A Quantitative and Dynamic Model of the Arabidopsis Flowering Time Gene Regulatory Network

Various environmental signals integrate into a network of floral regulatory genes leading to the final decision on when to flower. Although a wealth of qualitative knowledge is available on how flowering time genes regulate each other, only a few studies incorporated this knowledge into predictive models. Such models are invaluable as they enable to investigate how various types of inputs are combined to give a quantitative readout. To investigate the effect of gene expression disturbances on flowering time, we developed a dynamic model for the regulation of flowering time in Arabidopsis thaliana. Model parameters were estimated based on expression time-courses for relevant genes, and a consistent set of flowering times for plants of various genetic backgrounds. Validation was performed by predicting changes in expression level in mutant backgrounds and comparing these predictions with independent expression data, and by comparison of predicted and experimental flowering times for several double mutants. Remarkably, the model predicts that a disturbance in a particular gene has not necessarily the largest impact on directly connected genes. For example, the model predicts that SUPPRESSOR OF OVEREXPRESSION OF CONSTANS (SOC1) mutation has a larger impact on APETALA1 (AP1), which is not directly regulated by SOC1, compared to its effect on LEAFY (LFY) which is under direct control of SOC1. This was confirmed by expression data. Another model prediction involves the importance of cooperativity in the regulation of APETALA1 (AP1) by LFY, a prediction supported by experimental evidence. Concluding, our model for flowering time gene regulation enables to address how different quantitative inputs are combined into one quantitative output, flowering time.     

The Gender Gap in Second Language Acquisition: Gender Differences in the Acquisition of Dutch among Immigrants from 88 Countries with 49 Mother Tongues

Gender differences were analyzed across countries of origin and continents, and across mother tongues and language families, using a large-scale database, containing information on 27,119 adult learners of Dutch as a second language. Female learners consistently outperformed male learners in speaking and writing proficiency in Dutch as a second language. This gender gap remained remarkably robust and constant when other learner characteristics were taken into account, such as education, age of arrival, length of residence and hours studying Dutch. For reading and listening skills in Dutch, no gender gap was found. In addition, we found a general gender by education effect for all four language skills in Dutch for speaking, writing, reading, and listening. Female language learners turned out to profit more from higher educational training than male learners do in adult second language acquisition. These findings do not seem to match nurture-oriented explanatory frameworks based for instance on a human capital approach or gender-specific acculturation processes. Rather, they seem to corroborate a nature-based, gene-environment correlational framework in which language proficiency being a genetically-influenced ability interacting with environmental factors such as motivation, orientation, education, and learner strategies that still mediate between endowment and acquiring language proficiency at an adult stage.     

