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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

No evidence for social genetic effects or genetic similarity among friends beyond that due to population stratification: a reappraisal of Domingue et al (2018)

Using data from 5,500 adolescents from the National Longitudinal Study of Adolescent to Adult Health, Domingue et al. (2018) claimed to show that friends are genetically more similar to one another than randomly selected peers, beyond the confounding effects of population stratification by ancestry. The authors also claimed to show social-genetic effects, whereby individuals educational attainment (EA) is influenced by their friends genes. Neither claim is justified by the data. Mathematically we show that 1) although similarity at causal variants is expected under assortment, the genome-wide relationship between friends (and similarly between mates) is extremely small (an effect that could be explained by subtle population stratification) and 2) significant association between individuals EA and their friends polygenic score for EA is expected under homophily with no socio-genetic effects.

genetics↗

bioRxiv2019

Haplotype genetic score analysis in 10,734 mother/infant pairs reveals complex maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes

Many maternal traits are associated with a neonates gestational duration, birth weight and birth length. These birth outcomes are subsequently associated with late onset health conditions. Based on 10,734 mother/infant duos of European ancestry, we constructed haplotype genetic scores to dissect the maternal and fetal genetic effects underlying these observed associations. We showed that maternal height and fetal growth jointly affect the duration of gestation - maternal height positively influences the gestational duration, while faster fetal growth reduces gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: tall maternal stature and higher blood glucose causally increase birth size; in the fetus, the height and metabolic risk increasing alleles can lead to increased and decreased birth size respectively; birth weight-raising alleles in fetus may reduce gestational duration and increase maternal blood pressure. These maternal and fetal genetic effects can largely explain the observed associations between the studied maternal phenotypes and birth outcomes as well as the life-course associations between these birth outcomes and adult phenotypes.

genetics↗

bioRxiv2026

Genetic Variation in Organ System Decline Across the Drosophila Genetics Reference Panel

Genetic background has a significant impact on an organism's lifespan. Underlying this metric, ageing is characterised by a sequence of physiological systems decline that leads to death. Despite this, much of the ageing research performed on model organisms in the lab uses lifespan, rather than physiological decline, as a metric to measure ageing. Here, we sought to establish if differing genotype alters age-related organ system decline by repeatedly measuring the function of five organ systems throughout the lifespan of 19 lines from the Drosophila Genetic Reference Panel. We found that the magnitude of each organ system's decline differs across genotypes, and that different organ systems decline at different rates within a genotype. We also uncovered that while declines in activity rate and reproduction were associated with length of life, overall patterns of phenotypic organ system decline differed significantly across genotypes. Overall, these data suggest that individuals with different genetic backgrounds have distinct patterns of physiological decline, implying that the mechanisms driving ageing vary between individuals. These data underscore the importance of studying organ systems decline in addition to lifespan to gain a full understanding of ageing.

genetics↗

bioRxiv2020

Expanding the Genetic Architecture of Nicotine Dependence and its Shared Genetics with Multiple Traits: Findings from the Nicotine Dependence GenOmics (iNDiGO) Consortium

Cigarette smoking is the leading cause of preventable morbidity and mortality. Knowledge is evolving on genetics underlying initiation, regular smoking, nicotine dependence (ND), and cessation. We performed a genome-wide association study using the Fagerstrom Test for ND (FTND) in 58,000 smokers of European or African ancestry. Five genome-wide significant loci, including two novel loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416) were identified, and loci reported for other smoking traits were extended to ND. Using the heaviness of smoking index (HSI) in the UK Biobank (N=33,791), rs2714700 was consistently associated, but rs1862416 was not associated, likely reflecting ND features not captured by the HSI. Both variants were cis-eQTLs (rs2714700 for MAGI2-AS3 in hippocampus, rs1862416 for TENM2 in lung), and expression of genes spanning ND-associated variants was enriched in cerebellum. SNP-based heritability of ND was 8.6%, and ND was genetically correlated with 17 other smoking traits (rg=0.40-0.95) and co-morbidities. Our results emphasize the FTND as a composite phenotype that expands genetic knowledge of smoking, including loci specific to ND.

