Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development

The three-dimensional arrangement of the human genome comprises a complex network of structural and regulatory chromatin loops important for coordinating changes in transcription during human development. To better understand the mechanisms underlying context-specific 3D chromatin structure and transcription during cellular differentiation, we generated comprehensive in situ Hi-C maps of DNA loops during human monocyte-to-macrophage differentiation. We demonstrate that dynamic looping events are regulatory rather than structural in nature and uncover widespread coordination of dynamic enhancer activity at preformed and acquired DNA loops. Enhancer-bound loop formation and enhancer-activation of preformed loops represent two distinct modes of regulation that together form multi-loop activation hubs at key macrophage genes. Activation hubs connect 3.4 enhancers per promoter and exhibit a strong enrichment for Activator Protein 1 (AP-1) binding events, suggesting multi-loop activation hubs driven by cell-type specific transcription factors may represent an important class of regulatory chromatin structures for the spatiotemporal control of transcription

The BLAST View of the Star Forming Region in Aquila (ell=45deg,b=0deg)

We have carried out the first general submillimeter analysis of the field towards GRSMC 45.46+0.05, a massive star forming region in Aquila. The deconvolved 6 deg^2 (3\degree X 2\degree) maps provided by BLAST in 2005 at 250, 350, and 500 micron were used to perform a preliminary characterization of the clump population previously investigated in the infrared, radio, and molecular maps. Interferometric CORNISH data at 4.8 GHz have also been used to characterize the Ultracompact HII regions (UCHIIRs) within the main clumps. By means of the BLAST maps we have produced an initial census of the submillimeter structures that will be observed by Herschel, several of which are known Infrared Dark Clouds (IRDCs). Our spectral energy distributions of the main clumps in the field, located at ~7 kpc, reveal an active population with temperatures of T~35-40 K and masses of ~10^3 Msun for a dust emissivity index beta=1.5. The clump evolutionary stages range from evolved sources, with extended HII regions and prominent IR stellar population, to massive young stellar objects, prior to the formation of an UCHIIR.The CORNISH data have revealed the details of the stellar content and structure of the UCHIIRs. In most cases, the ionizing stars corresponding to the brightest radio detections are capable of accounting for the clump bolometric luminosity, in most cases powered by embedded OB stellar clusters

Coupled hydrogeophysical inversion of elecrical resitances and inflow measurements for topsoil hydraulic properties under constant head infiltration

Accurate estimation of topsoil hydraulic properties is important for understanding water flow and solute transport in the vadose zone. Coupled hydrogeophysical inversion schemes that enable the use of multiple geophysical and hydrological data for the estimation of soil hydraulic properties have recently been proposed. In these coupled inversion schemes, a hydrological model describing the process under investigation is coupled to a forward geophysical model and hydraulic parameters are directly estimated from geophysical measurements. While these schemes provide a suitable platform for the integration of multiple geophysical and hydrological data, efficient methods to combine these data types for improved parameter estimation still warrant investigation. In this study, we investigated the feasibility of estimating three topsoil Mualem-van Genuchten parameters from the fusion of inflow and electrical resistance measurements obtained under constant head infiltration. In addition to using only inflow or electrical resistances, we investigated three methods of combining these data for improved estimation of topsoil hydraulic parameters. Our results show that using inflow alone does not provide a unique solution to the inverse problem. Better results are obtained with the additional use of electrical resistance data. We show that successful data fusion within the coupled hydrogeophysical inversion framework depends on the choice of an appropriate objective function. We obtained the best data fusion results with an objective function defined as the sum of the root mean square error of both data types normalized by the standard deviation of the respective measurements. In this case, the inverted hydraulic parameters were very comparable to reference values obtained from a multi-step outflow experiment carried out with undisturbed soil cores from the experimental site. It is concluded that the coupled hydrogeophysical inversion framework is a promising tool for non-invasive near-surface hydrological investigations.status: publishe

Coupled hydrogeophysical inversion of electrical resistances and inflow measurements for topsoil hydraulic properties under constant head infiltration

