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bioRxiv2022

A 3D genome atlas of genetic variants and their pathological effects

The spatial architecture of the genome can be categorized into distinct layers. Each layer plays a critical role in transcriptional regulation and/or genomic integrity. Alterations at any level of the 3D genome can lead to an unwanted cascade of molecular events, which may ultimately drive the manifestation of disease. However, a comprehensive atlas of the mutations and structural genetic defects that affect genome organization has yet to be compiled. Moreover, we lack a centralized resource for interpretating the pathological effects of such genetic mutations. Therefore, we curated from the literature all the pathological alterations from the chromosome level on down to single nucleotide polymorphisms (SNPs) in order to investigate these diverse genetic mutations. Using a two-phase scoring algorithm, 3DFunc, we scored the transcriptomic causality of all variants in the context of 3D genome architecture from 20 cancer and 15 normal tissues. Further, 3DFunc can identify pathological variant-gene pairs in non-oncological diseases. Finally, we constructed a web-based database, 3DGeOD (https://www.csuligroup.com/3DGeOD/home), to provide all the curated variants, genomic disruptions, as well as the scoring results derived from 3DFunc. In summary, our study constructed a 3D genome atlas of genetic variants and will serve as a valuable resource for mining the putative pathological effects of any genetic mutation.

bioinformatics↗

bioRxiv2022

Investigating the genetic diversity of H5 avian influenza in the UK 2020-2022

Since 2020, the UK and Europe, have experienced annual epizootics of high pathogenicity avian influenza virus (HPAIV). The first during autumn/winter 2020/21 involved the detected with six H5Nx subtypes although H5N8 HPAIV dominated in the UK. Whilst genetic assessment of the H5N8 HPAIVs within the UK demonstrated relative homogeneity, there was a background of other genotypes circulating at a lower degree with different neuraminidase and internal genes. Following a small number of summer detections of H5N1 in wild birds over the summer of 2021, autumn/winter 2021/22 saw another European H5 HPAIV epizootic, that has dwarfed the prior epizootic. This second epizootic was dominated almost exclusively by H5N1 HPAIV, although six distinct genotypes were defined. We have used genetic analysis to evaluate the emergence of different genotypes and proposed reassortment events that have been observed. The existing data suggests that the H5N1 circulating in Europe during late 2020, continued to circulate in wild birds throughout 2021, with minimal adaptation, but has then gone on to reassort with AIVs in the wild bird population. We have undertaken an in-depth genetic assessment of H5 HPAIVs detected in the UK, over the last two winter seasons and demonstrate the utility of in-depth genetic analyses in defining the diversity of H5 HPAIVs circulating in avian species, the potential for zoonotic risk and whether incidents of lateral spread can be defined over independent incursion of infection from wild birds. Key supporting data for mitigation activities. ImportanceHigh pathogenicity avian influenza virus (HPAIV) outbreaks devastate avian species across all sectors having both economic and ecological impacts through mortalities in poultry and wild birds, respectively. These viruses can also represent a significant zoonotic risk. Since 2020, the UK has experienced two successive outbreaks of H5 HPAIV. Whilst H5N8 HPAIV was predominant during the 2020/21 outbreak, other H5 subtypes were also detected. The following year there was a shift in subtype dominance to H5N1 HPAIV, but multiple H5N1 genotypes were detected. Through thorough utilisation of whole-genome sequencing, it was possible to track and characterise the genetic evolution of these H5 HPAIVs in UK poultry and wild birds. This has enabled us to assess the risk posed by these viruses at the poultry:wild bird and the avian:human interface and to investigate potential lateral spread between infected premises, a key factor in understanding threat to the commercial sector.

molecular biology↗

bioRxiv2022

Parallels and divergences in landscape genetic and metacommunity patterns in zooplankton inhabiting soda pans

