The information content of DNA and evolution

The information content of DNA molecules has been calculated for various organisms using experimentally measured codon frequencies as well as those estimated theoretically. A direct relationship between the information content and the evolutionary rank of the organism is observed. The biological and physical significance of information content in the context of evolution is discussed.     

Reducing model complexity of the general Markov model of evolution

The selection of an optimal model for data analysis is an important component of model-based molecular phylogenetic studies. Owing to the large number of Markov models that can be used for data analysis, model selection is a combinatorial problem that cannot be solved by performing an exhaustive search of all possible models. Currently, model selection is based on a small subset of the available Markov models, namely those that assume the evolutionary process to be globally stationary, reversible, and homogeneous. This forces the optimal model to be time reversible even though the actual data may not satisfy these assumptions. This problem can be alleviated by including more complex models during the model selection. We present a novel heuristic that evaluates a small fraction of these complex models and identifies the optimal model.     

Entropy increase and information loss in Markov models of evolution

Markov models of evolution describe changes in the probability distribution of the trait values a population might exhibit. In consequence, they also describe how entropy and conditional entropy values evolve, and how the mutual information that characterizes the relation between an earlier and a later moment in a lineage’s history depends on how much time separates them. These models therefore provide an interesting perspective on questions that usually are considered in the foundations of physics—when and why does entropy increase and at what rates do changes in entropy take place? They also throw light on an important epistemological question: are there limits on what your observations of the present can tell you about the evolutionary past?     

Estimation of phylogeny and invariant sites under the general Markov model of nucleotide sequence evolution

The models of nucleotide substitution used by most maximum likelihood-based methods assume that the evolutionary process is stationary, reversible, and homogeneous. We present an extension of the Barry and Hartigan model, which can be used to estimate parameters by maximum likelihood (ML) when the data contain invariant sites and there are violations of the assumptions of stationarity, reversibility, and homogeneity. Unlike most ML methods for estimating invariant sites, we estimate the nucleotide composition of invariant sites separately from that of variable sites. We analyze a bacterial data set where problems due to lack of stationarity and homogeneity have been previously well noted and use the parametric bootstrap to show that the data are consistent with our general Markov model. We also show that estimates of invariant sites obtained using our method are fairly accurate when applied to data simulated under the general Markov model.     

Gene finding with a hidden Markov model of genome structure and evolution

Motivation: A growing number of genomes are sequenced. The differences in evolutionary pattern between functional regions can thus be observed genome-wide in a whole set of organisms. The diverse evolutionary pattern of different functional regions can be exploited in the process of genomic annotation. The modelling of evolution by the existing comparative gene finders leaves room for improvement. Results: A probabilistic model of both genome structure and evolution is designed. This type of model is called an Evolutionary Hidden Markov Model (EHMM), being composed of an HMM and a set of region-specific evolutionary models based on a phylogenetic tree. All parameters can be estimated by maximum likelihood, including the phylogenetic tree. It can handle any number of aligned genomes, using their phylogenetic tree to model the evolutionary correlations. The time complexity of all algorithms used for handling the model are linear in alignment length and genome number. The model is applied to the problem of gene finding. The benefit of modelling sequence evolution is demonstrated both in a range of simulations and on a set of orthologous human/mouse gene pairs. AVAILABILITY: Free availability over the Internet on www server: http://www.birc.dk/Software/evogene.     

The information content of a vernier judgement

Experimental results are given for the performance of a vernier task without visual input. Entropies obtained from the distribution of errors in performing this task are compared with entropies obtained from earlier experiments with visual input. The entropy difference gives the information in bits transmitted by the visual system. An information capacity for the visual system in performing the vernier task is deduced on the assumption that temporal summation of information is limited by the occurrence of an involuntary saccade.     

The content and availability of information affects the evolution of social-information gathering strategies

Social animals can gather information by observing the other members of their groups. Strategies for gathering this type of social information have many components. In particular, an animal can vary the number of other animals it observes. European starlings (Sturnus vulgaris) in flight pay attention to a number of neighbors that allows the flock to reach consensus quickly and robustly. The birds may do this because being in such a flock confers benefits on its members, or the birds may use the strategy that is individually beneficial without regard for the flock’s structure. To understand when individual-level optimization results in a group-level optimum, we develop a model of animals gathering social information about environmental cues, where the cue can be about either predators or resources, and we analyze two processes through which the number of neighbors changes over time. We then identify the number of neighbors the birds use when the two dynamics reach equilibrium. First, we find that the equilibrium number of neighbors is much lower when the birds are learning about the presence of resources rather than predators. Second, when the information is about the presence of predators, we find that the equilibrium number of neighbors increases as the information becomes more widespread. Third, we find that an optimization process converges on strategies that allow the flock to reach consensus when the information is about the presence of abundant resources, but not when it is about the presence of scarce resources or predators.     

Absorbent Markov chains as a model for the study of the evolution of proteins

The formalism of absorbent Markov chains, previously developed by Kemeny & Snell (1960) is used as a model for the study of the evolution of proteins. Within the limits of statistical analysis used, the amino acid substitution frequencies of McLachlan (1972) are explained by the numerical values derived from the model used. In addition, the amino acid composition of proteins is partially explained and the relative mutability of amino acids receives a new interpretation in the light of the above mentioned stochastic model. The results show that some basic aspect of protein evolution can be predicted by a stochastic model and therefore a significant component of protein evolution is driven by a random element.     

