Expectations of duplicate gene retention under the gene duplicability hypothesis.

BACKGROUND: Gene duplication is an important process in evolution. What causes some genes to be retained after duplication and others to be lost is a process not well understood. The most prevalent theory is the gene duplicability hypothesis, that something about the function and number of interacting partners (number of subunits of protein complex, etc.), determines whether copies have more opportunity to be retained for long evolutionary periods. Some genes are also more susceptible to dosage balance effects following WGD events, making them more likely to be retained for longer periods of time. One would expect these processes that affect the retention of duplicate copies to affect the conditional probability ratio after consecutive whole genome duplication events. The probability that a gene will be retained after a second whole genome duplication event (WGD2), given that it was retained after the first whole genome duplication event (WGD1) versus the probability a gene will be retained after WGD2, given it was lost after WGD1 defines the probability ratio that is calculated. RESULTS: Since duplicate gene retention is a time heterogeneous process, the time between the events (t1) and the time since the most recent event (t2) are relevant factors in calculating the expectation for observation in any genome. Here, we use a survival analysis framework to predict the probability ratio for genomes with different values of t1 and t2 under the gene duplicability hypothesis, that some genes are more susceptible to selectable functional shifts, some more susceptible to dosage compensation, and others only drifting. We also predict the probability ratio with different values of t1 and t2 under the mutational opportunity hypothesis, that probability of retention for certain genes changes in subsequent events depending upon how they were previously retained. These models are nested such that the mutational opportunity model encompasses the gene duplicability model with shifting duplicability over time. Here we present a formalization of the gene duplicability and mutational opportunity hypotheses to characterize evolutionary dynamics and explanatory power in a recently developed statistical framework. CONCLUSIONS: This work presents expectations of the gene duplicability and mutational opportunity hypotheses over time under different sets of assumptions. This expectation will enable formal testing of processes leading to duplicate gene retention.

2023 BMC Ecology and Evolution image competition: the winning images.

In 2023, researchers from around the world entered the BMC Ecology and Evolution photography competition. As a result, we received a spectacular collection of photographs that capture the wonder of nature, those looking to understand it and glimpses into long lost worlds. This editorial celebrates the winning images selected by the Editor of BMC Ecology and Evolution and senior members of the journal's editorial board.

Highly Abundant Proteins Are Highly Thermostable.

Highly abundant proteins tend to evolve slowly (a trend called E-R anticorrelation), and a number of hypotheses have been proposed to explain this phenomenon. The misfolding avoidance hypothesis attributes the E-R anticorrelation to the abundance-dependent toxic effects of protein misfolding. To avoid these toxic effects, protein sequences (particularly those of highly expressed proteins) would be under selection to fold properly. One prediction of the misfolding avoidance hypothesis is that highly abundant proteins should exhibit high thermostability (i.e., a highly negative free energy of folding, ΔG). Thus far, only a handful of analyses have tested for a relationship between protein abundance and thermostability, producing contradictory results. These analyses have been limited by 1) the scarcity of ΔG data, 2) the fact that these data have been obtained by different laboratories and under different experimental conditions, 3) the problems associated with using proteins' melting energy (Tm) as a proxy for ΔG, and 4) the difficulty of controlling for potentially confounding variables. Here, we use computational methods to compare the free energy of folding of pairs of human-mouse orthologous proteins with different expression levels. Even though the effect size is limited, the most highly expressed ortholog is often the one with a more negative ΔG of folding, indicating that highly expressed proteins are often more thermostable.

Dosage balance acts as a time-dependent selective barrier to subfunctionalization.

BACKGROUND: Gene duplication is an important process for genome expansion, sometimes allowing for new gene functions to develop. Duplicate genes can be retained through multiple processes, either for intermediate periods of time through processes such as dosage balance, or over extended periods of time through processes such as subfunctionalization and neofunctionalization. RESULTS: Here, we built upon an existing subfunctionalization Markov model by incorporating dosage balance to describe the interplay between subfunctionalization and dosage balance to explore selective pressures on duplicate copies. Our model incorporates dosage balance using a biophysical framework that penalizes the fitness of genetic states with stoichiometrically imbalanced proteins. These imbalanced states cause increased concentrations of exposed hydrophobic surface areas, which cause deleterious mis-interactions. We draw comparison between our Subfunctionalization + Dosage-Balance Model (Sub + Dos) and the previous Subfunctionalization-Only (Sub-Only) Model. This comparison includes how the retention probabilities change over time, dependent upon the effective population size and the selective cost associated with spurious interaction of dosage-imbalanced partners. We show comparison between Sub-Only and Sub + Dos models for both whole-genome duplication and small-scale duplication events. CONCLUSION: These comparisons show that following whole-genome duplication, dosage balance serves as a time-dependent selective barrier to the subfunctionalization process, by causing an overall delay but ultimately leading to a larger portion of the genome retained through subfunctionalization. This higher percentage of the genome that is ultimately retained is caused by the alternative competing process, nonfunctionalization, being selectively blocked to a greater extent. In small-scale duplication, the reverse pattern is seen, where dosage balance drives faster rates of subfunctionalization, but ultimately leads to a smaller portion of the genome retained as duplicates. This faster rate of subfunctionalization is because the dosage balance of interacting gene products is negatively affected immediately after duplication and the loss of a duplicate restores the stoichiometric balance. Our findings provide support that the subfunctionalization of genes that are susceptible to dosage balance effects, such as proteins involved in complexes, is not a purely neutral process. With stronger selection against stoichiometrically imbalanced gene partners, the rates of subfunctionalization and nonfunctionalization slow; however, this ultimately leads to a greater proportion of subfunctionalized gene pairs.

