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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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An experimental test of the mutation-selection balance model for the maintenance of genetic variance in fitness components

Despite decades of research, the factors that maintain genetic variation for fitness are poorly understood. Mutation selection balance will always contribute to standing variance, but it is unclear what fraction of the variance in a typical fitness component can be explained by mutation-selection balance and whether fitness components differ in this respect. In theory, the level of standing variance in fitness due to mutation-selection balance can be predicted using the rate of fitness decline under mutation accumulation, and this prediction can be directly compared to the actual standing variance observed. This approach allows for controlled statistical tests of the sufficiency of the mutation-selection balance model, and could be used to identify traits or populations where genetic variance is maintained by factors beyond mutation-selection balance. For example, some traits may be influenced by sexually antagonistic balancing selection, resulting in an excess of standing variance beyond that generated by deleterious mutations. To encourage the application of this approach, we describe the underlying theory and use it to test the mutation selection balance model for three traits in Drosophila melanogaster. We find some evidence for non-mutational variance in male mating success and female fecundity relative to larval viability, which is consistent with balancing selection on sexual fitness components. Finally, we discuss the theoretical and practical limitations to this approach, and discuss how to apply it successfully.

evolutionary biology

Amygdalar atrophy as the genetically mediated hub of limbic degeneration in Alzheimer’s disease

Pharmacological progress, basic science and medical practice can benefit from objective biomarkers that assist in early diagnosis and prognostic stratification of diseases. In the field of Alzheimers disease (AD), the clinical presentation of early stage dementia may not fulfill any diagnostic criteria for years, and quantifying structural brain changes by magnetic resonance imaging (MRI) has shown promise in the discovery of sensitive biomarkers. Although hippocampal atrophy is often used as an in vivo measure of AD, data-driven neuroimaging has revealed complex patterns of regional brain vulnerability that may not perfectly map to anatomical boundaries. In addition to aiding diagnosis, decoding genetic influences on neuroimaging measures of the disease can enlighten molecular mechanisms of the underlying pathology in living patients and guide the therapeutic design.\n\nHere, we aimed to extract a data-driven MRI feature of brain atrophy in AD by decomposing structural neuroimages using independent component analysis (ICA), a method for performing unbiased computational search in high dimensional data spaces. Our study of the AD Neuroimaging Initiative dataset (n=1,100 subjects) revealed a disease-vulnerable feature with a network-like topology, comprising amygdala, hippocampus, fornix and the inter-connecting white-matter tracts of the limbic system. Whole-genome sequencing identified a nonsynonymous variant (rs34173062) in SHARPIN, a gene coding for a synaptic protein, as a significant modifier of this new MRI feature (p=2.1x10-10). The risk variant was brought to replication in the UK Biobank dataset (n=8,428 subjects), where it was associated with reduced cortical thickness in areas co-localizing with those of the discovery sample (left entorhinal cortex p=0.002, right entorhinal cortex p=8.6x10-4; same direction), as well as with the history of AD in both parents (p=2.3x10-6; same direction).\n\nIn conclusion, our study shows that ICA can transform voxel-wise volumetric measures of the brain into a data-driven feature of neurodegeneration in AD. Structure of the limbic system, as the most vulnerable focus of brain atrophy in AD, is affected by genetic variability of SHARPIN. The elevated risk of dementia in carriers of the minor allele supports engagement of SHARPIN in the disease pathways, and its role in neurotransmitter receptor scaffolding and integrin signaling may inform on new molecular mechanisms of AD pathophysiology.\n\nAbbreviationsAlzheimers disease (AD), genome-wide association study (GWAS), independent component analysis (ICA), mild cognitive impairment (MCI), medial temporal circuit (MTC), single-nucleotide polymorphism (SNP), tensor-based morphometry (TBM)

neuroscience

Networks of genetic similarity reveal non-neutral processes shape strain structure in Plasmodium falciparum

Pathogens compete for hosts through patterns of cross-protection conferred by immune responses to antigens. In Plasmodium falciparum malaria, the var multigene family encoding for the major blood-stage antigen PfEMP1 has evolved enormous genetic diversity through ectopic recombination and mutation. With 50-60 var genes per genome, it is unclear whether immune selection can act as a dominant force in structuring var repertoires of local populations. The combinatorial complexity of the var system remains beyond the reach of existing strain theory, and previous evidence for non-random structure cannot demonstrate immune selection without comparison to neutral models. We develop two neutral models that encompass malaria epidemiology but exclude competitive interactions between parasites. These models, combined with networks of genetic similarity, reveal non-neutral strain structure in both simulated systems and an extensively sampled population in Ghana. The unique population structure we identify underlies the large transmission reservoir characteristic of highly endemic regions in Africa.

