Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.     

Gender-specific spatio-temporal patterns of colorectal cancer incidence in Navarre, Spain (1990-2005)

Introduction: In the last ten to twenty years, a stabilization or decline in colorectal cancer (CRC) incidence has been observed in some countries across the world but not in Spain. Our objective here is to assess the gender-specific CRC spatio-temporal pattern in the health areas of Navarre, a Spanish province, during the period 1990–2005. Methods: For each gender, a model with spatio-temporal CAR (Conditional Autoregressive) distributions is used for smoothing the incidence risks. Smoothing is carried out in two dimensions: space and time, allowing for a different time evolution in each health area. An estimated incidence trend curve for each health area and the corresponding confidence bands are obtained. To analyze the evolution of the geographical patterns of CRC incidence risks, maps are also provided. Results: In both genders, CRC shows an increasing trend in most of the areas. In the second half of the period 1998–2005 most of the areas have risks above one although not all statistically significant. In general females present equal or lower risks than males in all areas during the studied period. Conclusions: Colorectal cancer incidence risk is still increasing in the health areas of Navarre. Promoting healthful lifestyles for primary prevention and early detection programs could help to reverse the trend in the province.     

In silico model of an antenna of a phycobilisome and energy transfer rates determination by theoretical Förster approach

Energy transfer (ET) in phycobilisomes, a macrocomplex of phycobiliproteins and linker proteins, is a process that is difficult to understand completely. A model for a rod composed of two hexamers of Phycocyanin and two hexamers of Phycoerythrin was built using an in silico approach and the three‐dimensional structures of both phycobiliproteins from Gracilaria chilensis. The model was characterized and showed 125 Å wide and 230 Å high, which agree with the dimensions of a piling of four hexamers as observed in the images of subcomplexes of phycobilisomes obtained by transmission electron microscopy. ET rates between every pair of chromophores in the model were calculated using the Förster approach, and the fastest rates were selected to draw preferential ET pathways along the rod. Every path indicates that the ET is funneled toward the chromophores located at Cysteines 82 in Phycoerythrin and 84 in Phycocyanin. The chromophores that face the exterior of the rod are phycoerythrobilins, and they also show a preferential ET toward the chromophores located at the center of the rod. The values calculated, in general, agree with the experimental data reported previously, which validates the use of this experimental approach.     

Quand ils ne vivaient pas seulement de la chasse : preuves de domestication ancienne dans les gisements néolithiques d’Atxoste et de Mendandia (Pays Basque)

The combination of use wear analyses on lithic assemblages, palaeontological data and the presence of a quern-stone is considered direct and indirect proof of economic practices of production in the Neolithic sites of Atxoste and Mendandia. We also discuss the role that in this picture is suggested by a recent study on the genetics of the bovids from Mendandia. Both sites are rock-shelters seasonally occupied where the main economic vectors, but not the only ones, are hunting activities: they are integrated in a network created during the Mesolithic but still in use during the Early Neolithic until the mid sixth millennium cal BC when information on farming accumulates in the territory.     

Confidence Intervals for Relative Risks in Disease Mapping

Several analysis of the geographic variation of mortality rates in space have been proposed in the literature. Poisson models allowing the incorporation of random effects to model extra‐variability are widely used. The typical modelling approach uses normal random effects to accommodate local spatial autocorrelation. When spatial autocorrelation is absent but overdispersion persists, a discrete mixture model is an alternative approach. However, a technique for identifying regions which have significant high or low risk in any given area has not been developed yet when using the discrete mixture model. Taking into account the importance that this information provides to the epidemiologists to formulate hypothesis related to the potential risk factors affecting the population, different procedures for obtaining confidence intervals for relative risks are derived in this paper. These methods are the standard information‐based method and other four, all based on bootstrap techniques, namely the asymptotic‐bootstrap, the percentile‐bootstrap, the BC‐bootstrap and the modified information‐based method. All of them are compared empirically by their application to mortality data due to cardiovascular diseases in women from Navarra, Spain, during the period 1988–1994. In the small area example considered here, we find that the information‐based method is sensible at estimating standard errors of the component means in the discrete mixture model but it is not appropriate for providing standard errors of the estimated relative risks and hence, for constructing confidence intervals for the relative risk associated to each region. Therefore, the bootstrap‐based methods are recommended for this matter. More specifically, the BC method seems to provide better coverage probabilities in the case studied, according to a small scale simulation study that has been carried out using a scenario as encountered in the analysis of the real data.     

