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bioRxiv2021

Environmental differences explain subtle yet detectable genetic structure in a widespread pollinator

BackgroundThe environment is a strong driver of genetic structure in many natural populations, yet often neglected in population genetic studies. This may be a particular problem in vagile species, where subtle structure cannot be explained by limitations to dispersal. These species might falsely be considered panmictic and hence potentially mismanaged. Here we analysed the genetic structure in an economically important and widespread pollinator, the buff-tailed bumble bee (Bombus terrestris), which is considered to be quasi-panmictic at mainland continental scales. We first quantified population structure in Romania and Bulgaria with spatially implicit Fst and Bayesian clustering analyses. We then incorporated environmental information to infer the influence of the permeability of the habitat matrix between populations (resistance distances) as well as environmental differences among sites in explaining population divergence. ResultsGenetic structure of the buff-tailed bumble bee was subtle and not detected by Bayesian clustering. As expected, geographic distance and habitat permeability were not informative in explaining the spatial pattern of genetic divergence. Yet, environmental variables related to temperature, vegetation and topography were highly informative, explaining between 33 and 39% of the genetic variation observed. ConclusionsWhere in the past spatially implicit approaches had repeatedly failed, incorporating environmental data proved to be highly beneficial in detecting and unravelling the drivers of genetic structure in this vagile and opportunistic species. Indeed, structure followed a pattern of isolation by environment, where the establishment of dispersers is limited by environmental differences among populations, resulting in the disruption of genetic connectivity and the divergence of populations through genetic drift and divergent natural selection. With this work, we highlight the potential of incorporating environmental differences among population locations to complement the more traditional approach of isolation by geographic distance, in order to obtain a holistic understanding of the processes driving structure in natural populations.

ecology↗
bioRxiv2021

Local adaptation and spatiotemporal patterns of genetic diversity revealed by repeated sampling of Caenorhabditis elegans across the Hawaiian Islands

The nematode Caenorhabditis elegans is among the most widely studied organisms, but relatively little is known about its natural ecology. Wild C. elegans have been isolated from both temperate and tropical climates, where they feed on bacteria associated with decomposing plant material. Genetic diversity is low across much of the globe but high in the Hawaiian Islands and across the Pacific Rim. The high genetic diversity found there suggests that: (1) the origin of the species lies in Hawaii or the surrounding Pacific Rim; and (2) the ancestral niche of the species is likely similar to the Hawaiian niche. A recent study of the Hawaiian niche found that genetically distinct groups appeared to correlate with elevation and temperature, but the study had a limited sample size. To better characterize the niche and genetic diversity of C. elegans on the Hawaiian Islands and to explore how genetic diversity might be influenced by local adaptation, we repeatedly sampled nematodes over a three-year period, measured various environmental parameters at each sampling site, and whole-genome sequenced the C. elegans isolates that we identified. We found that the typical Hawaiian C. elegans niche is moderately moist native forests at high elevations (500 to 1500 meters) where temperatures are cool (15 to 20{degrees}C). We measured levels of genetic diversity and differentiation among Hawaiian strains and found evidence of seven genetically distinct groups distributed across the islands. Then, we scanned these genomes for signatures of local adaptation and identified 18 distinct regions that overlap with hyperdivergent regions, which are likely maintained by balancing selection and enriched for genes related to environmental sensing, xenobiotic detoxification, and pathogen resistance. These results provide strong evidence of local adaptation among Hawaiian C. elegans and a possible genetic basis for this adaptation.

ecology↗
bioRxiv2021

Quantifying the scale of genetic diversity extinction in the Anthropocene

More species than ever before are at risk of extinction due to anthropogenic habitat loss and climate change. But even species that are not threatened have seen reductions in their populations and geographic ranges, likely impacting their genetic diversity. Although preserving genetic diversity is key to maintaining adaptability of species, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. By bridging theories of biodiversity and population genetics, we introduce a mathematical framework to understand the loss of naturally occurring DNA mutations within decreasing habitat within a species. Analysing genome-wide variation data of 10,095 geo-referenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a power law with geographic area (the mutations-area relationship), which can predict genetic diversity loss in spatial computer simulations of local population extinctions. Given pre-21st century values of ecosystem transformations, we estimate that over 10% of genetic diversity may already be lost, surpassing the United Nations targets for genetic preservation. These estimated losses could rapidly accelerate with advancing climate change and habitat destruction, highlighting the need for forecasting tools that facilitate implementation of policies to protect genetic resources globally.