ecology

Compensatory evolution via cryptic genetic variation: Distinct trajectories to phenotypic and fitness recovery

Populations are constantly exposed to deleterious alleles, most of which are purged via natural selection. However, deleterious fitness effects of alleles can also be suppressed by compensatory adaptation. Compensatory mutations can act directly to reduce deleterious effects of an allele. Alternatively, compensation may also occur by altering other aspects of an organisms phenotype or performance, without suppressing the phenotypic effects of the deleterious allele. Moreover, the origin of allelic variation contributing to compensatory adaptation remains poorly understood. Compensatory evolution driven by mutations that arise during the selective process are well studied. However less is known about the role standing (cryptic) genetic variation plays in compensatory adaptation. To address these questions, we examined evolutionary trajectories of natural populations of Drosophila melanogaster fixed for mutations that disrupt wing morphology, resulting in deleterious effects on several components of fitness. Lineages subjected only to natural selection, evolved modifications to courtship behavior and several life history traits without compensation in wing morphology. Yet, we observed rapid phenotypic compensation of wing morphology under artificial selection, consistent with segregating variation for compensatory alleles. We show that alleles contributing to compensation of wing morphology have deleterious effects on other fitness components. These results demonstrate the potential for multiple independent avenues for rapid compensatory adaptation from standing genetic variation, which ultimately may reveal novel adaptive trajectories.

evolutionary biology

Scaling accurate genetic variant discovery to tens of thousands of samples

Comprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel assembly-based approach to variant calling, the GATK HaplotypeCaller (HC) and Reference Confidence Model (RCM), that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously. We show by calling over 90,000 samples from the Exome Aggregation Consortium (ExAC) that, in contrast to other algorithms, the HC-RCM scales efficiently to very large sample sizes without loss in accuracy; and that the accuracy of indel variant calling is superior in comparison to other algorithms. More importantly, the HC-RCM produces a fully squared-off matrix of genotypes across all samples at every genomic position being investigated. The HC-RCM is a novel, scalable, assembly-based algorithm with abundant applications for population genetics and clinical studies.

genomics

Slower environmental change hinders adaptation from standing genetic variation

Evolutionary responses to environmental change depend on the time available for adaptation before environmental degradation leads to extinction. Explicit tests of this relationship are limited to microbes where adaptation depends on the order of mutation accumulation, excluding standing genetic variation which is key for most natural species. When adaptation is determined by the amount of heritable genotype-by-environment fitness variance then genetic drift and/or maintenance of similarly fit genotypes may deter adaptation to slower the environmental changes. To address this hypothesis, we perform experimental evolution with self-fertilizing populations of the nematode Caenorhabditis elegans and develop a new inference model that follows pre-existing genotypes to describe natural selection in changing environments. Under an abrupt change, we find that selection rapidly increases the frequency of genotypes with high fitness in the most extreme environment. In contrast, under slower environmental change selection favors those genotypes that are worse at the most extreme environment. We further demonstrate with a second set of evolution experiments that, as a consequence of slower environmental change, population bottlenecks and small population sizes lead to the loss of beneficial genotypes, while maintenance of polymorphism impedes their fixation in large populations. Taken together, these results indicate that standing variation for genotype-by-environment fitness interactions alters the pace and outcome of adaptation under environmental change.

evolutionary biology

Machine Learning for Population Genetics: A New Paradigm

As population genomic datasets grow in size, researchers are faced with the daunting task of making sense of a flood of information. To keep pace with this explosion of data, computational methodologies for population genetic inference are rapidly being developed to best utilize genomic sequence data. In this review we discuss a new paradigm that has emerged in computational population genomics: that of supervised machine learning. We review the fundamentals of machine learning, discuss recent applications of supervised machine learning to population genetics that outperform competing methods, and describe promising future directions in this area. Ultimately, we argue that supervised machine learning is an important and underutilized tool that has considerable potential for the world of evolutionary genomics.