Modeling Lignin Polymerization. I. Simulation Model of Dehydrogenation Polymers

Lignin is a heteropolymer that is thought to form in the cell wall by combinatorial radical coupling of monolignols. Here, we present a simulation model of in vitro lignin polymerization, based on the combinatorial coupling theory, which allows us to predict the reaction conditions controlling the primary structure of lignin polymers. Our model predicts two controlling factors for the β-O-4 content of syringyl-guaiacyl lignins: the supply rate of monolignols and the relative amount of supplied sinapyl alcohol monomers. We have analyzed the in silico degradability of the resulting lignin polymers by cutting the resulting lignin polymers at β-O-4 bonds. These are cleaved in analytical methods used to study lignin composition, namely thioacidolysis and derivatization followed by reductive cleavage, under pulping conditions, and in some lignocellulosic biomass pretreatments.Lignins are aromatic polymers that are predominantly present in secondarily thickened cell walls. These polymers make the cell wall rigid and impervious, allowing transport of water and nutrients through the vascular system and protecting plants against microbial invasion. Lignins are heterogeneous polymers derived from phenylpropanoid monomers, mainly the hydroxycinnamyl alcohols coniferyl alcohol (G-monomer) and sinapyl alcohol (S-monomer) and minor amounts of p-coumaryl alcohol (H-monomer). These monolignols differ in their degree of aromatic methoxylation (-OCH₃ group; Fig. 1). The resulting units in the lignin polymer are the guaiacyl (G), syringyl (S), and p-hydroxyphenyl (H) units. They are linked by a variety of chemical bonds (Fig. 2) that have different chemical properties (Boerjan et al., 2003; Ralph et al., 2004; Vanholme et al., 2008).Open in a separate windowFigure 1.Chemical structures of three monolignols. A, H-monomer (p-coumaryl alcohol). B, G-monomer (coniferyl alcohol). C, S-monomer (sinapyl alcohol). G- and S-monomers are considered in our simulations. The G-monomer is methoxylated (-OCH₃ group) on position 3, and the S-monomer is methoxylated on positions 3 and 5.Open in a separate windowFigure 2.Chemical structures resulting from the possible bonding between two monomers (A) or a monomer and the bindable end of an oligomer (B). X and Y in the monomers denote the absence (for a G-unit) or presence (for an S-unit) of a methoxyl group at position 5 (see Fig. 1). The red line indicates the bonds generated by couplings of the B position and B, 4, or 5 position.Lignification is the process by which monomers and/or oligomers are polymerized via radical coupling reactions and typically occurs after the polysaccharides have been laid down in the cell wall. Lignin composition varies among cell types and can even be different in individual cell wall layers (Ruel et al., 2009). Lignin composition is also influenced by environmental conditions; for example, lignin in compression wood is enriched in H-units (Timell, 1986). Hence, both developmental and environmental parameters influence the composition and thus the structure of the lignin polymer (Boerjan et al., 2003; Ralph et al., 2004).Lignin is one of the main negative factors in the conversion of lignocellulosic plant biomass into pulp and bioethanol (Lynd et al., 1991; Hill et al., 2006). In these processes, lignin needs to be degraded by chemical or mechanical processes that are expensive and often environmentally polluting. Hence, major research efforts are devoted toward understanding lignin biosynthesis and structure. It has already been shown that reducing lignin content and modifying its composition in transgenic plants can result in dramatic improvements in pulping efficiency (Pilate et al., 2002; Baucher et al., 2003; Huntley et al., 2003; Leplé et al., 2007) and in the conversion of biomass into bioethanol (Stewart et al., 2006; Chen and Dixon, 2007; Custers, 2009). These altered biomass properties are related to the alterations in lignin composition and structure in terms of the frequencies of the lignin units and the bond types connecting them and possibly also their interaction with hemicelluloses (Ralph et al., 2004; Ralph, 2006).To study the parameters that influence lignin structure, lignin polymerization has been mimicked in vitro by experiments with dehydrogenation polymers (DHPs; Terashima et al., 1995). Indeed, lignification can be mimicked by oxidizing monolignols using a peroxidase, such as horseradish peroxidase (HRP), and supplying its cofactor hydrogen peroxide, producing synthetic DHP lignins. Monolignol oxidation can also be achieved without enzymes (e.g. by using transition metal one-electron oxidants, such as copper acetate). Some of these biomimetic DHPs have been suggested to be better models for wood lignins than HRP-generated DHPs (Landucci, 2000).In DHP experiments, the monolignols are either added in bulk (Zulauf experiment) or dropwise (Zutropf experiment) to the reaction mixture, yielding lignin polymers with very different bond frequencies (Freudenberg, 1956). Zutropf experiments approach the in vivo formation of lignin, which depends on the slow introduction of monolignols into the wall matrix via diffusion to the site of incorporation (Hatfield and Vermerris, 2001). Because the exact reaction conditions are known, such in vitro experiments have provided insight into the lignification process in planta. In this way, numerous factors were shown to influence lignin structure, including the relative supply of the monolignols, the pH, the presence of polysaccharides, hydrogen peroxide concentrations, and cell wall matrix elements in general (Grabber et al., 2003; Vanholme et al., 2008).Computer simulations of lignin polymerization can help explain and predict lignin structure from low-level chemical kinetic factors, including subunit-coupling probabilities and monolignol synthesis rates. Such models are helpful in explaining the mechanism behind a range of controlling factors identified in the experimental work, including (1) the ratio of coniferyl versus sinapyl alcohol monolignols, (2) the monolignol supply rate, and (3) the abundance of alternative monomers present during lignin biosynthesis in mutants and transgenics. Thus, computer models will also help in suggesting new targets for controlled lignin biosynthesis.Here, we propose a simulation model of synthetic lignin polymerization that is based upon an emerging consensus from a variety of observations and derives from a series of previous models of lignin polymerization (Glasser and Glasser, 1974; Glasser et al., 1976; Jurasek, 1995; Roussel and Lim, 1995). Our model uses a symbolic grammar to describe a constructive dynamical system (Fontana, 1992) or a rule-based system (Feret et al., 2009) in which it is not necessary to define all possible products in advance. We assume that G- and S-monomers and newly formed oligomers couple in a well-mixed medium, depending on coupling rules and experimentally measured coupling probabilities. To develop the model, we have used information from DHP experiments rather than natural lignins, as they are formed in a well-mixed medium and their reaction conditions are well known (e.g. the influx rate of monomers). Using information from natural lignin would have further complicated our model, as the structures of natural lignin polymers are influenced by many factors, including the possible involvement of dirigent proteins (Davin and Lewis, 2005), steric hindrance by polysaccharides, spatiotemporal regulation, and modifications during isolation procedures (Boerjan et al., 2003; Ralph et al., 2004).Using our simulation models, we study how putative controlling factors of lignin primary structure, including the influx rate of monomers and the relative amount of S-monomers, affect in silico lignin synthesis, and we compare our predictions with in vitro experiments. To predict the degradability of lignins formed in our simulations, we apply an in silico thioacidolysis, which cleaves the polymers at their β-O-4 positions. This simulates the molecular action of two of the most used methods to analyze lignin composition, thioacidolysis (Lapierre, 1993; Baucher et al., 2003) and derivatization followed by reductive cleavage (Lu and Ralph, 1997). The G+S-monomer yield is often taken as a reflection of the fraction of units bound by β-O-4 bonds. Cleavage of β-O-4 bonds is also the most important reaction in kraft pulping of wood (Baucher et al., 2003). The model predicts from first principles (1) that DHP lignins formed under Zutropf conditions have a higher β-O-4 content than those formed under Zulauf conditions, (2) that DHP lignins formed with high S content have a higher β-O-4 content than those formed with high G content, and (3) that a higher β-O-4 content does not necessarily reduce the average length of lignin fragments generated during in silico thioacidolysis.     