Accurate estimation of topsoil hydraulic properties is important for understanding water flow and solute transport in the vadose zone. Coupled hydrogeophysical inversion schemes that enable the use of multiple geophysical and hydrological data for the estimation of soil hydraulic properties have recently been proposed. In these coupled inversion schemes, a hydrological model describing the process under investigation is coupled to a forward geophysical model and hydraulic parameters are directly estimated from geophysical measurements. While these schemes provide a suitable platform for the integration of multiple geophysical and hydrological data, efficient methods to combine these data types for improved parameter estimation still warrant investigation. In this study, we investigated the feasibility of estimating three topsoil Mualem-van Genuchten parameters from the fusion of inflow and electrical resistance measurements obtained under constant head infiltration. In addition to using only inflow or electrical resistances, we investigated three methods of combining these data for improved estimation of topsoil hydraulic parameters. Our results show that using inflow alone does not provide a unique solution to the inverse problem. Better results are obtained with the additional use of electrical resistance data. We show that successful data fusion within the coupled hydrogeophysical inversion framework depends on the choice of an appropriate objective function. We obtained the best data fusion results with an objective function defined as the sum of the root mean square error of both data types normalized by the standard deviation of the respective measurements. In this case, the inverted hydraulic parameters were very comparable to reference values obtained from a multi-step outflow experiment carried out with undisturbed soil cores from the experimental site. It is concluded that the coupled hydrogeophysical inversion framework is a promising tool for non-invasive near-surface hydrological investigations

A semi-quantitative approach for modelling crop response to soil fertility: evaluation of the AquaCrop procedure

Most crop models make use of a nutrient-balance approach for modelling crop response to soil fertility. To counter the vast input data requirements that are typical of these models, the crop water productivity model AquaCrop adopts a semi-quantitative approach. Instead of providing nutrient levels, users of the model provide the soil fertility level as a model input. This level is expressed in terms of the expected impact on crop biomass production, which can be observed in the field or obtained from statistics of agricultural production. The present study is the first to describe extensively, and to calibrate and evaluate, the semi-quantitative approach of the AquaCrop model, which simulates the effect of soil fertility stress on crop production as a combination of slower canopy expansion, reduced maximum canopy cover, early decline in canopy cover and lower biomass water productivity. AquaCrop's fertility response algorithms are evaluated here against field experiments with tef (Eragrostis tef (Zucc.) Trotter) in Ethiopia, with maize (Zea mays L.) and wheat (Triticum aestivum L.) in Nepal, and with quinoa (Chenopodium quinoa Willd.) in Bolivia. It is demonstrated that AquaCrop is able to simulate the soil water content in the root zone, and the crop's canopy development, dry above-ground biomass development, final biomass and grain yield, under different soil fertility levels, for all four crops. Under combined soil water stress and soil fertility stress, the model predicts final grain yield with a relative root-mean-square error of only 11–13% for maize, wheat and quinoa, and 34% for tef. The present study shows that the semi-quantitative soil fertility approach of the AquaCrop model performs well and that the model can be applied, after case-specific calibration, to the simulation of crop production under different levels of soil fertility stress for various environmental conditions, without requiring detailed field observations on soil nutrient content

Dissolved Organic Matter: Linking Soils and Aquatic Systems

The guest editors introduce the contributions to the special section, Dissolved Organic Matter in Soil, with a focus on the three main directions in this complex and growing research effort. Dissolved organic matter (DOM) plays a crucial role in many important processes that take place in terrestrial and aquatic systems. These include carbon and nutrient cycling, pedogenesis, and microbial metabolism. Here we highlight the results of studies that demonstrate the role of DOM in linking terrestrial and aquatic systems. We emphasize three fundamental aspects of the research, which together show the importance of DOM in linking terrestrial and aquatic systems: First, tracing DOM properties during its transport through terrestrial and aquatic systems is a powerful tool for improving our conceptual understanding of the mechanistic drivers of DOM dynamics. Second, linking DOM dynamics to important physical processes such as hydrology provides important insights into the nature of terrestrial-aquatic links. Third, interrelations between DOM dynamics and human impacts on ecosystems highlight how the role of DOM in coupled terrestrial-aquatic systems may change in the future. New measurement and modeling approaches have enabled a more thorough assessment of all three aspects of DOM dynamics. They show that both natural and anthropogenic drivers not only greatly influence DOM dynamics in soils, but owing to the mobility of DOM, also have substantial influence on aquatic systems. This physical connection of soils and surface waters demonstrates the importance of understanding fundamental processes such as nutrient cycling, pedogenesis, and microbial metabolism at a whole-landscape scale