evolutionary biology

The effect of strong purifying selection on genetic diversity

Purifying selection reduces genetic diversity, both at sites under direct selection and at linked neutral sites. This process, known as background selection, is thought to play an important role in shaping genomic diversity in natural populations. Yet despite its importance, the effects of background selection are not fully understood. Previous theoretical analyses of this process have taken a backwards-time approach based on the structured coalescent. While they provide some insight, these methods are either limited to very small samples or are computationally prohibitive. Here, we present a new forward-time analysis of the trajectories of both neutral and deleterious mutations at a nonrecombining locus. We find that strong purifying selection leads to remarkably rich dynamics: neutral mutations can exhibit sweep-like behavior, and deleterious mutations can reach substantial frequencies even when they are guaranteed to eventually go extinct. Our analysis of these dynamics allows us to calculate analytical expressions for the full site frequency spectrum. We find that whenever background selection is strong enough to lead to a reduction in genetic diversity, it also results in substantial distortions to the site frequency spectrum, which can mimic the effects of population expansions or positive selection. Because these distortions are most pronounced in the low and high frequency ends of the spectrum, they become particularly important in larger samples, but may have small effects in smaller samples. We also apply our forward-time framework to calculate other quantities, such as the ultimate fates of polymorphisms or the fitnesses of their ancestral backgrounds.

evolutionary biology

New Cell Fate Potentials and Switching Kinetics Uncovered in a Classic Bistable Genetic Switch

Bistable switches are common gene regulatory motifs directing two mutually exclusive gene expression states, and consequently distinct cell fates. Theoretical studies suggest that the simple circuitry of bistable switches is sufficient to encode more than two cell fates due to the non-equilibrium, heterogeneous cellular environment, allowing a high degree of adaptation and differentiation. However, new cell fates arising from a classic bistable switch without rewiring the circuitry have not been experimentally observed. By developing a new, dual single-molecule gene-expression reporting system in live E. coli cells, we investigated the expression dynamics of two mutually repressing transcription factors, CI and Cro, in the classic genetic switch of bacteriophage {lambda}. We found that in addition to the two expected high-Cro and high-CI production states, there existed two new ones, in which neither CI nor Cro was produced, or both CI and Cro were produced. We constructed the corresponding potential landscape and mapped the transition kinetics between the four production states, providing insight into possible state-switching rates and paths. These findings uncover new cell fate potentials beyond the classical picture of {lambda} switch, and open a new window to explore the genetic and environmental origins of the cell fate decision-making process in gene regulatory networks.

biophysics

Genetic Single Neuron Anatomy reveals fine granularity of cortical interneuron subtypes

Parsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of discrete cell groups from population continuum. Combining genetic labeling with high-resolution, large volume light microscopy, we established a platform of genetic single neuron anatomy that resolves, registers and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segment, consist of multiple subtypes distinguished by laminar position, dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. Therefore, interneuron types likely consist of fine-grained subtypes with distinct input-output connectivity patterns.

neuroscience

Assessing the genetic effect mediated through gene expression from summary eQTL and GWAS data

Integrating genome-wide association (GWAS) and expression quantitative trait locus (eQTL) data into transcriptome-wide association studies (TWAS) based on predicted expression can boost power to detect novel disease loci or pinpoint the susceptibility gene at a known disease locus. However, it is often the case that multiple eQTL genes colocalize at disease loci, making the identification of the true susceptibility gene challenging, due to confounding through linkage disequilibrium (LD). To distinguish between true susceptibility genes (where the genetic effect on phenotype is mediated through expression) and colocalization due to LD, we examine an extension of the Mendelian Randomization Egger regression method that allows for LD while only requiring summary association data for both GWAS and eQTL. We derive the standard TWAS approach in the context of Mendelian Randomization and show in simulations that the standard TWAS does not control Type I error for causal gene identification when eQTLs have pleiotropic or LD-confounded effects on disease. In contrast, LD Aware MR-Egger regression can control Type I error in this case while attaining similar power as other methods in situations where these provide valid tests. However, when the direct effects of genetic variants on traits are correlated with the eQTL associations, all of the methods we examined including LD Aware MR-Egger regression can have inflated Type I error. We illustrate these methods by integrating gene expression within a recent large-scale breast cancer GWAS to provide guidance on susceptibility gene identification.

epidemiology

Shared Genetic Requirements for Atf5 Translation in the Vomeronasal Organ and Main Olfactory Epithelium

