Genetic variability maintained in a finite population due to mutational production of neutral and nearly neutral isoalleles

The overlooked evolutionary dynamics of 16S rRNA revises its role as the "gold standard" for bacterial species identification

The role of 16S rRNA has been and largely remains crucial for the identification of microbial organisms. Although 16S rRNA could certainly be described as one of the most studied sequences ever, the current view of it remains somewhat ambiguous. While some consider 16S rRNA to be a variable marker with resolution power down to the strain level, others consider them to be living fossils that carry information about the origin of domains of cellular life. We show that 16S rRNA is clearly an evolutionarily very rigid sequence, making it a largely unique and irreplaceable marker, but its applicability beyond the genus level is highly limited. Interestingly, it seems that the evolutionary rigidity is not driven by functional constraints of the sequence (RNA-protein interactions), but rather results from the characteristics of the host organism. Our results suggest that, at least in some lineages, Horizontal Gene Transfer (HGT) within genera plays an important role for the evolutionary non-dynamics (stasis) of 16S rRNA. Such genera exhibit an apparent lack of diversification at the 16S rRNA level in comparison to the rest of a genome. However, why it is limited specifically and solely to 16S rRNA remains enigmatic.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

Elevated HIV Viral Load is Associated with Higher Recombination Rate In Vivo

HIV's exceptionally high recombination rate drives its intrahost diversification, enabling immune escape and multidrug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intrahost populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (recombination analysis via time series linkage decay or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intrahost viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (<26,800 copies/mL), we estimate a recombination rate of 1.5×10-5 events/bp/generation (95% CI: 7×10-6 to 2.9×10-5), similar to existing estimates. However, among samples with the highest viral loads (>82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intrahost viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

Analyses of allele age and fitness impact reveal human beneficial alleles to be older than neutral controls

A classic population genetic prediction is that alleles experiencing directional selection should swiftly traverse allele frequency space, leaving detectable reductions in genetic variation in linked regions. However, despite this expectation, identifying clear footprints of beneficial allele passage has proven to be surprisingly challenging. We addressed the basic premise underlying this expectation by estimating the ages of large numbers of beneficial and deleterious alleles in a human population genomic data set. Deleterious alleles were found to be young, on average, given their allele frequency. However, beneficial alleles were older on average than non-coding, non-regulatory alleles of the same frequency. This finding is not consistent with directional selection and instead indicates some type of balancing selection. Among derived beneficial alleles, those fixed in the population show higher local recombination rates than those still segregating, consistent with a model in which new beneficial alleles experience an initial period of balancing selection due to linkage disequilibrium with deleterious recessive alleles. Alleles that ultimately fix following a period of balancing selection will leave a modest 'soft' sweep impact on the local variation, consistent with the overall paucity of species-wide 'hard' sweeps in human genomes.

Elevated HIV viral load is associated with higher recombination rate in vivo

HIV's exceptionally high recombination rate drives its intra-host diversification, enabling immune escape and multi-drug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intra-host populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (Recombination Analysis via Time Series Linkage Decay, or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intra-host viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (< 26,800 copies/mL), we estimate a recombination rate of 1.5 × 10-5 events/bp/generation (95% CI: 7 × 10-6 - 2.9 × 10-5), similar to existing estimates. However, among samples with the highest viral loads (> 82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intra-host viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development

The spread of coronavirus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has progressed into a global pandemic. To date, thousands of genetic variants have been identified among SARS-CoV-2 isolates collected from patients. Sequence analysis reveals that the codon adaptation index (CAI) values of viral sequences have decreased over time but with occasional fluctuations. Through evolution modeling, it is found that this phenomenon may result from the virus's mutation preference during transmission. Using dual-luciferase assays, it is further discovered that the deoptimization of codons in the viral sequence may weaken protein expression during virus evolution, indicating that codon usage may play an important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccines, it is designed several codon-optimized Omicron BA.2.12.1, BA.4/5, and XBB.1.5 spike mRNA vaccine candidates and experimentally validated their high levels of expression. This study highlights the importance of codon usage in virus evolution and provides guidelines for codon optimization in mRNA and DNA vaccine development.

Possible involvement of silent mutations in cancer pathogenesis and evolution

Recent studies have shown that some silent mutations can be harmful to various processes. In this study, we performed a comprehensive in silico analysis to elucidate the effects of silent mutations on cancer pathogenesis using exome sequencing data derived from the Cancer Genome Atlas. We focused on the codon optimality scores of silent mutations, which were defined as the difference between the optimality of synonymous codons, calculated using the codon usage table. The relationship between cancer evolution and silent mutations showed that the codon optimality score of the mutations that occurred later in carcinogenesis was significantly higher than of those that occurred earlier. In addition, mutations with higher scores were enriched in genes involved in the cell cycle and cell division, while those with lower scores were enriched in genes involved in apoptosis and cellular senescence. Our results demonstrate that some silent mutations can be involved in cancer pathogenesis.