Ecological processes maintaining landscape genetic variation and metacommunity structure in natural landscapes have traditionally been studied in isolation. Their integrated study may hold important information as to what extent the effect of major ecological processes are species-or landscape-specific, resulting in a more coherent picture on the spatial organization of biodiversity. Here, we explicitly compared the relative importance of spatial and environmental drivers of both cladoceran metacommunity structure as well as landscape genetic structure of its most widespread member, the water flea Daphnia magna, in soda pans of the Seewinkel region in Austria. This landscape of soda pans is characterized by strong environmental gradients and unidirectional wind acting as a key dispersal agent among these temporary habitats. Our study shows both parallels and divergences in the relative importance of local environmental sorting and spatial connectivity in determining landscape genetic versus metacommunity structure. The metacommunity is structured primarily by the environment, while in the D. magna metapopulation, the spatial signal is predominant. The much weaker environmental signal in Daphnia can be explained by the fact that the microsatellite markers are presumably neutral and was confirmed by a per-allele analysis. An important parallel between metacommunity and landscape genetic structure is the strong signal of the prevailing wind direction in determining the spatial pattern. This suggests that for both community assembly in cladocerans and population assembly in D. magna, wind plays an important role in determining connectivity among soda pans, thereby affecting dispersal and colonization rates, influencing both local species and genetic composition.

ecology↗

bioRxiv2023

The genetic architecture of the human skeletal form

The human skeletal form underlies our ability to walk on two legs, but unlike standing height, the genetic basis of limb lengths and skeletal proportions is less well understood. Here we applied a deep learning model to 31,221 whole body dual-energy X-ray absorptiometry (DXA) images from the UK Biobank (UKB) to extract 23 different image-derived phenotypes (IDPs) that include all long bone lengths as well as hip and shoulder width, which we analyzed while controlling for height. All skeletal proportions are highly heritable ([~]40-50%), and genome-wide association studies (GWAS) of these traits identified 179 independent loci, of which 102 loci were not associated with height. These loci are enriched in genes regulating skeletal development as well as associated with rare human skeletal diseases and abnormal mouse skeletal phenotypes. Genetic correlation and genomic structural equation modeling indicated that limb proportions exhibited strong genetic sharing but were genetically independent of width and torso proportions. Phenotypic and polygenic risk score analyses identified specific associations between osteoarthritis (OA) of the hip and knee, the leading causes of adult disability in the United States, and skeletal proportions of the corresponding regions. We also found genomic evidence of evolutionary change in arm-to-leg and hip-width proportions in humans consistent with striking anatomical changes in these skeletal proportions in the hominin fossil record. In contrast to cardiovascular, auto-immune, metabolic, and other categories of traits, loci associated with these skeletal proportions are significantly enriched in human accelerated regions (HARs), and regulatory elements of genes differentially expressed through development between humans and the great apes. Taken together, our work validates the use of deep learning models on DXA images to identify novel and specific genetic variants affecting the human skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis.

genomics↗

bioRxiv2023

Reliable genetic correlation estimation via multiple sample splitting and smoothing

In this paper, we aim to investigate the problem of estimating the genetic correlation between two traits. Instead of making assumptions about the distribution of effect sizes of the genetic factors, we propose the use of a high-dimensional linear model to relate a trait to genetic factors. To estimate the genetic correlation, we develop a generic strategy that combines the use of sparse penalization methods and multiple sample splitting approaches. The final estimate is determined by taking the median of the calculations, resulting in a smoothed and reliable estimate. Through simulations, we demonstrate that our proposed approach is reliable and accurate in comparison to naive plug-in methods. To further illustrate the advantages of our method, we apply it to a real-world example of a bacterial GWAS dataset, specifically to estimate the genetic correlation between antibiotic resistant traits in Streptococus pneumoniae. This application not only validates the effectiveness of our method but also highlights its potential in real-world applications.

bioinformatics↗

bioRxiv2023

FedDP: Secure Federated Learning for Disease Prediction with Imbalanced Genetic Data

It is challenging to share and aggregate biomedical data distributed among multiple institutions or computing resources due to various concerns including data privacy, security, and confidentiality. The federated Learning (FL) schema can effectively enable multiple institutions jointly perform machine learning by training a robust model with local data to satisfy the requirement of user privacy protection as well as data security. However, conventional FL methods are exposed to the risk of gradient leakage and cannot be directly applied to genetic data since they cannot address the unique challenges of data imbalance typically seen in genomics. To provide secure and efficient disease prediction based on genetic data distributed across multiple parties, we propose an FL framework enhanced with differential privacy (FedDP) on trained model parameters. In FedDP, local models can be trained among multiple local-hold genetic data with efficient secure and privacy-preserving techniques. The key idea of FedDP is to deploy differential privacy on compressed intermediate gradients that are computed and transmitted by optimizers from local parties. In addition, the unique weighted minmax loss in FedDP is able to address the difficulties of prediction for highly imbalanced genetic datasets. Our experiments on multiple genetic datasets demonstrate that FedDP provides a powerful tool to implement and evaluate various strategies in support of privacy preservation and model performance guarantee to overcome data imbalance.

