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bioRxiv2023

Host genetic variation guides hepacivirus clearance, chronicity, and liver fibrosis in mice

Background & AimsHuman genetic variation is thought to guide the outcome of hepatitis C virus (HCV) infection but model systems within which to dissect these host genetic mechanisms are limited. Norway rat hepacivirus (NrHV), closely related to HCV, causes chronic liver infection in rats but causes acute self-limiting hepatitis in typical strains of laboratory mice, which resolves in two weeks. The Collaborative Cross (CC) is a robust mouse genetics resource comprised of a panel of recombinant inbred strains, which model the complexity of the human genome and provide a system within which to understand diseases driven by complex allelic variation. Approach & ResultsWe infected a panel of CC strains with NrHV and identified several that failed to clear virus after 4 weeks. Strains displayed an array of virologic phenotypes ranging from delayed clearance (CC046) to chronicity (CC071, CC080) with viremia for at least 10 months. Body weight loss, hepatocyte infection frequency, viral evolution, T-cell recruitment to the liver, liver inflammation and the capacity to develop liver fibrosis varied among infected CC strains. ConclusionsThese models recapitulate many aspects of HCV infection in humans and demonstrate that host genetic variation affects a multitude of virus and host phenotypes. These models can be used to better understand the molecular mechanisms that drive hepacivirus clearance and chronicity, the virus and host interactions that promote chronic disease manifestations like liver fibrosis, therapeutic and vaccine performance, and how these factors are affected by host genetic variation.

microbiology↗

bioRxiv2023

Recombulator-X: a fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Background and ObjectiveGenetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. Recombination rates vary across the human genome and cannot be automatically derived from linkage physical maps. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, the only existing implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns, we developed Recombulator-X, a new open-source Python tool. MethodsThe most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm, coupled with JIT compilation to further increase performance. We also extended the statistical framework from STR to any polymorphic marker. ResultsCompared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. ConclusionsIn the genetic forensic community, state-of-the-art estimation methods for X chromosome recombination rates have seen limited usage due to the technical hurdles posed by previous implementations. Recombulator-X makes the process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices. Moreover, it extends the estimation framework to larger panels of genetic markers (not only STRs), allowing analyses of sequencing-based data.

bioinformatics↗

bioRxiv2023

Genetic basis of expression and splicing underlying spike architecture in wheat (Triticum aestivum L.)

IntroductionWheat is one of the most important staple crops worldwide, and an important source of human protein and mineral element intake. Continuously increasing stable production of wheat is critical for global food security under the challenge of population growth and limited resource input. ObjectiveSpike architecture determines the potential grain yield of wheat. However, the mechanisms of transcriptional regulation of spike architecture in wheat remain largely unknown, limiting further genetic improvement of wheat yield. In this study we explored the genetic basis of spike architecture in wheat. MethodsPopulation RNA-seq methods were used to identify the eQTLs and sQTLs associated with spike architecture and applied this to dissection of the genetic basis of gene expression and splicing controlling these complex yield-related traits. ResultsIn total, 4,143 expression quantitative trait loci (eQTLs) and 12,933 splice QTLs (sQTLs) were identified in wheat based on 178 RNA-seq samples, revealing 774 cis-eQTLs and 321 cis-sQTLs for 86 eGenes and 73 sGenes, respectively. Integration of eQTLs and sQTLs with genome-wide association study (GWAS) identified dozens of additional novel candidate genes that may contribute to spike-related traits. Gene network analysis showed that eQTLs and sQTLs were widely involved in the co-expression modules that regulate wheat spike architecture. Notably, the eQTL locus AX-108754757 regulated the expression of 5 eGenes that negatively controled grain number per spike. AX-111592099 regulated both the splicing and expression of TraesCS7B02G442100, encoding an E3 ubiquitin ligase, and playing a central role in regulating spike length. ConclusionThis study provides new insights into the genetic basis of spike architecture. This improved understanding of spike-related traits in wheat will contribute to more rapid genetic improvement.

plant biology↗

bioRxiv2023

Influence of oceanography and geographic distance on genetic structure: how varying the sampled domain influences conclusions in Laminaria digitata