BackgroundBoth olfactory sensory neurons (OSNs) and vomeronasal sensory neurons (VSNs) require the transcription factor Atf5 for maturation and survival. In OSNs, ATF5 translation is controlled by olfactory receptor (OR) expression-mediated activation of the PERK branch of the unfolded protein response. This study evaluated whether OSNs and VSNs share genetic requirements for ATF5 translation.\n\nMethodsATF5 immunoreactivity was assayed in whole vomeronasal organs from a series of genetic mutant animals identified in studies of OR gene choice, OR feedback, and regulation and OSN development.\n\nResultsATF5 expression in VSNs required the histone demethylase Lsd1, which has been previously reported to be required for OR expression. ATF5 expression also required PERK-mediated phosphorylation of the translation initiation factor eIF2. Finally, unlike previous observations in OSNs, ATF5 was found to be widespread in the mature VNO and co-expressed with mature VSN markers.\n\nConclusionsThese data suggest that the initiation of ATF5 translation in VSNs and OSNs is under similar regulation, and that persistent/prolonged ATF5 translation in VSNs may serve VSN-specific gene regulatory programs. This study firmly establishes the unfolded protein response as a major controller of sensory neuronal maturation and diversification.

developmental biology

Niche separation increases with genetic distance among bloom-forming cyanobacteria

Bacterial communities are composed of distinct groups of potentially interacting lineages, each thought to occupy a distinct ecological niche. It remains unclear, however, how quickly niche preference evolves and whether more closely related lineages are more likely to share ecological niches. We addressed these questions by following the dynamics of two bloom-forming cyanobacterial genera over an 8-year time-course in Lake Champlain, Canada, using 16S amplicon sequencing and measurements of several environmental parameters. The two genera, Microcystis (M) and Dolichospermum (D), are frequently observed simultaneously during bloom events and thus have partially overlapping niches. However, the extent of their niche overlap is debated, and it is also unclear to what extent niche partitioning occurs among strains within each genus. To identify strains within each genus, we applied minimum entropy decomposition (MED) to 16S rRNA gene sequences. We confirmed that at a genus level, M and D have different preferences for nitrogen and phosphorus concentrations. Within each genus, we also identified strains differentially associated with temperature, precipitation, and concentrations of nutrients and toxins. In general, niche similarity between strains (as measured by co-occurrence over time) declined with genetic distance. This pattern is consistent with habitat filtering - in which closely-related taxa are ecologically similar, and therefore tend to co-occur under similar environmental conditions. In contrast with this general pattern, similarity in certain niche dimensions (notably particulate nitrogen and phosphorus) did not decline linearly with genetic distance, and instead showed a complex polynomial relationship. This observation suggests the importance of processes other than habitat filtering - such as competition between closely-related taxa, or convergent trait evolution in distantly-related taxa - in shaping particular traits in microbial communities.

ecology

Determining cell fate specification and genetic contribution to cardiac disease risk in hiPSC-derived cardiomyocytes at single cell resolution

The majority of genetic loci underlying common disease risk act through changing genome regulation, and are routinely linked to expression quantitative trait loci, where gene expression is measured using bulk populations of mature cells. A crucial step that is missing is evidence of variation in the expression of these genes as cells progress from a pluripotent to mature state. This is especially important for cardiovascular disease, as the majority of cardiac cells have limited properties for renewal postneonatal. To investigate the dynamic changes in gene expression across the cardiac lineage, we generated RNA-sequencing data captured from 43,168 single cells progressing through in vitro cardiac-directed differentiation from pluripotency. We developed a novel and generalized unsupervised cell clustering approach and a machine learning method for prediction of cell transition. Using these methods, we were able to reconstruct the cell fate choices as cells transition from a pluripotent state to mature cardiomyocytes, uncovering intermediate cell populations that do not progress to maturity, and distinct cell trajectories that terminate in cardiomyocytes that differ in their contractile forces. Second, we identify new gene markers that denote lineage specification and demonstrate a substantial increase in their utility for cell identification over current pluripotent and cardiogenic markers. By integrating results from analysis of the single cell lineage RNA-sequence data with population-based GWAS of cardiovascular disease and cardiac tissue eQTLs, we show that the pathogenicity of disease-associated genes is highly dynamic as cells transition across their developmental lineage, and exhibit variation between cell fate trajectories. Through the integration of single cell RNA-sequence data with population-scale genetic data we have identified genes significantly altered at cell specification events providing insights into a context-dependent role in cardiovascular disease risk. This study provides a valuable data resource focused on in vitro cardiomyocyte differentiation to understand cardiac disease coupled with new analytical methods with broad applications to single-cell data.

genomics

Generation of Variation and Mean Fitness Increase: Necessity is the Mother of Genetic Invention

