On the origin of DNA genomes: evolution of the division of labor between template and catalyst in model replicator systems

The division of labor between template and catalyst is a fundamental property of all living systems: DNA stores genetic information whereas proteins function as catalysts. The RNA world hypothesis, however, posits that, at the earlier stages of evolution, RNA acted as both template and catalyst. Why would such division of labor evolve in the RNA world? We investigated the evolution of DNA-like molecules, i.e. molecules that can function only as template, in minimal computational models of RNA replicator systems. In the models, RNA can function as both template-directed polymerase and template, whereas DNA can function only as template. Two classes of models were explored. In the surface models, replicators are attached to surfaces with finite diffusion. In the compartment models, replicators are compartmentalized by vesicle-like boundaries. Both models displayed the evolution of DNA and the ensuing division of labor between templates and catalysts. In the surface model, DNA provides the advantage of greater resistance against parasitic templates. However, this advantage is at least partially offset by the disadvantage of slower multiplication due to the increased complexity of the replication cycle. In the compartment model, DNA can significantly delay the intra-compartment evolution of RNA towards catalytic deterioration. These results are explained in terms of the trade-off between template and catalyst that is inherent in RNA-only replication cycles: DNA releases RNA from this trade-off by making it unnecessary for RNA to serve as template and so rendering the system more resistant against evolving parasitism. Our analysis of these simple models suggests that the lack of catalytic activity in DNA by itself can generate a sufficient selective advantage for RNA replicator systems to produce DNA. Given the widespread notion that DNA evolved owing to its superior chemical properties as a template, this study offers a novel insight into the evolutionary origin of DNA.     

An improved alignment-free model for dna sequence similarity metric

Background

DNA Clustering is an important technology to automatically find the inherent relationships on a large scale of DNA sequences. But the DNA clustering quality can still be improved greatly. The DNA sequences similarity metric is one of the key points of clustering. The alignment-free methodology is a very popular way to calculate DNA sequence similarity. It normally converts a sequence into a feature space based on words’ probability distribution rather than directly matches strings. Existing alignment-free models, e.g. k-tuple, merely employ word frequency information and ignore many types of useful information contained in the DNA sequence, such as classifications of nucleotide bases, position and the like. It is believed that the better data mining results can be achieved with compounded information. Therefore, we present a new alignment-free model that employs compounded information to improve the DNA clustering quality.

Results

This paper proposes a Category-Position-Frequency (CPF) model, which utilizes the word frequency, position and classification information of nucleotide bases from DNA sequences. The CPF model converts a DNA sequence into three sequences according to the categories of nucleotide bases, and then yields a 12-dimension feature vector. The feature values are computed by an entropy based model that takes both local word frequency and position information into account. We conduct DNA clustering experiments on several datasets and compare with some mainstream alignment-free models for evaluation, including k-tuple, DMk, TSM, AMI and CV. The experiments show that CPF model is superior to other models in terms of the clustering results and optimal settings.

Conclusions

The following conclusions can be drawn from the experiments. (1) The hybrid information model is better than the model based on word frequency only. (2) For DNA sequences no more than 5000 characters, the preferred size of sliding windows for CPF is two which provides a great advantage to promote system performance. (3) The CPF model is able to obtain an efficient stable performance and broad generalization.     

Applying the stochastic difference equation to DNA conformational transitions: a study of B-Z and B-A DNA transitions

Despite the existence of numerous models to account for the B-Z DNA transition, experimenters have not yet arrived at a conclusive answer to the structural and dynamical features of the B-Z transition. By applying the stochastic difference equation to simulate the B-Z DNA transition, we have shown that the stretched intermediate model of the B-Z transition is more probable than other B-Z transition models such as the Harvey model. This is accomplished by comparing potential energy profiles of various B-Z DNA transition models and calculating relative probabilities based on the stochastic difference equation with respect to length (SDEL) formalism. The results garnered in this article allow for new approaches in determining the structural transition of B-DNA to Z-DNA experimentally. We have also simulated the B-A DNA transition using the stochastic difference equation. Unlike the B-Z DNA transition, the mechanism for the B-A DNA transition is well established. The variation in the pseudorotation angle during the transition is in good agreement with experimental results. Qualitative features of the simulated B-A transition also agree well with experimental data. The SDEL approach is thus a suitable numerical technique to compute long-time molecular dynamics trajectory for DNA molecules.     

