Evolution of the mutation rate

Spontaneous and environment induced genomic alterations in yeast model

While genomic alterations are fundamental to biological evolution, enabling adaptation and diversity, they can also result in detrimental outcomes, such as the development of genetic diseases including cancer. The budding yeast Saccharomyces cerevisiae serves as an exemplary model for investigating the mechanisms behind various genomic alterations, including point mutations, chromosomal rearrangements, and whole-chromosome aneuploidy. In this review, we highlight the application of genetic screening systems to assess the mutagenic effects of physical and chemical agents efficiently. Additionally, we discuss the utilization of high-throughput sequencing technologies to uncover comprehensive genomic alterations and rare genetic events. We provide a detailed summary of the features of genomic alterations and discuss the genetic mechanisms driving these changes under both spontaneous and stress-induced conditions. Given the high conservation of DNA replication and repair machinery across different organisms, the insights gained from studies on yeast offer valuable perspectives for understanding the delicate balance between genome plasticity and integrity in other species.

Continuous Evolution of Protein through T7 RNA Polymerase-Guided Base Editing in Corynebacterium glutamicum

In vivo targeted mutagenesis technologies are the basis for the continuous directed evolution of specific proteins. Here, an efficient mutagenesis system (CgMutaT7) for continuous evolution of the targeted gene in Corynebacterium glutamicum was developed. First, cytosine deaminase and uracil-DNA glycosylase inhibitor were sequentially fused to T7 RNA polymerase using flexible linkers to build the CgMutaT7 system, which introduces mutations in targeted regions controlled by the T7 promoter. After a series of optimizations, the resulting targeted mutagenesis system (CgMutaT74) can increase the mutant frequency of the target gene by 1.12 × 104-fold, with low off-target mutant frequency. Subsequently, high-throughput sequencing further revealed that the CgMutaT74 system performs efficient and uniform C → T transitions in at least a 1.8 kb DNA region. Finally, the xylose isomerase was successfully continuously evolved by CgMutaT74 to improve the xylose utilization, indicating that the CgMutaT7 system has great potential for applications in the continuous evolution of protein function and expression components.

The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs)

Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size n=300-1000), point mutations may recur in i out of n patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (i*) driven solely by neutral evolution. Since no neutral mutation can reach i*=3, all mutations recurring at i≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if n increases to 100,000 for each cancer type. At present, only <10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.

Dynamic expedition of leading mutations in SARS-CoV-2 spike glycoproteins

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the recent pandemic, has generated countless new variants with varying fitness. Mutations of the spike glycoprotein play a particularly vital role in shaping its evolutionary trajectory, as they have the capability to alter its infectivity and antigenicity. We present a time-resolved statistical method, Dynamic Expedition of Leading Mutations (deLemus), to analyze the evolutionary dynamics of the SARS-CoV-2 spike glycoprotein. The proposed L -index of the deLemus method is effective in quantifying the mutation strength of each amino acid site and outlining evolutionarily significant sites, allowing the comprehensive characterization of the evolutionary mutation pattern of the spike glycoprotein.

Forward-in-time simulation of chromosomal rearrangements: The invisible backbone that sustains long-term adaptation

While chromosomal rearrangements are ubiquitous in all domains of life, very little is known about their evolutionary significance, mostly because, apart from a few specifically studied and well-documented mechanisms (interaction with recombination, gene duplication, etc.), very few models take them into account. As a consequence, we lack a general theory to account for their direct and indirect contributions to evolution. Here, we propose Aevol, a forward-in-time simulation platform specifically dedicated to unravelling the evolutionary significance of chromosomal rearrangements (CR) compared to local mutations (LM). Using the platform, we evolve populations of organisms in four conditions characterized by an increasing diversity of mutational operators-from substitutions alone to a mix of substitutions, InDels and CR-but with a constant global mutational rate. Despite being almost invisible in the phylogeny owing to the scarcity of their fixation in the lineages, we show that CR make a decisive contribution to the evolutionary dynamics by comparing the outcome in these four conditions. As expected, chromosomal rearrangements allow fast expansion of the gene repertoire through gene duplication, but they also reduce the effect of diminishing-returns epistasis, hence sustaining adaptation on the long-run. At last, we show that chromosomal rearrangements tightly regulate the size of the genome through indirect selection for reproductive robustness. Overall, these results confirm the need to improve our theoretical understanding of the contribution of chromosomal rearrangements to evolution and show that dedicated platforms like Aevol can efficiently contribute to this agenda.

Population size interacts with reproductive longevity to shape the germline mutation rate

Mutation rates vary across the tree of life by many orders of magnitude, with lower mutation rates in species that reproduce quickly and maintain large effective population sizes. A compelling explanation for this trend is that large effective population sizes facilitate selection against weakly deleterious "mutator alleles" such as variants that interfere with the molecular efficacy of DNA repair. However, in multicellular organisms, the relationship of the mutation rate to DNA repair efficacy is complicated by variation in reproductive age. Long generation times leave more time for mutations to accrue each generation, and late reproduction likely amplifies the fitness consequences of any DNA repair defect that creates extra mutations in the sperm or eggs. Here, we present theoretical and empirical evidence that a long generation time amplifies the strength of selection for low mutation rates in the spermatocytes and oocytes. This leads to the counterintuitive prediction that the species with the highest germline mutation rates per generation are also the species with most effective mechanisms for DNA proofreading and repair in their germ cells. In contrast, species with different generation times accumulate similar mutation loads during embryonic development. Our results parallel recent findings that the longest-lived species have the lowest mutation rates in adult somatic tissues, potentially due to selection to keep the lifetime mutation load below a harmful threshold.

Somatic mutations in autoinflammatory and autoimmune disease

Somatic mutations (also known as acquired mutations) are emerging as common, age-related processes that occur in all cells throughout the body. Somatic mutations are canonically linked to malignant processes but over the past decade have been increasingly causally connected to benign diseases including rheumatic conditions. Here we outline the contribution of somatic mutations to complex and monogenic immunological diseases with a detailed review of unique aspects associated with such causes. Somatic mutations can cause early- or late-onset rheumatic monogenic diseases but also contribute to the pathogenesis of complex inflammatory and immune-mediated diseases, affect disease progression and define new clinical subtypes. Although even variants with a low variant allele fraction can be pathogenic, clonal dynamics could lead to changes over time in the proportion of mutant cells, with possible phenotypic consequences for the individual. Thus, somatic mutagenesis and clonal expansion have relevant implications in genetic testing and counselling. On the basis of both increased recognition of somatic diseases in clinical practice and improved technical and bioinformatic processes, we hypothesize that there will be an ever-expanding list of somatic mutations in various genes leading to inflammatory conditions, particularly in late-onset disease.