Mycorrhizal diversity,seed germination and long‐term changes in population size across nine populations of the terrestrial orchid Neottia ovata

In plant species that rely on mycorrhizal symbioses for germination and seedling establishment, seedling recruitment and temporal changes in abundance can be expected to depend on fungal community composition and local environmental conditions. However, disentangling the precise factors that determine recruitment success in species that critically rely on mycorrhizal fungi represents a major challenge. In this study, we used seed germination experiments, 454 amplicon pyrosequencing and assessment of soil conditions to investigate the factors driving changes in local abundance in 28 populations of the orchid Neottia ovata. Comparison of population sizes measured in 2003 and 2013 showed that nearly 60% of the studied populations had declined in size (average growth rate across all populations: ?0.01). Investigation of the mycorrhizal fungi in both the roots and soil revealed a total of 68 species of putatively mycorrhizal fungi, 21 of which occurred exclusively in roots, 25 that occurred solely in soil and 22 that were observed in both the soil and roots. Seed germination was limited and significantly and positively related to soil moisture content and soil pH, but not to fungal community composition. Large populations or populations with high population growth rates showed significantly higher germination than small populations or populations declining in size, but no significant relationships were found between population size or growth and mycorrhizal diversity. Overall, these results indicate that temporal changes in abundance were related to the ability of seeds to germinate, but at the same time they provided limited evidence that variation in fungal communities played an important role in determining population dynamics.     

Homologues of potato chromosome 5 show variable collinearity in the euchromatin,but dramatic absence of sequence similarity in the pericentromeric heterochromatin

Background

In flowering plants it has been shown that de novo genome assemblies of different species and genera show a significant drop in the proportion of alignable sequence. Within a plant species, however, it is assumed that different haplotypes of the same chromosome align well. In this paper we have compared three de novo assemblies of potato chromosome 5 and report on the sequence variation and the proportion of sequence that can be aligned.