bioinformatics↗

bioRxiv2023

Novel Pipeline for Large-Scale Comparative Population Genetics

As scientists continue to ask complex questions about biodiversity and deal with increasingly large amounts of data, there is a demand for new methods and computational developments to perform scientific analyses. Analytical pipelines and modules can provide a way to meet these demands and ensure reproducibility in scientific methods and analyses. The goal of this study was to create efficient, reproducible, reusable programming modules that are publicly available for future research. These modules were used to determine population genetic structure measures and compare these measures across species with different biological traits. The functionality of the modules is shown through a case study on Diptera (true fly) species from Canada and Greenland. We leveraged high-throughput DNA sequencing data from Northern areas, as it is a valuable resource and provides new opportunities to study the Arctic. Data were pulled from public databases (Barcode of Life Data System and Global Biodiversity Information Facility), as well as taxon-specific literature. The pipeline we developed in R includes fifteen modules, including modules to prepare and filter the data, calculate population genetic structure measures (e.g., FST), and run a multiple regression. These modules can be easily adapted and applied to a diverse set of animal groups, geographic regions, and biological traits. Best practices were followed for pipeline development, and the modules were designed and tested to work for datasets of different sizes by providing multiple different analyses and filtering options. Biological results were also obtained for Diptera species. Habitat and larval diet were both significantly related to population genetic structure. Evidence of isolation by distance and a relationship between population genetic structure and both latitude and longitude were also found. Overall, this study has created efficient, reusable bioinformatics modules, and provided insight into the factors affecting population genetic structure in Northern fly communities.

bioinformatics↗

bioRxiv2023

Genetic diversity of the eastern black rhinoceros (Diceros bicornis michaeli) in Tanzania; implications for future conservation

In the past decade, there has been a drastic decline in the number of Eastern Black rhinoceros (black rhinoceros) (Diceros bicornis michaeli), primarily because of poaching across their natural habitats, leaving few individuals in small, isolated populations that are vulnerable to demographic extinction, disease epidemics, genetic drift and inbreeding. However, genetic consequences of the demographic decline on the remaining populations have not been investigated. Using the mitochondrial control region, this study investigated how current levels of genetic diversity relate to historical patterns, quantified genetic differentiation between extant populations and assessed the impacts of previous translocations on genetic diversity across populations. A total of 74 individual eastern black rhinoceroses were sampled from five extant populations in Tanzania and one neighbouring cross-border population in the Maasai Mara in Kenya. Six maternal haplotypes were identified, with an overall haplotype diversity of h=0.7 but low overall nucleotide diversity within populations ({pi} = 0.017) compared to historical populations from Tanzania ({pi} = 0.021). There was extensive variation in haplotype distribution between populations, with more variation exists within (65.5 %) than among the populations (35.5%), which may indicate lack of migration between populations. Specifically, some geographically close populations with different histories of introductions didnt share any haplotypes, suggesting that gene flow is currently restricted. The haplotypes were distributed among three east African haplogroups (CV, CE and EA) that have been described in previous studies, suggesting that multiple lineages have been preserved despite loss of haplotypes. One of the haplotypes was highly divergent and matched sequences previously classified as a subspecies that has not been recognised in recent years (D. b. ladoensis). We recommend that current levels of diversity be maintained by allowing natural movements of rhinoceroses between the populations, with the possibility of introducing additional variations by translocation of individuals between sites.