A Genomic Conceptualization of Species.

Species concepts have been defined through a number of lenses, but are almost entirely empirical in nature. Fundamentally linked to various existing species concepts, an interpretation of genomic data through a species classification filter based upon a theoretical genotype-phenotype map with a monophyly requirement is discussed.

The Memory Problem for Neutral Mutational Models of Evolution.

Models for the evolution of various phenotypes are sometimes constructed with an assumption that mutational effects will be symmetrically distributed about a static mean. This model produces a memory effect that over long evolutionary times results in an expectation that randomized sequences underlying the genetic architecture of the trait will on average retain the ancestral phenotype. This expectation is unrealistic and also inconsistent with our current understanding of processes of molecular evolution.

Models for the retention of duplicate genes and their biological underpinnings.

Gene content in genomes changes through several different processes, with gene duplication being an important contributor to such changes. Gene duplication occurs over a range of scales from individual genes to whole genomes, and the dynamics of this process can be context dependent. Still, there are rules by which genes are retained or lost from genomes after duplication, and probabilistic modeling has enabled characterization of these rules, including their context-dependence. Here, we describe the biology and corresponding mathematical models that are used to understand duplicate gene retention and its contribution to the set of biochemical functions encoded in a genome.

WGDTree: a phylogenetic software tool to examine conditional probabilities of retention following whole genome duplication events.

BACKGROUND: Multiple processes impact the probability of retention of individual genes following whole genome duplication (WGD) events. In analyzing two consecutive whole genome duplication events that occurred in the lineage leading to Atlantic salmon, a new phylogenetic statistical analysis was developed to examine the contingency of retention in one event based upon retention in a previous event. This analysis is intended to evaluate mechanisms of duplicate gene retention and to provide software to generate the test statistic for any genome with pairs of WGDs in its history. RESULTS: Here a software package written in Python, 'WGDTree' for the analysis of duplicate gene retention following whole genome duplication events is presented. Using gene tree-species tree reconciliation to label gene duplicate nodes and differentiate between WGD and SSD duplicates, the tool calculates a statistic based upon the conditional probability of a gene duplicate being retained after a second whole genome duplication dependent upon the retention status after the first event. The package also contains methods for the simulation of gene trees with WGD events. After running simulations, the accuracy of the placement of events has been determined to be high. The conditional probability statistic has been calculated for Phalaenopsis equestris on a monocot species tree with a pair of consecutive WGD events on its lineage, showing the applicability of the method. CONCLUSIONS: A new software tool has been created for the analysis of duplicate genes in examination of retention mechanisms. The software tool has been made available on the Python package index and the source code can be found on GitHub here: https://github.com/cnickh/wgdtree .

2022 BMC Ecology and Evolution image competition: the winning images.

In 2022, researchers from around the world entered the BMC Ecology and Evolution photography competition. The contest produced a spectacular collection of photographs that capture the wonder of the natural world and the growing need to protect it as the human impact on the planet intensifies. This editorial celebrates the winning images selected by the Editor of BMC Ecology and Evolution and senior members of the journal's editorial board.

Nucleobases in Meteorites to Nucleobases in RNA and DNA?

Nucleic acids likely played a foundational role in the origin of life. However, the prebiotic chemistry of nucleoside and nucleotide synthesis has proved challenging on a number of fronts. The recent discovery of both pyrimidine and purine nucleobases in carbonaceous chondrite meteorites has garnered much attention from both the popular press and the scientific community. Here, we discuss these findings in the context of nucleoside/nucleotide prebiotic chemistry. We consider that the main challenge of prebiotic nucleoside synthesis, that of nucleosidic bond formation, is not addressed by the identification nucleobases in meteorites. We further discuss issues of selection that arise from the observation that such meteorites contain both canonical and non-canonical nucleobases. In sum, we argue that, despite the major analytical achievement of identifying and characterizing nucleobases in meteorites, this observation does little to advance our understanding of the prebiotic chemistry that could have led to the first genetic molecules that gave rise to us.