Understanding the environmental processes shaping connectivity can greatly improve management and conservation actions which are essential in the trailing edge of species distributions. In this study, we used a dataset built from 32 populations situated in the southern limit of the kelp species Laminaria digitata. By extracting data from 11 microsatellite markers, our aim was to (1) refine the analyses of population structure, (2) compare connectivity patterns and genetic diversity between island and mainland populations and (3) evaluate the influence of sampling year, hydrodynamic processes, habitat discontinuity, spatial distance and sea surface temperature on the genetic structure using a distance-based redundancy analysis (db-RDA). Analyses of population structure enabled to identify well connected populations associated to high genetic diversity, and others which appeared genetically isolated from neighboring populations and showing signs of genetic erosion verifying contrasting ecological (and demographic) status in Brittany and the English Channel. By performing db-RDA analyses on various sampling sizes, geographic distance appeared as the dominant factor influencing connectivity between populations separated by great distances, while hydrodynamic processes were the main factor at smaller scale. Finally, Lagrangian simulations enabled to study the directionality of gene flow which has implications on source-sink dynamics. Overall, our results have important significance in regard to the management of kelp populations facing pressures both from global warming and their exploitation for commercial use.

evolutionary biology↗

bioRxiv2023

Natural genetic variation underlying the negative effect of elevated CO2 on ionome composition in Arabidopsis thaliana

The elevation of atmospheric CO2 leads to a decline in the plant mineral content, which might pose a significant threat to food security in the coming decades. To date, very few genes have been identified as having a role in the negative effect of elevated CO2 on plant mineral composition. Yet, several studies have shown a certain degree of diversity in the ionomes response to elevated CO2, associated with genotypic variation. This suggests the existence of genetic factors controlling the effect of CO2 on ionome composition. However, no large-scale studies have been carried out to date to explore the genetic diversity of the ionome responses to elevated CO2. Here, we used six hundred Arabidopsis thaliana accessions, representing geographical distributions ranging from worldwide to regional and local environments, to analyze the natural genetic variation underlying the negative effect of elevated CO2 on the ionome composition in plants. We show that the growth under elevated CO2 leads to a global and important decrease of the ionome content whatever the geographic distribution of the population. We also observed a high range of genetic diversity in the response of the ionome composition to elevated CO2, and we identified sub-populations, showing effects on their ionome ranging from the most pronounced to resilience or even to a benefit in response to elevated CO2. Using genome-wide association mapping on the response of each mineral element to elevated CO2 or on integrative traits, we identified a large set of QTLs and genes associated with the ionome response to elevated CO2. Finally, we demonstrate that the function of one of these genes is associated to the negative effect of elevated CO2 on the plant mineral composition. This resource will contribute to understand the genetic mechanisms underlying the negative effect of elevated CO2 on plant mineral nutrition, and could help towards the development of crops adapted to a high-CO2 world.

plant biology↗

bioRxiv2023

Using a P. falciparum genetic cross to dissect the relative contributions of pfcrt and plasmepsin II/III to piperaquine response-related traits

Piperaquine (PPQ) is widely used in combination with dihydroartemisinin (DHA) as a first-line treatment against malaria parasites. Multiple genetic drivers of PPQ resistance have been reported, including mutations in the Plasmodium falciparum chloroquine resistance transporter (pfcrt) and increased copies of plasmepsin II/III (pm2/3). We generated a cross between a Cambodia-derived multi-drug resistant KEL1/PLA1 lineage isolate (KH004) and a drug susceptible parasite isolated in Malawi (Mal31). Mal31 harbors a wild-type (3D7-like) pfcrt allele and a single copy of pm2/3, while KH004 has a chloroquine-resistant (Dd2-like) pfcrt allele with an additional G367C substitution and four copies of pm2/3. We recovered 104 unique recombinant progeny and examined a targeted set of progeny representing all possible combinations of variants at pfcrt and pm2/3 for detailed analysis of competitive fitness and a range of PPQ susceptibility phenotypes, including PPQ survival assay (PSA), area under the dose-response curve (AUC), and a limited point IC50 (LP-IC50). We find that inheritance of the KH004 pfcrt allele is required for PPQ resistance, whereas copy number variation in pm2/3 further enhances resistance but does not confer resistance in the absence of PPQ-R-associated mutations in pfcrt. Deeper investigation of genotype-phenotype relationships demonstrates that progeny clones from experimental crosses can be used to understand the relative contributions of pfcrt, pm2/3, and parasite genetic background, to a range of PPQ-related traits and confirm the critical role of the PfCRT G367C substitution in PPQ resistance. ImportanceResistance to PPQ used in combination with DHA has emerged in Cambodia and threatens to spread to other malaria-endemic regions. Understanding the causal mutations of drug resistance and their impact on parasite fitness is critical for surveillance and intervention, and can also reveal new avenues to limiting the evolution and spread of drug resistance. An experimental genetic cross is a powerful tool for pinpointing the genetic determinants of key drug resistance and fitness phenotypes and have the distinct advantage of assaying the effects of naturally evolved genetic variation. Our study was significantly strengthened because the full a range of copies of KH004 pm2/3 was inherited among the progeny clones, allowing us to directly test the role of pm2/3 copy number on resistance-related phenotypes in the context of a unique pfcrt allele. Our multi-gene model suggests an important role for both loci in the evolution of this ACT resistant parasite lineage.