Ad fontes: divergence-time estimation and the age of angiosperms

Accurate divergence times are essential for interpreting and understanding the context in which lineages have evolved. Over the past several decades, debates have surrounded the discrepancies between the inferred molecular ages of crown angiosperms, often estimated from the Late Jurassic into the Permian, and the fossil record, placing angiosperms in the Early Cretaceous. That crown angiosperms could have emerged as early as the Permian or even the Triassic would have major implications for the paleoecological context of the origin of one of the most consequential clades in the tree of life. Here, we argue, and demonstrate through simulations, that the older ages inferred from molecular data and relaxed-clock models are misled by lineage-specific rate heterogeneity resulting from life history changes that occurred several times throughout the evolution of vascular plants. To overcome persistent discrepancies in age estimates, more biologically informed and realistic models should be developed, and our results should be considered in the context of their biological implications before we accept inferences that are a major departure from our strongest evidence.

The Effect of the Presence and Absence of DNA Repair Genes on the Rate and Pattern of Mutation in Bacteria

Bacteria lose and gain repair genes as they evolve. Here, we investigate the consequences of gain and loss of 11 DNA repair genes across a broad range of bacteria. Using synonymous polymorphisms from bacteria and a set of 50 phylogenetically independent contrasts, we find no evidence that the presence or absence of these 11 genes affects either the overall level of diversity or the pattern of mutation. Using phylogenetic generalized linear squares yields a similar conclusion. It seems likely that the lack of an effect is due to variation in the genetic background and the environment which obscures any effects that the presence or absence of individual genes might have.

Characterization and distribution of de novo mutations in the zebra finch

Germline de novo mutations (DNMs) provide the raw material for evolution. The DNM rate varies considerably between species, sexes and chromosomes. Here, we identify DNMs in the zebra finch (Taeniopygia guttata) across 16 parent-offspring trios using two genome assemblies of different quality. Using an independent genotyping assay, we validate 82% of the 150 candidate DNMs. DNM rates are consistent between both assemblies, with estimates of 6.14 × 10-9 and 6.36 × 10-9 per site per generation. We observe a strong paternal bias in DNM rates (male-to-female ratio ɑ ≈ 4), but this bias is in transition mutations only, leading to a transition-to-transversion ratio of 3.18 and 3.57. Finally, we find that DNMs tend to be randomly distributed across chromosomes, not associated with recombination hotspots or genic regions. However, the sex chromosome chrZ shows a roughly fourfold increased DNM rate compared to autosomes, which is more than the expected increase due to chrZ spending two-thirds of its time in males. Overall, our results further enhance our understanding of DNMs in passerine songbirds.

Unraveling the Genetic Legacy of Commercial Whaling and Population Dynamics in Arctic Bowhead Whales and Narwhals

Assessing genetic structure and diversity in wildlife is particularly important in the context of climate change. The Arctic is rapidly warming, and endemic species must adapt quickly or face significant threats to persistence. Bowhead whales (Balaena mysticetus) and narwhals (Monodon monoceros) are two long-lived Arctic species with similar habitat requirements and are often seen together in the Canadian Arctic. Although their ranges overlap extensively, bowhead whales experienced significantly greater commercial whaling mortality than narwhals over several centuries. The similar habitat requirements but different harvest histories of these two species provide an opportunity to examine present-day genetic diversity and the demographic and genetic consequences of commercial whaling. We whole-genome resequenced contemporary Canadian Arctic bowhead whales and narwhals to delineate population structure and reconstruct demographic history. We found higher genetic diversity in bowhead whales compared to narwhals. However, bowhead whale effective population size sharply declined contemporaneously with the intense commercial whaling period. Narwhals, in contrast, exhibited recent growth in effective population size, likely reflecting exposure to limited opportunistic commercial harvest. Bowhead whales will likely continue to experience significant genetic drift in the future, leading to the erosion of genetic diversity. In contrast, narwhals do not seem to be at imminent risk of losing their current levels of genetic variation due to their long-term low effective population size and lack of evidence for a recent decline. This work highlights the importance of considering population trajectories in addition to genetic diversity when assessing the genetics of populations for conservation and management purposes.

Population Size in Evolutionary Biology Is More Than the Effective Size

In population genetics idealized Wright-Fisher (WF) populations are generally considered equivalent to real populations with regard to the major evolutionary processes that influence genotype and allele frequencies. As a result we often model the response of populations by focusing on the effective size N e . The Diversity Partitioning Theorem (DPT) shows that you cannot model the behavior of a system solely on the basis of a diversity (accounting for unevenness among items) without taking richness into account. I show that the census population size (the number of adults, N c ) is equivalent to a richness, and that the effective size N e is equivalent to a true diversity. It follows logically from the DPT that we require both N e and N c to understand how drift, selection, mutation, and gene flow interact to shape the course of evolution of populations. Here I review evidence that both N c and N e affect evolutionary trajectories of populations for neutral and adaptive processes. This also influences how we should consider evolutionary potential and genetic criteria for conservation of populations. The effective size of a population is of huge importance in evolutionary biology, but it should not be the sole focus when population size is concerned. Applied evolutionary studies need to integrate N c in the equation more consistently when modeling the response to selection, mutation, migration, and drift.

Global and local genomic features together modulate the spontaneous single nucleotide mutation rate

Spontaneous mutations are evolutionary engines as they generate variants for the evolutionary downstream processes that give rise to speciation and adaptation. Single nucleotide mutations (SNM) are the most abundant type of mutations among them. Here, we perform a meta-analysis to quantify the influence of selected global genomic parameters (genome size, genomic GC content, genomic repeat fraction, number of coding genes, gene count, and strand bias in prokaryotes) and local genomic features (local GC content, repeat content, CpG content and the number of SNM at CpG islands) on spontaneous SNM rates across the tree of life (prokaryotes, unicellular eukaryotes, multicellular eukaryotes) using wild-type sequence data in two different taxon classification systems. We find that the spontaneous SNM rates in our data are correlated with many genomic features in prokaryotes and unicellular eukaryotes irrespective of their sample sizes. On the other hand, only the number of coding genes was correlated with the spontaneous SNM rates in multicellular eukaryotes primarily contributed by vertebrates data. Considering local features, we notice that local GC content and CpG content significantly were correlated with the spontaneous SNM rates in the unicellular eukaryotes, while local repeat fraction is an important feature in prokaryotes and certain specific uni- and multi-cellular eukaryotes. Such predictive features of the spontaneous SNM rates often support non-linear models as the best fit compared to the linear model. We also observe that the strand asymmetry in prokaryotes plays an important role in determining the spontaneous SNM rates but the SNM spectrum does not.

