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bioRxiv2022

An investigation of the sex-specific genetic architecture of fitness in Drosophila melanogaster

In dioecious populations, the sexes employ divergent reproductive strategies to maximize fitness and, as a result, genetic variants can affect fitness differently in males and females. Moreover, recent studies have highlighted an important role of the mating environment in shaping the strength and direction of sex-specific selection. Here, we measure adult fitness for each sex of 357 lines from the Drosophila Synthetic Population Resource (DSPR) in two different mating environments. We analyze the data using three different approaches to gain insight into the sex-specific genetic architecture for fitness: classical quantitative genetics, genomic associations, and a mutational burden approach. The quantitative genetics analysis finds that, on average segregating genetic variation in this population has concordant fitness effects both across the sexes and across mating environments. We do not find specific genomic regions with strong associations with either sexually antagonistic (SA) or sexually concordant (SC) fitness effects, yet there is modest evidence of an excess of genomic regions with weak associations, both with SA and SC fitness effects. Our examination of mutational burden indicates stronger selection against indels and loss-of-function variants in females than males.

evolutionary biology↗

bioRxiv2022

Using computational simulations to quantify genetic load and predict extinction risk

Small and isolated wildlife populations face numerous threats to extinction, among which is the deterioration of fitness due to an accumulation of deleterious genetic variation. Genomic tools are increasingly used to quantify the impacts of deleterious variation in small populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of individual mutations. Computational simulations of deleterious genetic variation offer an alternative and complementary tool that can help overcome these limitations, though such approaches have yet to be widely employed. In this Perspective, we aim to encourage conservation genomics researchers to adopt greater use of computational simulations to aid in quantifying and predicting the threat that deleterious genetic variation poses to extinction. We first provide an overview of the components of a simulation of deleterious genetic variation, describing the key parameters involved in such models. Next, we clarify several misconceptions about an essential simulation parameter, the distribution of fitness effects (DFE) of new mutations, and review recent debates over what the most appropriate DFE parameters are. We conclude by comparing modern simulation tools to those that have long been employed in population viability analysis, weighing the pros and cons of a genomics-informed simulation approach, and discussing key areas for future research. Our aim is that this Perspective will facilitate broader use of computational simulations in conservation genomics, enabling a deeper understanding of the threat that deleterious genetic variation poses to biodiversity.

evolutionary biology↗

bioRxiv2022

Analysis of a genetic region affecting mouse body weight

Genetic factors affect an individuals risk of developing obesity, but in most cases each genetic variant has a small effect. Discovery of genes that regulate obesity may provide clues about its underlying biological processes and point to new ways the disease can be treated. Pre-clinical animal models facilitate genetic discovery in obesity because environmental factors can be better controlled compared to the human population. We studied inbred mouse strains to identify novel genes affecting obesity and glucose metabolism. BTBR T+ Itpr3tf/J (BTBR) mice are fatter and more glucose intolerant than C57BL/6J (B6) mice. Prior genetic studies of these strains identified an obesity locus on chromosome 2. Using congenic mice, we found that obesity was affected by a ~316 kb region, with only two known genes, pyruvate dehydrogenase kinase 1 (Pdk1) and integrin alpha 6 (Itga6). Both genes had mutations affecting their amino acid sequence and reducing mRNA levels. Both genes have known functions that could modulate obesity, lipid metabolism, insulin secretion and/or glucose homeostasis. We hypothesized that genetic variation in or near Pdk1 or Itga6 causing reduced Pdk1 and Itga6 expression would promote obesity and impaired glucose tolerance. We used knockout mice lacking Pdk1 or Itga6 fed an obesigenic diet to test this hypothesis. Under the conditions we studied, we were unable to detect an individual contribution of either Pdk1 or Itga6 to body weight. However, we identified a previously unknown role for Pdk1 in cardiac lipid metabolism providing the basis for future investigations in that area.

physiology↗

bioRxiv2022

Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency

Preclinical models of neurodevelopmental disorders typically use single inbred strains which fail to capture human genetic and symptom heterogeneity that is common clinically. We tested if systematically modeling human genetic diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. Trait disruptions mimicked those seen in human populations, including high penetrance of macrocephaly and disrupted behavior, but with robust strain and sex differences. For every trait, some strains exhibited a range of large effect size disruptions, sometimes in opposite directions, and remarkably others expressed resilience. Thus, systematically introducing genetic diversity into mouse models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies and improved treatments. One-Sentence SummaryAutism trait heterogeneity due to a syndromic gene mutation is recapitulated in mice by incorporating genetic diversity.