genomics↗

bioRxiv2023

Evaluating the ileal and cecal microbiota composition of a 1940 heritage genetic line and a 2016 commercial line of white leghorns fed representative diets from 1940 and 2016

This study was conducted to identify and evaluate the differences between the microbiome composition of the ileum and ceca of 1940 and 2016 genetic strains of white leghorns fed representative contemporary diets from those times. Ileal and cecal samples were aseptically collected from both genetic lines at 69 weeks of age. The genomic DNA of the ileal and cecal contents were extracted and the V4 region of the 16S rDNA was sequenced on an Illumina Miseq. Microbiota data were filtered and aligned using the QIIME2 2020.2 pipeline. Alpha and beta diversity metrics were generated and the Analysis of Composition of Microbiomes (ANCOM) was utilized to determine significantly different taxa. Data were considered significant at P [≤] 0.05 for main effects and Q [≤] 0.05 for pairwise differences. Alpha diversity of the ileum and ceca were significantly different (P = 0.001; Q = 0.001; however, no differences between genetic lineage were observed (P > 0.05; Q > 0.05). The beta diversity between the ileum and ceca, as well as between the genetic lines (1940 vs. 2016) were significantly different from one another (P = 0.001; Q = 0.001). Using ANCOM, Proteobacteria and Actinobacteriota were significantly different than other phyla (P 0.05) with a higher relative abundance of Proteobacteria being observed among treatment groups 2 and 3, while Actinobacteriota had higher relative abundance in treatment groups 1 and 4. Among the significantly different genera in the ileum, Pseudomonas, Rhizobiaceae, Leuconostoc, and Aeriscardovia were different (P 0.05) with treatment groups 1 and 4 having a higher relative abundance of Aeriscardovia, while treatment groups 2 and 3 had higher relative abundance in both Pseudomonas and Leuconostoc. In the ceca, Proteobacteria, Firmicutes, Actinobacteriota, and Euryarchaeota were significantly different phyla (P 0.05) with Firmicutes having the highest relative abundance across all treatment groups. Among the significantly different genera (Pseudomonas, Leuconostoc, Alloprevotella, and Aeriscardovia), Alloprevotella had the highest relative abundance across all treatment groups 1 and 2, while Leuconostoc and Pseudomonas had the highest relative abundance in treatment group 4. Results from this study suggest that genetic makeup in conjunction with the nutritional composition of laying hens influences the cecal and ileal microbiota of corresponding hens.

microbiology↗

bioRxiv2023

Machine learning and phylogenetic models identify predictors of genetic variation in Neotropical amphibians

AimIntraspecific genetic variation is key for adaptation and survival in changing environments and is known to be influenced by many factors, including population size, migration, and life history traits. We investigated genetic variation within Neotropical amphibian species to provide insights into how natural history traits, phylogeny, climatic, and geographic characteristics influence intraspecific diversity. LocationNeotropics. TaxonAmphibians. MethodsWe assembled datasets using open-access databases for natural history traits, genetic sequences, phylogenetic trees, climatic, and geographic data. For each species, we calculated overall nucleotide diversity ({pi}) and tested for isolation by distance (IBD) and isolation by environment (IBE). We then identified predictors of {pi}, IBD, and IBE using Random Forest (RF) regression or RF classification. To incorporate phylogenetic relationships, we fitted phylogenetic generalized linear mixed models (PGLMMs) to predict {pi}, IBD, and IBE. ResultsWe compiled 4,052 mitochondrial DNA sequences from 256 amphibian species (230 frogs and 26 salamanders), georeferencing 2,477 sequences from 176 species that were not linked to occurrence data. RF regressions and PGLMMs were congruent in identifying range size and precipitation ({sigma}) as the most important predictors of {pi}. RF classification and PGLMMs identified minimum elevation as an important predictor of IBD, and maximum latitude and precipitation ({sigma}) as the best predictors of IBE. Main conclusionsThis study unified machine learning and phylogenetic methods and identified predictors of genetic variation in Neotropical amphibians. This approach was valuable to determine which predictors were congruent between methods. We found that species with small ranges or living in zones with less variable precipitation tended to have low genetic diversity. We also showed that Western Mesoamerica, Andes, and Atlantic Forest biogeographic units harbor high diversity across many species that should be prioritized for protection. These results could play a key role in the development of conservation strategies for Neotropical amphibians.