Genome-wide patterns of selection-drift variation strongly associate with organismal traits across the green plant lineage

There are many gaps in our knowledge of how life cycle variation and organismal body architecture associate with molecular evolution. Using the diverse range of green algal body architectures and life cycle types as a test case, we hypothesize that increases in cytomorphological complexity are likely to be associated with a decrease in the effective population size, because larger-bodied organisms typically have smaller populations, resulting in increased drift. For life cycles, we expect haploid-dominant lineages to evolve under stronger selection intensity relative to diploid-dominant life cycles owing to masking of deleterious alleles in heterozygotes. We use a genome-scale data set spanning the phylogenetic diversity of green algae and phylogenetic comparative approaches to measure the relative selection intensity across different trait categories. We show stronger signatures of drift in lineages with more complex body architectures compared with unicellular lineages, which we consider to be a consequence of smaller effective population sizes of the more complex algae. Significantly higher rates of synonymous as well as nonsynonymous substitutions relative to other algal body architectures highlight that siphonous and siphonocladous body architectures, characteristic of many green seaweeds, form an interesting test case to study the potential impacts of genome redundancy on molecular evolution. Contrary to expectations, we show that levels of selection efficacy do not show a strong association with life cycle types in green algae. Taken together, our results underline the prominent impact of body architecture on the molecular evolution of green algal genomes.

Conservation of mutation and recombination parameters between mammals and zebra finch

Most of our understanding of the fundamental processes of mutation and recombination stems from a handful of disparate model organisms and pedigree studies of mammals, with little known about other vertebrates. To gain a broader comparative perspective, we focused on the zebra finch (Taeniopygia castanotis), which, like other birds, differs from mammals in its karyotype (which includes many micro-chromosomes), in the mechanism by which recombination is directed to the genome, and in aspects of ontogenesis. We collected genome sequences from three generation pedigrees that provide information about 80 meioses, inferring 202 single-point de novo mutations, 1,174 crossovers, and 275 non-crossovers. On that basis, we estimated a sex-averaged mutation rate of 5.0 × 10-9 per base pair per generation, on par with mammals that have a similar generation time. Also as in mammals, we found a paternal germline mutation bias at later stages of gametogenesis (of 1.7 to 1) but no discernible difference between sexes in early development. We also examined recombination patterns, and found that the sex-averaged crossover rate on macro-chromosomes (1.05 cM/Mb) is again similar to values observed in mammals, as is the spatial distribution of crossovers, with a pronounced enrichment near telomeres. In contrast, non-crossover rates are more uniformly distributed. On micro-chromosomes, sex-averaged crossover rates are substantially higher (4.21 cM/Mb), as expected from crossover homeostasis, and both crossover and non-crossover events are more uniformly distributed. At a finer scale, recombination events overlap CpG islands more often than expected by chance, as expected in the absence of PRDM9. Despite differences in the mechanism by which recombination events are specified and the presence of many micro-chromosomes, estimates of the degree of GC-biased gene conversion (59%), the mean non-crossover conversion tract length (~23 bp), and the non-crossover to crossover ratio (6.7:1) are all comparable to those reported in primates and mice. The conservation of mutation and recombination properties from zebra finch to mammals suggest that these processes have evolved under stabilizing selection.

Convergent evolution of allele-specific gene expression that leads to non-small cell lung cancer in different human populations

Phenotypical innovations during evolution are caused by novel mutations, which are usually heterozygous at the beginning. The gene expressions on two alleles of these mutation sites are not necessarily identical, leading to flexible allele-specific regulation in cell systems. We retrieve the transcriptome data of normal and non-small cell lung cancer (NSCLC) tissues from 47 African Americans (AA) and 50 European Americans (EA). We analyze the differentially expressed genes (DEGs) in NSCLC as well as the tumor-specific mutations. Expression and mutation profiles show convergent evolution in AA and EA populations. The tumor-specific mutations are poorly overlapped, but many of them are located in the same genes, mainly oncogenes and tumor suppressor genes. The DEGs in tumors are majorly caused by the mutated alleles rather than normal alleles. The relative expressions of mutated alleles are highly correlated between AA and EA. The differential expression in NSCLC is predominantly mediated by the mutated alleles on heterozygous sites. This molecular mechanism underlying NSCLC oncogenesis is conserved across different human populations, exhibiting convergent evolution. We present this novel angle that differential expression analysis should be performed separately for different alleles. Our ideas should greatly benefit the cancer community.

Embodied Computational Evolution: A Model for Investigating Randomness and the Evolution of Morphological Complexity

For an integrated understanding of how evolutionary dynamics operate in parallel on multiple levels, computational models can enable investigations that would be otherwise infeasible or impossible. We present one modeling framework, Embodied Computational Evolution (ECE), and employ it to investigate how two types of randomness-genetic and developmental-drive the evolution of morphological complexity. With these two types of randomness implemented as germline mutation and transcription error, with rates varied in an [Formula: see text] factorial experimental design, we tested two related hypotheses: ( H1 ) Randomness in the gene transcription process alters the direct impact of selection on populations; and ( H2 ) Selection on locomotor performance targets morphological complexity. The experiment consisted of 121 conditions; in each condition, nine starting phenotypic populations developed from different randomly generated genomic populations of 60 individuals. Each of the resulting 1089 phenotypic populations evolved over 100 generations, with the autonomous, self-propelled individuals under directional selection for enhanced locomotor performance. As encoded by their genome, individuals had heritable morphological traits, including the numbers of segments, sensors, neurons, and connections between sensors and motorized joints that they activated. An individual's morphological complexity was measured by three different metrics derived from counts of the body parts. In support of H1 , variations in the rate of randomness in the gene transcription process varied the dynamics of selection. In support of H2 , the morphological complexity of populations evolved adaptively.

Dual genetic level modification engineering accelerate genome evolution of Corynebacterium glutamicum

High spontaneous mutation rate is crucial for obtaining ideal phenotype and exploring the relationship between genes and phenotype. How to break the genetic stability of organisms and increase the mutation frequency has become a research hotspot. Here, we present a practical and controllable evolutionary tool (oMut-Cgts) based on dual genetic level modification engineering for Corynebacterium glutamicum. Firstly, the modification engineering of transcription and replication levels based on RNA polymerase α subunit and DNA helicase Cgl0854 as the 'dock' of cytidine deaminase (pmCDA1) significantly increased the mutation rate, proving that the localization of pmCDA1 around transient ssDNA is necessary for genome mutation. Then, the combined modification and optimization of engineering at dual genetic level achieved 1.02 × 104-fold increased mutation rate. The genome sequencing revealed that the oMut-Cgts perform uniform and efficient C:G→T:A transitions on a genome-wide scale. Furthermore, oMut-Cgts-mediated rapid evolution of C. glutamicum with stress (acid, oxidative and ethanol) tolerance proved that the tool has powerful functions in multi-dimensional biological engineering (rapid phenotype evolution, gene function mining and protein evolution). The strategies for rapid genome evolution provided in this study are expected to be applicable to a variety of applications in all prokaryotic cells.