ecology↗
bioRxiv2021

Core circadian clock and light signalling genes brought into genetic linkage across the green lineage

The circadian clock ensures that biological processes are phased to the correct time of day. In plants the circadian clock is conserved at both the level of transcriptional networks as well as core genes. In the model plant Arabidopsis thaliana, the core circadian singleMYB (sMYB) genes CCA1 and RVE4 are in genetic linkage with the PSEUDO-RESPONSE REGULATOR (PRR) genes PRR9 and PRR7 respectively. Leveraging chromosome-resolved plant genomes and syntenic ortholog analysis it was possible to trace this genetic linkage back to the basal angiosperm Amborella and identify an additional evolutionarily conserved genetic linkage between PIF3 and PHYA. The LHY/CCA1-PRR5/9, RVE4/8-PRR3/7 and PIF3-PHYA genetic linkages emerged in the bryophyte lineage and progressively moved within several genes of each other across an array of higher plant families representing distinct whole genome duplication and fractionation events. Soybean maintains all but two genetic linkages, and expression analysis revealed the PIF3-PHYA linkage overlapping with the E4 maturity group locus was the only pair to robustly cycle with an evening phase in contrast to the sMYB-PRR morning and midday phase. While most monocots maintain the genetic linkages, they have been lost in the economically important grasses (Poaceae) such as maize where the genes have been fractionated to separate chromosomes and presence/absence variation results in the segregation of PRR7 paralogs across heterotic groups. The evolutionary conservation of the genetic linkage as well as its loss in the grasses provides new insight in the plant circadian clock, which has been a critical target of breeding and domestication. Summary SentenceThe genetic linkage of the core circadian clock components has evolutionary origins in bryophytes and sheds light on the current functioning and selection on the circadian clock in crops.

plant biology↗
bioRxiv2022

Reexamining Waddington: Canalization and new mutations are not required for the evolution of genetic assimilation

Over 65 years ago, Waddington demonstrated ancestrally phenotypically plastic traits can evolve to become constitutive, a process he termed genetic assimilation. Genetic assimilation evolves rapidly, assumed to be in large part due to segregating genetic variation only expressed in rare/novel environments, but otherwise phenotypically cryptic. Despite previous work suggesting a substantial role of cryptic genetic variation contributing to the evolution of genetic assimilation, some have argued for a prominent role for new mutations of large effect concurrent with selection. Interestingly, Waddington was less concerned by the relative contribution of CGV or new variants, but aimed to test the role of canalization, an evolved form of robustness. While canalization has been extensively studied, its role in the evolution of genetic assimilation is disputed, in part because explicit tests of evolved robustness are lacking. To address these questions, we recreated Waddingtons selection experiments on an environmentally sensitive change in Drosophila wing morphology (crossvein development), using many independently evolved replicate lineages. Using these, we show that 1) a polygenic CGV, but not new variants of large effect are largely responsible for the evolved response demonstrated using both genomic and genetic approaches. 2) Using both environmental manipulations and mutagenesis of the evolved lineages that there is no evidence for evolved changes in canalization contributing to genetic assimilation. Finally, we demonstrate that 3) CGV has potentially pleiotropic and fitness consequences in natural populations and may not be entirely "cryptic".

evolutionary biology↗
bioRxiv2022

Additive genetic effects in interacting species jointly determine the outcome of caterpillar herbivory

Plant-insect interactions are common and important in basic and applied biology. Trait and genetic variation can affect the outcome and evolution of these interactions, but the relative contributions of plant and insect genetic variation and how these interact remain unclear and are rarely subject to assessment in the same experimental context. Here we address this knowledge gap using a recent host range expansion onto alfalfa by the Melissa blue butterfly. Common garden rearing experiments and genomic data show that caterpillar performance depends on plant and insect genetic variation, with insect genetics contributing to performance earlier in development and plant genetics later. Our models of performance based on caterpillar genetics retained predictive power when applied to a second common garden. Much of the plant genetic effect could be explained by heritable variation in plant phytochemicals, especially saponins, peptides, and phosphatidyl cholines, providing a mechanistic understanding of variation in the species interaction. We find evidence of polygenic, mostly additive effects within and between species, with consistent effects of plant genotype on growth and development across multiple butterfly species. Our results inform theories of plant-insect coevolution and the evolution of diet breadth in herbivorous insects and other host-specific parasites. Teaser summaryThe combined, additive effects of plant and insect genetic variation explain Melissa blue caterpillar growth and development on alfalfa plants.