evolutionary biology↗

bioRxiv2023

1LocusSim a mobile-friendly simulator for teaching population genetics

SummaryBiology students often struggle with the fundamental concepts of evolutionary genetics, including genetic drift, mutation, and selection. To address this problem, 1LocusSim was developed to simulate the interaction of different factors, such as population size, mutation, selection, and dominance, to study their effect on allelic frequency during evolution. With 1LocusSim, students can compare theoretical results with simulation outputs and solve and analyze different problems of population genetics. The 1LocusSim web has a responsive design which means that it has been specifically designed to be used on smartphones. To demonstrate its use, I review the classical overdominance model of population genetics and highlight a characteristic that is often not explicitly stated. Specifically, it is emphasized that the equilibrium of the model does not depend on the homozygous selection coefficients but rather on the ratio of the selection coefficients. This is already clear from the classical formula but maybe not so much for students. Also it implies that the equilibrium can be expressed solely in terms of the dominance coefficient h. To verify these theoretical prediction, I utilize the simulator and calculate the equilibrium for the well-known case of sickle cell anaemia. Simulating basic population genetic models on smartphones can be a powerful learning aid that fosters critical skills and opens up new opportunities for Biology students. By utilizing this tool, students can learn at their own pace and convenience, anywhere and anytime. Software and data availability1LocusSim if freely available at https://1LocusSim-biosdev.pythonanywhere.com/. Website implemented under the Bottle micro web-framework for Python, with all major browsers supported. Contactacraaj@uvigo.es Supplementary informationThe manual and examples are available from the help button of the program or directly at https://acraaj.webs.uvigo.es/1LocusSim/1LocusSim_EN.html. Both the program and the manual pages are in English and Spanish.

scientific communication and education↗

bioRxiv2023

The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change

Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 years, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets. Significance statementThe relative contribution of random genetic drift and natural selection to the change in allele frequencies through time is a long standing question in Evolutionary Biology. We show through theory and simulation how genomic time series - such as ancient DNA datasets - can be used to decompose the genome-wide contributions of selection, gene flow, and genetic drift to allele frequency change. We apply these methods to two time time series from ancient Europeans and show that gene flow accounts for most allele frequency change over the last few thousand years, with genetic drift and not selection making up much of the rest of the contribution to genome-wide evolutionary change.

evolutionary biology↗

bioRxiv2023

Urban colonization of invasive species on islands: Mus musculus and Rattus rattus genetics of establishment on Cozumel island

Humans and wildlife experience complex interactions in urban ecosystems, favoring the presence of commensal species, among which invasive species are particularly successful. Rodents are the main vertebrate group introduced to oceanic islands, where the invasion process and dispersal patterns strongly influence their evolutionary and genetic patterns. We evaluated the house mouse Mus musculus and the black rat Rattus rattus on Cozumel island, Mexico. We assessed genetic diversity and structure, connectivity, gene flow, relatedness and bottleneck signals based on microsatellite loci. Our findings show that the constant introduction of individuals of different origins to the island promotes high allelic diversity and the effective establishment of migrants. We identified a clear genetic structure and low connectivity for the two species, tightly linked with anthropogenic and urban features. Moreover, we found M. musculus has a particularly restricted distribution within the city of San Miguel Cozumel, whilst its genetic structure is associated with the historical human population growth pulses accompanying the urbanization of the city. At the fine-scale genetic level, the main urban drivers of connectivity of the house mouse were both the impervious land surfaces, i.e. the urban landscape, and the informal commerce across the city (a proxy of resources availability). Chances of a secondary invasion to natural environments have been relatively low, which is crucial for the endemic taxa of the island. Nonetheless, improving urban planning to regulate future expansions of San Miguel Cozumel is of the outmost importance in order to prevent these invasive species to disperse further.

evolutionary biology↗

bioRxiv2023

Genetic consequences of improved river connectivity in brown trout (Salmo trutta, L.)