evolutionary biology↗

bioRxiv2023

Hypothesis-free phenotype prediction within a genetics-first framework

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed rare, even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population1-3). Our understanding of how rare genetic variants influence disease and organism-level phenotypes has achieved limited progress, partly explained by the intrinsic difficulty in statistically evaluating the biological significance of rare events. Here we show that discoveries can instead be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible novel genetic causes for developmental disorders that have eluded other established methods and present novel molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

genomics↗

bioRxiv2023

The Pathfinder plasmid toolkit for genetically engineering newly isolated bacteria enables the study of Drosophila-colonizing Orbaceae

Toolkits of plasmids and genetic parts streamline the process of assembling DNA constructs and engineering microbes. Many of these kits were designed with specific industrial or laboratory microbes in mind. For researchers interested in non-model microbial systems, it is often unclear which tools and techniques will function in newly isolated strains. To address this challenge, we designed the Pathfinder toolkit for quickly determining the compatibility of a bacterium with different plasmid components. Pathfinder plasmids combine three different broad-host-range origins of replication with multiple antibiotic resistance cassettes and reporters, so that sets of parts can be rapidly screened through multiplex conjugation. We first tested these plasmids in Escherichia coli, a strain of Sodalis praecaptivus that colonizes insects, and a Rosenbergiella isolate from leafhoppers. Then, we used the Pathfinder plasmids to engineer previously unstudied bacteria from the family Orbaceae that were isolated from several fly species. Engineered Orbaceae strains were able to colonize Drosophila melanogaster and could be visualized in fly guts. Orbaceae are common and abundant in the guts of wild-caught flies but have not been included in laboratory studies of how the Drosophila microbiome affects fly health. Thus, this work provides foundational genetic tools for studying new host-associated microbes, including bacteria that are a key constituent of the gut microbiome of a model insect species. IMPORTANCETo fully understand how microbes have evolved to interact with their environments, one must be able to modify their genomes. However, it can be difficult and laborious to discover which genetic tools and approaches work for a new isolate. Bacteria from the recently described Orbaceae family are common in the microbiomes of insects. We developed the Pathfinder plasmid toolkit for testing the compatibility of different genetic parts with newly cultured bacteria. We demonstrate its utility by engineering Orbaceae strains isolated from flies to express fluorescent proteins and characterizing how they colonize the Drosophila melanogaster gut. Orbaceae are widespread in Drosophila in the wild but have not been included in laboratory studies examining how the gut microbiome affects fly nutrition, health, and longevity. Our work establishes a path for genetic studies aimed at understanding and altering interactions between these and other newly isolated bacteria and their hosts.

microbiology↗

bioRxiv2023

Testing the efficacy of different molecular tools for parasite conservation genetics: a case study using horsehair worms (Phylum Nematomorpha)

In recent years, parasite conservation has become a globally significant issue. Because of this, there is a need for standardised methods for inferring population status and possible cryptic diversity. However, given the lack of molecular data for some groups, it is challenging to establish procedures for genetic diversity estimation. Therefore, universal tools, such as double digest restriction-site associated DNA sequencing (ddRADseq), could be useful when conducting conservation genetic studies on rarely studied parasites. Here, we generated a ddRADseq dataset that includes all three described Taiwanese horsehair worms (Phylum Nematomorpha), possibly one of the most understudied animal groups. Additionally, we produced data for a fragment of the cytochrome c oxidase subunit I (COXI) for said species. We used the COXI dataset in combination with previously published sequences of the same locus for inferring the effective population size (Ne) trends and possible population structure. We found that a larger and geographically broader sample size combined with more sequenced loci resulted in a better estimation of changes in Ne. We were able to detect demographic changes associated with Pleistocene events in all the species. Furthermore, the ddRADseq dataset for Chordodes formosanus did not reveal a genetic structure based on geography, implying a great dispersal ability, possibly due to its hosts. We showed that different molecular tools can be used to reveal genetic structure and demographic history at different historical times and geographical scales, which can help with conservation genetic studies in rarely studied parasites.

zoology↗

bioRxiv2023

Whole-genome sequencing of ethnolinguistic diverse northwestern Chinese Hexi Corridor people from the 10K_CPGDP project suggested the differentiated East-West genetic admixture along the Silk Road and their biological adaptations

