Breeding without breeding: minimum fingerprinting effort with respect to the effective population size

We present a probabilistic model to minimize the fingerprinting effort associated with the implementation of the “breeding without breeding” scheme under partial pedigree reconstruction. Our approach is directed at achieving a declared target population’s minimum effective population size (N _e ), following the pedigree reconstruction and genotypic selection and is based on the graph theory algorithm. The primary advantage of the proposed method is to reduce the cost associated with fingerprinting before the implementation of the pedigree reconstruction for seed parent–offspring derived from breeding arboreta and production or natural populations. Stochastic simulation was conducted to test the method’s efficiency assuming a simple polygenic model and a single trait. Hypothetical population consisted of 30 parental trees that were paired at random (selfing excluded), resulting in 600 individuals (potential candidates for forwards selection). The male parentage was assumed initially unknown. The model was used to estimate the minimum genotyping sample size needed to reaching the prescribed N _e . Results were compared with the known pedigree data. The model was successful in revealing the true relationship pattern over the whole range of N _e . Two to three offspring entered genotyping to meet the N _e  = 2 while 41 to 43 were required to satisfy the N _e  = 14. Importantly, genetic gain was affected at the lower limits of the genotyping effort. Doubling the number of parents resulted in considerable reduction of the genotyping effort at higher N _e values.     

Synchronization dynamics of two coupled neural oscillators receiving shared and unshared noisy stimuli

The response of neurons to external stimuli greatly depends on the intrinsic dynamics of the network. Here, the intrinsic dynamics are modeled as coupling and the external input is modeled as shared and unshared noise. We assume the neurons are repetitively firing action potentials (i.e., neural oscillators), are weakly and identically coupled, and the external noise is weak. Shared noise can induce bistability between the synchronous and anti-phase states even though the anti-phase state is the only stable state in the absence of noise. We study the Fokker-Planck equation of the system and perform an asymptotic reduction ρ ₀. The ρ ₀ solution is more computationally efficient than both the Monte Carlo simulations and the 2D Fokker-Planck solver, and agrees remarkably well with the full system with weak noise and weak coupling. With moderate noise and coupling, ρ ₀ is still qualitatively correct despite the small noise and coupling assumption in the asymptotic reduction. Our phase model accurately predicts the behavior of a realistic synaptically coupled Morris-Lecar system.

Structure-preserving model reduction of passive and quasi-active neurons

The spatial component of input signals often carries information crucial to a neuron’s function, but models mapping synaptic inputs to the transmembrane potential can be computationally expensive. Existing reduced models of the neuron either merge compartments, thereby sacrificing the spatial specificity of inputs, or apply model reduction techniques that sacrifice the underlying electrophysiology of the model. We use Krylov subspace projection methods to construct reduced models of passive and quasi-active neurons that preserve both the spatial specificity of inputs and the electrophysiological interpretation as an RC and RLC circuit, respectively. Each reduced model accurately computes the potential at the spike initiation zone (SIZ) given a much smaller dimension and simulation time, as we show numerically and theoretically. The structure is preserved through the similarity in the circuit representations, for which we provide circuit diagrams and mathematical expressions for the circuit elements. Furthermore, the transformation from the full to the reduced system is straightforward and depends on intrinsic properties of the dendrite. As each reduced model is accurate and has a clear electrophysiological interpretation, the reduced models can be used not only to simulate morphologically accurate neurons but also to examine computations performed in dendrites.     

