Genomic relationships computed from either next- generation sequence or array SNP data
Perez Enciso, M. - \ 2014
Journal of Animal Breeding and Genetics 131 (2014)2. - ISSN 0931-2668 - p. 85 - 96.
genetic-variation - complex traits - selection - pig - predictions - genotype - samples - cattle
The use of sequence data in genomic prediction models is a topic of high interest, given the decreasing prices of current next'-generation sequencing technologies (NGS) and the theoretical possibility of directly interrogating the genomes for all causal mutations. Here, we compare by simulation how well genetic relationships (G) could be estimated using either NGS or ascertained SNP arrays. DNA sequences were simulated using the coalescence according to two scenarios: a cattle' scenario that consisted of a bottleneck followed by a split in two breeds without migration, and a pig' model where Chinese introgression into international pig breeds was simulated. We found that introgression results in a large amount of variability across the genome and between individuals, both in differentiation and in diversity. In general, NGS data allowed the most accurate estimates of G, provided enough sequencing depth was available, because shallow NGS (4x) may result in highly distorted estimates of G elements, especially if not standardized by allele frequency. However, high-density genotyping can also result in accurate estimates of G. Given that genotyping is much less noisy than NGS data, it is suggested that specific high-density arrays (similar to 3M SNPs) that minimize the effects of ascertainment could be developed in the population of interest by sequencing the most influential animals and rely on those arrays for implementing genomic selection.
Advancing projections of phytoplankton responses to climate change through ensemble modelling
Trolle, D. ; Elliott, J.A. ; Mooij, W.M. - \ 2014
Environmental Modelling & Software 61 (2014). - ISSN 1364-8152 - p. 371 - 379.
fresh-water cyanobacteria - shallow lakes - multimodel ensembles - environmental-change - community structure - blooms - restoration - temperature - predictions - challenges
A global trend of increasing health hazards associated with proliferation of toxin-producing cyanobacteria makes the ability to project phytoplankton dynamics of paramount importance. Whilst ensemble (multi-)modelling approaches have been used for a number of years to improve the robustness of weather forecasts this approach has until now never been adopted for ecosystem modelling. We show that the average simulated phytoplankton biomass derived from three different aquatic ecosystem models is generally superior to any of the three individual models in describing observed phytoplankton biomass in a typical temperate lake ecosystem, and we simulate a series of climate change projections. While this is the first multi-model ensemble approach applied for some of the most complex aquatic ecosystem models available, we consider it sets a precedent for what will become commonplace methodology in the future, as it enables increased robustness of model projections, and scenario uncertainty estimation due to differences in model structures.
Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations
Pryce, J. ; Johnston, J. ; Hayes, B.J. ; Sahana, G. ; Weigel, K. ; McParland, S. ; Spurlok, D. ; Krattenmacher, N. ; Spelman, R.J. ; Wall, E. ; Calus, M.P.L. - \ 2014
Journal of Dairy Science 97 (2014)3. - ISSN 0022-0302 - p. 1799 - 1811.