genomics↗

bioRxiv2021

Genomic time-series data show that gene flow maintains high genetic diversity despite substantial genetic drift in a butterfly species

Effective population size affects the efficacy of selection, rate of evolution by drift, and neutral diversity levels. When species are subdivided into multiple populations connected by gene flow, evolutionary processes can depend on global or local effective population sizes. Theory predicts that high levels of diversity might be maintained by gene flow, even very low levels of gene flow, consistent with species long-term effective population size, but tests of this idea are mostly lacking. Here, we show that Lycaeides butterfly populations maintain low contemporary (variance) effective population sizes (e.g., [~]200 individuals) and thus evolve rapidly by genetic drift. Contemporary effective sizes were consistent with local census populations sizes. In contrast, populations harbored high levels of genetic diversity consistent with an effective population size several orders of magnitude larger. We hypothesized that the differences in the magnitude and variability of contemporary versus long-term effective population sizes were caused by gene flow of sufficient magnitude to maintain diversity but only subtly affect evolution on generational time scales. Consistent with this hypothesis, we detected low but non-trivial gene flow among populations. Furthermore, using population-genomic time-series data, we documented patterns consistent with predictions from this hypothesis, including a weak but detectable excess of evolutionary change in the direction of the mean (migrant gene pool) allele frequencies across populations, and consistency in the direction of allele frequency change over time. The documented decoupling of diversity levels and short-term change by drift in Lycaeides has implications for our understanding of contemporary evolution and the maintenance of genetic variation in the wild.

evolutionary biology↗

bioRxiv2022

Quantitative genetic study suggests sex-specific genetic architecture for fetal testosterone in a wild mammal

Testosterone plays a critical role in mediating fitness-related traits in many species. Although it is highly responsive to environmental and social conditions, evidence from several species show a heritable component to its individual variation. Despite the known effects that in utero testosterone exposure have on adult fitness, the heritable component of individual testosterone variation in fetuses is mostly unexplored. Furthermore, testosterone has sex-differential effects on fetal development, i.e., a specific level may be beneficial for male fetuses but detrimental for females. The above mentioned may lead to a different genetic structure underlying the heritability of testosterone between the sexes. Here, we used a wild animal model, the feral nutria, quantified testosterone using hair-testing and estimated its heritability between parent and offspring from the same and opposite sex. We found that in utero accumulated hair testosterone levels were heritable between parents and offspring of the same sex. However, there was a low additive genetic covariance between the sexes, and a relatively low cross-sex genetic correlation, suggesting a potential for sex-dependent trait evolution, expressed early on, in utero.

molecular biology↗

bioRxiv2025

Plant phylogeny and life history predict AM fungal species and genetic composition, but only life history and genetic composition predict feedback

Symbioses exert strong influences on host phenotypes; however, benefits from symbioses can increase or degrade over time. Understanding the context-dependence of reinforcing or degrading dynamics is pivotal to predicting stability of symbiotic benefits. Host phylogenetic relationships and host life history traits are two candidate axes that have been proposed to structure symbioses. However, the relative influence of host evolutionary history and life history on symbiont composition, and whether changes in symbiont composition translate into stronger mutualistic benefits is unknown. We tested the influence of plant phylogenetic relationships and plant life history on the composition of Arbuscular Mycorrhizal (AM) fungi, perhaps the most ancestral and influential of plant symbionts, and then tested whether AM fungal differentiation resulted in improved mutualism. We constructed mycobiomes composed of seven AM fungal isolates derived from tallgrass prairie and grew them for two growing seasons with 38 grassland plant species. We found that host phylogenetic structure was a significant predictor of the composition of AM fungal communities and the genetic composition of AM fungal species, patterns consistent with phylosymbiosis. However, the phylogenetic structure of AM fungi failed to translate to improved benefit to their host. While AM fungi generally improved plant growth and mycorrhizal feedback was generally positive, the strength of feedback was not predicted by plant phylogenetic distance. The composition of the AM fungal community and genetic composition within AM fungal species were also significantly influenced by plant life history. In addition, feedbacks between early and late successional species were generally positive. Interestingly, changes in species composition did not predict feedback, while changes in genetic composition of the two most abundant AM fungal species predicted positive mycorrhizal feedback. These reinforcing mycorrhizal feedbacks across life history can mediate plant species turnover during succession and suggests that consideration of mycorrhizal dynamics could improve restoration.