Induced Transmembrane Voltage and Its Correlation with Electroporation-Mediated Molecular Transport

Exposure of a cell to an electric field results in inducement of a voltage across its membrane (induced transmembrane voltage, ΔΨ _m) and, for sufficiently strong fields, in a transient increase of membrane permeability (electroporation). We review the analytical, numerical and experimental methods for determination of ΔΨ _m and a method for monitoring of transmembrane transport. We then combine these methods to investigate the correlation between ΔΨ _m and molecular transport through an electroporated membrane for isolated cells of regular and irregular shapes, for cells in dense suspensions as well as for cells in monolayer clusters. Our experiments on isolated cells of both regular and irregular shapes confirm the theoretical prediction that the highest absolute values of ΔΨ _m are found in the membrane regions facing the electrodes and that electroporation-mediated transport is confined to these same regions. For cells in clusters, the location of transport regions implies that, at the field strengths sufficient for electroporation, the cells behave as electrically insulated (i.e., as individual) cells. In contrast, with substantially weaker, nonelectroporating fields, potentiometric measurements show that the cells in these same clusters behave as electrically interconnected cells (i.e., as one large cell). These results suggest that sufficiently high electric fields affect the intercellular pathways and thus alter the electric behavior of the cells with respect to their normal physiological state.     

Impact of magnetic field inhomogeneity on electron cyclotron radiative loss in tokamak reactors

The potential importance of electron cyclotron (EC) emission in the local electron power balance in the steady-state regimes of ITER operation with high temperatures, as well as in the DEMO reactor, requires accurate calculation of the one-dimensional (over magnetic surfaces) distribution of the net radiated power density, P _EC(ρ). When the central electron temperature increases to ∼30 keV, the local EC radiative loss comprises a substantial fraction of the heating power from fusion alphas and is close to the total auxiliary NBI heating power, P _EC(0) ≃ 0.3P _α(0) ≃ P _aux(0). In the present paper, the model of EC radiative transport in an axisymmetric toroidal plasma is extended to the case of an inhomogeneous magnetic field B(R, Z). The impact of such inhomogeneity on local and total power losses is analyzed in the framework of this model by using the CYNEQ code. It is shown that, for the magnetic field B, temperature T _e , density n _e , and wall reflection coefficient R _w expected in ITER and DEMO, accurate simulations of the EC radiative loss require self-consistent 1.5D transport analysis (i.e., one-dimensional simulations of plasma transport and two-dimensional simulations of plasma equilibrium). It is shown that EC radiative transport can be described with good accuracy in the 1D approximation with the surface-averaged magnetic field, B(ρ) = 〈B(R, Z)〉 _ms . This makes it possible to substantially reduce the computational time required for time-dependent self-consistent 1.5D transport analysis. Benchmarking of the CYNEQ results with available results of the RAYTEC, EXACTEC, and CYTRAN codes is performed for various approximations of the magnetic field.     

A Contact-Network-Based Formulation of a Preferential Mixing Model

Heterogeneity in the number of potentially infectious contacts and connectivity correlations (“like attaches to like” i.e., assortatively mixed or “opposites attract” i.e., disassortatively mixed) have important implications for the value of the basic reproduction ratio R ₀ and final epidemic size. In this paper, we present a contact-network-based derivation of a simple differential equation model that accounts for preferential mixing based on the number of contacts. We show that results based on this model are in good qualitative agreement with results obtained from preferential mixing models used in the context of sexually transmitted diseases (STDs). This simple model can accommodate any mixing pattern ranging from completely disassortative to completely assortative and allows the derivation of a series of analytical results.     

H<Subscript>2</Subscript> enrichment from synthesis gas by <Emphasis Type="Italic">Desulfotomaculum</Emphasis><Emphasis Type="Italic">carboxydivorans</Emphasis> for potential applications in synthesis gas purification and biodesulfurization

Desulfotomaculum carboxydivorans, recently isolated from a full-scale anaerobic wastewater treatment facility, is a sulfate reducer capable of hydrogenogenic growth on carbon monoxide (CO). In the presence of sulfate, the hydrogen formed is used for sulfate reduction. The organism grows rapidly at 200 kPa CO, pH 7.0, and 55°C, with a generation time of 100 min, producing nearly equimolar amounts of H₂ and CO₂ from CO and H₂O. The high specific CO conversion rates, exceeding 0.8 mol CO (g protein)⁻¹ h⁻¹, makes this bacterium an interesting candidate for a biological alternative of the currently employed chemical catalytic water–gas shift reaction to purify synthesis gas (contains mainly H₂, CO, and CO₂). Furthermore, as D. carboxydivorans is capable of hydrogenotrophic sulfate reduction at partial CO pressures exceeding 100 kPa, it is also a good candidate for biodesulfurization processes using synthesis gas as electron donor at elevated temperatures, e.g., in biological flue gas desulfurization. Although high maximal specific sulfate reduction rates (32 mmol (g protein)⁻¹ h⁻¹) can be obtained, its sulfide tolerance is rather low and pH dependent, i.e., maximally 9 and 5 mM sulfide at pH 7.2 and pH 6.5, respectively.     