genome-wide associations - dutch holstein cattle - friesian dairy-cows - breeding values - nordic holstein - data sets - predictions - accuracy - traits - panels
Combining data from research herds may be advantageous, especially for difficult or expensive-to-measure traits (such as dry matter intake). Cows in research herds are often genotyped using low-density single nucleotide polymorphism (SNP) panels. However, the precision of quantitative trait loci detection in genome-wide association studies and the accuracy of genomic selection may increase when the low-density genotypes are imputed to higher density. Genotype data were available from 10 research herds: 5 from Europe [Denmark, Germany, Ireland, the Netherlands, and the United Kingdom (UK)], 2 from Australasia (Australia and New Zealand), and 3 from North America (Canada and the United States). Heifers from the Australian and New Zealand research herds were already genotyped at high density (approximately 700,000 SNP). The remaining genotypes were imputed from around 50,000 SNP to 700,000 using 2 reference populations. Although it was not possible to use a combined reference population, which would probably result in the highest accuracies of imputation, differences arising from using 2 high-density reference populations on imputing 50,000-marker genotypes of 583 animals (from the UK) were quantified. The European genotypes (n=4,097) were imputed as 1 data set, using a reference population of 3,150 that included genotypes from 835 Australian and 1,053 New Zealand females, with the remainder being males. Imputation was undertaken using population-wide linkage disequilibrium with no family information exploited. The UK animals were also included in the North American data set (n=1,579) that was imputed to high density using a reference population of 2,018 bulls. After editing, 591,213 genotypes on 5,999 animals from 10 research herds remained. The correlation between imputed allele frequencies of the 2 imputed data sets was high (>0.98) and even stronger (>0.99) for the UK animals that were part of each imputation data set. For the UK genotypes, 2.2% were imputed differently in the 2 high-density reference data sets used. Only 0.025% of these were homozygous switches. The number of discordant SNP was lower for animals that had sires that were genotyped. Discordant imputed SNP genotypes were most common when a large difference existed in allele frequency between the 2 imputed genotype data sets. For SNP that had =20% discordant genotypes, the difference between imputed data sets of allele frequencies of the UK (imputed) genotypes was 0.07, whereas the difference in allele frequencies of the (reference) high-density genotypes was 0.30. In fact, regions existed across the genome where the frequency of discordant SNP was higher. For example, on chromosome 10 (centered on 520,948 bp), 52 SNP (out of a total of 103 SNP) had =20% discordant SNP. Four hundred and eight SNP had more than 20% discordant genotypes and were removed from the final set of imputed genotypes. We concluded that both discordance of imputed SNP genotypes and differences in allele frequencies, after imputation using different reference data sets, may be used to identify and remove poorly imputed SNP.
Novel genomic approaches unravel genetic architecture of complex traits in apple.
Kumar, S. ; Garrick, D.J. ; Bink, M.C.A.M. ; Whitworth, C. ; Chagné, D. - \ 2013
BMC Genomics 14 (2013). - ISSN 1471-2164
x domestica borkh. - wide association - mixed-model - linkage disequilibrium - fruit - selection - predictions - accuracy - pedigree - mdmyb10
BACKGROUND: Understanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × domestica Borkh.) seedlings genotyped for an 8K SNP array, we report the first systematic evaluation of the relative contributions of different genomic regions to various traits related to eating quality and susceptibility to some physiological disorders. Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously. The patterns of linkage disequilibrium (LD) were also investigated. RESULTS: A high degree of LD even at longer distances between markers was observed, and the patterns of LD decay were similar across successive generations. Genomic regions were identified, some of which coincided with known candidate genes, with significant effects on various traits. Phenotypic variation explained by the loci identified through a whole-genome scan ranged from 3% to 25% across different traits, while fitting all markers simultaneously generally provided heritability estimates close to those from pedigree-based analysis. Results from 'Q+K' and 'K' models were very similar, suggesting that the SNP-based kinship matrix captures most of the underlying population structure. Correlations between allele substitution effects obtained from single-marker and all-marker analyses were about 0.90 for all traits. Use of SNP-derived realized relationships in linear mixed models provided a better goodness-of-fit than pedigree-based expected relationships. Genomic regions with probable pleiotropic effects were supported by the corresponding higher linkage group (LG) level estimated genetic correlations. CONCLUSIONS: The accuracy of artificial selection in plants species can be increased by using more precise marker-derived estimates of realized coefficients of relationships. All-marker analyses that indirectly account for population- and pedigree structure will be a credible alternative to single-SNP analyses in GWAS. This study revealed large differences in the genetic architecture of apple fruit traits, and the marker-trait associations identified here will help develop genome-based breeding methods for apple cultivar development.