neuroscience↗

bioRxiv2022

Effect of beneficial sweeps and background selection on genetic diversity in changing environments

Neutral theory predicts that the genetic diversity within a population is proportional to the census population size. In contrast, observed genetic diversity for various species is much lower than theoretical prediction (Lewontins paradox). The selective sweeps and background selection, reduce the genetic variation at the linked neutral sites and have been studied considering the environment to be selectively constant. However, in a natural population, the selective environment varies with time. Here, we investigate the impact of selective sweeps and background selection on neutral genetic diversity when the selection coefficient changes periodically over time. The reduction in genetic variation due to selective sweeps is known to depend on the conditional fixation time. Here, we find that the effect of changing environment on conditional mean fixation time is most substantial for the randomly mating population than the inbreeding population with arbitrary inbreeding coefficient. We also study the effect of background selection on neutral sites when the selection co-efficient of linked deleterious mutation change periodically in time. In the slowly changing environment, we find that neutral heterozygosity is significantly different, and the site frequency spectrum has a different shape than that in the static environment.

evolutionary biology↗

bioRxiv2022

Genetic control of RNA editing in Neurodegenerative disease

A-to-I RNA editing diversifies human transcriptome to confer its functional effects on the downstream genes or regulations, potentially involving in neurodegenerative pathogenesis. Its variabilities are attributed to multiple regulators, including the key factor of genetic variant. To comprehensively investigate the potentials of neurodegenerative disease-susceptibility variants from the view of A-to-I RNA editing, we analyzed matched genetic and transcriptomic data of 1,596 samples across nine brain tissues and whole blood from two large consortiums, Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) and Parkinsons Progression Markers Initiative (PPMI). The large-scale and genome-wide identification of 95,637 RNA editing quantitative trait loci revealed the preferred genetic effects on adjacent editing events. Furthermore, to explore the underlying mechanisms of the genetic controls of A-to-I RNA editing, several top RNA binding proteins were pointed out, such as EIF4A3, U2AF2, NOP58, FBL, NOP56, and DHX9, since their regulations on multiple RNA editing events probably interfered by these genetic variants. Moreover, these variants may also contribute to the variability of other molecular phenotypes associated with RNA editing, including the functions of four proteins, expressions of 148 genes, and splicing of 417 events. All the analyses results shown in NeuroEdQTL (https://relab.xidian.edu.cn/NeuroEdQTL/) constituted a unique resource for the understanding of neurodegenerative pathogenesis from genotypes to phenotypes related to A-to-I RNA editing.

bioinformatics↗

bioRxiv2022

Direct inference and control of genetic population structure from RNA sequencing data

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

bioinformatics↗

bioRxiv2022

Population level genetic memory of prior metabolic adaptation in E. coli

Bacteria must often survive following the exhaustion of their external growth resources. Fitting with this need, many bacterial species that cannot sporulate, can enter a state known as long term stationary phase (LTSP) in which they can persist for years within spent media. Several recent studies have revealed the dynamics of genetic adaptation of Escherichia coli under LTSP. Yet, the metabolic consequences of such genetic adaptation were not addressed. Here, we characterized the metabolic changes LTSP populations experience and link them to their genetic adaptation. We observed that during growth within fresh resources E. coli produces the short chain fatty acid butyrate, which wildtype E. coli cannot consume. Once resources are otherwise exhausted, E. coli adapts genetically to consume butyrate through the convergent, temporally precise emergence of mutation combinations within genes that regulate fatty acid metabolism. These mutations appear to negatively affect bacterial fitness when butyrate is not available, and hence rapidly decrease in frequency, once all butyrate is consumed. Yet despite this, E. coli populations show a remarkable capability of maintaining a population-level genetic memory of prior adaptation to consume butyrate. The maintenance of such a memory allows bacteria to rapidly re-adapt, at an ecological, rather than an evolutionary timeframe, to re-consume previously encountered metabolites.

evolutionary biology↗

bioRxiv2022

GRETA: an R package for mapping in silico genetic interaction and essentiality networks