Economic weights of somatic cell score in dairy sheep

The economic weights for somatic cell score (SCS) have been calculated using profit functions. Economic data were collected in the Latxa breed. Three aspects have been considered: bulk tank milk payment, veterinary treatments due to high SCS, and culling. All of them are non-linear profit functions. Milk payment is based on the sum of the log-normal distributions of somatic cell count, and veterinary treatments on the probability of subclinical mastitis, which is inferred when individual SCS surpass some threshold. Both functions lead to non-standard distributions. The derivatives of the profit function were computed numerically. Culling was computed by assuming that a conceptual trait culled by mastitis (CBM) is genetically correlated to SCS. The economic weight considers the increase in the breeding value of CBM correlated to an increase in the breeding value of SCS, assuming genetic correlations ranging from 0 to 0.9. The relevance of the economic weights for selection purposes was checked by the estimation of genetic gains for milk yield and SCS under several scenarios of genetic parameters and economic weights. The overall economic weights for SCS range from − 2.6 to − 9.5 € per point of SCS, with an average of − 4 € per point of SCS, depending on the expected average SCS of the flock. The economic weight is higher around the thresholds for payment policies. Economic weights did not change greatly with other assumptions. The estimated genetic gains with economic weights of 0.83 € per l of milk yield and − 4 € per point of SCS, assuming a genetic correlation of − 0.30, were 3.85 l and − 0.031 SCS per year, with an associated increase in profit of 3.32 €. This represents a very small increase in profit (about 1%) relative to selecting only for milk yield. Other situations (increased economic weights, different genetic correlations) produced similar genetic gains and changes in profit. A desired-gains index reduced the increase in profit by 3%, although it could be greater depending on the genetic parameters. It is concluded that the inclusion of SCS in dairy sheep breeding programs is of low economic relevance and recommended only if recording is inexpensive or for animal welfare concerns.     

Economic weights of fertility, prolificacy, milk yield and longevity in dairy sheep

Economic weights have been estimated in two breeds (Latxa and Manchega) using economic and technical data collected in 41 Latxa and 12 Manchega dairy sheep flocks. The traits considered were fertility (lambing per year), prolificacy (number of lambs), milk yield (litres) and longevity (as productive life, in years). A linear function was used, relating these traits to the different costs in the flock. The variable costs involved in the profit function were feed and labour. From this function, economic weights were obtained. Labour is considered in the Latxa breed to be a constraint. Moreover, farm profits are unusually high, which probably means that some costs were not included according to the economic theory. For that reason, a rescaling procedure was applied constraining total labour time at the farm. Genetic gains were estimated with the resulting economic weights to test if they give any practical difference. Milk yield only as selection criterion was also considered. The medians of the estimated economic weights for fertility, prolificacy, milk yield and longevity were 138.60 € per lambing, 40.00 € per lamb, 1.18 € per l, 1.66 € per year, and 137.66 € per lambing, 34.17 € per lamb, 0.73 € per l, 2.16 € per year under the linear approach in the Latxa and Manchega breeds respectively. Most differences between breeds can be related to differences in production systems. As for the genetic gains, they were very similar for all economic weights, except when only milk yield was considered, where a correlated decrease in fertility led to a strong decrease in profit. It is concluded that the estimates are robust for practical purposes and that breeding programmes should consider inclusion of fertility. More research is needed to include other traits such as somatic cell score, milk composition and udder traits.