Meta-analysis of character utility and phylogenetic information content in cladistic studies of ammonoids

While previous workers have argued persuasively that ammonoid workers should use cladistic approaches to reconstruct phylogeny, relatively few cladistic studies have been published to date. An essential yet challenging part of cladistic analysis is the selection of characters. Are certain types of characters more likely to show homoplasy? Are certain aspects of shell anatomy more likely to contain phylogenetically informative characters? Are datasets with more characters inherently better? To answer these questions, a meta-analysis of character data from published ammonoid phylogenies was performed. I compiled 14 datasets, published between 1989 and 2007, representing parsimony-based phylogenetic analyses of ammonoids. These studies defined a combined total of 323 characters, which were grouped into categories reflecting different aspects of anatomy: shell size and shape, ornament, suture, early ontogeny, body chamber and apertural modifications. Tree searches were re-run to determine overall tree statistics, parsimony permutation tail probability (PTP) tests were calculated to assess the phylogenetic information content of the matrices, and retention and rescaled consistency indices for each character were calculated. My analyses revealed that studies with higher character/taxon ratios did not necessarily produce trees with more information content and less homoplasy, as measured by retention or rescaled consistency indices, because additional characters were often parsimony-uninformative. Rather, studies with relatively few characters could produce high-quality trees if the characters were well-chosen and character states carefully defined. Characters related to the body chamber and adult aperture typically had retention indices of either 0 or 1, rarely in between, indicating that they either worked perfectly or not at all. Suture characters tended to have higher indices than shell shape or ornament characters, suggesting more phylogenetic information and less homoplasy in the suture line than in shell traits. These results should aid in the selection of characters for future cladistic studies of ammonoids.     

A model of evolution for accumulating genetic information

By taking into account recent knowledge of multigene families and other repetitive DNA sequences, a model of evolution by gene duplication for accumulating genetic information is studied. Genetic information is defined as the sum of distinct functions that the gene family can perform. A coefficient, "genetic diversity" is defined and used in this study, that is highly correlated with genetic information. Initially, a multigene family with a few gene copies is assumed, and natural selection starts to work on this gene family to increase genetic diversity contained in the gene family. As an important mechanism, unequal crossing-over is incorporated. Together with mutation, it is responsible for supplying genetic variability among individuals for selection to work. A specific model, in which individuals with less genetic diversity are selectively disadvantageous, has been studied in detail. Through approximate theoretical analysis and extensive Monte Carlo studies, it has been shown that the system is an extremely efficient way to accumulate genetic information. For attaining one gene, the genetic load is much smaller under this model than under the traditional model of natural selection. The model may be applied to the process of origin of multigene families with diverse copy members such as those of immunoglobulin or cytochrome P450. In general, the process of creating new genes by duplication might be somewhere between the present and the traditional models.     

Significance of the information content of DNA in mutations and evolution

One point mutations in human haemoglobins have been analysed and it is seen that most of these mutations satisfy the condition P₁ > P₂, where P₁ is the probability of occurrence of the codon that mutates and PZ is that of the codon it mutates to. Further, it is shown that the hypothesis that the information content of DNA is a reasonable evolutionary measure is consistent with the above condition.     

Bayesian inference of character evolution

Much recent progress in evolutionary biology is based on the inference of ancestral states and past transformations in important traits on phylogenetic trees. These exercises often assume that the tree is known without error and that ancestral states and character change can be mapped onto it exactly. In reality, there is often considerable uncertainty about both the tree and the character mapping. Recently introduced Bayesian statistical methods enable the study of character evolution while simultaneously accounting for both phylogenetic and mapping uncertainty, adding much needed credibility to the reconstruction of evolutionary history.     

Properties of a general model of DNA evolution under no-strand-bias conditions

Under the hypothesis of no-strand-bias conditions, the Watson and Crick base-pairing rule decreases the complexity of models of DNA evolution by reducing to six the maximum number of substitution rates. It was shown that intrastrand equimolarity between A and T (A ^* T ^*) and between G and C (G ^* C ^*) is a general asymptotic property of this class of models. This statistical prediction was observed on 60 long genomic fragments (>50 kbp) from various kingdoms, even when the effect of the two opposite orientations for coding sequences is removed. The practical consequence of the model for estimating the expected number of substitutions per site between two homologous DNA sequences is discussed.Abbreviations BPR Watson and Crick base pairing rule (A:T, G:C) - PRI Intrastrand type-1 parity rule (i j, m(i,j)m( )) - PRII Intra strand type-2 parity rule (A ^* T ^*, G ^* C ^*)     

Constrained evolution of a quantitative character by pleiotropic mutation

The long-term response to directional selection and its selection limit are derived for a quantitative character that is controlled by pleiotropic mutations with direct deleterious effect on fitness. Directional selection is assumed to be weaker than the selection acting directly on mutations via deleterious effects (purging selection), which renders all mutations to eventual elimination. The analysis embedding this restrictive assumption indicates that the evolutionary response of the character starting from an equilibrium state, in which mutation and purging selection balance but no directional selection is operating, decreases monotonically with time at an exponential rate. And the fading rate of responses is mostly determined by the direct deleterious effect. Contrary to the expectation by the standard selection limit theory based on fixation of extant genetic variation, the present model predicts that the selection limit depends on the intensity of directional selection, the limit being proportional to the ratio of the directional selection intensity to the direct deleterious effect. A slightly larger genetic variance is maintained at the selection limit than would be without directional selection.