ecology↗

bioRxiv2025

Uncovering genetic architecture of the heart via genetic association studies of unsupervised deep learning derived endophenotypes

Recent genome-wide association studies (GWAS) have effectively linked genetic variants to quantitative traits derived from time-series cardiac magnetic resonance imaging, revealing insights into cardiac morphology and function. Deep learning approach generally requires extensive supervised training on manually annotated data. In this study, we developed a novel framework using a 3D U-architecture autoencoder (cineMAE) to learn deep image phenotypes from cardiac magnetic resonance (CMR) imaging for genetic discovery, focusing on long-axis two-chamber and four-chamber views. We trained a masked autoencoder to develop Unsupervised Derived Image Phenotypes for heart (Heart-UDIPs). These representations were found to be informative to indicate various heart-specific phenotypes (e.g., left ventricular hypertrophy) and diseases (e.g., hypertrophic cardiomyopathy). GWAS on Heart UDIP identified 323 lead SNP and 628 SNP-prioritized genes, which exceeded previous methods. The genes identified by method described herein, exhibited significant associations with cardiac function and showed substantial enrichment in pathways related to cardiac disorders. These results underscore the utility of our Heart-UDIP approach in enhancing the discovery potential for genetic associations, without the need for clinically defined phenotypes or manual annotations.

bioinformatics↗

bioRxiv2020

Genetic drift from the out-of-Africa bottleneck leads to biased estimation of genetic architecture and selection

Most complex traits evolved in the ancestors of all modern humans and have been under negative or balancing selection to maintain the distribution of phenotypes observed today. Yet all large studies mapping genomes to complex traits occur in populations that have experienced the Out-of-Africa bottleneck. Does this bottleneck affect the way we characterise complex traits? We demonstrate using the 1000 Genomes dataset and hypothetical complex traits that genetic drift can strongly affect the joint distribution of effect size and SNP frequency, and that the bias can be positive or negative depending on subtle details. Characterisations that rely on this distribution therefore conflate genetic drift and selection. We provide a model to identify the underlying selection parameter in the presence of drift, and demonstrate that a simple sensitivity analysis may be enough to validate existing characterisations. We conclude that biobanks characterising more worldwide diversity would benefit studies of complex traits.

genetics↗

bioRxiv2020

Genetic Fine-mapping with Dense Linkage Disequilibrium Blocks: genetics of nicotine dependence

