Improved mammalian family phylogeny using gap-rare multiple sequence alignment: A timetree of extant placentals and marsupials

The timing of mammalian diversification in relation to the Cretaceous-Paleogene (KPg) mass extinction continues to be a subject of substantial debate. Previous studies have either focused on limited taxonomic samples with available whole-genome data or relied on short sequence alignments coupled with extensive species samples. In the present study, we improved an existing dataset from the landmark study of Meredith et al. (2011) by filling in missing fragments and further generated another dataset containing 120 taxa and 98 exonic markers. Using these two datasets, we then constructed phylogenies for extant mammalian families, providing improved resolution of many conflicting relationships. Moreover, the timetrees generated, which were calibrated using appropriate molecular clock models and multiple fossil records, indicated that the interordinal diversification of placental mammals initiated before the Late Cretaceous period. Additionally, intraordinal diversification of both extant placental and marsupial lineages accelerated after the KPg boundary, supporting the hypothesis that the availability of numerous vacant ecological niches subsequent to the mass extinction event facilitated rapid diversification. Thus, our results support a scenario of placental radiation characterized by both basal cladogenesis and active interordinal divergences spanning from the Late Cretaceous into the Paleogene.

Evaluating the effects of policies on building construction waste management: a hybrid dynamic approach

The construction industry, as a vital pillar of a country's economy, generates a significant amount of construction waste, which places a tremendous burden on the environment and society. Although previous studies have explored the impact of policies on construction waste management, there is a lack of a simulation model that can be easily used, taking into account the dynamic nature, generality, and practicability of the model. To fill this gap, a hybrid dynamics model of construction waste management system is developed using agent-based modeling, system dynamics, perceived value, and experienced weighted attraction. Based on relevant data from the construction waste industry in Shenzhen, China, the effect of five policies on contractor strategy selection and overall evolution is tested. The results indicate that industry rectification policy and combination policy can effectively promote the resource treatment of construction waste and reduce illegal dumping, pollution to the environment of waste and treatment process, and waste treatment cost. The findings of this research will help not only researchers better analyze the effect of construction waste policies but also policymakers and practitioners in proposing effective construction waste management policies.

Embeddability of centrosymmetric matrices capturing the double-helix structure in natural and synthetic DNA

In this paper, we discuss the embedding problem for centrosymmetric matrices, which are higher order generalizations of the matrices occurring in strand symmetric models. These models capture the substitution symmetries arising from the double helix structure of the DNA. Deciding whether a transition matrix is embeddable or not enables us to know if the observed substitution probabilities are consistent with a homogeneous continuous time substitution model, such as the Kimura models, the Jukes-Cantor model or the general time-reversible model. On the other hand, the generalization to higher order matrices is motivated by the setting of synthetic biology, which works with different sizes of genetic alphabets.

POInT: Modeling Polyploidy in the Era of Ubiquitous Genomics

Thirteen years ago, we described an evolutionary modeling tool that could resolve the orthology relationships among the homologous genomic regions created by a whole-genome duplication. This tool, which we subsequently named POInT (the Polyploid Orthology Inference Tool), was originally only useful for studying a genome duplication known from bakers' yeast and its relatives. Now, with hundreds of genome sequences that contain the relicts of ancient polyploidy available, POInT can be used to study dozens of different polyploidies, asking both questions about the history of individual events and about the commonalities and differences seen between those events. In this chapter, I give a brief history of the development of POInT as an illustration of the interconnected nature of computational biology research. I then further describe how POInT operates and some of the strengths and drawbacks of its structure. I close with a few examples of discoveries we have made using it.

An evolutionary perspective on stress responses, damage and repair

Variation in stress responses has been investigated in relation to environmental factors, species ecology, life history and fitness. Moreover, mechanistic studies have unravelled molecular mechanisms of how acute and chronic stress responses cause physiological impacts ('damage'), and how this damage can be repaired. However, it is not yet understood how the fitness effects of damage and repair influence stress response evolution. Here we study the evolution of hormone levels as a function of stressor occurrence, damage and the efficiency of repair. We hypothesise that the evolution of stress responses depends on the fitness consequences of damage and the ability to repair that damage. To obtain some general insights, we model a simplified scenario in which an organism repeatedly encounters a stressor with a certain frequency and predictability (temporal autocorrelation). The organism can defend itself by mounting a stress response (elevated hormone level), but this causes damage that takes time to repair. We identify optimal strategies in this scenario and then investigate how those strategies respond to acute and chronic exposures to the stressor. We find that for higher repair rates, baseline and peak hormone levels are higher. This typically means that the organism experiences higher levels of damage, which it can afford because that damage is repaired more quickly, but for very high repair rates the damage does not build up. With increasing predictability of the stressor, stress responses are sustained for longer, because the animal expects the stressor to persist, and thus damage builds up. This can result in very high (and potentially fatal) levels of damage when organisms are exposed to chronic stressors to which they are not evolutionarily adapted. Overall, our results highlight that at least three factors need to be considered jointly to advance our understanding of how stress physiology has evolved: (i) temporal dynamics of stressor occurrence; (ii) relative mortality risk imposed by the stressor itself versus damage caused by the stress response; and (iii) the efficiency of repair mechanisms.