Evolution and maintenance of mtDNA gene content across eukaryotes

Across eukaryotes, most genes required for mitochondrial function have been transferred to, or otherwise acquired by, the nucleus. Encoding genes in the nucleus has many advantages. So why do mitochondria retain any genes at all? Why does the set of mtDNA genes vary so much across different species? And how do species maintain functionality in the mtDNA genes they do retain? In this review, we will discuss some possible answers to these questions, attempting a broad perspective across eukaryotes. We hope to cover some interesting features which may be less familiar from the perspective of particular species, including the ubiquity of recombination outside bilaterian animals, encrypted chainmail-like mtDNA, single genes split over multiple mtDNA chromosomes, triparental inheritance, gene transfer by grafting, gain of mtDNA recombination factors, social networks of mitochondria, and the role of mtDNA dysfunction in feeding the world. We will discuss a unifying picture where organismal ecology and gene-specific features together influence whether organism X retains mtDNA gene Y, and where ecology and development together determine which strategies, importantly including recombination, are used to maintain the mtDNA genes that are retained.

The Evolutionary Interplay of Somatic and Germline Mutation Rates

Novel sequencing technologies are making it increasingly possible to measure the mutation rates of somatic cell lineages. Accurate germline mutation rate measurement technologies have also been available for a decade, making it possible to assess how this fundamental evolutionary parameter varies across the tree of life. Here, we review some classical theories about germline and somatic mutation rate evolution that were formulated using principles of population genetics and the biology of aging and cancer. We find that somatic mutation rate measurements, while still limited in phylogenetic diversity, seem consistent with the theory that selection to preserve the soma is proportional to life span. However, germline and somatic theories make conflicting predictions regarding which species should have the most accurate DNA repair. Resolving this conflict will require carefully measuring how mutation rates scale with time and cell division and achieving a better understanding of mutation rate pleiotropy among cell types.

Measuring the burden of hundreds of BioBricks defines an evolutionary limit on constructability in synthetic biology

Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Escape mutants that alleviate this burden can rapidly evolve and take over cell populations, making genetic engineering less reliable and predictable. Synthetic biologists often use genetic parts encoded on plasmids, but their burden is rarely characterized. We measured how 301 BioBrick plasmids affected Escherichia coli growth and found that 59 (19.6%) were burdensome, primarily because they depleted the limited gene expression resources of host cells. Overall, no BioBricks reduced the growth rate of E. coli by >45%, which agreed with a population genetic model that predicts such plasmids should be unclonable. We made this model available online for education ( https://barricklab.org/burden-model ) and added our burden measurements to the iGEM Registry. Our results establish a fundamental limit on what DNA constructs and genetic modifications can be successfully engineered into cells.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations.

CANDy: Automated analysis of domain architectures in carbohydrate-active enzymes

Carbohydrate-active enzymes (CAZymes) can be found in all domains of life and play a crucial role in metabolic and physiological processes. CAZymes often possess a modular structure, comprising not only catalytic domains but also associated domains such as carbohydrate-binding modules (CBMs) and linker domains. By exploring the modular diversity of CAZy families, catalysts with novel properties can be discovered and further insight in their biological functions and evolutionary relationships can be obtained. Here we present the carbohydrate-active enzyme domain analysis tool (CANDy), an assembly of several novel scripts, tools and databases that allows users to analyze the domain architecture of all protein sequences in a given CAZy family. CANDy's usability is shown on glycoside hydrolase family 48, a small yet underexplored family containing multi-domain enzymes. Our analysis reveals the existence of 35 distinct domain assemblies, including eight known architectures, with the remaining assemblies awaiting characterization. Moreover, we substantiate the occurrence of horizontal gene transfer from prokaryotes to insect orthologs and provide evidence for the subsequent removal of auxiliary domains, likely through a gene fission event. CANDy is available at https://github.com/PyEED/CANDy.

Heteroplasmy Is Rare in Plant Mitochondria Compared with Plastids despite Similar Mutation Rates

Plant cells harbor two membrane-bound organelles containing their own genetic material-plastids and mitochondria. Although the two organelles coexist and coevolve within the same plant cells, they differ in genome copy number, intracellular organization, and mode of segregation. How these attributes affect the time to fixation or, conversely, loss of neutral alleles is currently unresolved. Here, we show that mitochondria and plastids share the same mutation rate, yet plastid alleles remain in a heteroplasmic state significantly longer compared with mitochondrial alleles. By analyzing genetic variants across populations of the marine flowering plant Zostera marina and simulating organelle allele dynamics, we examine the determinants of allele segregation and allele fixation. Our results suggest that the bottlenecks on the cell population, e.g. during branching or seeding, and stratification of the meristematic tissue are important determinants of mitochondrial allele dynamics. Furthermore, we suggest that the prolonged plastid allele dynamics are due to a yet unknown active plastid partition mechanism. The dissimilarity between plastid and mitochondrial novel allele fixation at different levels of organization may manifest in differences in adaptation processes. Our study uncovers fundamental principles of organelle population genetics that are essential for further investigations of long-term evolution and molecular dating of divergence events.

Improving laboratory animal genetic reporting: LAG-R guidelines

The biomedical research community addresses reproducibility challenges in animal studies through standardized nomenclature, improved experimental design, transparent reporting, data sharing, and centralized repositories. The ARRIVE guidelines outline documentation standards for laboratory animals in experiments, but genetic information is often incomplete. To remedy this, we propose the Laboratory Animal Genetic Reporting (LAG-R) framework. LAG-R aims to document animals' genetic makeup in scientific publications, providing essential details for replication and appropriate model use. While verifying complete genetic compositions may be impractical, better reporting and validation efforts enhance reliability of research. LAG-R standardization will bolster reproducibility, peer review, and overall scientific rigor.