genomics↗
bioRxiv2022

Gene selection by incorporating genetic networks into case-control association studies

Large-scale genome-wide association studies (GWAS) have been successfully applied to a wide range of genetic variants underlying complex diseases. The network-based penalized regression approach has been developed to overcome the challenges caused by the computational efficiency for analyzing high-dimensional genomic data by incorporating a biological genetic network. In this paper, we propose a gene selection approach by incorporating genetic networks into case-control association studies for DNA sequence data or DNA methylation data. Instead of using traditional dimension reduction techniques such as principal component analyses and supervised principal component analyses, we use a linear combination of genotypes at SNPs or methylation values at CpG sites in each gene to capture gene-level signals. We develop three approaches for the linear combination: optimally weighted sum (OWS), LD-adjusted polygenic risk score (LD-PRS), and beta-based weighted sum (BWS). OWS and LD-PRS are supervised approaches that depend on the effect of each SNP or CpG site on the case-control status, while BWS can be extracted without using the case-control status. After using one of the linear combinations of genotypes or methylation values in each gene to capture gene-level signals, we regularize them to perform gene selection based on the biological network. Simulation studies show that the proposed approaches have higher true positive rates than using traditional dimension reduction techniques. We also apply our approaches to DNA methylation data and UK Biobank DNA sequence data for analyzing rheumatoid arthritis. The results show that the proposed methods can select potentially rheumatoid arthritis related genes that are missed by existing methods. Author SummaryThere is strong evidence showing that when genes are functionally related to each other in a genetic network, statistical methods utilizing prior biological network knowledge can outperform other methods that ignore genetic network structures. Therefore, statistical methods that can incorporate genetic network information into association analysis in human genetic association studies have been widely used since 2008. Here, we take advantage of recently developed methods to capture the gene-level signals in network-based penalized regression of high-dimensional genetic data. We have shown that the selection performance of our proposed methods can outperform three traditional principal component-based dimension reduction techniques in several simulation scenarios in terms of true positive rates. Meanwhile, by applying our methods in both DNA methylation data and DNA sequence data, the genes identified by our proposed methods can be significantly enriched into the rheumatoid arthritis pathway, such as genes HLA-DMA, HLA-DPB1, and HLA-DQA2 in the HLA region.

bioinformatics↗
bioRxiv2022

Epigenetic and genetic population structure is coupled in a marine invertebrate

Delineating the relative influence of genotype and the environment on DNA methylation is critical for characterizing the spectrum of organism fitness as driven by adaptation and phenotypic plasticity. In this study, we integrated genomic and DNA methylation data for two distinct Olympia oyster (Ostrea lurida) populations while controlling for within-generation environmental influences. In addition to providing the first characterization of genome-wide DNA methylation patterns in the oyster genus Ostrea, we identified 3,963 differentially methylated loci between populations. Our results show a clear coupling between genetic and epigenetic patterns of variation, with 27% of variation in inter-individual methylation differences explained by genotype. Underlying this association are both direct genetic changes in CpGs (CpG-SNPs) and genetic variation with indirect influence on methylation (mQTLs). The association between genetic and epigenetic patterns breaks down when comparing measures of population divergence at specific genomic regions, which has implications for the methods used to study epigenetic and genetic coupling in marine invertebrates. Significance statementWe know that genotype and epigenetic patterns are primarily responsible for phenotype, yet there is a lack of understanding to what degree the two are linked. Here we characterized the mechanisms and the degree by which genetic variation and DNA methylation variation are coupled in a marine invertebrate, with almost a third of the methylation variation attributable to genotype. This study provides a framework for future studies in environmental epigenetics to take genetic variation into account when teasing apart the drivers of phenotypic variation. By identifying methylation variation that cannot be attributed to genotype or environmental changes during development, our results also highlight the need for future research to characterize molecular mechanisms adjacent to genetic adaptation for producing long-term shifts in phenotype.