Biological control of aphids in the presence of thrips and their enemies
Messelink, G.J. ; Bloemhard, C.M.J. ; Sabelis, M.W. ; Janssen, A. - \ 2013
BioControl 58 (2013)1. - ISSN 1386-6141 - p. 45 - 55.
intraguild predation - generalist predators - alternative prey - apparent competition - suppression - biocontrol - biodiversity - communities - parasitoids - predictions
Generalist predators are often used in biological control programs, although they can be detrimental for pest control through interference with other natural enemies. Here, we assess the effects of generalist natural enemies on the control of two major pest species in sweet pepper: the green peach aphid Myzus persicae (Sulzer) and the western flower thrips Frankliniella occidentalis (Pergande). In greenhouses, two commonly used specialist natural enemies of aphids, the parasitoid Aphidius colemani Viereck and the predatory midge Aphidoletes aphidimyza (Rondani), were released together with either Neoseiulus cucumeris Oudemans, a predator of thrips and a hyperpredator of A. aphidimyza, or Orius majusculus (Reuter), a predator of thrips and aphids and intraguild predator of both specialist natural enemies. The combined use of O. majusculus, predatory midges and parasitoids clearly enhanced the suppression of aphids and consequently decreased the number of honeydew-contaminated fruits. Although intraguild predation by O. majusculus on predatory midges and parasitoids will have affected control of aphids negatively, this was apparently offset by the consumption of aphids by O. majusculus. In contrast, the hyperpredator N. cucumeris does not prey upon aphids, but seemed to release aphids from control by consuming eggs of the midge. Both N. cucumeris and O. majusculus did not affect rates of aphid parasitism by A. colemani. Thrips were also controlled effectively by O. majusculus. A laboratory experiment showed that adult predatory bugs feed on thrips as well as aphids and have no clear preference. Thus, the presence of thrips probably promoted the establishment of the predatory bugs and thereby the control of aphids. Our study shows that intraguild predation, which is potentially negative for biological control, may be more than compensated by positive effects of generalist predators, such as the control of multiple pests, and the establishment of natural enemies prior to pest invasions. Future work on biological control should focus on the impact of species interactions in communities of herbivorous arthropods and their enemies.
Genomic selection in the French Lacaune dairy sheep breed
Duchemin, S.I. ; Colombani, C. ; Legarra, A. ; Baloche, G. ; Larroque, H. ; Astruc, J.M. - \ 2012
Journal of Dairy Science 95 (2012)5. - ISSN 0022-0302 - p. 2723 - 2733.
genetic-improvement - cattle - predictions
Genomic selection aims to increase accuracy and to decrease generation intervals, thus increasing genetic gains in animal breeding. Using real data of the French Lacaune dairy sheep breed, the purpose of this study was to compare the observed accuracies of genomic estimated breeding values using different models (infinitesimal only, markers only, and joint estimation of infinitesimal and marker effects) and methods [BLUP, Bayes Cp, partial least squares (PLS), and sparse PLS]. The training data set included results of progeny tests of 1,886 rams born from 1998 to 2006, whereas the validation set had results of 681 rams born in 2007 and 2008. The 3 lactation traits studied (milk yield, fat content, and somatic cell scores) had heritabilities varying from 0.14 to 0.41. The inclusion of molecular information, as compared with traditional schemes, increased accuracies of estimated breeding values of young males at birth from 18 up to 25%, according to the trait. Accuracies of genomic methods varied from 0.4 to 0.6, according to the traits, with minor differences among genomic approaches. In Bayes Cp, the joint estimation of marker and infinitesimal effects had a slightly favorable effect on the accuracies of genomic estimated breeding values, and were especially beneficial for somatic cell counts, the less heritable trait. Inclusion of infinitesimal effects also improved slopes of predictive regression equations. Methods that select markers implicitly (Bayes Cp and sparse PLS) were advantageous for some models and traits, and are of interest for further quantitative trait loci studies.
Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures
Bastiaansen, J.W.M. ; Coster, A. ; Calus, M.P.L. ; Arendonk, J.A.M. van; Bovenhuis, H. - \ 2012
Genetics, Selection, Evolution 44 (2012). - ISSN 0999-193X
wide breeding values - dairy-cattle - accuracy - information - predictions - variance - impact
Background: Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects. Methods: Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations. Results: Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure. Conclusions: The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was achieved. The reference population structure had a limited effect on long-term accuracy and response. Use of a shallow reference population, most closely related to the selection candidates, gave early benefits while in later generations, when marker effects were not updated, the estimation of marker effects based on a deeper reference population did not pay off.
Reliability of direct genomic values for animals with different relationships within and to the reference population
Pszczola, M.J. ; Strabel, T. ; Mulder, H.A. ; Calus, M.P.L. - \ 2012
Journal of Dairy Science 95 (2012)1. - ISSN 0022-0302 - p. 389 - 400.
quantitative trait loci - genetic-relationship information - estimated breeding values - dairy-cattle - linkage disequilibrium - holstein population - selection - accuracy - association - predictions
Accuracy of genomic selection depends on the accuracy of prediction of single nucleotide polymorphism effects and the proportion of genetic variance explained by markers. Design of the reference population with respect to its family structure may influence the accuracy of genomic selection. The objective of this study was to investigate the effect of various relationship levels within the reference population and different level of relationship of evaluated animals to the reference population on the reliability of direct genomic breeding values (DGV). The DGV reliabilities, expressed as squared correlation between estimated and true breeding value, were calculated for evaluated animals at 3 heritability levels. To emulate a trait that is difficult or expensive to measure, such as methane emission, reference populations were kept small and consisted of females with own performance records. A population reflecting a dairy cattle population structure was simulated. Four chosen reference populations consisted of all females available in the first genotyped generation. They consisted of highly (HR), moderately (MR), or lowly (LR) related animals, by selecting paternal half-sib families of decreasing size, or consisted of randomly chosen animals (RND). Of those 4 reference populations, RND had the lowest average relationship. Three sets of evaluated animals were chosen from 3 consecutive generations of genotyped animals, starting from the same generation as the reference population. Reliabilities of DGV predictions were calculated deterministically using selection index theory. The randomly chosen reference population had the lowest average relationship within the reference population. Average reliabilities increased when average relationship within the reference population decreased and the highest average reliabilities were achieved for RND (e.g., from 0.53 in HR to 0.61 in RND for a heritability of 0.30). A higher relationship to the reference population resulted in higher reliability values. At the average squared relationship of evaluated animals to the reference population of 0.005, reliabilities were, on average, 0.49 (HR) and 0.63 (RND) for a heritability of 0.30; 0.20 (HR) and 0.27 (RND) for a heritability of 0.05; and 0.07 (HR) and 0.09 (RND) for a heritability of 0.01. Substantial decrease in the reliability was observed when the number of generations to the reference population increased [e.g., for heritability of 0.30, the decrease from evaluated set I (chosen from the same generation as the reference population) to II (one generation younger than the reference population) was 0.04 for HR, and 0.07 for RND]. In this study, the importance of the design of a reference population consisting of cows was shown and optimal designs of the reference population for genomic prediction were suggested.
Effect of enlarging the reference population with (un)genotyped animals on the accuracy of genomic selection in dairy cattle
Pszczola, M.J. ; Mulder, H.A. ; Calus, M.P.L. - \ 2011
Journal of Dairy Science 94 (2011)1. - ISSN 0022-0302 - p. 431 - 441.