Assessing the performance of DNA barcoding using posterior predictive simulations

Accurate estimates of biodiversity are required for research in a broad array of biological subdisciplines including ecology, evolution, systematics, conservation and biodiversity science. The use of statistical models and genetic data, particularly DNA barcoding, has been suggested as an important tool for remedying the large gaps in our current understanding of biodiversity. However, the reliability of biodiversity estimates obtained using these approaches depends on how well the statistical models that are used describe the evolutionary process underlying the genetic data. In this study, we utilize data from the Barcode of Life Database and posterior predictive simulations to assess the performance of DNA barcoding under commonly used substitution models. We demonstrate that the success of DNA barcoding varies widely across DNA substitution models and that model choice has a substantial impact on the number of operational taxonomic units identified (changing results by ~4–31%). Additionally, we demonstrate that the widely followed practice of a priori assuming the Kimura 2‐parameter model for DNA barcoding is statistically unjustified and should be avoided. Using both data‐based and inference‐based test statistics, we detect variation in model performance across taxonomic groups, clustering algorithms, genetic divergence thresholds and substitution models. Taken together, these results illustrate the importance of considering both model selection and model adequacy in studies quantifying biodiversity.     

Test of models for replication of simian virus 40 DNA following ultraviolet irradiation.

When mammalian cells are irradiated with ultraviolet light, semiconservative DNA replication is inhibited and the length of newly synthesized daughter strands is reduced. We have used the simian virus 40 (SV40) viral system to examine the molecular mechanism by which this inhibition of DNA replication occurs immediately following ultraviolet irradiation. We tested two models for DNA replication-inhibition by using a procedure first developed by Danna, K. J., and D. Nathans (1972, Proc. Natl. Acad. Sci. USA, 69:3097-3100) in which the distribution of 3H-label in segments of newly completed SV40 form-I molecules is measured after short pulse labeling with 3H-thymidine. Our experimental results were compared with those predicted by mathematical models that describe two possible molecular mechanisms of replication inhibition. Our data are best fit by a "blockage" model in which any pyrimidine dimer encountered by the replication fork prevents complete replication of the SV40 genome. An alternative model called "slowdown" in which DNA damage causes a generalized slowdown of replication fork movement on all genomes has more adjustable parameters but does not fit the data as well as the blockage model.     

Effect of a neutralized phosphate backbone on the minor groove of B-DNA: molecular dynamics simulation studies

Alternative models have been presented to provide explanations for the sequence-dependent variation of the DNA minor groove width. In a structural model groove narrowing in A-tracts results from direct, short-range interactions among DNA bases. In an electrostatic model, the narrow minor groove of A-tracts is proposed to respond to sequence-dependent localization of water and cations. Molecular dynamics simulations on partially methylphosphonate substituted helical chains of d(TATAGGCCTATA) and d(CGCGAATTCGCG) duplexes have been carried out to help evaluate the effects of neutralizing DNA phosphate groups on the minor groove width. The results show that the time-average minor groove width of the GGCC duplex becomes significantly more narrow on neutralizing the phosphate backbone with methylphosphonates. The minor groove of the AATT sequence is normally narrow and the methylphosphonate substitutions have a smaller but measurable affect on this sequence. These results and models provide a system that can be tested by experiment and they support the hypothesis that the electrostatic environment around the minor groove affects the groove width in a sequence-dependent dynamic and time-average manner.     

The split-end model for homologous recombination at double-strand breaks and at Chi

In recent years two different styles of model for homologous recombination have been discussed, depending on whether or not the recombination event occurs in the vicinity of a double-strand break in DNA. The models of Holliday and Meselson and Radding exemplify those that do not involve a break whereas the model of Szostak et al is taken as an example of those that do. Recent advances in understanding a prototypic recombination system thought to promote exchange distant from DNA ends, at Chi sites, suggest a mechanism of initiation neither like Holliday/Meselson-Radding nor like Szostak et al. In those models, only one strand of DNA may invade a homologous DNA molecule. We propose a model for Chi in which exonuclease degrades DNA from a double-strand break to the Chi site; the exonuclease is converted into a helicase upon interaction with Chi; unwinding produces a recombinagenic split-end, and both 3'- and 5'-ending strands at the split-end are capable of invading a homologue. Different genetic consequences are proposed to result from invasion by each. We review evidence supporting the split-end model and suggest its application in at least some cases previously considered to proceed via the Meselson/Radding model and by the double-strand-break repair model of Szostak et al.     