Results

For the diploid potato clone RH89-039-16 (RH) we produced two linkage phase controlled and haplotype-specific assemblies of chromosome 5 based on BAC-by-BAC sequencing, which were aligned to each other and compared to the 52 Mb chromosome 5 reference sequence of the doubled monoploid clone DM 1–3 516 R44 (DM). We identified 17.0 Mb of non-redundant sequence scaffolds derived from euchromatic regions of RH and 38.4 Mb from the pericentromeric heterochromatin. For 32.7 Mb of the RH sequences the correct position and order on chromosome 5 was determined, using genetic markers, fluorescence in situ hybridisation and alignment to the DM reference genome. This ordered fraction of the RH sequences is situated in the euchromatic arms and in the heterochromatin borders. In the euchromatic regions, the sequence collinearity between the three chromosomal homologs is good, but interruption of collinearity occurs at nine gene clusters. Towards and into the heterochromatin borders, absence of collinearity due to structural variation was more extensive and was caused by hemizygous and poorly aligning regions of up to 450 kb in length. In the most central heterochromatin, a total of 22.7 Mb sequence from both RH haplotypes remained unordered. These RH sequences have very few syntenic regions and represent a non-alignable region between the RH and DM heterochromatin haplotypes of chromosome 5.

Conclusions

Our results show that among homologous potato chromosomes large regions are present with dramatic loss of sequence collinearity. This stresses the need for more de novo reference assemblies in order to capture genome diversity in this crop. The discovery of three highly diverged pericentric heterochromatin haplotypes within one species is a novelty in plant genome analysis. The possible origin and cytogenetic implication of this heterochromatin haplotype diversity are discussed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1578-1) contains supplementary material, which is available to authorized users.     

Implementation of asymmetric yielding in case-specific finite element models improves the prediction of femoral fractures

Although asymmetric yielding in bone is widely shown in experimental studies, previous case-specific non-linear finite element (FE) studies have mainly adopted material behaviour using the Von Mises yield criterion (VMYC), assuming equal bone strength in tension and compression. In this study, it was verified that asymmetric yielding in FE models can be captured using the Drucker-Prager yield criterion (DPYC), and can provide better results than simulations using the VMYC. A sensitivity analysis on parameters defining the DPYC (i.e. the degree of yield asymmetry and the yield stress settings) was performed, focusing on the effect on bone failure. In this study, the implementation of a larger degree of yield asymmetry improved the prediction of the fracture location; variations in the yield stress mainly affected the predicted failure force. We conclude that the implementation of asymmetric yielding in case-specific FE models improves the prediction of femoral bone strength.     

Toward the modeling of mucus draining from the human lung: role of the geometry of the airway tree

Mucociliary clearance and cough are the two main natural mucus draining methods in the bronchial tree. If they are affected by a pathology, they can become insufficient or even ineffective, then therapeutic draining of mucus plays a critical role to keep mucus levels in the lungs acceptable. The manipulations of physical therapists are known to be very efficient clinically but they are mostly empirical since the biophysical mechanisms involved in these manipulations have never been studied. We develop in this work a model of mucus clearance in idealized rigid human bronchial trees and focus our study on the interaction between (1) tree geometry, (2) mucus physical properties and (3) amplitude of flow rate in the tree. The mucus is considered as a Bingham fluid (gel-like) which is moved upward in the tree thanks to its viscous interaction with air flow. Our studies point out the important roles played both by the geometry and by the physical properties of mucus (yield stress and viscosity). More particularly, the yield stress has to be overcome to make mucus flow. Air flow rate and yield stress determine the maximal possible mucus thickness in each branch of the tree at equilibrium. This forms a specific distribution of mucus in the tree whose characteristics are strongly related to the multi-scaled structure of the tree. The behavior of any mucus distribution is then dependent on this distribution. Finally, our results indicate that increasing air flow rates ought to be more efficient to drain mucus out of the bronchial tree while minimizing patient discomfort.     

SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks

Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.