genomics↗
bioRxiv2022

Tree species and genetic diversity increase productivity via functional diversity and trophic feedbacks

Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how the diversity within a given plant species (genetic diversity) affects plant productivity remains limited. Here, we use a tree species x genetic diversity experiment to disentangle the effects of species diversity and genetic diversity, and how they are related to tree functional diversity and trophic feedbacks. Tree species as well as genetic diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity and marginally reduced herbivory. The effect of tree genetic diversity on productivity was partly different between tree species monocultures and mixtures: the functional diversity effect resulting from tree genetic diversity was only found in tree species monocultures, but the trophic feedbacks via herbivory were similar in species monocultures and mixtures. Given the complexity of interactions between tree species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in reforestation.

ecology↗
bioRxiv2022

Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation

Metabolic syndrome (MetSyn) is a cluster of dysregulated metabolic conditions that occur together to increase the risk for cardiometabolic disorders such as type 2 diabetes (T2D). One key condition associated with MetSyn, abdominal obesity, is measured by computing the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI). WHRadjBMI and T2D are complex traits with genetic and environmental components, which has enabled genome-wide association studies (GWAS) to identify hundreds of loci associated with both. Statistical genetics analyses of these GWAS have predicted that WHRadjBMI is a strong causal risk factor of T2D and that these traits share genetic architecture at many loci. To date, no variants have been described that are simultaneously associated with protection from T2D but with increased abdominal obesity. Here, we used colocalization analysis to identify genetic variants with a shared association for T2D and abdominal obesity. This analysis revealed the presence of five loci associated with discordant effects on T2D and abdominal obesity. The alleles of the lead genetic variants in these loci that were protective against T2D were also associated with increased abdominal obesity. We further used publicly available expression, epigenomic, and genetic regulatory data to predict the effector genes (eGenes) and functional tissues at the 2p21, 5q21.1, and 19q13.11 loci. We also computed the correlation between the subcutaneous adipose tissue (SAT) expression of predicted effector genes (eGenes) with metabolic phenotypes and adipogenesis. We proposed a model to resolve the discordant effects at the 5q21.1 locus. We find that eGenes gypsy retrotransposon integrase 1 (GIN1), diphosphoinositol pentakisphosphate kinase 2 (PPIP5K2), and peptidylglycine alpha-amidating monooxygenase (PAM) represent the likely causal eGenes at the 5q21.1 locus. Taken together, these results are the first to describe a potential mechanism through which a genetic variant can confer increased abdominal obesity but protection from T2D risk. Understanding precisely how and which genetic variants confer increased risk for MetSyn will develop the basic science needed to design novel therapeutics for metabolic syndrome.

genomics↗
bioRxiv2022

Widespread epistasis among beneficial genetic variants revealed by high-throughput genome editing

Genetic interactions occur when a variants phenotypic effect is altered by variation at other genomic loci. Also known as epistasis, these interactions shape the genetic architecture of complex traits and modify phenotypes across genetic backgrounds. However, the factors associated with their occurrence remain poorly understood. To investigate this, we employed high-throughput genome editing to measure the fitness effects of 1,826 naturally polymorphic variants in four genetically diverse strains of Saccharomyces cerevisiae. About 31% of variants affect fitness in a common laboratory environment, of which 24% have strain-specific fitness effects indicative of epistasis. We found that beneficial variants are more likely to exhibit genetic interactions, and that genetic interactions are depleted among variants at higher allele frequencies. In addition, we demonstrate that these epistatic interactions for fitness can be mediated by specific traits such as flocculation ability. This work suggests that adaptive evolution from standing variation will often involve trade-offs where a variant is only beneficial in some genetic backgrounds, potentially explaining why many beneficial variants remain polymorphic. In sum, we provide a framework to understand the factors influencing epistasis in natural genetic variants with single-nucleotide resolution, revealing widespread epistasis among beneficial variants.