genetic evaluation - full pedigree - information - predictions - haplotypes
Genomic selection (GS) permits accurate breeding values to be obtained for young animals, shortening the generation interval and accelerating the genetic gain, thereby leading to reduced costs for proven bulls. Genotyping a large number of animals using high-density single nucleotide polymorphism marker arrays is nevertheless expensive, and therefore, a method to reduce the costs of GS is desired. The aim of this study was to investigate an influence of enlarging the reference population, with either genotyped animals or individuals with predicted genotypes, on the accuracy of genomic estimated breeding values. A dairy cattle population was simulated in which proven bulls with 100 daughters were used as a reference population for GS. Phenotypic records were simulated for bulls with heritability equal to the reliability of daughter yield deviations based on 100 daughters. The simulated traits represented heritabilities at the level of individual daughter performance of 0.3, 0.05, and 0.01. Three scenarios were considered in which (1) the reference population consisted of 1,000 genotyped animals, (2) 1,000 ungenotyped animals were added to the reference population, and (3) the 1,000 animals added in scenario 2 were genotyped in addition to the 1,000 animals from scenario 1. Genotypes for ungenotyped animals were predicted with an average accuracy of 0.58. Additionally, an adjustment of the diagonal elements of the G matrix was proposed for animals with predicted genotypes. The accuracy of genomic estimated breeding values for juvenile animals was the highest for the scenario with 2,000 genotyped animals, being 0.90, 0.79, and 0.60 for the heritabilities of 0.3, 0.05, and 0.01, respectively. Accuracies did not differ significantly between the scenario with 1,000 genotyped animals only and the scenario in which 1,000 ungenotyped animals were added and the adjustment of the G matrix was applied. The absence of significant increase in the accuracy of genomic estimated breeding values was attributed to the low accuracy of predicted genotypes. Although the differences were not significant, the difference between scenario 1 and 2 increased with decreasing heritability. Without the adjustment of the diagonal elements of the G matrix, accuracy decreased. Results suggest that inclusion of ungenotyped animals is only expected to enhance the accuracy of GS when the unknown genotypes can be predicted with high accuracy
Modelling impacts of changes in carbon dioxide concentration, climate and nitrogen deposition on carbon sequestration by European forests and forest soils
Wamelink, G.W.W. ; Wieggers, H.J.J. ; Reinds, G.J. ; Kros, J. ; Mol-Dijkstra, J.P. ; Oijen, M. van; Vries, W. de - \ 2009
Forest Ecology and Management 258 (2009)8. - ISSN 0378-1127 - p. 1794 - 1805.
elevated atmospheric co2 - plant-growth - productivity - ecosystems - temperate - responses - canopy - face - metaanalysis - predictions
Changes in the Earth's atmosphere are expected to influence the growth, and therefore, carbon accumulation of European forests. We identify three major changes: (1) a rise in carbon dioxide concentration, (2) climate change, resulting in higher temperatures and changes in precipitation and (3) a decrease in nitrogen deposition. We adjusted and applied the hydrological model Watbal, the soil model SMART2 and the vegetation model SUMO2 to asses the effect of expected changes in the period 1990 up to 2070 on the carbon accumulation in trees and soils of 166 European forest plots. The models were parameterized using measured soil and vegetation parameters and site-specific changes in temperature, precipitation and nitrogen deposition. The carbon dioxide concentration was assumed to rise uniformly across Europe. The results were compared to a reference scenario consisting of a constant CO2 concentration and deposition scenario. The temperature and precipitation scenario was a repetition of the period between 1960 and 1990. All scenarios were compared to the reference scenario for biomass growth and carbon sequestration for both the soil and the trees. The predicted effects of changes in climate, CO2 concentration and nitrogen deposition on carbon sequestration by trees depend largely on tree species and location (latitude). The assumed decrease in nitrogen deposition causes a decrease of carbon accumulation all over Europe and for all modelled tree species. A rise in carbon dioxide concentration gives a rise in carbon accumulation all over Europe. Climate change gives a mixed result, with a decrease in carbon accumulation in the South of Europe and an increase in the North. When the scenarios are combined, an increase in biomass accumulation is predicted at most of the sites, with a rise in growth rate mostly between 0 and 100%. The predicted effects of a change in climate, CO2 concentration and nitrogen deposition on soil carbon sequestration is generally lower than the effect on carbon sequestration by the trees. However, the magnitude is similar as is the location effect (latitude). A net carbon release was predicted at several sites in the south due to the effect of climate change. Overall, we conclude that where nitrogen deposition was a major driver for a change in forest growth in the past, it is climate change, and to a lesser extent CO2 change, that will influence forest growth in the future.