Inferring parameters of cancer evolution in chronic lymphocytic leukemia

As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer, where two longitudinal samples are available for sequencing. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occurred after the founding of the tumor, as well as sequencing coverage. Chronic lymphocytic leukemia (CLL), which often does not require treatment for years after diagnosis, presents an optimal system to study the untreated, natural evolution of cancer cell populations. When we apply our methodology to reconstruct the individual evolutionary histories of CLL patients, we find that the parental leukemic clone typically appears within the first fifteen years of life.

Blib is a multi-module simulation platform for genetics studies and intelligent breeding

Simulation is an efficient approach for the investigation of theoretical and applied issues in population and quantitative genetics, and animal and plant breeding. In this study, we report a multi-module simulation platform called Blib, that is able to handle more complicated genetic effects and models than existing tools. Two derived data types are first defined in Blib, one to hold the required information on genetic models, and the other one to represent the genetics and breeding populations. A number of subroutines are then developed to perform specific tasks. Four case studies are present as examples to show the applications of Blib, i.e., genetic drift of multiple alleles in randomly mating populations, joint effects of neutral mutation and genetic drift, comparison of mass versus family selection, and choice of testers in hybrid breeding. Blib together with its application modules, has great potential to benefit theoretical genetic studies and intelligent breeding by simulating and predicting outcomes in a large number of scenarios, and identifying the best optimum selection and crossing schemes.

Novel trends of genome evolution in highly complex tropical sponge microbiomes

BACKGROUND

Tropical members of the sponge genus Ircinia possess highly complex microbiomes that perform a broad spectrum of chemical processes that influence host fitness. Despite the pervasive role of microbiomes in Ircinia biology, it is still unknown how they remain in stable association across tropical species. To address this question, we performed a comparative analysis of the microbiomes of 11 Ircinia species using whole-metagenomic shotgun sequencing data to investigate three aspects of bacterial symbiont genomes-the redundancy in metabolic pathways across taxa, the evolution of genes involved in pathogenesis, and the nature of selection acting on genes relevant to secondary metabolism.

RESULTS

A total of 424 new, high-quality bacterial metagenome-assembled genomes (MAGs) were produced for 10 Caribbean Ircinia species, which were evaluated alongside 113 publicly available MAGs sourced from the Pacific species Ircinia ramosa. Evidence of redundancy was discovered in that the core genes of several primary metabolic pathways could be found in the genomes of multiple bacterial taxa. Across hosts, the metagenomes were depleted in genes relevant to pathogenicity and enriched in eukaryotic-like proteins (ELPs) that likely mimic the hosts' molecular patterning. Finally, clusters of steroid biosynthesis genes (CSGs), which appear to be under purifying selection and undergo horizontal gene transfer, were found to be a defining feature of Ircinia metagenomes.

CONCLUSIONS

These results illustrate patterns of genome evolution within highly complex microbiomes that illuminate how associations with hosts are maintained. The metabolic redundancy within the microbiomes could help buffer the hosts from changes in the ambient chemical and physical regimes and from fluctuations in the population sizes of the individual microbial strains that make up the microbiome. Additionally, the enrichment of ELPs and depletion of LPS and cellular motility genes provide a model for how alternative strategies to virulence can evolve in microbiomes undergoing mixed-mode transmission that do not ultimately result in higher levels of damage (i.e., pathogenicity) to the host. Our last set of results provides evidence that sterol biosynthesis in Ircinia-associated bacteria is widespread and that these molecules are important for the survival of bacteria in highly complex Ircinia microbiomes. Video Abstract.

Joint effect of changing selection and demography on the site frequency spectrum

The site frequency spectrum (SFS) is an important statistic that summarizes the molecular variation in a population, and is used to estimate population-genetic parameters and detect natural selection. Here, we study the SFS in a randomly mating, diploid population in which both the population size and selection coefficient vary periodically with time using a diffusion theory approach, and derive simple analytical expressions for the time-averaged SFS in slowly and rapidly changing environments. We show that for strong selection and in slowly changing environments where the population experiences both positive and negative cycles of the selection coefficient, the time-averaged SFS differs significantly from the equilibrium SFS in a constant environment. The deviation is found to depend on the time spent by the population in the deleterious part of the selection cycle and the phase difference between the selection coefficient and population size, and can be captured by an effective population size.

Detecting signatures of selection on gene expression

A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.