genomics↗
bioRxiv2022

AGO1 and HSP90 buffer different genetic variants in Arabidopsis thaliana

Argonaute 1 (AGO1), the principal protein component of microRNA-mediated regulation, plays a key role in plant growth and development. AGO1 physically interacts with the chaperone HSP90, which buffers cryptic genetic variation in plants and animals. We sought to determine whether genetic perturbation of AGO1 in Arabidopsis thaliana would also reveal cryptic genetic variation, and if so, whether AGO1-dependent loci overlap with those dependent on HSP90. To address these questions, we introgressed a hypomorphic mutant allele of AGO1 into a set of mapping lines derived from the commonly used Arabidopsis strains Col-0 and Ler. Although we identified several cases in which AGO1 buffered genetic variation, none of the AGO1-dependent loci overlapped with those buffered by HSP90 for the traits assayed. We focused on one buffered locus where AGO1 perturbation uncoupled the traits days to flowering and rosette leaf number, which are otherwise closely correlated. Using a bulk segregant approach, we identified a non-functional Ler hua2 mutant allele as the causal AGO1-buffered polymorphism. Introduction of a non-functional hua2 allele into a Col-0 ago1 mutant background recapitulated the Ler-dependent ago1 phenotype, implying that coupling of these traits involves different molecular players in these closely related strains. Taken together, our findings demonstrate that even though AGO1 and HSP90 buffer genetic variation in the same traits, these robustness regulators interact epistatically with different genetic loci, suggesting that higher-order epistasis is uncommon. Article SummaryArgonaute 1 (AGO1), a key player in plant development, interacts with the chaperone HSP90 which buffers environmental and genetic variation. We found that AGO1 buffers environmental and genetic variation in the same traits; however, AGO1-dependent and HSP90-dependent loci do not overlap. Detailed analysis of a buffered locus found that a non-functional HUA2 allele decouples days to flowering and rosette leaf number in an AGO1-dependent manner, suggesting the AGO1-dependent buffering acts at the network level.

plant biology↗
bioRxiv2022

Annotation of Phage Genomes with Multiple Genetic Codes

Some of recently discovered in human gut microbiome highly divergent crAssphages were reported to use multiple genetic codes. Opal or amber stop codon reassignments were present in parts of the genomes, while the standard genetic code was used in the remaining genome sections. Essentially, the phage genomes were divided into distinct blocks where one or another code was used. We have developed a tool, Mgcod, that identifies blocks with specific genetic codes and annotates protein-coding regions. We used Mgcod to scan a large set of human metagenomic contigs. As a result, we identified hundreds of contigs of viral origin with the standard genetic code used in some parts while genetic codes with opal or amber stop codon reassignments were used in others. Many of these contigs originated from known crAssphages. Further investigation revealed that while the genes in one genomic block could be translated by a distinct genetic code, translation of genes by either of the two genetic codes genes in an adjacent block would produce proteins with little difference from each other. The dual-coded genes were enriched with early-stage phage genes, while a single code was used for the late-stage genes. The code-block structure expands the phages ability to infect bacteria whose genomes employ the standard genetic code. The new tool provides means for accurate annotation of unusual genomes of these phages.

bioinformatics↗
bioRxiv2022

Investigating genetic diversity within the most abundant and prevalent non-pathogenic leaf-associated bacteria interacting with Arabidopsis thaliana in natural habitats

Plants interact simultaneously with highly diversified microbes defined as the plant microbiota. Microbiota modulates plant health and appears as a promising lever to develop innovative, sustainable and eco-friendly agro-ecosystems. Key patterns of microbiota assemblages in plants have been revealed by an extensive number of studies based on taxonomic profiling by metabarcoding. However, understanding the functionality of microbiota and identifying the genetic and molecular mechanisms underlying the interplay between plants and their microbiota are still in its infancy and relies on reductionist approaches primarily based on the establishment of representative microbial collections. In Arabidopsis thaliana, most of these microbial collections include one strain per OTU isolated from a limited number of habitats, thereby neglecting the ecological potential of genetic diversity within microbial species to affect the plant-microbiota molecular dialog. With this study, we aimed at estimating the extent of genetic variation between strains within the most abundant and prevalent leaf-associated non-pathogenic bacterial species in 163 natural populations of A. thaliana located south-west of France. By combining a culture-based collection approach consisting of the isolation of more than 7,000 bacterial colonies with an informative-driven approach, we isolated 35 pure strains from eight non-pathogenic bacterial species. We detected significant intra-specific genetic variation at the genomic level and for growth rate in synthetic media. In addition, significant host genetic variation was detected in response to most bacterial strains in in vitro conditions, with the presence of both negative and positive responses on plant growth. Our study provides new genetic and genomic resources for a better understanding of the plant-microbe ecological interactions at the microbiota level. We also highlight the need of considering genetic variation in both non-pathogenic bacterial species and A. thaliana to decipher the genetic and molecular mechanisms involved in the ecologically relevant dialog between hosts and leaf microbiota.