Transmissible cancers, the genomes that do not melt down

Evolutionary theory predicts that the accumulation of deleterious mutations in asexually reproducing organisms should lead to genomic decay. Clonally reproducing cell lines, i.e., transmissible cancers, when cells are transmitted as allografts/xenografts, break these rules and survive for centuries and millennia. The currently known 11 transmissible cancer lineages occur in dogs (canine venereal tumour disease), in Tasmanian devils (devil facial tumor diseases, DFT1 and DFT2), and in bivalves (bivalve transmissible neoplasia). Despite the mutation loads of these cell lines being much higher than observed in human cancers, they have not been eliminated in space and time. Here, we provide potential explanations for how these fascinating cell lines may have overcome the fitness decline due to the progressive accumulation of deleterious mutations and propose that the high mutation load may carry an indirect positive fitness outcome. We offer ideas on how these host-pathogen systems could be used to answer outstanding questions in evolutionary biology. The recent studies on the evolution of these clonal pathogens reveal key mechanistic insight into transmissible cancer genomes, information that is essential for future studies investigating how these contagious cancer cell lines can repeatedly evade immune recognition, evolve, and survive in the landscape of highly diverse hosts.

High heteroplasmy is associated with low mitochondrial copy number and selection against non-synonymous mutations in the snail Cepaea nemoralis

Molluscan mitochondrial genomes are unusual because they show wide variation in size, radical genome rearrangements and frequently show high variation (> 10%) within species. As progress in understanding this variation has been limited, we used whole genome sequencing of a six-generation matriline of the terrestrial snail Cepaea nemoralis, as well as whole genome sequences from wild-collected C. nemoralis, the sister species C. hortensis, and multiple other snail species to explore the origins of mitochondrial DNA (mtDNA) variation. The main finding is that a high rate of SNP heteroplasmy in somatic tissue was negatively correlated with mtDNA copy number in both Cepaea species. In individuals with under ten mtDNA copies per nuclear genome, more than 10% of all positions were heteroplasmic, with evidence for transmission of this heteroplasmy through the germline. Further analyses showed evidence for purifying selection acting on non-synonymous mutations, even at low frequency of the rare allele, especially in cytochrome oxidase subunit 1 and cytochrome b. The mtDNA of some individuals of Cepaea nemoralis contained a length heteroplasmy, including up to 12 direct repeat copies of tRNA-Val, with 24 copies in another snail, Candidula rugosiuscula, and repeats of tRNA-Thr in C. hortensis. These repeats likely arise due to error prone replication but are not correlated with mitochondrial copy number in C. nemoralis. Overall, the findings provide key insights into mechanisms of replication, mutation and evolution in molluscan mtDNA, and so will inform wider studies on the biology and evolution of mtDNA across animal phyla.

Temporal challenges in detecting balancing selection from population genomic data

The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).

GTDrift: a resource for exploring the interplay between genetic drift, genomic and transcriptomic characteristics in eukaryotes

We present GTDrift, a comprehensive data resource that enables explorations of genomic and transcriptomic characteristics alongside proxies of the intensity of genetic drift in individual species. This resource encompasses data for 1506 eukaryotic species, including 1413 animals and 93 green plants, and is organized in three components. The first two components contain approximations of the effective population size, which serve as indicators of the extent of random genetic drift within each species. In the first component, we meticulously investigated public databases to assemble data on life history traits such as longevity, adult body length and body mass for a set of 979 species. The second component includes estimations of the ratio between the rate of non-synonymous substitutions and the rate of synonymous substitutions (dN/dS) in protein-coding sequences for 1324 species. This ratio provides an estimate of the efficiency of natural selection in purging deleterious substitutions. Additionally, we present polymorphism-derived N e estimates for 66 species. The third component encompasses various genomic and transcriptomic characteristics. With this component, we aim to facilitate comparative transcriptomics analyses across species, by providing easy-to-use processed data for more than 16 000 RNA-seq samples across 491 species. These data include intron-centered alternative splicing frequencies, gene expression levels and sequencing depth statistics for each species, obtained with a homogeneous analysis protocol. To enable cross-species comparisons, we provide orthology predictions for conserved single-copy genes based on BUSCO gene sets. To illustrate the possible uses of this database, we identify the most frequently used introns for each gene and we assess how the sequencing depth available for each species affects our power to identify major and minor splice variants.

Mutational robustness and the role of buffer genes in evolvability

Organisms rely on mutations to fuel adaptive evolution. However, many mutations impose a negative effect on fitness. Cells may have therefore evolved mechanisms that affect the phenotypic effects of mutations, thus conferring mutational robustness. Specifically, so-called buffer genes are hypothesized to interact directly or indirectly with genetic variation and reduce its effect on fitness. Environmental or genetic perturbations can change the interaction between buffer genes and genetic variation, thereby unmasking the genetic variation's phenotypic effects and thus providing a source of variation for natural selection to act on. This review provides an overview of our understanding of mutational robustness and buffer genes, with the chaperone gene HSP90 as a key example. It discusses whether buffer genes merely affect standing variation or also interact with de novo mutations, how mutational robustness could influence evolution, and whether mutational robustness might be an evolved trait or rather a mere side-effect of complex genetic interactions.

Effects of urban-induced mutations on ecology, evolution and health

Increasing evidence suggests that urbanization is associated with higher mutation rates, which can affect the health and evolution of organisms that inhabit cities. Elevated pollution levels in urban areas can induce DNA damage, leading to de novo mutations. Studies on mutations induced by urban pollution are most prevalent in humans and microorganisms, whereas studies of non-human eukaryotes are rare, even though increased mutation rates have the potential to affect organisms and their populations in contemporary time. Our Perspective explores how higher mutation rates in urban environments could impact the fitness, ecology and evolution of populations. Most mutations will be neutral or deleterious, and higher mutation rates associated with elevated pollution in urban populations can increase the risk of cancer in humans and potentially other species. We highlight the potential for urban-driven increased deleterious mutational loads in some organisms, which could lead to a decline in population growth of a wide diversity of organisms. Although beneficial mutations are expected to be rare, we argue that higher mutation rates in urban areas could influence adaptive evolution, especially in organisms with short generation times. Finally, we explore avenues for future research to better understand the effects of urban-induced mutations on the fitness, ecology and evolution of city-dwelling organisms.

Coevolution of longevity and female germline maintenance

An often-overlooked aspect of life-history optimization is the allocation of resources to protect the germline and secure safe transmission of genetic information. While failure to do so renders significant fitness consequences in future generations, germline maintenance comes with substantial costs. Thus, germline allocation should trade off with other life-history decisions and be optimized in accordance with an organism's reproductive schedule. Here, we tested this hypothesis by studying germline maintenance in lines of seed beetle, selected for early (E) or late (L) reproduction for 350 and 240 generations, respectively. Female animals provide maintenance and screening of male gametes in their reproductive tract and oocytes. Here, we reveal the ability of young and aged E- and L-females to provide this form of germline maintenance by mating them to males with ejaculates with artificially elevated levels of protein and DNA damage. We find that germline maintenance in E-females peaks at young age and then declines, while the opposite is true for L-females, in accordance with the age of reproduction in the respective regime. These findings identify the central role of allocation to secure germline integrity in life-history evolution and highlight how females can play a crucial role in mitigating the effects of male germline decisions on mutation rate and offspring quality.