Regional crop modelling in Europe: The impact of climate conditions and farm characteristics on maize yields
Reidsma, P. ; Ewert, F. ; Boogaard, H. ; Diepen, K. van - \ 2009
Agricultural Systems 100 (2009)1-3. - ISSN 0308-521X - p. 51 - 60.
uk grain yields - simulation-models - land-use - productivity - predictions
Impacts of climate variability and climate change on regional crop yields are commonly assessed using process-based crop models. These models, however, simulate potential and water limited yields, which do not always relate to observed yields. The latter are largely influenced by crop management, which varies by farm and region. Data on specific management strategies may be obtained at the field level, but at the regional level information about the diversity in management strategies is rarely available and difficult to be considered adequately in process-based crop models. Alternatively, understanding the factors influencing management may provide helpful information to improve simulations at the regional level. In this study, we aim to identify factors at the regional level that explain differences between observed and simulated yields. Observed yield data were provided by the Farm Accountancy Data Network (FADN) and Eurostat. The Crop Growth Monitoring System (CGMS), based on the WOFOST model, was used to simulate potential and water limited maize yields in the EU15 (i.e., the old member states of the European Union). Differences between observed and simulated maize yields were analysed using regression models including: (i) climatic factors (temperature and precipitation), (ii) farm size, (iii) farm intensity, (iv) land use, (v) income and (vi) subsidies. We assumed that the highest yields observed in a region were close to the yield potential as determined by climate and considered the average regional yields as also influenced by management. Model performance was analysed with respect to spatial and temporal yield variability. Results indicate that for potential yield, the model performed unsatisfactory in southern regions, where high temperatures increased observed yields which was in contrast to model simulations. When considering management effects, we find that especially irrigation and the maize area explain much of the differences between observed and simulated yields across regions. Simulations of temporal yield variability also diverted from observed data of which about 80% could be explained by the climatic factors (35%) and farm characteristics (50%) considered in the analysis. However, effects of specific factors differed depending on the regions. Accordingly, we propose different groups of regions with factors related to management which should be considered to improve regional yield simulations with CGMS
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?
Vrugt, J.A. ; Braak, C.J.F. ter; Gupta, H.V. ; Robinson, B.A. - \ 2009
Stochastic environmental research and risk assessment 23 (2009)7. - ISSN 1436-3240 - p. 1011 - 1026.
rainfall-runoff models - uncertainty assessment - metropolis algorithm - parameter-estimation - sensitivity - calibration - optimization - zone - methodology - predictions
In recent years, a strong debate has emerged in the hydrologic literature regarding what constitutes an appropriate framework for uncertainty estimation. Particularly, there is strong disagreement whether an uncertainty framework should have its roots within a proper statistical (Bayesian) context, or whether such a framework should be based on a different philosophy and implement informal measures and weaker inference to summarize parameter and predictive distributions. In this paper, we compare a formal Bayesian approach using Markov Chain Monte Carlo (MCMC) with generalized likelihood uncertainty estimation (GLUE) for assessing uncertainty in conceptual watershed modeling. Our formal Bayesian approach is implemented using the recently developed differential evolution adaptive metropolis (DREAM) MCMC scheme with a likelihood function that explicitly considers model structural, input and parameter uncertainty. Our results demonstrate that DREAM and GLUE can generate very similar estimates of total streamflow uncertainty. This suggests that formal and informal Bayesian approaches have more common ground than the hydrologic literature and ongoing debate might suggest. The main advantage of formal approaches is, however, that they attempt to disentangle the effect of forcing, parameter and model structural error on total predictive uncertainty. This is key to improving hydrologic theory and to better understand and predict the flow of water through catchments
Comprehensive theory for star-like polymer micelles: combining classical nucleation and polymer brush theory
Sprakel, J.H.B. ; Leermakers, F.A.M. ; Cohen Stuart, M.A. ; Besseling, N.A.M. - \ 2008
Physical Chemistry Chemical Physics 10 (2008). - ISSN 1463-9076 - p. 5308 - 5316.