Combining Two-Stage Testing and Interval Mapping Strategies to Detect QTL for Resistance to Bonamiosis in the European Flat Oyster Ostrea edulis

We have identified quantitative trait loci (QTL) in the flat oyster (Ostrea edulis) for resistance to Bonamia ostreae, a parasite responsible for the dramatic reduction in the aquaculture of this species. An F₂ family from a cross between a wild oyster and an individual from a family selected for resistance to bonamiosis was cultured with wild oysters injected with the parasite, leading to 20% cumulative mortality. Selective genotyping of 92 out of a total of 550 F₂ progeny (i.e., 46 heavily infected oysters that died and 46 parasite-free oysters that survived) was performed using 20 microsatellites and 34 amplification fragment length polymorphism primer pairs. Both a two-stage testing strategy and QTL interval mapping methods were used. The two-stage detection strategy had a high power with a low rate of false positives and identified nine and six probable markers linked to genes of resistance and susceptibility, respectively. Parent-specific genetic linkage maps were built for the family, spanning ten linkage groups (n = 10) with an observed genome coverage of 69–84%. Three QTL were identified by interval mapping in the first parental map and two in the second. Good concordance was observed between the results obtained after the two-stage testing strategy and QTL mapping.     

The importance of base composition in the correct assessment of genetic distance

Through a simple computer simulation, we provide clear evidence that the base composition of nucleotide sequences should be taken into account to obtain accurate estimates of the genetic distances between homologous nucleotide sequences. We tested several stochastic models and demonstrated clearly that the inferred estimates of the number of substitutions are strongly dependent on the a priori conditions superimposed in the model, i.e., equiprobability in base composition and/or transition transversion ratio. In general, the more a priori assumptions there are, the more inaccurate the results. Whereas, rather accurate estimates are obtained with stochastic methods, which take into account base composition and do not superimpose unverified a priori conditions. Correspondence to: G. Pesole     

Monitoring the biofertilizing potential and establishment of inoculated cyanobacteria in soil using physiological and molecular markers

This paper aims to develop methods for quantifying their establishment; using physiological activity (chlorophyll as a growth index and nitrogen-fixing potential as a measure of their biofertilizing capacity), along with evaluation based on DNA fingerprints generated using repeat sequences/palindromes. Time course studies were undertaken in liquid and soil microcosm experiments inoculated with a set of four rhizosphere cyanobacterial strains (BF1 Anabaena sp., BF2 Nostoc sp., BF3 Nostoc sp., BF4 Anabaena sp.). Observations revealed the synergistic effect of three-membered combinations (especially the i.e. BF1 + 2 + 3, 1 + 2 + 4, 1 + 3 + 4) in terms of enhancing chlorophyll and acetylene reducing activity. PCR-based amplification profiles (using short tandemly repetitive repeat (STRR) 1A, STRR_mod, and HIP_AT sequences) proved discriminative in monitoring the presence of the inoculated cyanobacteria in soil microcosm. Future work is in progress to assess the utility of the selected markers/primers in pot experiments, followed by field-level experiments with crop.     