A Concept of Complementarity Between Complexity and Redundancy can Account for Kant's Biological Teleology and Unify Mechanistic and Finalistic Biology

Over 160 years after Darwin and 70 years after the discovery of DNA, two fundamental questions of biology remain unanswered: What differentiates the living from the nonliving? How can mechanistic and finalistic or holistic biology be unified? Niels Bohr introduced a concept of complementarity in quantum physics and based on the paradox of light as a simultaneous wave and particle, conjectured that a similar concept might exist in biology that would solve the paradox of life originating from the nonliving. Bohr proposed that two mutually exclusive-independent observations may be necessary to explain a phenomenon and provided support to Immanuel Kant's idea that the "purposive" behaviour of organisms could only be explained in teleological terms and that mechanical and teleological approaches were necessary and complementary to explain biology. We present a concept of complementarity whereby biochemical pathways or cellular channels for the flow of information are simultaneously complex and redundant and complexity and redundancy complement each other. The postulates of biological complementarity are that (1) it was an essential condition in the origin of life; (2) it provided physiological flexibility that allowed organisms to mount self-protection response and complexity to evolve in the face of deleterious mutations before the evolution of bi-parental sex; (3) it laid the foundation for the evolution of a choice of response when confronted with threat; and (4) it applies to all levels of biological organizations and, thus, can serve as a basis for the unification of mechanistic and holistic biology. It is proposed that teleology is simultaneously constitutive and heuristic: constitutive because organisms' "purposive" behaviours are adaptive and are grounded in mechanism (complexity and redundancy), and heuristic because with our finite cognition and our goal-oriented (humans alone are aware of "tomorrow") and anthropomorphic pre-disposition, teleology will remain useful as a guide to our making sense of the world, even how to ask a meaningful question.

H3K4me1 recruits DNA repair proteins in plants

DNA repair proteins can be recruited by their histone reader domains to specific epigenomic features, with consequences on intragenomic mutation rate variation. Here, we investigated H3K4me1-associated hypomutation in plants. We first examined 2 proteins which, in plants, contain Tudor histone reader domains: PRECOCIOUS DISSOCIATION OF SISTERS 5 (PDS5C), involved in homology-directed repair, and MUTS HOMOLOG 6 (MSH6), a mismatch repair protein. The MSH6 Tudor domain of Arabidopsis (Arabidopsis thaliana) binds to H3K4me1 as previously demonstrated for PDS5C, which localizes to H3K4me1-rich gene bodies and essential genes. Mutations revealed by ultradeep sequencing of wild-type and msh6 knockout lines in Arabidopsis show that functional MSH6 is critical for the reduced rate of single-base substitution (SBS) mutations in gene bodies and H3K4me1-rich regions. We explored the breadth of these mechanisms among plants by examining a large rice (Oryza sativa) mutation data set. H3K4me1-associated hypomutation is conserved in rice as are the H3K4me1-binding residues of MSH6 and PDS5C Tudor domains. Recruitment of DNA repair proteins by H3K4me1 in plants reveals convergent, but distinct, epigenome-recruited DNA repair mechanisms from those well described in humans. The emergent model of H3K4me1-recruited repair in plants is consistent with evolutionary theory regarding mutation modifier systems and offers mechanistic insight into intragenomic mutation rate variation in plants.

Comprehensive analysis of the complete mitochondrial genome of Lilium tsingtauense reveals a novel multichromosome structure

KEY MESSAGE

Lilium tsingtauense mitogenome comprises 27 independent chromosome molecules, it undergoes frequent genomic recombination, and the rate of recombination and mutation between different repetitive sequences affects the formation of multichromosomal structures. Given the extremely large genome of Lily, which likely harbors additional genetic resources, it serves as an ideal material for studying the phylogenetic evolution of organisms. Although the Lilium chloroplast genome has been documented, the sequence of its mitochondrial genome (mitogenome) remains uncharted. Using BGI short reads and Nanopore long reads, we sequenced, assembled, and annotated the mitogenome of Lilium tsingtauense. This effort culminated in the characterization of Lilium's first complete mitogenome. Comparative analysis with other angiosperms revealed the unique multichromosomal structure of the L. tsingtauense mitogenome, spanning 1,125,108 bp and comprising 27 independent circular chromosomes. It contains 36 protein-coding genes, 12 tRNA genes, and 3 rRNA genes, with a GC content of 44.90%. Notably, three chromosomes in the L. tsingtauense mitogenome lack identifiable genes, hinting at the potential existence of novel genes and noncoding elements. The high degree of observed genome fragmentation implies frequent reorganization, with recombination and mutation rates among diverse repetitive sequences likely driving the formation of multichromosomal structures. Our comprehensive analysis, covering genome size, coding genes, structure, RNA editing, repetitive sequences, and sequence migration, sheds light on the evolutionary and molecular biology of multichromosomal mitochondria in Lilium. This high-quality mitogenome of L. tsingtauense not only enriches our understanding of multichromosomal mitogenomes but also establishes a solid foundation for future genome breeding and germplasm innovation in Lilium.

Mutation Rate and Effective Population Size of the Model Cooperative Bacterium Myxococcus xanthus

Intrinsic rates of genetic mutation have diverged greatly across taxa and exhibit statistical associations with several other parameters and features. These include effective population size (Ne), genome size, and gametic multicellularity, with the latter being associated with both increased mutation rates and decreased effective population sizes. However, data sufficient to test for possible relationships between microbial multicellularity and mutation rate (µ) are lacking. Here, we report estimates of two key population-genetic parameters, Ne and µ, for Myxococcus xanthus, a bacterial model organism for the study of aggregative multicellular development, predation, and social swarming. To estimate µ, we conducted an ∼400-day mutation accumulation experiment with 46 lineages subjected to regular single colony bottlenecks prior to clonal regrowth. Upon conclusion, we sequenced one clonal-isolate genome per lineage. Given collective evolution for 85,323 generations across all lines, we calculate a per base-pair mutation rate of ∼5.5 × 10-10 per site per generation, one of the highest mutation rates among free-living eubacteria. Given our estimate of µ, we derived Ne at ∼107 from neutral diversity at four-fold degenerate sites across two dozen M. xanthus natural isolates. This estimate is below average for eubacteria and strengthens an already clear negative correlation between µ and Ne in prokaryotes. The higher and lower than average mutation rate and Ne for M. xanthus, respectively, amplify the question of whether any features of its multicellular life cycle-such as group-size reduction during fruiting-body development-or its highly structured spatial distribution have significantly influenced how these parameters have evolved.