The three-dimensional structure of supercoiled deoxyribonucleic acid in solution. Evidence obtained from the angular distribution of scattered light

1. The size and shape of superhelical double-stranded circular DNA from bacteriophage ØX174 were investigated by light-scattering. The molecular weight of the DNA is 3.17×10⁶ and the root-mean-square radius is 103.5nm. 2. The light-scattering envelopes of various theoretical three-dimensional models for such DNA molecules were calculated by repetitive computational techniques, and the results were compared with the experimental findings. 3. It is concluded that the structure of supercoiled DNA containing −12 superhelical turns in buffer of I0.2 corresponds best to one of the more compact models for superhelix structure such as the branched model, and the commonly employed straight interwound superhelix model is incompatible with the experimental results, at the superhelix density found.     

A detailed model and Monte Carlo simulation for predicting DIP genome length distribution in baculovirus infection of insect cells

Baculoviruses have enormous potential for use as biopesticides to control insect pest populations without the adverse environmental effects posed by the widespread use of chemical pesticides. However, continuous baculovirus production is susceptible to DNA mutation and the subsequent production of defective interfering particles (DIPs). The amount of DIPs produced and their genome length distribution are of great interest not only for baculoviruses but for many other DNA and RNA viruses. In this study, we elucidate this aspect of virus replication using baculovirus as an example system and both experimental and modeling studies. The existing mathematical models for the virus replication process consider DIPs as a lumped quantity and do not consider the genome length distribution of the DIPs. In this study, a detailed population balance model for the cell‐virus culture is presented, which predicts the genome length distribution of the DIP population along with their relative proportion. The model is simulated using the kinetic Monte Carlo algorithm, and the results agree well with the experimental results. Using this model, a practical strategy to maintain the DIP fraction to near to its maximum and minimum limits has been demonstrated.     

Experimental evaluation of the Liu–Beveridge dinucleotide step model of DNA structure

Methods for predicting DNA curvature have many possible applications. Dinucleotide step models describe DNA shape by characterization of helical twist, deflection angles and the direction of deflection for nearest neighbor base pairs. Liu and Beveridge have extended previous applications of dinucleotide step models with the development and qualitative validation of a predictive method for sequence-dependent DNA curvature (the LB model). We tested whether the LB model accurately predicts experimentally deduced curvature angles and helical repeat parameters for DNA sequences not in its training set, particularly when challenged with quantitative data and subtle sequence phasings. We examined a series of 17 well-characterized DNA sequences to compare electrophoretic and computational results. The LB model is superior to two other models in the prediction of helical repeat parameters. We observed a strong linear correlation between curvature magnitudes predicted using the LB model and those determined by electrophoretic ligation ladder experiments, although the LB model somewhat underestimated apparent curvature. With longer electrophoretic phasing probes the LB model slightly overestimated gel mobility anomalies, with modest deviations in predicted helical repeat parameters. Overall, our analyses suggest that the LB model provides reasonably accurate predictions for the electrophoretic behavior of DNA.     

A Mathematical Model for Basepair Opening in a DNA Double Helix

In this paper, we consider a mathematical model that draws an analogy between a DNA molecule and a mechanical system consisting of two chains of interconnected pendulums. This model is designed to explore the dynamics of the system determined by rotational movements of nucleobases around a double-stranded pentose phosphate backbone. The workability of this model is assessed with respect to various factors: inhomogeneity of the chain of nucleobases, the properties of bonds in complementary pairs, and the formation of open states. It has been shown that simplified models for averaging the characteristics of the chain of nucleobases or simplification of the type of hydrogen bond in their complementary pairs influence the type of solution significantly, impairing the validity of the results. Therefore, the approach to the solution of rotational DNA molecule dynamics developed here is more consistent with its actual biomechanics. It is shown that the emergence of open states within nucleobase pairs and restoration of the closed structure may occur in the tested mathematical model.     

Performance of likelihood ratio tests of evolutionary hypotheses under inadequate substitution models.

In recent years, likelihood ratio tests (LRTs) based on DNA and protein sequence data have been proposed for testing various evolutionary hypotheses. Because conducting an LRT requires an evolutionary model of nucleotide or amino acid substitution, which is almost always unknown, it becomes important to investigate the robustness of LRTs to violations of assumptions of these evolutionary models. Computer simulation was used to examine performance of LRTs of the molecular clock, transition/transversion bias, and among-site rate variation under different substitution models. The results showed that when correct models are used, LRTs perform quite well even when the DNA sequences are as short as 300 nt. However, LRTs were found to be biased under incorrect models. The extent of bias varies considerably, depending on the hypotheses tested, the substitution models assumed, and the lengths of the sequences used, among other things. A preliminary simulation study also suggests that LRTs based on parametric bootstrapping may be more sensitive to substitution models than are standard LRTs. When an assumed substitution model is grossly wrong and a more realistic model is available, LRTs can often reject the wrong model; thus, the performance of LRTs may be improved by using a more appropriate model. On the other hand, many factors of molecular evolution have not been considered in any substitution models so far built, and the possibility of an influence of this negligence on LRTs is often overlooked. The dependence of LRTs on substitution models calls for caution in interpreting test results and highlights the importance of clarifying the substitution patterns of genes and proteins and building more realistic models.     