Toward an accurate statistics of gapped alignments

Sequence alignment has been an invaluable tool for finding homologous sequences. The significance of the homology found is often quantified statistically by p-values. Theory for computing p-values exists for gapless alignments [Karlin, S., Altschul, S.F., 1990. Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc. Natl. Acad. Sci. USA 87, 2264–2268; Karlin, S., Dembo A., 1992. Limit distributions of maximal segmental score among Markov-dependent partial sums. Adv. Appl. Probab. 24, 13–140], but a full generalization to alignments with gaps is not yet complete. We present a unified statistical analysis of two common sequence comparison algorithms: maximum-score (Smith-Waterman) alignments and their generalized probabilistic counterparts, including maximum-likelihood alignments and hidden Markov models. The most important statistical characteristic of these algorithms is the distribution function of the maximum score S _max, resp. the maximum free energy F _max, for mutually uncorrelated random sequences. This distribution is known empirically to be of the Gumbel form with an exponential tail P(S _max > x) ∼ exp(−λx) for maximum-score alignment and P(F _max > x) ∼ exp(−λx) for some classes of probabilistic alignment. We derive an exact expression for λ for particular probabilistic alignments. This result is then used to obtain accurate λ values for generic probabilistic and maximum-score alignments. Although the result demonstrated uses a simple match-mismatch scoring system, it is expected to be a good starting point for more general scoring functions.     

A stochastic model for the synthesis and degradation of natural organic matter part II: molecular property distributions

A stochastic biogeochemical model has been developed to simulate the transformation and degradation of natural organic matter (NOM) using an agent-based algorithm which treats each molecule as a separate and potentially unique entity. Molecules react when a pseudo-random number is lower than the calculated reaction probability in a given time step; repeated time steps simulate the transformation of precursor molecules into a complex NOM assemblage. The data for each molecule—elemental and functional group composition—can be used to calculate many properties directly and exactly for each molecule in the assemblage, e.g., molecular weight (MW), fraction of aromatic C (Ar), and charge at pH 7 (Z). Empirical quantitative structure activity relationships (QSARs) are developed which permit the estimation of thermodynamic quantities K _ow (the octanol–water partition coefficient) and pK _a (acidity) for each molecule. Root mean square errors for these QSARs are 0.39 log units for log K _ow and 0.45 log units for pK _a. Distributions of both exactly calculated (MW, Ar, Z) and estimated thermodynamic (K _ow, pK _a) properties are examined and compared with published experimental data. Molecular weight distributions from size exclusion HPLC experiments on aquatic NOM are quantitatively similar to simulation results. pH titrations and polarity distributions from reversed-phase HPLC are qualitatively similar to simulation results. This agreement suggests that the agent-based model can be used to explore hypotheses regarding both compositional and thermodynamic properties of NOM. Robert Wetzel—deceased.     

Biochemical characterization of ethanol-dependent reduction of furfural by alcohol dehydrogenases

Lignocellulosic biomass is usually converted to hydrolysates, which consist of sugars and sugar derivatives, such as furfural. Before yeast ferments sugars to ethanol, it reduces toxic furfural to non-inhibitory furfuryl alcohol in a prolonged lag phase. Bioreduction of furfural may shorten the lag phase. Cupriavidus necator JMP134 rapidly reduces furfural with a Zn-dependent alcohol dehydrogenase (FurX) at the expense of ethanol (Li et al. 2011). The mechanism of the ethanol-dependent reduction of furfural by FurX and three homologous alcohol dehydrogenases was investigated. The reduction consisted of two individual reactions: ethanol-dependent reduction of NAD⁺ to NADH and then NADH-dependent reduction of furfural to furfuryl alcohol. The kinetic parameters of the coupled reaction and the individual reactions were determined for the four enzymes. The data indicated that limited NADH was released in the coupled reaction. The enzymes had high affinities for NADH (e.g., K _d of 0.043 μM for the FurX-NADH complex) and relatively low affinities for NAD⁺ (e.g., K _d of 87 μM for FurX-NAD⁺). The kinetic data suggest that the four enzymes are efficient “furfural reductases” with either ethanol or NADH as the reducing power. The standard free energy change (ΔG°′) for ethanol-dependent reduction of furfural was determined to be −1.1 kJ mol⁻¹. The physiological benefit for ethanol-dependent reduction of furfural is likely to replace toxic and recalcitrant furfural with less toxic and more biodegradable acetaldehyde.     