Spontaneous mutations and mutational responses to penicillin treatment in the bacterial pathogen Streptococcus pneumoniae D39

Bacteria with functional DNA repair systems are expected to have low mutation rates due to strong natural selection for genomic stability. However, our study of the wild-type Streptococcus pneumoniae D39, a pathogen responsible for many common diseases, revealed a high spontaneous mutation rate of 0.02 per genome per cell division in mutation-accumulation (MA) lines. This rate is orders of magnitude higher than that of other non-mutator bacteria and is characterized by a high mutation bias in the A/T direction. The high mutation rate may have resulted from a reduction in the overall efficiency of selection, conferred by the tiny effective population size in nature. In line with this, S. pneumoniae D39 also exhibited the lowest DNA mismatch-repair (MMR) efficiency among bacteria. Treatment with the antibiotic penicillin did not elevate the mutation rate, as penicillin did not induce DNA damage and S. pneumoniae lacks a stress response pathway. Our findings suggested that the MA results are applicable to within-host scenarios and provide insights into pathogen evolution.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-024-00220-6.

Experimental evolution for the recovery of growth loss due to genome reduction

As the genome encodes the information crucial for cell growth, a sizeable genomic deficiency often causes a significant decrease in growth fitness. Whether and how the decreased growth fitness caused by genome reduction could be compensated by evolution was investigated here. Experimental evolution with an Escherichia coli strain carrying a reduced genome was conducted in multiple lineages for approximately 1000 generations. The growth rate, which largely declined due to genome reduction, was considerably recovered, associated with the improved carrying capacity. Genome mutations accumulated during evolution were significantly varied across the evolutionary lineages and were randomly localized on the reduced genome. Transcriptome reorganization showed a common evolutionary direction and conserved the chromosomal periodicity, regardless of highly diversified gene categories, regulons, and pathways enriched in the differentially expressed genes. Genome mutations and transcriptome reorganization caused by evolution, which were found to be dissimilar to those caused by genome reduction, must have followed divergent mechanisms in individual evolutionary lineages. Gene network reconstruction successfully identified three gene modules functionally differentiated, which were responsible for the evolutionary changes of the reduced genome in growth fitness, genome mutation, and gene expression, respectively. The diversity in evolutionary approaches improved the growth fitness associated with the homeostatic transcriptome architecture as if the evolutionary compensation for genome reduction was like all roads leading to Rome.

Scuphr: A probabilistic framework for cell lineage tree reconstruction

Cell lineage tree reconstruction methods are developed for various tasks, such as investigating the development, differentiation, and cancer progression. Single-cell sequencing technologies enable more thorough analysis with higher resolution. We present Scuphr, a distance-based cell lineage tree reconstruction method using bulk and single-cell DNA sequencing data from healthy tissues. Common challenges of single-cell DNA sequencing, such as allelic dropouts and amplification errors, are included in Scuphr. Scuphr computes the distance between cell pairs and reconstructs the lineage tree using the neighbor-joining algorithm. With its embarrassingly parallel design, Scuphr can do faster analysis than the state-of-the-art methods while obtaining better accuracy. The method's robustness is investigated using various synthetic datasets and a biological dataset of 18 cells.

High allelic diversity in Arabidopsis NLRs is associated with distinct genomic features

Plants rely on Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) for pathogen recognition. Highly variable NLRs (hvNLRs) show remarkable intraspecies diversity, while their low-variability paralogs (non-hvNLRs) are conserved between ecotypes. At a population level, hvNLRs provide new pathogen-recognition specificities, but the association between allelic diversity and genomic and epigenomic features has not been established. Our investigation of NLRs in Arabidopsis Col-0 has revealed that hvNLRs show higher expression, less gene body cytosine methylation, and closer proximity to transposable elements than non-hvNLRs. hvNLRs show elevated synonymous and nonsynonymous nucleotide diversity and are in chromatin states associated with an increased probability of mutation. Diversifying selection maintains variability at a subset of codons of hvNLRs, while purifying selection maintains conservation at non-hvNLRs. How these features are established and maintained, and whether they contribute to the observed diversity of hvNLRs is key to understanding the evolution of plant innate immune receptors.

From cyanobacteria and cyanophages to chloroplasts: the fate of the genomes of oxyphototrophs and the genes encoding photosystem II proteins

Chloroplasts are the result of endosymbiosis of cyanobacterial organisms with proto-eukaryotes. The psbA, psbD and psbO genes are present in all oxyphototrophs and encode the D1/D2 proteins of photosystem II (PSII) and PsbO, respectively. PsbO is a peripheral protein that stabilizes the O2-evolving complex in PSII. Of these genes, psbA and psbD remained in the chloroplastic genome, while psbO was transferred to the nucleus. The genomes of selected cyanobacteria, chloroplasts and cyanophages carrying psbA and psbD, respectively, were analysed. The highest density of genes and coding sequences (CDSs) was estimated for the genomes of cyanophages, cyanobacteria and chloroplasts. The synonymous mutation rate (rS) of psbA and psbD in chloroplasts remained almost unchanged and is lower than that of psbO. The results indicate that the decreasing genome size in chloroplasts is more similar to the genome reduction observed in contemporary endosymbiotic organisms than in streamlined genomes of free-living cyanobacteria. The rS of atpA, which encodes the α-subunit of ATP synthase in chloroplasts, suggests that psbA and psbD, and to a lesser extent psbO, are ancient and conservative and arose early in the evolution of oxygenic photosynthesis. The role of cyanophages in the evolution of oxyphototrophs and chloroplastic genomes is discussed.

The distribution of fitness effects during adaptive walks using a simple genetic network

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.

Measuring the burden of hundreds of BioBricks defines an evolutionary limit on constructability in synthetic biology

Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Populations of engineered cells can rapidly become dominated by "escape mutants" that evolve to alleviate this burden by inactivating the intended function. Synthetic biologists working with bacteria rely on genetic parts and devices encoded on plasmids, but the burden of different engineered DNA sequences is rarely characterized. We measured how 301 BioBricks on high-copy plasmids affected the growth rate of Escherichia coli. Of these, 59 (19.6%) negatively impacted growth. The burden imposed by engineered DNA is commonly associated with diverting ribosomes or other gene expression factors away from producing endogenous genes that are essential for cellular replication. In line with this expectation, BioBricks exhibiting burden were more likely to contain highly active constitutive promoters and strong ribosome binding sites. By monitoring how much each BioBrick reduced expression of a chromosomal GFP reporter, we found that the burden of most, but not all, BioBricks could be wholly explained by diversion of gene expression resources. Overall, no BioBricks reduced the growth rate of E. coli by >45%, which agreed with a population genetic model that predicts such plasmids should be "unclonable" because escape mutants will take over during growth of a bacterial colony or small laboratory culture from a transformed cell. We made this model available as an interactive web tool for synthetic biology education and added our burden measurements to the iGEM Registry descriptions of each BioBrick.