Synonymous mutations in representative yeast genes are mostly strongly non-neutral

Synonymous mutations in protein-coding genes do not alter protein sequences and are thus generally presumed to be neutral or nearly neutral^1-5. Here, to experimentally verify this presumption, we constructed 8,341 yeast mutants each carrying a synonymous, nonsynonymous or nonsense mutation in one of 21 endogenous genes with diverse functions and expression levels and measured their fitness relative to the wild type in a rich medium. Three-quarters of synonymous mutations resulted in a significant reduction in fitness, and the distribution of fitness effects was overall similar-albeit nonidentical-between synonymous and nonsynonymous mutations. Both synonymous and nonsynonymous mutations frequently disturbed the level of mRNA expression of the mutated gene, and the extent of the disturbance partially predicted the fitness effect. Investigations in additional environments revealed greater across-environment fitness variations for nonsynonymous mutants than for synonymous mutants despite their similar fitness distributions in each environment, suggesting that a smaller proportion of nonsynonymous mutants than synonymous mutants are always non-deleterious in a changing environment to permit fixation, potentially explaining the common observation of substantially lower nonsynonymous than synonymous substitution rates. The strong non-neutrality of most synonymous mutations, if it holds true for other genes and in other organisms, would require re-examination of numerous biological conclusions about mutation, selection, effective population size, divergence time and disease mechanisms that rely on the assumption that synoymous mutations are neutral.

Eukaryogenesis: The Rise of an Emergent Superorganism

Although it is widely taught that all modern life descended via modification from a last universal common ancestor (LUCA), this dominant paradigm is yet to provide a generally accepted explanation for the chasm in design between prokaryotic and eukaryotic cells. Counter to this dominant paradigm, the viral eukaryogenesis (VE) hypothesis proposes that the eukaryotes originated as an emergent superorganism and thus did not evolve from LUCA via descent with incremental modification. According to the VE hypothesis, the eukaryotic nucleus descends from a viral factory, the mitochondrion descends from an enslaved alpha-proteobacteria and the cytoplasm and plasma membrane descend from an archaeal host. A virus initiated the eukaryogenesis process by colonising an archaeal host to create a virocell that had its metabolism reprogrammed to support the viral factory. Subsequently, viral processes facilitated the entry of a bacterium into the archaeal cytoplasm which was also eventually reprogrammed to support the viral factory. As the viral factory increased control of the consortium, the archaeal genome was lost, the bacterial genome was greatly reduced and the viral factory eventually evolved into the nucleus. It is proposed that the interaction between these three simple components generated a superorganism whose emergent properties allowed the evolution of eukaryotic complexity. If the radical tenets of the VE hypothesis are ultimately accepted, current biological paradigms regarding viruses, cell theory, LUCA and the universal Tree of Life (ToL) should be fundamentally altered or completely abandoned.

Prochlorococcus have low global mutation rate and small effective population size

Prochlorococcus are the most abundant free-living photosynthetic carbon-fixing organisms in the ocean. Prochlorococcus show small genome sizes, low genomic G+C content, reduced DNA repair gene pool and fast evolutionary rates, which are typical features of endosymbiotic bacteria. Nevertheless, their evolutionary mechanisms are believed to be different. Evolution of endosymbiotic bacteria is dominated by genetic drift owing to repeated population bottlenecks, whereas Prochlorococcus are postulated to have extremely large effective population sizes (N_e) and thus drift has rarely been considered. However, accurately extrapolating N_e requires measuring an unbiased global mutation rate through mutation accumulation, which is challenging for Prochlorococcus. Here, we managed this experiment over 1,065 days using Prochlorococcus marinus AS9601, sequenced genomes of 141 mutant lines and determined its mutation rate to be 3.50 × 10^-10 per site per generation. Extrapolating N_e additionally requires identifying population boundaries, which we defined using PopCOGenT and over 400 genomes related to AS9601. Accordingly, we calculated its N_e to be 1.68 × 10⁷, which is only reasonably greater than that of endosymbiotic bacteria but surprisingly smaller than that of many free-living bacteria extrapolated using the same approach. Our results therefore suggest that genetic drift is a key driver of Prochlorococcus evolution.

Exact site frequency spectra of neutrally evolving tumors: A transition between power laws reveals a signature of cell viability

The site frequency spectrum (SFS) is a popular summary statistic of genomic data. While the SFS of a constant-sized population undergoing neutral mutations has been extensively studied in population genetics, the rapidly growing amount of cancer genomic data has attracted interest in the spectrum of an exponentially growing population. Recent theoretical results have generally dealt with special or limiting cases, such as considering only cells with an infinite line of descent, assuming deterministic tumor growth, or taking large-time or large-population limits. In this work, we derive exact expressions for the expected SFS of a cell population that evolves according to a stochastic branching process, first for cells with an infinite line of descent and then for the total population, evaluated either at a fixed time (fixed-time spectrum) or at the stochastic time at which the population reaches a certain size (fixed-size spectrum). We find that while the rate of mutation scales the SFS of the total population linearly, the rates of cell birth and cell death change the shape of the spectrum at the small-frequency end, inducing a transition between a 1/j² power-law spectrum and a 1/j spectrum as cell viability decreases. We show that this insight can in principle be used to estimate the ratio between the rate of cell death and cell birth, as well as the mutation rate, using the site frequency spectrum alone. Although the discussion is framed in terms of tumor dynamics, our results apply to any exponentially growing population of individuals undergoing neutral mutations.