Fine-mapping is an analytical step to perform causal prioritization of the polymorphic variants on a trait-associated genomic region observed from genome-wide association studies (GWAS). The prioritization of causal variants can be challenging due to the linkage disequilibrium (LD) patterns among hundreds to thousands of polymorphisms associated with a trait. We propose a novel{ell} 0 graph norm shrinkage algorithm to select causal variants from dense LD blocks consisting of highly correlated SNPs that may not be proximal or contiguous. We extract dense LD blocks and perform regression shrinkage to calculate a prioritization score to select a parsimonious set of causal variants. Our approach is computationally efficient and allows performing fine-mapping on thousands of polymorphisms. We demonstrate its application using a large UK Biobank (UKBB) sample related to nicotine addiction. Our results suggest that polymorphic variances in both neighboring and distant variants can be consolidated into dense blocks of highly correlated loci. Simulations were used to evaluate and compare the performance of our method and existing fine-mapping algorithms. The results demonstrated that our method outperformed comparable fine-mapping methods with increased sensitivity and reduced false-positive error rate regarding causal variant selection. The application of this method to smoking severity trait in UKBB sample replicated previously reported loci and suggested the causal prioritization of genetic effects on nicotine dependency. Author summaryDisentangling the complex linkage disequilibrium (LD) pattern and selecting the underlying causal variants have been a long-term challenge for genetic fine-mapping. We find that the LD pattern within GWAS loci is intrinsically organized in delicate graph topological structures, which can be effectively learned by our novel{ell} 0 graph norm shrinkage algorithm. The extracted LD graph structure is critical for causal variant selection. Moreover, our method is less constrained by the width of GWAS loci and thus can fine-map a massive number of correlated SNPs.

genetics↗

bioRxiv2021

Genetic behavior analysis for phytochemical traits in coriander: Heterosis, inbreeding depression and genetic effects

Increasing fruit yield, fatty acids and essential oils content in coriander are the main objectives. Reaching them need to understand the nature of gene action and quantifying the heterosis and inbreeding depression. Six genetically diverse parents, their 15 F1 one-way hybrids and 15 F2 populations were evaluated under different levels of water treatments. Beside the water treatment and genotype effects, the genetic effects of general (GCA) and specific (SCA) combining ability and their interactions with water treatment were significant for all traits. Water deficit stress decreased all traits in both F1 and F2 generations except for essential oil content which were significantly increased due to water deficit stress. Under water deficit stress, a non-additive gene action nature was predominant in F1 generation while an additive gene action nature was more important in F2 generation for all the traits except fruit yield under severe water deficit stress. There was a positive high heterosis for the traits examined in some hybrids. Also, in F2 generation even after inbreeding depression, some promising populations displayed appropriate mean performance. These show that the parents used for crossing had rich gene pool for studied traits. Therefore, selection between the individuals of relevant F2 populations could be led to develop high yielding hybrids or transgressed lines.

genetics↗

bioRxiv2022

Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission

BackgroundInfectious disease spread in populations is controlled by individuals susceptibility (propensity to acquire infection), infectivity (propensity to pass on infection to others) and recoverability (propensity to recover/die). Estimating the effects of genetic risk factors on these host epidemiological traits can help reduce disease spread through genetic control strategies. However, the effects of previously identified disease resistance SNPs on these epidemiological traits are usually unknown. Recent advances in computational statistics make it now possible to estimate the effects of single nucleotide polymorphisms (SNPs) on these traits from longitudinal epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known how to optimally design disease transmission experiments or field studies to maximise the precision at which pleiotropic SNP effects estimates for susceptibility, infectivity and recoverability can be estimated. ResultsWe develop and validate analytical expressions for the precision of SNP effects estimates on the three host traits assuming a disease transmission experiment with one or more non-interacting contact groups. Maximising these leads to three distinct experimental designs, each specifying a different set of ideal SNP genotype compositions across groups: a) appropriate for a single contact-group, b) a multi-group design termed "pure", and c) a multi-group design termed "mixed", where pure and mixed refer to contact groups consisting of individuals with the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than infectivity. Data from multiple groups were found more informative about infectivity effects than from a single group containing the same number of individuals. Whilst the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferable because it uses information from naturally occurring infections rather than those artificially induced. The same optimal design principles apply to estimating other categorical fixed effects, such as vaccinations status, helping to more effectively quantify their epidemiological impact. An online software tool SIRE-PC has been developed which calculates the precision of estimated substitution and dominance effects of a single SNP (or vaccine status) associated with all three traits depending on experimental design parameters. ConclusionsThe developed methodology and software tool can be used to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables underlying host susceptibility, infectivity and recoverability.

