus promoting the formation of broader and more uniform methylation patterns. This study offers insights into the manner by which DNA methylation patterns are deposited and reveals a new level of interplay between members of the de novo DNMT family.     

Scaling up the diversity–resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire

Understanding the mechanisms underlying ecosystem resilience – why some systems have an irreversible response to disturbances while others recover – is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large‐scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small‐scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four‐corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local‐scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues.     

Determining synthesis rates of individual proteins in zebrafish (Danio rerio) with low levels of a stable isotope labelled amino acid

The zebrafish is a powerful model organism for the analysis of human cardiovascular development and disease. Understanding these processes at the protein level not only requires changes in protein concentration to be determined but also the rate at which these changes occur on a protein‐by‐protein basis. The ability to measure protein synthesis and degradation rates on a proteome‐wide scale, using stable isotope labelling in conjunction with mass spectrometry is now a well‐established experimental approach. With the advent of more selective and sensitive mass spectrometers, it is possible to accurately measure lower levels of stable isotope incorporation, even when sample is limited. In order to challenge the sensitivity of this approach, we successfully determined the synthesis rates of over 600 proteins from the cardiac muscle of the zebrafish using a diet where either 30% or 50% of the L‐leucine was replaced with a stable isotope labelled analogue ([²H₇]L‐leucine]. It was possible to extract sufficient protein from individual zebrafish hearts to determine the incorporation rate of the label into hundreds of proteins simultaneously, with the two labelling regimens showing a good correlation of synthesis rates.     

Comparative demographics of a Hawaiian forest bird community

Estimates of demographic parameters such as survival and reproductive success are critical for guiding management efforts focused on species of conservation concern. Unfortunately, reliable demographic parameters are difficult to obtain for any species, but especially for rare or endangered species. Here we derived estimates of adult survival and recruitment in a community of Hawaiian forest birds, including eight native species (of which three are endangered) and two introduced species at Hakalau Forest National Wildlife Refuge, Hawai?i. Integrated population models (IPM) were used to link mark–recapture data (1994–1999) with long‐term population surveys (1987–2008). To our knowledge, this is the first time that IPM have been used to characterize demographic parameters of a whole avian community, and provides important insights into the life history strategies of the community. The demographic data were used to test two hypotheses: 1) arthropod specialists, such as the ‘Akiapōlā‘au Hemignathus munroi, are ‘slower’ species characterized by a greater relative contribution of adult survival to population growth, i.e. lower fecundity and increased adult survival; and 2) a species’ susceptibility to environmental change, as reflected by its conservation status, can be predicted by its life history traits. We found that all species were characterized by a similar population growth rate around one, independently of conservation status, origin (native vs non‐native), feeding guild, or life history strategy (as measured by ‘slowness’), which suggested that the community had reached an equilibrium. However, such stable dynamics were achieved differently across feeding guilds, as demonstrated by a significant increase of adult survival and a significant decrease of recruitment along a gradient of increased insectivory, in support of hypothesis 1. Supporting our second hypothesis, we found that slower species were more vulnerable species at the global scale than faster ones. The possible causes and conservation implications of these patterns are discussed.     

Introduced annual grass increases regional fire activity across the arid western USA (1980–2009)

Non‐native, invasive grasses have been linked to altered grass‐fire cycles worldwide. Although a few studies have quantified resulting changes in fire activity at local scales, and many have speculated about larger scales, regional alterations to fire regimes remain poorly documented. We assessed the influence of large‐scale Bromus tectorum (hereafter cheatgrass) invasion on fire size, duration, spread rate, and interannual variability in comparison to other prominent land cover classes across the Great Basin, USA. We compared regional land cover maps to burned area measured using the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2000–2009 and to fire extents recorded by the USGS registry of fires from 1980 to 2009. Cheatgrass dominates at least 6% of the central Great Basin (650 000 km²). MODIS records show that 13% of these cheatgrass‐dominated lands burned, resulting in a fire return interval of 78 years for any given location within cheatgrass. This proportion was more than double the amount burned across all other vegetation types (range: 0.5–6% burned). During the 1990s, this difference was even more extreme, with cheatgrass burning nearly four times more frequently than any native vegetation type (16% of cheatgrass burned compared to 1–5% of native vegetation). Cheatgrass was also disproportionately represented in the largest fires, comprising 24% of the land area of the 50 largest fires recorded by MODIS during the 2000s. Furthermore, multi‐date fires that burned across multiple vegetation types were significantly more likely to have started in cheatgrass. Finally, cheatgrass fires showed a strong interannual response to wet years, a trend only weakly observed in native vegetation types. These results demonstrate that cheatgrass invasion has substantially altered the regional fire regime. Although this result has been suspected by managers for decades, this study is the first to document recent cheatgrass‐driven fire regimes at a regional scale.     

Neck muscle paths and moment arms are significantly affected by wrapping surface parameters

In this paper, we studied the effects of wrapping surfaces on muscle paths and moment arms of the neck muscle, semispinalis capitis. Sensitivities to wrapping surface size and the kinematic linkage to vertebral segments were evaluated. Kinematic linkage, but not radius, significantly affected the accuracy of model muscle paths compared to centroid paths from images. Both radius and linkage affected the moment arm significantly. Wrapping surfaces that provided the best match to centroid paths over a range of postures had consistent moment arms. For some wrapping surfaces with poor matches to the centroid path, a kinematic method (tendon excursion) predicted flexion moment arms in certain postures, whereas geometric method (distance to instant centre) predicted extension. This occurred because the muscle lengthened as it wrapped around the surface. This study highlights the sensitivity of moment arms to wrapping surface parameters and the importance of including multiple postures when evaluating muscle paths and moment arm.     

Coalescent inference for infectious disease: meta-analysis of hepatitis C

Genetic analysis of pathogen genomes is a powerful approach to investigating the population dynamics and epidemic history of infectious diseases. However, the theoretical underpinnings of the most widely used, coalescent methods have been questioned, casting doubt on their interpretation. The aim of this study is to develop robust population genetic inference for compartmental models in epidemiology. Using a general approach based on the theory of metapopulations, we derive coalescent models under susceptible–infectious (SI), susceptible–infectious–susceptible (SIS) and susceptible–infectious–recovered (SIR) dynamics. We show that exponential and logistic growth models are equivalent to SI and SIS models, respectively, when co-infection is negligible. Implementing SI, SIS and SIR models in BEAST, we conduct a meta-analysis of hepatitis C epidemics, and show that we can directly estimate the basic reproductive number (R₀) and prevalence under SIR dynamics. We find that differences in genetic diversity between epidemics can be explained by differences in underlying epidemiology (age of the epidemic and local population density) and viral subtype. Model comparison reveals SIR dynamics in three globally restricted epidemics, but most are better fit by the simpler SI dynamics. In summary, metapopulation models provide a general and practical framework for integrating epidemiology and population genetics for the purposes of joint inference.