Extensive C->U transition biases in the genomes of a wide range of mammalian RNA viruses; potential associations with transcriptional mutations, damage- or host-mediated editing of viral RNA

The rapid evolution of RNA viruses has been long considered to result from a combination of high copying error frequencies during RNA replication, short generation times and the consequent extensive fixation of neutral or adaptive changes over short periods. While both the identities and sites of mutations are typically modelled as being random, recent investigations of sequence diversity of SARS coronavirus 2 (SARS-CoV-2) have identified a preponderance of C->U transitions, proposed to be driven by an APOBEC-like RNA editing process. The current study investigated whether this phenomenon could be observed in datasets of other RNA viruses. Using a 5% divergence filter to infer directionality, 18 from 36 datasets of aligned coding region sequences from a diverse range of mammalian RNA viruses (including Picornaviridae, Flaviviridae, Matonaviridae, Caliciviridae and Coronaviridae) showed a >2-fold base composition normalised excess of C->U transitions compared to U->C (range 2.1x-7.5x), with a consistently observed favoured 5' U upstream context. The presence of genome scale RNA secondary structure (GORS) was the only other genomic or structural parameter significantly associated with C->U/U->C transition asymmetries by multivariable analysis (ANOVA), potentially reflecting RNA structure dependence of sites targeted for C->U mutations. Using the association index metric, C->U changes were specifically over-represented at phylogenetically uninformative sites, potentially paralleling extensive homoplasy of this transition reported in SARS-CoV-2. Although mechanisms remain to be functionally characterised, excess C->U substitutions accounted for 11-14% of standing sequence variability of structured viruses and may therefore represent a potent driver of their sequence diversification and longer-term evolution.

Inferring Adaptive Codon Preference to Understand Sources of Selection Shaping Codon Usage Bias

Alternative synonymous codons are often used at unequal frequencies. Classically, studies of such codon usage bias (CUB) attempted to separate the impact of neutral from selective forces by assuming that deviations from a predicted neutral equilibrium capture selection. However, GC-biased gene conversion (gBGC) can also cause deviation from a neutral null. Alternatively, selection has been inferred from CUB in highly expressed genes, but the accuracy of this approach has not been extensively tested, and gBGC can interfere with such extrapolations (e.g., if expression and gene conversion rates covary). It is therefore critical to examine deviations from a mutational null in a species with no gBGC. To achieve this goal, we implement such an analysis in the highly AT rich genome of Dictyostelium discoideum, where we find no evidence of gBGC. We infer neutral CUB under mutational equilibrium to quantify "adaptive codon preference," a nontautologous genome wide quantitative measure of the relative selection strength driving CUB. We observe signatures of purifying selection consistent with selection favoring adaptive codon preference. Preferred codons are not GC rich, underscoring the independence from gBGC. Expression-associated "preference" largely matches adaptive codon preference but does not wholly capture the influence of selection shaping patterns across all genes, suggesting selective constraints associated specifically with high expression. We observe patterns consistent with effects on mRNA translation and stability shaping adaptive codon preference. Thus, our approach to quantifying adaptive codon preference provides a framework for inferring the sources of selection that shape CUB across different contexts within the genome.

Next generation sequencing-aided comprehensive geographic coverage sheds light on the status of rare and extinct populations of Aporia butterflies (Lepidoptera: Pieridae)

The Black-veined White Aporia crataegi (Linnaeus, 1758), a common and widespread butterfly ranging from northwestern Africa to Europe and Asia, has been extinct in Britain since the 1920s and is on a steady decline in several other parts of its range. In order to investigate genetic diversity within A. crataegi and its correspondence with current subspecies-level taxonomy, we barcoded 173 specimens from across its range including, for the first time, extinct populations from Britain and Korea. Using next generation sequencing we also obtained a sequence for Aporia joubini, a peculiar taxon from China known only by its type specimen collected in the early twentieth century. Our phylogenetic analysis placed A. joubini sister to A. oberthuri, although further taxon sampling may reveal a different scheme. Within A. crataegi, we observed a shallow and weak mitogenomic structure with only a few distinct lineages in North Africa, Sicily, Iran, and Japan. Eurasian populations, including those extinct in Britain and Korea, clustered into a large set of closely allied lineages, consistent with a recent expansion during the Late Pleistocene glacial period. This study highlights the importance of museum collections and the unique opportunities they provide in documenting species diversity and helping conservation efforts.