SummaryMapping genetic interaction and essentiality networks in human cell lines have been used to identify vulnerabilities of cells carrying specific genetic alterations and to associate novel functions to genes, respectively. In vitro and in vivo genetic screens to decipher these networks are resource-intensive, limiting the throughput of samples that can be analyzed. In this application note, we provide an R package we call Genetic inteRaction and EssentialiTy mApper (GRETA). GRETA is an accessible tool for in silico genetic interaction screens and essentiality network analyses using publicly available data, requiring only basic R programming knowledge. Availability and implementationThe R package, GRETA, is licensed under GNU General Public License v3.0 and freely available at https://github.com/ytakemon/GRETA and https://doi.org/10.5281/zenodo.6940757, with documentation and tutorial. A Singularity container is also available at https://cloud.sylabs.io/library/ytakemon/greta/greta. Contactmmarra@bcgsc.ca Supplemental informationSupplemental materials are available at Bioinformatics online. Issue sectionSystems biology

bioinformatics↗

bioRxiv2022

The population-level impact of Enterococcus faecalis genetics on intestinal colonisation and extraintestinal infection

Enterococcus faecalis is a commensal pathogenic bacterium commonly found in the human gastrointestinal tract and a cause of opportunistic infections typically associated with multidrug resistance. The E. faecalis genetic changes associated with pathogenicity and extraintestinal infection, particularly through gut-to-bloodstream translocation, are poorly understood. Here, we investigate the E. faecalis genetic signatures associated with intestinal colonisation and extraintestinal infection and infection of hospitalised and non-hospitalised individuals using heritability estimation and a genome-wide association study (GWAS). We analysed 750 whole-genome sequences of faecal and bloodstream E. faecalis isolates from hospitalised patients and non-hospitalised individuals, respectively, predominantly in Europe. We found that E. faecalis infection of individuals depending on their hospitalisation status and extraintestinal infection are heritable traits and that [~]24% and [~]34% of their variation is explained by the considered genetic effects, respectively. Further, a GWAS using linear mixed models did not pinpoint any clear enrichment of individual genetic changes in isolates from different isolation sites and individuals with varying hospitalisation statuses, suggesting that these traits are highly polygenic. Altogether, our findings indicate that E. faecalis infection and extraintestinal infection are influenced by variation in genetic, host, and environmental factors, and ultimately the opportunistic pathogenic lifestyle of this versatile host generalist bacterium.

microbiology↗

bioRxiv2022

Chromosome-scale reference genome and RAD-based genetic map of yellow starthistle (Centaurea solstitialis) reveal putative structural variation and QTLs associated with invader traits

Invasive species offer outstanding opportunities to identify the genomic sources of variation that contribute to rapid adaptation, as well as the genetic mechanisms facilitating invasions. The Eurasian plant yellow starthistle (Centaurea solstitialis) is highly invasive in North and South American grasslands and known to have evolved increased growth and reproduction during invasion. Here we develop new genomic resources for C. solstitialis and map the genetic basis of invasiveness traits. We present a chromosome-scale (1N = 8) reference genome using PacBio CLR and Dovetail Omni-C technologies, and functional gene annotation using RNAseq. We find repeat structure typical of the family Asteraceae, with over 25% of gene content derived from ancestral whole genome duplications (paleologs). Using an F2 mapping population derived from a cross between native and invading parents, with a restriction site-associated DNA (RAD)-based genetic map, we validate the assembly and identify 13 QTL underpinning size traits that have evolved during invasion. We find evidence that large effect QTL may be associated with structural variants between native and invading genotypes, including a variant with an overdominant and pleiotropic effect on key invader traits. We also find evidence of significant paleolog enrichment under two QTL. Our results add to growing evidence of the importance of structural variants in evolution, and to understanding of the rapid evolution of invaders. Significance StatementInvasive species often evolve rapidly in new environments, potentially informing our understanding of the genomic basis of adaptation, but genomic studies of these non-model systems are limited. We provide a chromosome-scale reference genome, annotation, and genetic map for the invasive plant yellow starthistle, and we investigate the genetic basis of invader trait evolution in this system. We find regions of the genome with large effects on traits that differ between native and invading genotypes, and evidence suggesting genome structural variants and past genome duplications could play a role in rapid adaptation of invading populations. These genomic resources and evolutionary insights aid in our understanding of the sources of genomic variation for adaptation, and how their evolution facilitates invasion.