telechelic associative polymers - consistent-field-theory - spherical micelles - thermodynamic characteristics - nonionic polymers - block-copolymers - water - micellization - model - predictions
A comprehensive theory is proposed that combines classical nucleation and polymer brush theory to describe star-like polymer micelles. With a minimum of adjustable parameters, the model predicts properties such as critical micelle concentrations and micellar size distributions. The validity of the present theory is evidenced in direct comparison to experiments; this revealed that the proportionality constant in the Daoud¿Cotton model is of the order of unity and that the star-limit is valid down to relatively short corona chains. Furthermore, we show that the predicted saddle points in the free energy correspond to those solutions that are accessible with self-consistent field methods for self-assembly.
TreeDomViewer: a tool for the visualization of phylogeny and protein domain structure
Alako, B.T.F. ; Rainey, D. ; Nijveen, H. ; Leunissen, J.A.M. - \ 2006
Nucleic acids research 34 (2006). - ISSN 0305-1048 - p. W104 - W109.
sequence - predictions - recognition - gene
Phylogenetic analysis and examination of protein domains allow accurate genome annotation and are invaluable to study proteins and protein complex evolution. However, two sequences can be homologous without sharing statistically significant amino acid or nucleotide identity, presenting a challenging bioinformatics problem. We present TreeDomViewer, a visualization tool available as a web-based interface that combines phylogenetic tree description, multiple sequence alignment and InterProScan data of sequences and generates a phylogenetic tree projecting the corresponding protein domain information onto the multiple sequence alignment. Thereby it makes use of existing domain prediction tools such as InterProScan. TreeDom Viewer adopts an evolutionary perspective on how domain structure of two or more sequences can be aligned and compared, to subsequently infer the function of an unknown homolog. This provides insight into the function assignment of, in terms of amino acid substitution, very divergent but yet closely related family members. Our tool produces an interactive scalar vector graphics image that provides orthological relationship and domain content of proteins of interest at one glance. In addition, PDF, JPEG or PNG formatted output is also provided. These features make TreeDomViewer a valuable addition to the annotation pipeline of unknown genes or gene products
A constitutive model with moderate chain stretch for linear polymer melts
Tchesnokov, M.A. ; Molenaar, J. ; Slot, J.J.M. ; Stepanyan, R. - \ 2004
Journal of Non-Newtonian Fluid Mechanics 123 (2004)2-3. - ISSN 0377-0257 - p. 185 - 199.
convective constraint release - cox-merz rule - entangled polymers - microscopic theory - polystyrene solutions - molecular theory - fast flows - shear - reptation - predictions
In our previous publication, we presented a molecular model to describe the dynamics of the interfacial layer between a flowing polymer melt and a die wall. We showed that the ensemble-averaged behavior of polymer molecules adsorbed on the wall could be successfully described in terms of the so-called bond vector probability distribution function (BVPDF). The BVPDF couples the chain orientation and chain stretch on the level of single segment, and thus is an extension of the orientation distribution function of Doi and Edwards introduced for inextensible chains. In this paper, the developed formalism is extended to molecules in the polymer bulk. We show how the well-known Doi and Edwards theory (DE) for inextensible chains based on the orientation distribution function can be naturally extended to include chain stretch and (convective) constraint release (CCR). The final constitutive equation accounts for such mechanisms on polymer chains as reptation, retraction, convection, contour length fluctuations, and (convective) constraint release. It is valid for both linear and non-linear flow regimes. The proposed theory is quantitative, and contains the same input parameters as the original DE model. As an application of the full theory, a simple equation of motion for the stress tensor is derived. Despite the simplicity, its predictions are found to be in good agreement with available experimental data over a wide range of flow regimes and histories.