Fragmentation of watercourses poses a significant threat to biodiversity, particularly for migratory fish species. Mitigation measures such as fishways, have been increasingly implemented to restore river connectivity and support fish migration. The effects of such restoration efforts are typically tested using telemetry and fisheries methods, which do not fully capture the broader population movements that may have important consequences for population viability. We performed a before-and-after control-impact (BACI) study using genetic tools (SNPs) to investigate the effect of a newly implemented fishway, aiming to enhance upstream spawning migration of brown trout (Salmo trutta, Linnaeus) in a reservoir with two headwater tributaries fragmented by man-made weirs. Another reservoir with two barrier-free tributaries was also analysed as a control. Our results showed that the isolated brown trout population was spawning in the reservoir before the installation of the fishway, and we found genetic structuring and differentiation between fragmented headwater tributaries before the fishway construction, but not in the control reservoir. Unexpectedly, after the fishway construction we observed signals consistent with increased genetic differentiation between populations of newly recruited juvenile fish in the reservoir tributary and fish in the reservoir. We propose this was caused by newly enabled philopatric behaviour of brown trout to their natal spawning tributary. In contrast, we did not find any genetic changes in the tributary without a fishway or in the barrier-free reservoir system. Given the scarcity of similar studies, we advocate for an increased use of genetic analyses in BACI studies to monitor and evaluate the effect of efforts to restore habitat connectivity and inform future management strategies.

evolutionary biology↗

bioRxiv2023

New machine learning method identifies subtle fine-scale genetic stratification in diverse populations

Fine-scale genetic structure impacts genetic risk predictions and furthers the understanding of the demography of populations. Current approaches (e.g., PCA, DAPC, t-SNE, and UMAP) either produce coarse and ambiguous cluster divisions or fail to preserve the correct genetic distance between populations. We proposed a new machine learning algorithm named ALFDA. ALFDA considers both local and global genetic affinity between individuals and also preserves the multimodal structure within populations. ALFDA outperformed the existing approaches in identifying fine-scale genetic structure and in retaining population geogenetic distance, providing a valuable tool for geographic ancestry inference as well as correction for spatial stratification in population health studies.

genomics↗

bioRxiv2023

Genotype x Environment interaction and the evolution of sexual dimorphism: adult nutritional environment mediates selection and expression of sex-specific genetic variance in D. melanogaster

Sexual conflict plays a key role in the dynamics of adaptive evolution in sexually reproducing populations, and theory suggests an important role for variance in resource acquisition in generating or masking sexual conflict over fitness and life history traits. Here, I used a quantitative genetic genotype x environment experiment in Drosophila melanogaster, to test the theoretical prediction that variance in resource acquisition mediates variation in sex-specific component fitness. Holding larval conditions constant, I found that adult nutritional environments characterized by high protein content resulted in reduced survival of both sexes compared to an environment of lower protein content, and lower male reproductive success. Despite reduced mean fitness of both sexes in high protein environments, I found a sex*treatment interaction for the relationship between resource acquisition and fitness; estimates of the adaptive landscape indicate males were furthest from their optimum resource acquisition level in high protein environments, and females were furthest in low protein environments. Expression of genetic variance in resource acquisition and survival was highest for each sex in the environment it was best adapted to, although the treatment effects on expression of genetic variance eroded in the path from resource acquisition to total fitness. Cross-sex genetic correlations were strongly positive for resource acquisition, survival, and total fitness, and negative for mating success, although estimation error was high for all. These results demonstrate that environmental effects on resource acquisition can have predictable consequences for the expression of sex-specific genetic variance, but also that these effects of resource acquisition can erode through the life history.

evolutionary biology↗

bioRxiv2023

Genetically mediated associations between chronotype and neuroimaging phenotypes in the UK Biobank: a Mendelian randomisation study