Decoding populations in the ocean microbiome

Understanding the characteristics and structure of populations is fundamental to comprehending ecosystem processes and evolutionary adaptations. While the study of animal and plant populations has spanned a few centuries, microbial populations have been under scientific scrutiny for a considerably shorter period. In the ocean, analyzing the genetic composition of microbial populations and their adaptations to multiple niches can yield important insights into ecosystem function and the microbiome's response to global change. However, microbial populations have remained elusive to the scientific community due to the challenges associated with isolating microorganisms in the laboratory. Today, advancements in large-scale metagenomics and metatranscriptomics facilitate the investigation of populations from many uncultured microbial species directly from their habitats. The knowledge acquired thus far reveals substantial genetic diversity among various microbial species, showcasing distinct patterns of population differentiation and adaptations, and highlighting the significant role of selection in structuring populations. In the coming years, population genomics is expected to significantly increase our understanding of the architecture and functioning of the ocean microbiome, providing insights into its vulnerability or resilience in the face of ongoing global change. Video Abstract.

Deleterious phenotypes in wild Arabidopsis arenosa populations are common and linked to runs of homozygosity

In this study, we aimed to systematically assess the frequency at which potentially deleterious phenotypes appear in natural populations of the outcrossing model plant Arabidopsis arenosa, and to establish their underlying genetics. For this purpose, we collected seeds from wild A. arenosa populations and screened over 2,500 plants for unusual phenotypes in the greenhouse. We repeatedly found plants with obvious phenotypic defects, such as small stature and necrotic or chlorotic leaves, among first-generation progeny of wild A. arenosa plants. Such abnormal plants were present in about 10% of maternal sibships, with multiple plants with similar phenotypes in each of these sibships, pointing to a genetic basis of the observed defects. A combination of transcriptome profiling, linkage mapping and genome-wide runs of homozygosity patterns using a newly assembled reference genome indicated a range of underlying genetic architectures associated with phenotypic abnormalities. This included evidence for homozygosity of certain genomic regions, consistent with alleles that are identical by descent being responsible for these defects. Our observations suggest that deleterious alleles with different genetic architectures are segregating at appreciable frequencies in wild A. arenosa populations.

Genome copy number predicts extreme evolutionary rate variation in plant mitochondrial DNA

Nuclear and organellar genomes can evolve at vastly different rates despite occupying the same cell. In most bilaterian animals, mitochondrial DNA (mtDNA) evolves faster than nuclear DNA, whereas this trend is generally reversed in plants. However, in some exceptional angiosperm clades, mtDNA substitution rates have increased up to 5,000-fold compared with closely related lineages. The mechanisms responsible for this acceleration are generally unknown. Because plants rely on homologous recombination to repair mtDNA damage, we hypothesized that mtDNA copy numbers may predict evolutionary rates, as lower copy numbers may provide fewer templates for such repair mechanisms. In support of this hypothesis, we found that copy number explains 47% of the variation in synonymous substitution rates of mtDNA across 60 diverse seed plant species representing ~300 million years of evolution. Copy number was also negatively correlated with mitogenome size, which may be a cause or consequence of mutation rate variation. Both relationships were unique to mtDNA and not observed in plastid DNA. These results suggest that homologous recombinational repair plays a role in driving mtDNA substitution rates in plants and may explain variation in mtDNA evolution more broadly across eukaryotes. Our findings also contribute to broader questions about the relationships between mutation rates, genome size, selection efficiency, and the drift-barrier hypothesis.

Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery

Errors in protein translation can lead to non-genetic, phenotypic mutations, including amino acid misincorporations. While phenotypic mutations can increase protein diversity, the systematic characterization of their proteome-wide frequencies and their evolutionary impact has been lacking. Here, we developed a mechanistic model of translation errors to investigate how selection acts on protein populations produced by amino acid misincorporations. We fitted the model to empirical observations of misincorporations obtained from over a hundred mass spectrometry datasets of E. coli and S. cerevisiae. We found that on average 20% to 23% of proteins synthesized in the cell are expected to harbor at least one amino acid misincorporation, and that deleterious misincorporations are less likely to occur. Combining misincorporation probabilities and the estimated fitness effects of amino acid substitutions in a population genetics framework, we found 74% of mistranslation events in E. coli and 94% in S. cerevisiae to be neutral. We further show that the set of available synonymous tRNAs is subject to evolutionary pressure, as the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates. Overall, we find that the translation machinery is likely optimal in E. coli and S. cerevisiae and that both local solutions at the level of codons and a global solution such as the tRNA pool can mitigate the impact of translation errors. We provide a framework to study the evolutionary impact of codon-specific translation errors and a method for their proteome-wide detection across organisms and conditions.

Order-of-Mutation Effects on Cancer Progression: Models for Myeloproliferative Neoplasm

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found: JAK2 V617F and one in the TET2 gene. Whether one mutation is present influences how the other subsequent mutation will affect the regulation of gene expression. In other words, when a patient carries both mutations, the order of when they first arose has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation, the Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. Combined, these observations are used to shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.

A nonadaptive explanation for macroevolutionary patterns in the evolution of complex multicellularity

"Complex multicellularity," conventionally defined as large organisms with many specialized cell types, has evolved five times independently in eukaryotes, but never within prokaryotes. A number of hypotheses have been proposed to explain this phenomenon, most of which posit that eukaryotes evolved key traits (e.g., dynamic cytoskeletons, alternative mechanisms of gene regulation, or subcellular compartments) which were a necessary prerequisite for the evolution of complex multicellularity. Here, we propose an alternative, nonadaptive hypothesis for this broad macroevolutionary pattern. By binning cells into groups with finite genetic bottlenecks between generations, the evolution of multicellularity greatly reduces the effective population size (Ne) of cellular populations, increasing the role of genetic drift in evolutionary change. While both prokaryotes and eukaryotes experience this phenomenon, they have opposite responses to drift: eukaryotes tend to undergo genomic expansion, providing additional raw genetic material for subsequent multicellular innovation, while prokaryotes generally face genomic erosion. Taken together, we hypothesize that these idiosyncratic lineage-specific evolutionary dynamics play a fundamental role in the long-term divergent evolution of complex multicellularity across the tree of life.

The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.