The ancient Silk Road served as the main connection between East and West Eurasia for several centuries. At any rate, the genetic exchange between populations along the ancient Silk Road was likely to leave traces on the contemporary gene pool of local people in Northwest China, which was the passage of the Northern Silk Road. However, genetic sources from northwestern China are under-represented in the current population-scale genomic database. To characterize the genetic architecture and adaptative history of the Northern Silk Road ethnic populations, we performed whole-genome sequencing on 126 individuals from six ethnolinguistic groups (Tibeto-Burman (TB)-speaking Tibetan, Mongolic (MG)-speaking Dongxiang/Tu/eastern Yugur, and Turkic (TK)-speaking Salar/western Yugur) living in Gansu and Qinghai in the 10K Chinese people Genomic Diversity Project (10K_CPGDP). We observed ethnicity-related differentiated population structures among these geographically close Northwest Chinese populations, that is, Salar and Tu people showed a close affinity with southwestern TB groups, and other studied populations shared more alleles with MG and Tungusic groups. Overall, the patterns of genetic clustering were not consistent with linguistic classifications. We estimated that Dongxiang, Tibetan, and Yugur people inherited more than 10% West Eurasian ancestry, much higher than that of Salar and Tu people (<7%). Hence, the difference in the proportion of West Eurasian ancestry has primarily contributed to the genetic divergence of geographically close Northwest Chinese populations. The signatures of natural selection were identified in genes associated with cardiovascular system diseases or lipid metabolism related to triglyceride levels (e.g., PRIM2, PDE4DIP, NOTCH2, DDAH1, GALNT2, and MLIP) and developmental and neurogenetic diseases (e.g., NBPFs 8/9/20/25P, etc.). Moreover, the EPAS1 gene, a transcription factor regulating hypoxia response, showed relatively high PBS values in our studied groups. The sex-biased admixture history, in which the West Eurasian ancestry was introduced primarily by males, was identified in Dongxiang, Tibetan, and Yugur populations. We determined that the eastern-western admixture occurred [~]783-1131 years ago, coinciding with the intensive economic and cultural exchanges during the historic Trans-Eurasian cultural exchange era.

genomics↗

bioRxiv2023

Revealing the chassis-effect on a broad-host-range genetic switch and its concordance with interspecies bacterial physiologies

Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to "model status", synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the "chassis-effect". It remains a major challenge to uncover which genome encoded and physiological biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of toggle switch performance. This was accomplished using comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis-effect and characterize the performance dynamics of a genetic toggle switch operating within six Gammaproteobacteria. Our results solidify the notion that genetic devices are significantly impacted by host-context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar toggle switch performance, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.

synthetic biology↗

bioRxiv2023

Epigenetic then genetic variations underpin rapid adaptation of oyster populations (Crassostrea gigas) to Pacific Oyster Mortality Syndrome (POMS)

Disease emergence is accelerating in response to human activity-induced global changes. Understanding the mechanisms by which host populations can rapidly adapt to this threat will be crucial for developing future management practices. Pacific Oyster Mortality Syndrome (POMS) imposes a substantial and recurrent selective pressure on oyster populations (Crassostrea gigas). Rapid adaptation to this disease may arise through both genetic and epigenetic mechanisms. In this study, we used a combination of whole exome capture of bisulfite-converted DNA, next-generation sequencing, and (epi)genome-wide association mapping, to show that natural oyster populations differentially exposed to POMS displayed signatures of selection both in their genome (single nucleotide polymorphisms) and epigenome (CG-context DNA methylation). Consistent with higher resistance to POMS, the genes targeted by genetic and epigenetic variations were mainly related to host immunity. By combining correlation analyses, DNA methylation quantitative trait loci, and variance partitioning, we revealed that a third of the observed phenotypic variation was explained by interactions between the genetic sequence and epigenetic information, [~]14% by the genetic sequence, and up to 25% by the epigenome alone. Thus, as well as genetic adaptation, epigenetic mechanisms governing immune responses contribute significantly to the rapid adaptation of hosts to emerging infectious diseases.