Chance, Variation and Shared Ancestry: Population Genetics After the Synthesis

Chance has been a focus of attention ever since the beginning of population genetics, but neutrality has not, as natural selection once appeared to be the only worthwhile issue. Neutral change became a major source of interest during the neutralist-selectionist debate, 1970-1980. It retained interest beyond this period for two reasons that contributed to its becoming foundational for evolutionary reasoning. On the one hand, neutral evolution was the first mathematical prediction to emerge from Mendelian inheritance: until then evolution by natural selection was considered the alternative to the fixity of species; now it appears to be the alternative to continuous change. Second, neutral change generated a set of clear predictions on standing variation. These could be used as a reference for detecting more elusive alternative mechanisms of evolution including natural selection. In the wake of the transition from Mendelism to genomics, the combination of coalescent theory, DNA sequence variation, and numerical analysis made it possible to integrate contingent aspects of the history of species into a new null model, thus opening a new dimension in the concept of population that the Modern Synthesis formerly considered as a mere gene pool.

Cooperation in Microbial Populations: Theory and Experimental Model Systems

Cooperative behavior, the costly provision of benefits to others, is common across all domains of life. This review article discusses cooperative behavior in the microbial world, mediated by the exchange of extracellular products called public goods. We focus on model species for which the production of a public good and the related growth disadvantage for the producing cells are well described. To unveil the biological and ecological factors promoting the emergence and stability of cooperative traits we take an interdisciplinary perspective and review insights gained from both mathematical models and well-controlled experimental model systems. Ecologically, we include crucial aspects of the microbial life cycle into our analysis and particularly consider population structures where ensembles of local communities (subpopulations) continuously emerge, grow, and disappear again. Biologically, we explicitly consider the synthesis and regulation of public good production. The discussion of the theoretical approaches includes general evolutionary concepts, population dynamics, and evolutionary game theory. As a specific but generic biological example, we consider populations of Pseudomonas putida and its regulation and use of pyoverdines, iron scavenging molecules, as public goods. The review closes with an overview on cooperation in spatially extended systems and also provides a critical assessment of the insights gained from the experimental and theoretical studies discussed. Current challenges and important new research opportunities are discussed, including the biochemical regulation of public goods, more realistic ecological scenarios resembling native environments, cell-to-cell signaling, and multispecies communities.

Genetic Diversity and Demographic History of Ganoderma boninense in Oil Palm Plantations of Sarawak, Malaysia Inferred from ITS Regions

Ganoderma boninense causes basal stem rot (BSR) and is responsible for substantial economic losses to Southeast Asia’s palm oil industry. Sarawak, a major producer in Malaysia, is also affected by this disease. Emergence of BSR in oil palm planted on peat throughout Sarawak is alarming as the soil type was previously regarded as non-conducive. Phylogenetic analysis indicated a single species, G. boninense as the cause of BSR in Sarawak. Information on evolutionary and demographic history for G. boninense in Sarawak inferred through informative genes is lacking. Hence, a haplotype study on single nucleotide polymorphisms in internal transcribed spacers (SNPs-ITS) of G. boninense was carried out. Sequence variations were analysed for population structure, phylogenetic and phylogeographic relationships. The internal transcribed spacers (ITS) region of 117 isolates from four populations in eight locations across Sarawak coastal areas revealed seven haplotypes. A major haplotype, designated GbHap1 (81.2%), was found throughout all sampling locations. Single nucleotide polymorphisms were observed mainly in the ITS1 region. The genetic structure was not detected, and genetic distance did not correlate with geographical distance. Haplotype network analysis suggested evidence of recent demographic expansion. Low genetic differences among populations also suggested that these isolates belong to a single G. boninense founder population adapting to oil palm as the host.

Experimental Evidence that Stochasticity Contributes to Bacterial Composition and Functioning in a Decomposer Community

Randomness can alter the diversity and composition of ecological communities. Such stochasticity may therefore obscure the relationship between the environment and community composition and hinder our ability to predict the relationship between biodiversity and ecosystem functioning. This study investigated the role of stochastic processes, environmental selection, and dispersal in microbial composition and its functioning on an intact field community. To do this, we used a controlled and replicated experiment that was similar to that used to study population genetics in the laboratory. Our study showed that, while the stochastic effects on taxonomic composition are smaller than expected, the degree to which stochasticity contributes to variability in ecosystem processes may be much higher than previously assumed.