A unique four-stranded model of a homologous recombination intermediate

This paper proposes a model of four-stranded DNA synapsis during recombination between homologous segments of two DNA duplexes. The proposed intermediate is one of only two known models having relative chain orientations about the synaptic junction that are consistent with recent topological results on the integrative recombination of bacteriophage lambda. This model has the advantage of providing a mechanism for recognition of sequence homology between duplexes through specific hydrogen-bond formation; other models are discussed in comparison. The new model is based on an alternative family of DNA structures having chain directions opposite to those of the Watson-Crick family of structures. Idealized coordinates for generating both right- and left-handed forms of these alternative structures are presented for further study.     

Double-stranded DNA organization in bacteriophage heads: an alternative toroid-based model.

Studies of the organization of double-stranded DNA within bacteriophage heads during the past four decades have produced a wealth of data. However, despite the presentation of numerous models, the true organization of DNA within phage heads remains unresolved. The observations of toroidal DNA structures in electron micrographs of phage lysates have long been cited as support for the organization of DNA in a spool-like fashion. This particular model, like all other models, has not been found to be consistent will all available data. Recently we proposed that DNA within toroidal condensates produced in vitro is organized in a manner significantly different from that suggested by the spool model. This new toroid model has allowed the development of an alternative model for DNA organization within bacteriophage heads that is consistent with a wide range of biophysical data. Here we propose that bacteriophage DNA is packaged in a toroid that is folded into a highly compact structure.     

Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition

We present an approach to integrate physical properties of DNA, such as DNA bendability or GC content, into our probabilistic promoter recognition system McPROMOTER. In the new model, a promoter is represented as a sequence of consecutive segments represented by joint likelihoods for DNA sequence and profiles of physical properties. Sequence likelihoods are modeled with interpolated Markov chains, physical properties with Gaussian distributions. The background uses two joint sequence/profile models for coding and non-coding sequences, each consisting of a mixture of a sense and an anti-sense submodel. On a large Drosophila test set, we achieved a reduction of about 30% of false positives when compared with a model solely based on sequence likelihoods.     

Optimal operation of high-pressure homogenization for intracellular product recovery

An optimal control methodology for the homogenization of bacterial cells to recover intracellular products is presented. A Fluent computational fluid dynamics (CFD) model is used to quantify the hydrodynamic forces present in the homogenizer, and empirical models are used to relate these forces to experimentally obtained cell disruption and product recovery data. The optimal homogenizer operation, in terms of either constant cell breakage or maximum intracellular product recovery, is determined using these empirical models. We illustrate this methodology with an Escherichia coli bacterial system used to produce DNA plasmids. Homogenization is performed using an industrial APV–Gaulin high-pressure homogenizer. The modeling and optimization results for this E. coli–DNA plasmid system show good agreement with the experimental data.     

Physical Models for Exploring DNA Topology

Abstract

Two types of physical models have been developed for treating DNA molecules whose topology is of interest The two model motifs combine jacks-and-straws molecular representations with flexible tubing in different proportions. Both motifs present a low-resolution construct of DNA that retains helix axes, strand individuality and the distinguishabiity of the major and minor grooves. Molecules whose double helix axes are branched are modelled by stiff double helices and flexible branch sites. Supercoiled and knotted DNA molecules are modelled on a smaller scale, in a system in which a flexible backbone is supported by a series of stiff helical struts; removal of this scaffolding immediately reveals the linking of the strands. The models are light and easy to construct. They may be used either for demonstrations or as a research tool that assists the interpretation data.     

基于贝叶斯网络的DNA序列剪接位点预测

采用基于贝叶斯网络的建模方法,预测真核生物DNA序列中的剪接位点．分别建立了供体位点和受体位点模型,并根据两种位点的生物学特性,对模型的拓扑结构和上下游节点的选择进行了优化．通过贝叶斯网络的最大似然学习算法求出模型参数后,利用10分组交互验证方法对测试数据进行剪接位点预测。结果显示,受体位点的平均预测准确率为92．5％,伪受体位点的平均预测准确率为94．0％,供体位点的平均预测准确率为92．3％,伪供体位点的平均预测准确率为93．5％,整体效果要好于基于使用独立和条件概率矩阵、以及隐Markov模型的预测方法．表明利用贝叶斯网络对剪接位点建模是预测剪接位点的一种有效手段．