Selection Shapes Synonymous Stop Codon Use in Mammals

Phylogenetic models of the evolution of protein-coding sequences can provide insights into the selection pressures that have shaped them. In the application of these models synonymous nucleotide substitutions, which do not alter the encoded amino acid, are often assumed to have limited functional consequences and used as a proxy for the neutral rate of evolution. The ratio of nonsynonymous to synonymous substitution rates is then used to categorize the selective regime that applies to the protein (e.g., purifying selection, neutral evolution, diversifying selection). Here, we extend the Muse and Gaut model of codon evolution to explore the extent of purifying selection acting on substitutions between synonymous stop codons. Using a large collection of coding sequence alignments, we estimate that a high proportion (approximately 57%) of mammalian genes are affected by selection acting on stop codon preference. This proportion varies substantially by codon, with UGA stop codons far more likely to be conserved. Genes with evidence of selection acting on synonymous stop codons have distinctive characteristics, compared to unconserved genes with the same stop codon, including longer [Formula: see text] untranslated regions (UTRs) and shorter mRNA half-life. The coding regions of these genes are also much more likely to be under strong purifying selection pressure. Our results suggest that the preference for UGA stop codons found in many multicellular eukaryotes is selective rather than mutational in origin.

Simulation data for the estimation of numerical constants for approximating pairwise evolutionary distances between amino acid sequences

Estimating the number of substitution events per site that have occurred during the evolution of a pair of amino acid sequences is a common task in phylogenetics and comparative genomics that often requires quite slow maximum-likelihood procedures when taking into account explicit evolutionary models. Data presented in this article are large sets of numbers of substitution events and associated numbers of observed differences between pairs of aligned amino acid sequences that have been generated through a simulation procedure of sequence evolution under a broad range of evolutionary models. These data are available at https://zenodo.org/record/2653704 (doi:10.5281/zenodo.2653704). They are accompanied in this paper by figures showing the strong relationship between the corresponding evolutionary and uncorrected distances, as well as estimated numerical constants that determine non-linear functions that fit the simulated data. These numerical constants can be useful to quickly estimate pairwise evolutionary distances directly from uncorrected distances between aligned amino acid sequences.

An Extension of the Kimura Two-Parameter Model to the Natural Evolutionary Process

Accurate estimates of genetic difference are required for research in evolutionary biology. Here we extend the Kimura two-parameter (K2P) model by considering gaps (insertions and/or deletions) and introduce a new measure for estimating genetic difference between two nucleotide sequences in terms of nucleotide changes that have occurred during the evolutionary process. Using the nuclear ribosomal DNA internal transcribed spacer 2 region from the genus Physalis, we demonstrate that species identification and phylogenetic studies strongly depend on evolutionary models. It is especially noteworthy that the use of different models affects the degree of overlap between intraspecific and interspecific genetic differences. We observe that the percentage of interspecific sequence pairs with values less than the maximum intraspecific genetic difference is 43.2% for the K2P model which is calculated by removing gap sites across all sequences, 22.7% for the K2P model which is calculated by removing gap sites for sequence pairs, and 16.9% for our model which is calculated without removing gap sites. Additionally, the numbers of sequence pairs with interspecific genetic differences of zero are 50 for the K2P model and 29 for our model. The genetic difference measure based on the K2P model, compared to our model, overestimates 21 sequence pairs that are not originally identical. These results indicate the importance of estimating genetic differences under the model of sequence evolution that includes insertions and deletions in addition to substitutions.

Embeddability of Kimura 3ST Markov matrices

In this note, we characterize the embeddability of generic Kimura 3ST Markov matrices in terms of their eigenvalues. As a consequence, we are able to compute the volume of such matrices relative to the volume of all Markov matrices within the model. We also provide examples showing that, in general, mutation rates are not identifiable from substitution probabilities. These examples also illustrate that symmetries between mutation probabilities do not necessarily arise from symmetries between the corresponding mutation rates.

The independent loss model with ordered insertions for the evolution of CRISPR spacers

Today, the CRISPR (clustered regularly interspaced short palindromic repeats) region within bacterial and archaeal genomes is known to encode an adaptive immune system. We rely on previous results on the evolution of the CRISPR arrays, which led to the ordered independent loss model, introduced by Kupczok and Bollback (2013). When focusing on the spacers (between the repeats), new elements enter a CRISPR array at rate θ at the leader end of the array, while all spacers present are lost at rate ρ along the phylogeny relating the sample. Within this model, we compute the distribution of distances of spacers which are present in all arrays in a sample of size n. We use these results to estimate the loss rate ρ from spacer array data for n=2 and n=3.