Stochasticity emerging from random differences in replication, death, mutation, and dispersal is thought to alter the composition of ecological communities. However, the importance of stochastic effects remains somewhat speculative because stochasticity is not directly measured but is instead inferred from unexplained variations in beta-diversity. Here, we performed a field experiment to more directly disentangle the role of stochastic processes, environmental selection, and dispersal in the composition and functioning of a natural bacterial decomposer community in the field. To increase our ability to detect these effects, we reduced initial biological and environmental heterogeneity using replicate nylon litterbags in the field. We then applied two treatments: ambient/added precipitation and bacterial and fungal dispersal using “open” litterbags (made from 18.0-μm-pore-size mesh) (“open bacterial dispersal”) versus bacterial and fungal dispersal using “closed” litterbags (made from 22.0-μm-pore-size mesh) (“closed bacterial dispersal”). After 5 months, we assayed composition and functioning by the use of three subsamples from each litterbag to disentangle stochastic effects from residual variation. Our results indicate that stochasticity via ecological drift can contribute to beta-diversity in bacterial communities. However, residual variation, which had previously been included in stochasticity estimates, accounted for more than four times as much variability. At the same time, stochastic effects on beta-diversity were not attenuated at the functional level, as measured by genetic functional potential and extracellular enzyme activity. Finally, dispersal was found to interact with precipitation availability to influence the degree to which stochasticity contributed to functional variation. Together, our results demonstrate that the ability to quantify stochastic processes is key to understanding microbial diversity and its role in ecosystem functioning.

Neutral Theory in Cancer Cell Population Genetics

Kimura's neutral theory provides the whole theoretical basis of the behavior of mutations in a Wright-Fisher population. We here discuss how it can be applied to a cancer cell population, in which there is an increasing interest in genetic variation within a tumor. We explain a couple of fundamental differences between cancer cell populations and asexual organismal populations. Once these differences are taken into account, a number of powerful theoretical tools developed for a Wright-Fisher population could be readily contribute to our deeper understanding of the evolutionary dynamics of cancer cell population.

How chromosomal rearrangements shape adaptation and speciation: Case studies in Drosophila pseudoobscura and its sibling species Drosophila persimilis

The gene arrangements of Drosophila have played a prominent role in the history of evolutionary biology from the original quantification of genetic diversity to current studies of the mechanisms for the origin and establishment of new inversion mutations within populations and their subsequent fixation between species supporting reproductive barriers. This review examines the genetic causes and consequences of inversions as recombination suppressors and the role that recombination suppression plays in establishing inversions in populations as they are involved in adaptation within heterogeneous environments. This often results in the formation of clines of gene arrangement frequencies among populations. Recombination suppression leads to the differentiation of the gene arrangements which may accelerate the accumulation of fixed genetic differences among populations. If these fixed mutations cause incompatibilities, then inversions pose important reproductive barriers between species. This review uses the evolution of inversions in Drosophila pseudoobscura and D. persimilis as a case study for how inversions originate, establish and contribute to the evolution of reproductive isolation.

Codon based co-occurrence network motifs in human mitochondria

The nucleotide polymorphism in the human mitochondrial genome (mtDNA) tolled by codon position bias plays an indispensable role in human population dispersion and expansion. Herein, genome-wide nucleotide co-occurrence networks were constructed using data comprised of five different geographical regions and around 3000 samples for each region. We developed a powerful network model to describe complex mitochondrial evolutionary patterns among codon and non-codon positions. We found evidence that the evolution of human mitochondria DNA is dominated by adaptive forces, particularly mutation and selection, which was supported by many previous studies. The diversity observed in the mtDNA was compared with mutations, co-occurring mutations, network motifs considering codon positions as causing agent. This comparison showed that long-range nucleotide co-occurrences have a large effect on genomic diversity. Most notably, codon motifs apparently underpinned the preferences among codon positions for co-evolution which is probably highly biased during the origin of the genetic code. Our analysis also showed that variable nucleotide positions of different human sub-populations implemented the independent mtDNA evolution to its geographical dispensation. Ergo, this study has provided both a network framework and a codon glance to investigate co-occurring genomic variations that are critical in underlying complex mitochondrial evolution.

What factors shape genetic diversity in cetaceans?

Understanding what factors drive patterns of genetic diversity is a central aspect of many biological questions, ranging from the inference of historical demography to assessing the evolutionary potential of a species. However, as a larger number of datasets have become available, it is becoming clear that the relationship between the characteristics of a species and its genetic diversity is more complex than previously assumed. This may be particularly true for cetaceans, due to their relatively long lifespans, long generation times, complex social structures, and extensive ranges. In this study, we used microsatellite and mitochondrial DNA data from a systematic literature review to produce estimates of diversity for both markers across 42 cetacean species. Factors relating to demography, distribution, classification, biology, and behavior were then tested using phylogenetic methods and linear models to assess their relative influence on the genetic diversity of both marker types. The results show that while relative nuclear diversity is correlated with population size, mitochondrial diversity is not. This is particularly relevant given the widespread use of mitochondrial DNA to infer historical demography. Instead, mitochondrial diversity was mostly influenced by the range and social structure of the species. In addition to population size, habitat type (neritic vs. oceanic) had a significant correlation with relative nuclear diversity. Combined, these results show that many often-unconsidered factors are likely influencing patterns of genetic diversity in cetaceans, with implications regarding how to interpret, and what can be inferred from, existing patterns of diversity.