genetics↗

bioRxiv2023

Leveraging genetic correlations and multiple populations to improve genetic risk prediction for non-European populations

Genetic prediction accuracy for non-European populations is hindered by the limited sample size of Genome-wide association studies (GWAS) data in these populations. Additionally, it is challenging to tune model parameters with a small tuning dataset for methods that require tuning data, which is often the case for non-European samples. To address these challenges, we propose JointPRS, a novel, data-adaptive framework that simultaneously models multiple populations using GWAS summary statistics. JointPRS incorporates genetic correlation structures into the prediction framework, enabling accurate performance even without individual-level tuning data. Additionally, it uniquely employs a data-adaptive approach, providing a robust solution when only a small tuning dataset is available. Through extensive simulations and real data applications to 22 quantitative traits and four binary traits in five continental populations (European (EUR); East Asian (EAS); African (AFR); South Asian (SAS); and Admixed American (AMR)) evaluated using the UK Biobank (UKBB) and All of Us (AoU), we demonstrate that JointPRS outperforms six other state-of-art methods across three different data scenarios (no tuning data, tuning and testing data from the same cohort, and tuning and testing data from different cohorts) for most traits in non-European populations, while maintaining model simplicity and computational efficiency.

genetics↗

bioRxiv2024

Computer prediction and genetic analysis identifies retinoic acid modulation as a driver of conserved longevity pathways in genetically-diverse Caenorhabditis nematodes

Aging is a pan-metazoan process with significant consequences for human health and society--discovery of new compounds that ameliorate the negative health impacts of aging promise to be of tremendous benefit across a number of age-based comorbidities. One method to prioritize a testable subset of the nearly infinite universe of potential compounds is to use computational prediction of their likely anti-aging capacity. Here we present a survey of longevity effects for 16 compounds suggested by a previously published computational prediction set, capitalizing upon the comprehensive, multi-species approach utilized by the Caenorhabditis Intervention Testing Program (CITP). While eleven compounds (aldosterone, arecoline, bortezomib, dasatinib, decitabine, dexamethasone, erlotinib, everolimus, gefitinib, temsirolimus, and thalidomide) either had no effect on median lifespan or were toxic, five compounds (all-trans retinoic acid, berberine, fisetin, propranolol, and ritonavir) extended lifespan in Caenorhabditis elegans. These computer predictions yield a remarkable positive hit rate of 30%. Deeper genetic characterization of the longevity effects of one of the most efficacious compounds, the endogenous signaling ligand all-trans retinoic acid (atRA, designated tretinoin in medical products), which is widely prescribed for treatment of acne, skin photoaging and acute promyelocytic leukemia, demonstrated a requirement for the regulatory kinases AKT-1 and AKT-2. While the canonical Akt-target FOXO/DAF-16 was largely dispensable, other conserved Akt-targets (Nrf2/SKN-1 and HSF1/HSF-1), as well as the conserved catalytic subunit of AMPK AAK-2, were all necessary for longevity extension by atRA. Evolutionary conservation of retinoic acid as a signaling ligand and the structure of the downstream effector network of retinoic acid combine to suggest that the all-trans retinoic acid pathway is an ancient metabolic regulatory system that can modulate lifespan. Our results highlight the potential of combining computational prediction of longevity interventions with the power of nematode functional genetics and underscore that the manipulation of a conserved metabolic regulatory circuit by co-opting endogenous signaling molecules is a powerful approach for discovering aging interventions.

genetics↗

bioRxiv2020

Application of DNA barcodes and spatial analysis in conservation genetics and modeling of Iranian Salicornia genetic resources