genomics↗

bioRxiv2022

Kinship and genetic variation in aquarium-spawned Acropora hyacinthus corals

Recent scientific advances in ex situ system design and operation make it possible to complete gametogenic cycles of broadcast spawning corals. Breeding corals in aquaria are critical advances for population management, particularly genetic rescue and assisted gene flow efforts. Genetic rescue projects for corals are already underway to bring threatened species into ex situ culture and propagation, thereby preserving standing genetic variation. However, while breeding corals is increasingly feasible, the consequences of the aquarium environment on the genetic and phenotypic composition of coral populations is not yet known. The aquarium environment may in itself be a selective pressure on corals, but it also presents relaxed selective pressure in other respects. In 2019 and 2020, gravid Acropora hyacinthus coral colonies were collected from Palauan reefs and shipped to the California Academy of Sciences (CAS) in San Francisco. In both years, gametes were batch-fertilized to produce larvae that were then settled and reared to recruits. As of April 2021, when they were sampled for sequencing, 23 corals produced at CAS in 2019 and 16 corals produced at CAS in 2020 had survived for two years and one year, respectively. We sequenced the full genomes of the 39 offspring corals and their 15 potential parents to a median 26x depth of coverage. We find clear differential parentage, with some parents producing the vast majority of offspring, while the majority of parents produced no surviving offspring. After scanning 12.9 million single nucleotide polymorphisms (SNPs), we found 887 SNPs that may be under selection in the aquarium environment, and we identified the genes and pathways these SNPs may affect. We present recommendations for preserving standing genetic variation in aquarium-bred corals based on the results of this pilot project.

evolutionary biology↗

bioRxiv2022

How density dependence, genetic erosion, and the extinction vortex impact evolutionary rescue

Following severe environmental change that reduces mean population fitness below replacement, populations must adapt to avoid eventual extinction, a process called evolutionary rescue. Models of evolutionary rescue demonstrate that initial size, genetic variation, and degree of maladaptation influence population fates. However, many models feature populations that grow without negative density dependence or with constant genetic diversity despite precipitous population decline, assumptions likely to be violated in conservation settings. We examined the simultaneous influences of density-dependent growth and erosion of genetic diversity on populations adapting to novel environmental change using stochastic, individual-based simulations. Density dependence decreased the probability of rescue and increased the probability of extinction, especially in large and initially well-adapted populations that previously have been predicted to be at low risk. Increased extinction occurred shortly following environmental change, as populations under density dependence experienced more rapid decline and reached smaller sizes. Populations that experienced evolutionary rescue lost genetic diversity through drift and adaptation, particularly under density dependence. Populations that declined to extinction entered an extinction vortex, where small size increased drift, loss of genetic diversity, and the fixation of maladaptive alleles, hindered adaptation, and kept populations at small densities where they were vulnerable to extinction via demographic stochasticity.

ecology↗

bioRxiv2022

Different genetic architectures of complex traits and their relevance to polygenic score performance

BackgroundDespite the many insights gleaned from GWAS, polygenic predictions of complex traits have had limited success, particularly when these predictions are applied to individuals of non-European descent. A deeper understanding of the genetic architecture of complex traits may inform why some traits are easier to predict than others. MethodsExamining 163 complex traits from the UK Biobank, we compared and contrasted three aspects of genetic architecture (SNP heritability, LD variability, and genomic inequality) with three aspects of polygenic score performance (prediction accuracy in the source population, portability across populations, and trait divergence across populations). Here, genomic inequality refers to how unequally the genetic variance of each trait is distributed across the top trait-associated SNPs, as quantified via a novel application of Gini coefficients. ResultsConsistent with reduced statistical power, polygenic predictions of binary traits performed worse than predictions of quantitative traits. Traits with low Gini coefficients (i.e., highly polygenic architectures) include hip circumference as well as systolic and diastolic blood pressure. Traits with large population-level differences in polygenic scores include skin pigmentation and hair color. Focusing on 96 quantitative traits, we found that highly heritable traits were easier to predict and had predictions that were more portable to other ancestries. Traits with highly divergent polygenic score distributions across populations were less likely to have portable predictions. Intriguingly, LD variability was largely uninformative regarding the portability of polygenic predictions. This suggests that factors other than the differential tagging of causal SNPs drive the reduction in polygenic score accuracy across populations. Subsequent analyses identified suites of traits with similar genetic architecture and polygenic score performance profiles. Importantly, lifestyle and psychological traits tended to have low heritability, as well as poor predictability and portability. ConclusionsNovel metrics capture different aspects of trait-specific genetic architectures and polygenic score performance. Our findings also caution against the application of polygenic scores to traits like general happiness, alcohol frequency, and average income, especially when polygenic scores are applied to individuals who have an ancestry that differs from the original source population.

genomics↗

bioRxiv2022

Assessing the impact of pedigree quality on the validity of quantitative genetic parameterestimates