Generation of variation may be detrimental in well-adapted populations evolving under constant selection. In a constant environment, genetic modifiers that reduce the rate at which variation is generated by processes such as mutation and migration, succeed. However, departures from this reduction principle have been demonstrated. Here we analyze a general model of evolution under constant selection where the rate at which variation is generated depends on the individual. We find that if a modifier allele increases the rate at which individuals of below-average fitness generate variation, then it will increase in frequency and increase the population mean fitness. This principle applies to phenomena such as stress-induced mutagenesis and condition-dependent dispersal, and exemplifies \"Necessity is the mother of genetic invention.\"

evolutionary biology

A Genetic Pathway Composed of EDT1/HDG11, ERECTA, and E2Fa Loci Regulates Water Use Efficiency by Modulating Stomatal Density

Improvement of crop drought resistance and water use efficiency (WUE) has been a major endeavor in agriculture. ERECTA is the first identified major effector of water use efficiency. However, the underlying molecular mechanism is not well understood. Here, we report a genetic pathway, composed of EDT1/HDG11, ERECTA, and E2Fa loci, which regulates water use efficiency by modulating stomatal density. The HD-START transcription factor EDT1/HDG11 transcriptionally activates ERECTA expression by binding to an HD cis-element in the ERECTA promoter. ERECTA in turn relies on E2Fa to control the expression of cell-cycle related genes and the transition from mitosis to endocycle, which leads to increased nuclear DNA content in leaf cells, and therefore increased cell size and decreased stomatal density. The decreased stomatal density improves plant WUE. Our study demonstrates the EDT1/HDG11-ERECTA-E2Fa genetic pathway that reduces stomatal density by increasing cell size, providing a new avenue to improve WUE of crops.

plant biology

The ecological genetics of Pseudomonas syringae residing on the kiwifruit leaf surface

Interactions between commensal microbes and invading pathogens are understudied, despite their likely effects on pathogen population structure and infection processes. We describe the population structure and genetic diversity of a broad range of co-occurring Pseudomonas syringae isolated from infected and uninfected kiwifruit during an outbreak of bleeding canker disease caused by P. syringae pv. actinidiae (Psa) in New Zealand. Overall population structure was clonal and affected by ecological factors including infection status and cultivar. Most isolates are members of a new clade in phylogroup 3 (PG3a), also present on kiwifruit leaves in China and Japan. Stability of the polymorphism between pathogenic Psa and commensal P. syringae PG3a isolated from the same leaf was tested using reciprocal invasion from rare assays in vitro and in planta. P. syringae G33C (PG3a) inhibited Psa NZ54, while the presence of Psa NZ54 enhanced the growth of P. syringae G33C. This effect could not be attributed to virulence activity encoded by the Type 3 secretion system of Psa. Together our data contribute toward the development of an ecological perspective on the genetic structure of pathogen populations.\n\nORIGINALITY-SIGNIFICANT STATEMENTBacterial pathogen populations are often studied with little consideration of co-occurring microbes and yet interactions between pathogens and commensals can affect both population structure and disease progression. A fine-scale sampling of commensals present on kiwifruit leaves during an outbreak of bleeding canker disease caused by P. syringae pv. actinidiae reveals a clonal population structure. A new clade of non-pathogenic P. syringae (PG3a) appears to be associated with kiwifruit on a global scale. The presence of PG3a on kiwifruit has significant effects on the outcome of infection by P. syringae pv. actinidiae. This emphasises the value of studying the effect of co-occurring bacteria on pathogen-plant interactions.

microbiology

Experimental Evolution Across Different Thermal Regimes Yields Genetic Divergence in Recombination Fraction But No Divergence in Temperature-Associated Plastic Recombination

Phenotypic plasticity is pervasive in nature. One mechanism underlying the evolution and maintenance of such plasticity is environmental heterogeneity. Indeed, theory indicates that both spatial and temporal variation in the environment should favor the evolution of phenotypic plasticity under a variety of conditions. Cyclical environmental conditions have also been shown to yield evolved increases in recombination frequency. Here were use a panel of replicated experimental evolution populations of D. melanogaster to test whether variable environments favor enhanced plasticity in recombination rate and/or increased recombination rate in response to temperature. In contrast to expectation, we find no evidence for either enhanced plasticity in recombination or increased rates of recombination in the variable environment lines. Our data confirm a role of temperature in mediating recombination fraction in D. melanogaster, and indicate that recombination is genetically and plastically depressed under lower temperatures. Our data further suggest that the genetic architectures underlying plastic recombination and population-level variation in recombination rate are likely to be distinct.

evolutionary biology