Iran is one of the origins of some Salicornia species. Nevertheless, so far, comprehensive research has not been conducted on genetic potential, distribution, selection of populations, and the economic utilization of Salicornia in Iran. In the current study, Salicornia was collected based on the previous research locations available on 26 different geographical locations of provinces in Iran. Subsequently, an accurate model was provided for identifying of Salicornia species biodiversity by performing spatial analysis and modeling of distributed areas. The results provided valuable information on the diversity of specific geographical regions, conservation status of existing species, prioritization of conservation areas, and selection of areas for Agro-Ecological, leading to the development of industrial agriculture. Further, we validated genes in the field of DNA barcoding in Salicornia plants using matK, rbcL, trnH-psbA, ycf and ITS2 identifying species groups. Together, integrating our results will provide useful information for the management and utilization of Salicornia genetic resources in Iran.

ecology↗

bioRxiv2021

Cas9-Assisted Biological Containment of a Genetically Engineered Human Commensal Bacterium and Genetic Elements

Sophisticated gene circuits built by synthetic biology can enable bacteria to sense their environment and respond predictably. Biosensing bacteria can potentially probe the human gut microbiome to prevent, diagnose, or treat disease. To provide robust biocontainment for engineered bacteria, we devised a Cas9-assisted auxotrophic biocontainment system combining thymidine auxotrophy, an Engineered Riboregulator (ER) for controlled gene expression, and a CRISPR Device (CD). The CD prevents the engineered bacteria from acquiring thyA via horizontal gene transfer, which would disrupt the biocontainment system, and inhibits the spread of genetic elements by killing bacteria harboring the gene cassette. This system tunably controlled gene expression in the human gut commensal bacterium Bacteroides thetaiotaomicron, prevented escape from thymidine auxotrophy, and blocked transgene dissemination for at least 10 days. These capabilities were validated in vitro and in vivo. This biocontainment system exemplifies a powerful strategy for bringing genetically engineered microorganisms safely into biomedicine.

synthetic biology↗

bioRxiv2022

Multi-ancestry genome-wide analysis identifies common genetic variants for self-reported sleep duration and shared genetic effects

Both short and long sleep duration are associated with increased risk of chronic diseases, but the genetic determinants of sleep duration are largely unknown outside of European populations. Here we report transferability of a polygenic score of 78 European ancestry sleep duration SNPs to an African (n=7,288; p=0.003), a South Asian (n=7,485; p=0.025), and a Japanese (n=13,618; p=6x10-4) cohort, but not to a cohort of Hispanic/Latino (n- XXX; p=0.71) participants. Furthermore, in a pan-ancestry (N = 483,235) meta-analysis of genome-wide association studies (GWAS) for habitual sleep duration, 5 novel and 68 known loci are associated with genome-wide significance. For the novel loci, sleep duration signals colocalize with expression-QTLs for PRR12 and COG5 in brain tissues, and pleiotropic associations are observed with cardiovascular and neuropsychiatric traits. Overall, our results suggest that the genetic basis of sleep duration is at least partially shared across diverse ancestry groups.

genomics↗

bioRxiv2022

Combining two Genetic Sexing Strains allows sorting of non-transgenic males for Aedes genetic control

Chemical control of disease vectoring mosquitoes Aedes albopictus and Aedes aegypti is costly, unsustainable, and increasingly ineffective due to the spread of insecticide resistance. The Sterile Insect Technique is a valuable alternative but is limited by the slow, error-prone, and wasteful sex-separation requirement. Here, we present four Genetic Sexing Strains (two for each Aedes species) based on fluorescence markers linked to the m and M sex loci, allowing for the isolation of transgenic males. Furthermore, we demonstrate how combining these sexing strains enables the production of non-transgenic males. Scaling-up would allow the sorting of 100,000 first instar male larvae in under 1.5 hours with an estimated 0.01-0.1% female contamination. Cost-efficiency analyses revealed that using these strains could result in important savings while setting up and running a mass-rearing facility. Altogether, these Genetic Sexing Strains should enable a major upscaling in control programmes against these important vectors. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/483912v2_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@761545org.highwire.dtl.DTLVardef@6e80f2org.highwire.dtl.DTLVardef@d3911dorg.highwire.dtl.DTLVardef@1dc19ce_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