Neutral Evolution

Neutral evolution is the default process of genomic changes. This is because our world is finite, and the randomness, indispensable for neutral evolution, is important when we consider the history of a finite world. The random nature of DNA propagation is discussed using branching process, coalescent process, Markov process, and diffusion process. Expected evolutionary patterns under neutrality are then discussed on fixation probability, rate of evolution, and amount of DNA variation kept in population. We then discuss various features of neutral evolution starting from evolutionary rates, synonymous and nonsynonymous substitutions, junk DNA, and pseudogenes.

Modelling Evolutionary Algorithms with Stochastic Differential Equations

There has been renewed interest in modelling the behaviour of evolutionary algorithms (EAs) by more traditional mathematical objects, such as ordinary differential equations or Markov chains. The advantage is that the analysis becomes greatly facilitated due to the existence of well established methods. However, this typically comes at the cost of disregarding information about the process. Here, we introduce the use of stochastic differential equations (SDEs) for the study of EAs. SDEs can produce simple analytical results for the dynamics of stochastic processes, unlike Markov chains which can produce rigorous but unwieldy expressions about the dynamics. On the other hand, unlike ordinary differential equations (ODEs), they do not discard information about the stochasticity of the process. We show that these are especially suitable for the analysis of fixed budget scenarios and present analogues of the additive and multiplicative drift theorems from runtime analysis. In addition, we derive a new more general multiplicative drift theorem that also covers non-elitist EAs. This theorem simultaneously allows for positive and negative results, providing information on the algorithm's progress even when the problem cannot be optimised efficiently. Finally, we provide results for some well-known heuristics namely Random Walk (RW), Random Local Search (RLS), the (1+1) EA, the Metropolis Algorithm (MA), and the Strong Selection Weak Mutation (SSWM) algorithm.

Is PMI the Hypothesis or the Null Hypothesis?

Over the past several decades, there have been several strident exchanges regarding whether forensic entomologists estimate the postmortem interval (PMI), minimum PMI, or something else. During that time, there has been a proliferation of terminology reflecting this concern regarding "what we do." This has been a frustrating conversation for some in the community because much of this debate appears to be centered on what assumptions are acknowledged directly and which are embedded within a list of assumptions (or ignored altogether) in the literature and in case reports. An additional component of the conversation centers on a concern that moving away from the use of certain terminology like PMI acknowledges limitations and problems that would make the application of entomology appear less useful in court-a problem for lawyers, but one that should not be problematic for scientists in the forensic entomology community, as uncertainty is part of science that should and can be presented effectively in the courtroom (e.g., population genetic concepts in forensics). Unfortunately, a consequence of the way this conversation is conducted is that even as all involved in the debate acknowledge the concerns of their colleagues, parties continue to talk past one another advocating their preferred terminology. Progress will not be made until the community recognizes that all of the terms under consideration take the form of null hypothesis statements and that thinking about "what we do" as a null hypothesis has useful legal and scientific ramifications that transcend arguments over the usage of preferred terminology.

ASSOCIATIONS BETWEEN MITOCHONDRIAL AND NUCLEAR GENOTYPES IN CUTTHROAT TROUT HYBRID SWARMS

We examined mtDNA and nuclear allozyme genotypes in hybrid populations formed from interbreeding of westslope cutthroat trout (Oncorhynchus clarki lewisi) and Yellowstone cutthroat trout (O. c. bouvieri). These subspecies show substantial genetic divergence (Nei's D = 0.30; mtDNA P = 0.02). Diagnostic alleles at multiple nuclear loci and two distinct mtDNA haplotypes segregate in the hybrids. Nuclear and mtDNA genotypes are largely randomly associated, although there is slight disequilibrium in both nuclear and cytonuclear measures in some samples. Consistent positive gametic disequilibria for three pairs of nuclear loci confirm one previously reported linkage, and indicate two more. Allele frequencies provide no evidence for selection on individual chromosome segments. However, westslope mtDNA haplotype frequencies exceed westslope nuclear allele frequencies in all samples. This may be explained by differences in the frequency of occurrence of reciprocal F₁ matings, by viability, fertility, or sex ratio differences in the progeny of reciprocal matings, or by weak selection on mtDNA haplotypes.