Nonlinear effects in evolution - an ab initio study: A model in which the classical theory of evolution occurs as a special case

An ab initio approach was used to study the molecular-level interactions that connect gene-mutation to changes in an organism׳s phenotype. The study provides new insights into the evolutionary process and presents a simplification whereby changes in phenotypic properties may be studied in terms of the binding affinities of the chemical interactions affected by mutation, rather than by correlation to the genes. The study also reports the role that nonlinear effects play in the progression of organs, and how those effects relate to the classical theory of evolution. Results indicate that the classical theory of evolution occurs as a special case within the ab initio model - a case having two attributes. The first attribute: proteins and promoter regions are not shared among organs. The second attribute: continuous limiting behavior exists in the physical properties of organs as well as in the binding affinity of the associated chemical interactions, with respect to displacements in the chemical properties of proteins and promoter regions induced by mutation. Outside of the special case, second-order coupling contributions are significant and nonlinear effects play an important role, a result corroborated by analyses of published activity levels in binding and transactivation assays. Further, gradations in the state of perfection of an organ may be small or large depending on the type of mutation, and not necessarily closely-separated as maintained by the classical theory. Results also indicate that organs progress with varying degrees of interdependence, the likelihood of successful mutation decreases with increasing complexity of the affected chemical system, and differences between the ab initio model and the classical theory increase with increasing complexity of the organism.

A theoretical model of the evolution of actuarial senescence under environmental stress

Free-living organisms are exposed to a wide range of stressors, all of which can disrupt components of stress-related and detoxification physiology. The subsequent accumulation of somatic damage is widely believed to play a major role in the evolution of senescence. Organisms have evolved sophisticated physiological regulatory mechanisms to maintain homeostasis in response to environmental perturbations, but these systems are likely to be constrained in their ability to optimise robustness to multiple stressors due to functional correlations among related traits. While evolutionary change can accelerate due to human ecological impacts, it remains to be understood how exposure to multiple environmental stressors could affect senescence rates and subsequently population dynamics and fitness. We used a theoretical evolutionary framework to quantify the potential consequences for the evolution of actuarial senescence in response to exposure to simultaneous physiological stressors – one versus multiple and additive versus synergistic – in a hypothetical population of avian “urban adapters”. In a model in which multiple stressors have additive effects on physiology, species may retain greater capacity to recover, or respond adaptively, to environmental challenges. However, in the presence of high synergy, physiological dysregulation suddenly occurs, leading to a rapid increase in age-dependent mortality and subsequent population collapse. Our results suggest that, if the synergistic model is correct, population crashes in environmentally-stressed species could happen quickly and with little warning, as physiological thresholds of stress resistance are overcome.

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Environmental stressors challenge physiological systems linked to senescence.

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Various scenarios of stress exposure were simulated on a hypothetical “urban adapter”.

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Actuarial senescence increased rapidly in synergistic models of stress.

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Wild populations may be at greater risk of collapse than demography alone suggests.

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An explicit model of how stressors affect physiology underlying ageing is required.

Do tree split probabilities determine the branch lengths?

The evolution of aligned DNA sequence sites is generally modeled by a Markov process operating along the edges of a phylogenetic tree. It is well known that the probability distribution on the site patterns at the tips of the tree determines the tree topology, and its branch lengths. However, the number of patterns is typically much larger than the number of edges, suggesting considerable redundancy in the branch length estimation. In this paper we ask whether the probabilities of just the 'edge-specific' patterns (the ones that correspond to a change of state on a single edge) suffice to recover the branch lengths of the tree, under a symmetric 2-state Markov process. We first show that this holds provided the branch lengths are sufficiently short, by applying the inverse function theorem. We then consider whether this restriction to short branch lengths is necessary. We show that for trees with up to four leaves it can be lifted. This leaves open the interesting question of whether this holds in general. Our results also extend to certain Markov processes on more than 2-states, such as the Jukes-Cantor model.

Phylogenetic inference from binary sequences reduced by primary DNA sequences

Given a bi-classification of nucleotides, we can obtain a reduced binary sequence of a primary DNA sequence. This binary sequence will undoubtedly retain some biological information and lose the rest. Here we want to know what kind of and how much biological information an individual binary sequence carries. Three classifications of nucleotides are explored in the present article. Phylogenetic trees are built from these binary sequences by the Neighbor-Joining (NJ) method, with evolutionary distance evaluated on the basis of a symbolic sequence complexity. We find that, for all data sets studied, binary sequences reduced by the purine/pyrimidine classification give reliable phylogeny (almost the same as that from the primary sequences), while the other two result in discrepancies at different levels. Some possible reasons and a simple model of sequence evolutionary are introduced to interpret this phenomenon.