Effect of mutation on helper T-cells and viral population: A computer simulation model for HIV

Summary A Monte Carlo simulation is proposed to study the dynamics of helper T-cells (N _H) and viral (N _V) populations in an immune response model relevant to HIV. Cellular states are binary variables and the interactions are described by logical expressions. Viral population shows a nonmonotonic growth before reaching a constant value while helper T-cells grow to a constant after a relaxation/reaction time. Initially, the population of helper cells grows with time with a power-law, N _H ∼t ^β, before reaching the steady-state; the growth exponent β increases systematically (β ≈ 1 – 2) with the mutation rate (P _mut≈0.1–0.4). The critical recovery time (t _c) increases exponentially with the viral mutation, t _c≈Ae ^αP _mut , with α=4.52±0.29 in low mutation regime and α=15.21±1.41 in high mutation regime. The equilibrium population of helper T-cell declines slowly with P _mut and collapses at ∼ 0.40; the viral population exhibits a reverse trend, i.e., a slow increase before the burst around the same mutation regime.     

Conservation genetics of Houbara Bustard (Chlamydotis undulata undulata): population structure and its implications for the reinforcement of wild populations

The major decline of Houbara Bustards—sensu lato—throughout their range has led to their classification as ‘vulnerable’ on the IUCN Red List. Within this context, a captive breeding program was established in Morocco to restock North African wild populations of Houbara Bustard (Chlamydotis undulata undulata). At present, founders originate from locations that are currently being reinforced through the addition of captive bred individuals. However, it is planned to restock others areas of the species’ range. Before this could be considered, an accurate knowledge of the genetic structure of the wild recipient population is essential to delineate potential conservation units. We therefore sampled populations throughout most of the remaining range, and used several methods to evaluate their genetic differentiation by means of both mtDNA and microsatellite markers. Very little genetic differentiation was found for both genetic markers (Φ_st ranged from −0.181 to 0.118 and F _st ranged from −0.004 to 0.019). This suggests that C. u. undulata populations could be managed as a single Conservation Unit.     

Mechanisms of very fast oscillations in networks of axons coupled by gap junctions

Because electrical coupling among the neurons of the brain is much faster than chemical synaptic coupling, it is natural to hypothesize that gap junctions may play a crucial role in mechanisms underlying very fast oscillations (VFOs), i.e., oscillations at more than 80 Hz. There is now a substantial body of experimental and modeling literature supporting this hypothesis. A series of modeling papers, starting with work by Roger Traub and collaborators, have suggested that VFOs may arise from expanding waves propagating through an “axonal plexus”, a large random network of electrically coupled axons. Traub et al. also proposed a cellular automaton (CA) model to study the mechanisms of VFOs in the axonal plexus. In this model, the expanding waves take the appearance of topologically circular “target patterns”. Random external stimuli initiate each wave. We therefore call this kind of VFO “externally driven”. Using a computational model, we show that an axonal plexus can also exhibit a second, distinctly different kind of VFO in a wide parameter range. These VFOs arise from activity propagating around cycles in the network. Once triggered, they persist without any source of excitation. With idealized, regular connectivity, they take the appearance of spiral waves. We call these VFOs “re-entrant”. The behavior of the axonal plexus depends on the reliability with which action potentials propagate from one axon to the next, which, in turn, depends on the somatic membrane potential V _s and the gap junction conductance g _gj . To study these dependencies, we impose a fixed value of V _s , then study the effects of varying V _s and g _gj . Not surprisingly, propagation becomes more reliable with rising V _s and g _gj . Externally driven VFOs occur when V _s and g _gj are so high that propagation never fails. For lower V _s or g _gj , propagation is nearly reliable, but fails in rare circumstances. Surprisingly, the parameter regime where this occurs is fairly large. Even a single propagation failure can trigger re-entrant VFOs in this regime. Lowering V _s and g _gj further, one finds a third parameter regime in which propagation is unreliable, and no VFOs arise. We analyze these three parameter regimes by means of computations using model networks adapted from Traub et al., as well as much smaller model networks.     