Investigating the evolutionary dynamics of complex traits in nature requires the accurate assessment of their genetic architecture. Using a quantitative genetic (QG) modeling approach (e.g., animal model), relatedness information from a pedigree combined with phenotypic measurements can be used to infer the amount of additive genetic variance in traits. However, pedigree information from natural systems is not perfect and might contain errors or be of low quality. Published sensitivity analyses revealed a limited impact of expected error rates on parameter estimates. However, natural systems will differ in many respects (e.g., mating system, data availability, pedigree structure), thus it can be inappropriate to generalize outcomes from one system to another. French-Canadian (FC) genealogies are extensive and deep-rooted (up to 9 generations in this study) making them ideal to study how the quality and properties (e.g., errors, completeness) of pedigrees affect QG estimates. We conducted simulation analyses to infer the reliability of QG estimates using FC pedigrees and how it is impacted by genealogical errors and variation in pedigree structure. Broadly, results show that pedigree size and depth are important determinants of precision but not of accuracy. While the mean genealogical entropy (based on missing links) seems to be a good indicator of accuracy. Including a shared familial component into the simulations led to on average a 46% overestimation of the additive genetic variance. This has crucial implications for evolutionary studies aiming to estimate QG parameters given that many traits of interest, such as life history, exhibit important non-genetic sources of variation.

evolutionary biology↗

bioRxiv2022

The genetic structure within a single tree is determined by the behavior of the stem cells in the meristem

Genomic sequencing revealed that somatic mutations cause a genetic differentiation of the cells in a single tree. In this study, we consider a mathematical model for stem cell proliferation in the shoot apical meristem (abbrev. SAM), which results in genetic diversification between the cells differing in the distance along the shoot and the angle around a shoot axis. The assumptions are as follows. Stem cells in the SAM normally undergo asymmetric cell division and produce successor stem cells and differentiated cells. The differentiated cells proliferate and contribute to shoot elongation. Occasionally, a stem cell is replaced by a copy of an adjacent stem cell. We discuss the "coalescent length" between cells indicating their genetic difference with respect to neutral mutations. A mathematical analysis revealed the following. The genetic diversity of cells sampled at the same position along the shoot increases with the distance from the bottom of the shoot. Stem cells hold a larger variation if they are replaced only by the nearest neighbors than if they are replaced by any cells. The coalescent length between two cells increases not only with the difference in the position along the shoot but also in the angle around the shoot axis. The dynamics of stem cells at the SAM determine the genetic pattern of the entire shoot.

evolutionary biology↗

bioRxiv2022

A compendium of genetic regulatory effects across pig tissues

The Farm animal Genotype-Tissue Expression (FarmGTEx, https://www.farmgtex.org/) project has been established to develop a comprehensive public resource of genetic regulatory variants in domestic animal species, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biology discovery and exploitation in animal breeding and human biomedicine. Here we present results from the pilot phase of PigGTEx (http://piggtex.farmgtex.org/), where we processed 9,530 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs. We build a pig genotype imputation panel, characterize the transcriptional landscape across over 100 tissues, and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We study interactions between genotype and breed/cell type, evaluate tissue specificity of regulatory effects, and elucidate the molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying about 80% of the genetic associations for 207 pig complex phenotypes, and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, corroborating the importance of pigs as a human biomedical model.

genomics↗

bioRxiv2022

Short-term adaptation on tunable fitness landscapes from standing genetic variation in recombining populations

How does standing genetic variation affect polygenic adaptation in recombining populations? Despite a large body of work in quantitative genetics, epistatic and weak additive fitness effects among simultaneously segregating genetic variants are difficult to capture experimentally or to predict theoretically. In this study, we simulated adaptation on fitness landscapes with tunable ruggedness driven by standing genetic variation in recombining populations. We confirmed that recombination hinders the movement of a population through a rugged fitness landscape. When surveying the effect of epistasis on the fixation of alleles, we found that the combined effects of high ruggedness and high recombination probabilities lead to preferential fixation of alleles that had a high initial frequency. This indicates that positively epistatic alleles escape from being broken down by recombination when they start at high frequency. We further extract direct selection coefficients and pairwise epistasis along the adaptive path. When taking the final fixed genotype as the reference genetic background, we observe that, along the adaptive path, beneficial direct selection appears stronger and pairwise epistasis weaker than in the underlying fitness landscape. Quantitatively, the ratio of epistasis and direct selection is smaller along the adaptive path ({approx} 1) than expected. Thus, adaptation on a rugged fitness landscape may lead to spurious signals of direct selection generated through epistasis. Our study highlights how the interplay of epistasis and recombination constrains the adaptation of a diverse population to a new environment.

evolutionary biology↗