Chronotype impacts numerous physiological and disease traits, from metabolic syndrome to schizophrenia. The suprachiasmatic nucleus (SCN) maintains transcriptional-translational feedback loop (TTFL) which acts as a central chronobiological pacemaker, regulating 24-hour cycles throughout the human body. However, each tissue maintains its own peripheral clock, and both endogenous hormones and neurotransmitters and exogenous environmental cues regulate the SCNs central clock. The extent to which brain regions outside the SCN influence the core TTFL is unknown. Here, we investigated how genetic variability affecting brain regions outside the SCN may indirectly influence chronotype, using Mendelian randomization and causal inference. We performed genome wide association studies (GWAS) based on image derived phenotypes (IDPs) from neuroimaging data (grey matter volume, thickness and surface area, microstructural white matter measures; 42,062 participants), and additionally for sleep duration and morning/evening chronotype (361,739 participants). Significant, single nucleotide polymorphisms (SNPs) associating with each phenotype were entered into 2-sample Mendelian randomization performed using inverse-variance weighted methods (exposure versus outcome): 1) chronotype versus each IDP, 2) sleep versus each IDP and 3) each IDP versus chronotype. Subsequently, we investigated genes where significant instrumental SNPs were located for circadian periodic cycling, interaction with TTFL genes in common biological pathways (genetic, physical, or functional interaction), and enrichment of traits from UK Biobank and GWAS Catalogs. We found three associations with chronotype (morning/evening diurnal preference) outside the SCN based on genetically predicted (FAM76B, DENND1A, CDH11) regional differences in brain volume. Specifically, genetically predicted lower inferior temporal gyrus volume linked to morning phenotype, while lower volume of the superior parietal lobule and angular gyrus linked to evening preference. In addition, evening chronotype exposure influenced superior temporal gyrus volume, and both increased sleep duration and evening chronotype influenced thalamic volume. We conclude that genetically mediated associations between chronotype and brain regions outside SCN exist suggesting novel zeitgeber mechanisms.

neuroscience↗

bioRxiv2023

A General Approach to Adjusting Genetic Studies for Assortative Mating

The effects of assortative mating (AM) on estimates from genetic studies has been receiving increasing attention in recent years. We extend existing AM theory to more general models of sorting and conclude that correct theory-based AM adjustments require knowledge of complicated, unknown historical sorting patterns. We propose a simple, general-purpose approach using polygenic indexes (PGIs). Our approach can estimate the fraction of genetic variance and genetic correlation that is driven by AM. Our approach is less effective when applied to Mendelian randomization (MR) studies for two reasons: AM can induce a form of selection bias in MR studies that remains after our adjustment; and, in the MR context, the adjustment is particularly sensitive to PGI estimation error. Using data from the UK Biobank, we find that AM inflates genetic correlation estimates between health traits and education by 14% on average. Our results suggest caution in interpreting genetic correlations or MR estimates for traits subject to AM.

genomics↗

bioRxiv2023

High standing diversity masks extreme genetic erosion in a declining snake.

Average heterozygosity is frequently used as a proxy for genetic health, and to compare genetic diversity between species and populations. However, this measurement could be misleading if the distribution of heterozygosity across the genome is highly skewed. We investigated this pitfall in methodology using whole-genome sequencing of the adder (Vipera berus), a species experiencing dramatic declines in the UK. We find that mean heterozygosity in adders is notably high, exceeding that of other vertebrates typically regarded as genetically diverse. Their genome-wide distribution of heterozygosity, however, approximates a negative exponential distribution, with most genome regions showing extremely low heterozygosity. Modelling approaches show that this pattern is likely to have resulted from a recent, severe bottleneck and fragmentation most likely caused by anthropogenic activity in a previously large, interconnected adder population. Our results highlight that high standing diversity may mask severe genetic erosion when declines are recent and rapid. In such situations, whole-genome sequencing may provide the best option for genetic risk assessment and targeted conservation actions.

genomics↗

bioRxiv2023

A genetic circuit on a single DNA molecule as autonomous dissipative nanodevice

Realizing genetic circuits on single DNA molecules as self-encoded dissipative nanodevices is a major step toward miniaturization of autonomous biological systems. A circuit operating on a single DNA implies that genetically encoded proteins localize during coupled transcriptiontranslation to DNA, but a single-molecule measurement demonstrating this has remained a challenge. Here, we used a genetically encoded fluorescent reporter system with improved spatiotemporal resolution and observed the synthesis of individual proteins tethered to a DNA molecule by transient complexes of RNA polymerase, messenger RNA, and ribosome. Against expectations in dilute cell-free conditions where equilibrium considerations favor dispersion, these nascent proteins linger long enough to regulate cascaded reactions on the same DNA. We rationally designed a pulsatile genetic circuit by encoding an activator and repressor in feedback on the same DNA molecule. Driven by the local synthesis of only several proteins per hour and gene, the circuit dynamics exhibited enhanced variability between individual DNA molecules, and fluctuations with a broad power spectrum. Our results demonstrate that coexpressional localization, as a nonequilibrium process, facilitates single-DNA genetic circuits as dissipative nanodevices, with implications for nanobiotechnology applications and artificial cell design.

synthetic biology↗