Evaluating the carbon balance estimate from an automated ground‐level flux chamber system in artificial grass mesocosms

Measuring and modeling carbon (C) stock changes in terrestrial ecosystems are pivotal in addressing global C‐cycling model uncertainties. Difficulties in detecting small short‐term changes in relatively large C stocks require the development of robust sensitive flux measurement techniques. Net ecosystem exchange (NEE) ground‐level chambers are increasingly used to assess C dynamics in low vegetation ecosystems but, to date, have lacked formal rigorous field validation against measured C stock changes. We developed and deployed an automated and multiplexed C‐flux chamber system in grassland mesocosms in order rigorously to compare ecosystem total C budget obtained using hourly C‐flux measurements versus destructive net C balance. The system combines transparent NEE and opaque respiration chambers enabling partitioning of photosynthetic and respiratory fluxes. The C‐balance comparison showed good agreement between the two methods, but only after NEE fluxes were corrected for light reductions due to chamber presence. The dark chamber fluxes allowed assessing temperature sensitivity of ecosystem respiration (R_eco) components (i.e., heterotrophic vs. autotrophic) at different growth stages. We propose that such automated flux chamber systems can provide an accurate C balance, also enabling pivotal partitioning of the different C‐flux components (e.g., photosynthesis and respiration) suitable for model evaluation and developments.     

Temperature Sensing by Plants: Calcium-Permeable Channels as Primary Sensors—A Model

Recently the properties of temperature sensing in plants have been demonstrated experimentally by Plieth et al. (The Plant Journal 1999. 18:491–497). The relevant biophysical parameters are established here by mathematical modeling in order to understand the experimental findings in quantitative terms. A simple one-compartment model is presented, as a preliminary approach to explain how the input signal (i.e., temperature T) is perceived and how the information is translated into an output signal in the plant cell (i.e., [Ca²⁺] _c ). The model is based on the fact that calcium influx into the cytoplasm is mediated by calcium-permeable channels which are assumed to be solely dependent on cooling rate (dT/dt) and calcium efflux is mediated by calcium pumps which have been shown to be dependent on absolute temperature (T). Firstly, it is demonstrated that this model is able to meet the demand for a satisfactory interpretation of the experimental data, and secondly that it reproduces the experimentally observed features of the cooling induced [Ca²⁺] _c changes well. This suggests that the primary temperature sensor in plants might be a Ca²⁺-permeable channel. Received: 4 June 1999/Revised: 26 July 1999     

Generality of the Final Size Formula for an Epidemic of a Newly Invading Infectious Disease

The well-known formula for the final size of an epidemic was published by Kermack and McKendrick in 1927. Their analysis was based on a simple susceptible-infected-recovered (SIR) model that assumes exponentially distributed infectious periods. More recent analyses have established that the standard final size formula is valid regardless of the distribution of infectious periods, but that it fails to be correct in the presence of certain kinds of heterogeneous mixing (e.g., if there is a core group, as for sexually transmitted diseases). We review previous work and establish more general conditions under which Kermack and McKendrick's formula is valid. We show that the final size formula is unchanged if there is a latent stage, any number of distinct infectious stages and/or a stage during which infectives are isolated (the durations of each stage can be drawn from any integrable distribution). We also consider the possibility that the transmission rates of infectious individuals are arbitrarily distributed—allowing, in particular, for the existence of super-spreaders—and prove that this potential complexity has no impact on the final size formula. Finally, we show that the final size formula is unchanged even for a general class of spatial contact structures. We conclude that whenever a new respiratory pathogen emerges, an estimate of the expected magnitude of the epidemic can be made as soon the basic reproduction number ℝ₀ can be approximated, and this estimate is likely to be improved only by more accurate estimates of ℝ₀, not by knowledge of any other epidemiological details.