PHENOTYPIC EVOLUTION BY NEUTRAL MUTATION

A general model is developed for predicting the genetic variance within populations and the rate of divergence of population mean phenotypes for quantitative traits under the joint operation of random sampling drift and mutation in the absence of selection. In addition to incorporating the dominance effects of mutant alleles, the model yields some insight into the effects of linkage and the mating system on the mutational production of quantitative-genetic variation. Despite these additional and potentially serious complications, it is found that, for small populations, the simple predictions obtained by previous investigators using additive-genetic models hold reasonably well. Even after accounting for dominance and linkage, the equilibrium level of genetic variance is unlikely to be much less than 2NV_m or to be more than 4NV_m , where N is the effective population size and V_m is the new variance from mutation appearing each generation. The rate of increase of the between-line variance per generation ultimately equals 2V_m regardless of population size, although the time to attain the asymptotic rate is proportional to N. Expressions are presented for the rate of approach to the equilibrium level of genetic variance and for the expected variance of the within-population and between-population genetic variances. The relevance of the derived model, which amounts to a generalization of the neutral theory to the phenotypic level, is discussed in the context of the detection of natural selection, the maintenance of pure lines for biomedical and agricultural purposes, the development of genetic conservation programs, and the design of indices of morphological distance between species.

High mutation rates explain low population genetic divergence at copy-number-variable loci in Homo sapiens

Copy-number-variable (CNV) loci differ from single nucleotide polymorphic (SNP) sites in size, mutation rate, and mechanisms of maintenance in natural populations. It is therefore hypothesized that population genetic divergence at CNV loci will differ from that found at SNP sites. Here, we test this hypothesis by analysing 856 CNV loci from the genomes of 1184 healthy individuals from 11 HapMap populations with a wide range of ancestry. The results show that population genetic divergence at the CNV loci is generally more than three times lower than at genome-wide SNP sites. Populations generally exhibit very small genetic divergence (G_st = 0.05 ± 0.049). The smallest divergence is among African populations (G_st = 0.0081 ± 0.0025), with increased divergence among non-African populations (G_st = 0.0217 ± 0.0109) and then among African and non-African populations (G_st = 0.0324 ± 0.0064). Genetic diversity is high in African populations (~0.13), low in Asian populations (~0.11), and intermediate in the remaining 11 populations. Few significant linkage disequilibria (LDs) occur between the genome-wide CNV loci. Patterns of gametic and zygotic LDs indicate the absence of epistasis among CNV loci. Mutation rate is about twice as large as the migration rate in the non-African populations, suggesting that the high mutation rates play dominant roles in producing the low population genetic divergence at CNV loci.

Measuring Natural Selection

In this chapter, I review the basic algorithm underlying the CODEML model implemented in the software package PAML. This is intended as a companion to the software's manual, and a primer to the extensive literature available on CODEML. At the end of this chapter, I hope that you will be able to understand enough of how CODEML operates to plan your own analyses.

Identifying molecular signatures of hypoxia adaptation from sex chromosomes: A case for Tibetan Mastiff based on analyses of X chromosome

Genome-wide studies on high-altitude adaptation have received increased attention as a classical case of organismal evolution under extreme environment. However, the current genetic understanding of high-altitude adaptation emanated mainly from autosomal analyses. Only a few earlier genomic studies paid attention to the allosome. In this study, we performed an intensive scan of the X chromosome of public genomic data generated from Tibetan Mastiff (TM) and five other dog populations for indications of high-altitude adaptation. We identified five genes showing signatures of selection on the X chromosome. Notable among these genes was angiomotin (AMOT), which is related to the process of angiogenesis. We sampled additional 11 dog populations (175 individuals in total) at continuous altitudes in China from 300 to 4,000 meters to validate and test the association between the haplotype frequency of AMOT gene and altitude adaptation. The results suggest that AMOT gene may be a notable candidate gene for the adaptation of TM to high-altitude hypoxic conditions. Our study shows that X chromosome deserves consideration in future studies of adaptive evolution.

Testing neutrality at copy-number-variable loci under the finite-allele and finite-site models

Copy-number variation (CNV) is an important form of DNA structural variation because a certain proportion of genomes in many eukaryotic species can contribute to such variations. Owing to the differences between CNVs and single nucleotide polymorphisms (SNPs) in size, mutation rate and maintaining mechanism, it is more realistic to characterize CNV evolution under the finite-allele and finite-site models. Here, we propose a method to test multiple CNVs neutrality under the finite-allele and finite-site models and the assumption of mutation-drift process. The statistical property of the method is evaluated through Monte Carlo simulations under the effects of the sample size, the scaled mutation rates, the number of CNVs, the population demographic change, and selection. Different from Tajima's D test, a bootstrap or a permutation approach is suggested to conduct a neutrality test. Application of this method is illustrated using the diploid CNV genotypes measured in discrete copy numbers in 11 HapMap phase III populations. The results show that the mutation-drift process can explain the variation of genome-wide CNVs among 1184 individuals (856 CNVs, ∼0.02Mb on average in size), irrespective of the historical demographic changes. Patterns from allele-frequency-spectrum analysis also support the hypothesis of neutral CNVs. Our results suggest that most human chromosomal changes in healthy individuals via unbalanced rearrangements of the segments with certain sizes are neutral.