evolutionary biology↗

bioRxiv2023

Ultra-high throughput mapping of genetic design space

Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements. However, because these approaches only interrogate short sequences, it remains challenging to perform high throughput (HT) assays on constructs containing combinations of multiple sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate synthetic biology; by screening diverse gene circuit designs and learning "composition-to-function" mappings that reveal genetic part composability rules and enable rapid identification of behavior-optimized variants. Here, we introduce CLASSIC, a genetic screening platform that combines long- and short-read next-generation sequencing (NGS) modalities to quantitatively assess pools of constructs of arbitrary length containing diverse part compositions. We show that CLAS-SIC can measure expression profiles of >105 gene circuit designs (from 5-20 kb) in a single experiment in human cells. The resulting datasets can be used to train ML models that accurately predict circuit behavior across expansive circuit design landscapes, revealing part composability rules that govern circuit performance. Our work shows that by expanding the throughput of each design-build-test-learn (DBTL) cycle, CLASSIC enhances the pace and scale of synthetic biology and establishes an experimental basis for data-driven design of complex genetic systems.

synthetic biology↗

bioRxiv2023

Determinants of genetic diversity in sticklebacks

Understanding what determines species and population differences in levels of genetic diversity has important implications for our understanding of evolution, as well as for the conservation and management of wild populations. Previous comparative studies have emphasized the roles of linked selection, life-history trait variation and genomic properties, rather than pure demography, as important determinants of genetic diversity. However, these findings are based on coarse estimates across a range of highly diverged taxa, and it is unclear how well they represent the processes within individual species. We assessed genome-wide genetic diversity ({pi}) in 45 nine-spined stickleback (Pungitius pungitius) populations and found that{pi} varied 15-fold among populations ({pi}min{approx}0.00015,{pi} max{approx}0.0023) whereas estimates of recent effective population sizes varied 122-fold. Analysis of inbreeding coefficients (FROH) estimated from runs of homozygosity revealed strong negative association between{pi} and FROH. Genetic diversity was also negatively correlated with mean body size and longevity, but these associations were not statistically significant after controlling for demographic effects (FROH). The results give strong support for the view that populations demographic features, rather than life history differences, are the chief determinants of genetic diversity in the wild.

evolutionary biology↗

bioRxiv2023

Evolutionary rescue through gene flow despite genetic incompatibilities shaped diversity of the pseudo-cereal grain amaranth

Crop domestication and the subsequent expansion of crops have long been thought of as a linear process from a wild ancestor to a domesticate. However, evidence of gene flow from locally adapted wild relatives that provided adaptive alleles into crops has been identified in multiple species. Yet, little is known about the evolutionary consequences of gene flow during domestication and the interaction of gene flow and genetic load in crop populations. We study the pseudo-cereal grain amaranth that has been domesticated three times in different geographic regions of the Americas. We quantify the amount and distribution of gene flow and genetic load along the genome of the three grain amaranth species and their two wild relatives. Our results show ample gene flow between crop species and between crops and their wild relatives. Gene flow from wild relatives decreased genetic load in the three crop species. This suggests that wild relatives could provide evolutionary rescue by replacing deleterious alleles in crops. We assess experimental hybrids between the three crop species and found genetic incompatibilities between one Central American grain amaranth and the other two crop species. These incompatibilities might have created recent reproductive barriers and maintained species integrity today. Together, our results show that gene flow played an important role in the domestication and expansion of grain amaranth, despite genetic species barriers. The domestication of plants was likely not linear and created a genomic mosaic by multiple contributors with varying fitness effects for todays crops.

evolutionary biology↗

bioRxiv2023

Genetic and Environmental interactions contribute to immune variation in rewilded mice

The relative and synergistic contributions of genetics and environment to inter-individual immune response variation remain unclear, despite its implications for understanding both evolutionary biology and medicine. Here, we quantify interactive effects of genotype and environment on immune traits by investigating three inbred mouse strains rewilded in an outdoor enclosure and infected with the parasite, Trichuris muris. Whereas cytokine response heterogeneity was primarily driven by genotype, cellular composition heterogeneity was shaped by interactions between genotype and environment. Notably, genetic differences under laboratory conditions can be decreased following rewilding, and variation in T cell markers are more driven by genetics, whereas B cell markers are driven more by environment. Importantly, variation in worm burden is associated with measures of immune variation, as well as genetics and environment. These results indicate that nonheritable influences interact with genetic factors to shape immune variation, with synergistic impacts on the deployment and evolution of defense mechanisms.

immunology↗