Characterizing Amino Acid Substitution with Complete Linkage of Sites on a Lineage.

Amino acid substitution models are commonly used for phylogenetic inference, for ancestral sequence reconstruction, and for the inference of positive selection. All commonly used models explicitly assume that each site evolves independently, an assumption that is violated by both linkage and protein structural and functional constraints. We introduce two new models for amino acid substitution which incorporate linkage between sites, each based on the (population-genetic) Moran model. The first model is a generalized population process tracking arbitrarily many sites which undergo mutation, with individuals replaced according to their fitnesses. This model provides a reasonably complete framework for simulations but is numerically and analytically intractable. We also introduce a second model which includes several simplifying assumptions but for which some theoretical results can be derived. We analyze the simplified model to determine conditions where linkage is likely to have meaningful effects on sitewise substitution probabilities, as well as conditions under which the effects are likely to be negligible. These findings are an important step in the generation of tractable phylogenetic models that parameterize selective coefficients for amino acid substitution while accounting for linkage of sites leading to both hitchhiking and background selection.

Detecting Selection on Segregating Gene Duplicates in a Population.

Gene duplication is a fundamental process that has the potential to drive phenotypic differences between populations and species. While evolutionarily neutral changes have the potential to affect phenotypes, detecting selection acting on gene duplicates can uncover cases of adaptive diversification. Existing methods to detect selection on duplicates work mostly inter-specifically and are based upon selection on coding sequence changes, here we present a method to detect selection directly on a copy number variant segregating in a population. The method relies upon expected relationships between allele (new duplication) age and frequency in the population dependent upon the effective population size. Using both a haploid and a diploid population with a Moran Model under several population sizes, the neutral baseline for copy number variants is established. The ability of the method to reject neutrality for duplicates with known age (measured in pairwise dS value) and frequency in the population is established through mathematical analysis and through simulations. Power is particularly good in the diploid case and with larger effective population sizes, as expected. With extension of this method to larger population sizes, this is a tool to analyze selection on copy number variants in any natural or experimentally evolving population. We have made an R package available at https://github.com/peterbchi/CNVSelectR/ which implements the method introduced here.

Inaugural BMC Ecology and Evolution image competition: the winning images.

The inaugural BMC Ecology and Evolution image competition attracted entries from talented ecologists and evolutionary biologists worldwide. Together, these photos beautifully capture biodiversity, how it arose and why we should conserve it. This editorial celebrates the winning images as selected by the Editor of BMC Ecology and Evolution and senior members of the journal's editorial board.

Inferring the number and position of changes in selective regime in a non-equilibrium mutation-selection framework.

BACKGROUND: Recovering the historical patterns of selection acting on a protein coding sequence is a major goal of evolutionary biology. Mutation-selection models address this problem by explicitly modelling fixation rates as a function of site-specific amino acid fitness values.However, they are restricted in their utility for investigating directional evolution because they require prior knowledge of the locations of fitness changes in the lineages of a phylogeny. RESULTS: We apply a modified mutation-selection methodology that relaxes assumptions of equlibrium and time-reversibility. Our implementation allows us to identify branches where adaptive or compensatory shifts in the fitness landscape have taken place, signalled by a change in amino acid fitness profiles. Through simulation and analysis of an empirical data set of [Formula: see text]-lactamase genes, we test our ability to recover the position of adaptive events within the tree and successfully reconstruct initial codon frequencies and fitness profile parameters generated under the non-stationary model. CONCLUSION: We demonstrate successful detection of selective shifts and identification of the affected branch on partitions of 300 codons or more. We successfully reconstruct fitness parameters and initial codon frequencies in simulated data and demonstrate that failing to account for non-equilibrium evolution can increase the error in fitness profile estimation. We also demonstrate reconstruction of plausible shifts in amino acid fitnesses in the bacterial [Formula: see text]-lactamase family and discuss some caveats for interpretation.

Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond.

As both a computational and an experimental endeavor, ancestral sequence reconstruction remains a timely and important technique. Modern approaches to conduct ancestral sequence reconstruction for proteins are built upon a conceptual framework from journal founder Emile Zuckerkandl. On top of this, work on maximum likelihood phylogenetics published in Journal of Molecular Evolution in 1996 was one of the first approaches for generating maximum likelihood ancestral sequences of proteins. From its computational history, future model development needs as well as potential applications in areas as diverse as computational systems biology, molecular community ecology, infectious disease therapeutics and other biomedical applications, and biotechnology are discussed. From its past in this journal, there is a bright future for ancestral sequence reconstruction in the field of evolutionary biology.