microbiology↗
bioRxiv2022

Genetic drift shapes the evolution of a highly dynamic metapopulation

The dynamics of extinction and (re)colonization in habitat patches are common features of metapopulations, causing them to evolve differently than large, stable populations. The propagule model, which assumes genetic bottlenecks during colonization, posits that newly founded subpopulations have low genetic diversity and are genetically highly differentiated from each other. Immigration may then increase diversity and decrease differentiation between subpopulations. Thus, older and/or less isolated subpopulations are expected to have higher genetic diversity and less genetic differentiation. We tested this theory using whole-genome pool-sequencing to characterize nucleotide diversity and differentiation in 60 subpopulations of a natural metapopulation of the cyclical parthenogen Daphnia magna. For comparison, we characterized diversity in a single, large, stable D. magna population. We found reduced (synonymous) genomic diversity, a proxy for effective population size, weak purifying selection, and low rates of adaptive evolution in the metapopulation compared to the large, stable population. These differences suggest that genetic bottlenecks during colonization reduce effective population sizes, which leads to strong genetic drift and reduced selection efficacy in the metapopulation. Consistent with the propagule model, we found lower diversity and increased differentiation in more isolated, younger subpopulations. Our study sheds light on the genomic consequences of extinction-(re)colonization dynamics to an unprecedented degree, giving strong support for the propagule model. We demonstrate that the metapopulation evolves differently from a large, stable population and that the evolutionary process is largely driven by genetic drift.

evolutionary biology↗
bioRxiv2022

Genetic and ecological drivers of molt in a migratory bird

The ability of animals to sync the timing and location of molting (the replacement of hair, skin, exoskeletons or feathers) with peaks in resource availability has important implications for their ecology and evolution. In migratory birds, the timing and location of pre-migratory feather molting, a period when feathers are shed and replaced with newer, more aerodynamic feathers, can vary within and between species. While hypotheses to explain the evolution of intraspecific variation in the timing and location of molt have been proposed, little is known about the genetic basis of this trait or the specific environmental drivers that may result in natural selection for distinct molting phenotypes. Here we take advantage of intraspecific variation in the timing and location of molt in the iconic songbird, the Painted Bunting (Passerina ciris) to investigate the genetic and ecological drivers of distinct molting phenotypes. Specifically, we use genome-wide genetic sequencing in combination with stable isotope analysis to determine population genetic structure and molting phenotype across thirteen breeding sites. We then use genome-wide association analysis (GWAS) to identify a suite of genes associated with molting and pair this with gene-environment association analysis (GEA) to investigate potential environmental drivers of genetic variation in this trait. Associations between genetic variation in molt-linked genes and the environment are further tested via targeted SNP genotyping in 25 additional breeding populations across the range. Together, our integrative analysis suggests that molting is in part regulated by genes linked to feather development and structure (GLI2 and CSPG4) and that genetic variation in these genes is associated with seasonal variation in precipitation and aridity. Overall, this work provides important insights into the genetic basis and potential selective forces behind phenotypic variation in what is arguably one of the most important fitness-linked traits in a migratory bird.

ecology↗
bioRxiv2022

The influence of genetic structure on phenotypic diversity in the Australian mango (Mangifera indica) gene pool

Genomic selection is a promising breeding technique for tree crops to accelerate the development of new cultivars. However, factors such as genetic structure can create spurious associations between genotype and phenotype due to the shared history between populations with different trait values. Genetic structure can therefore reduce the accuracy of the genotype to phenotype map, a fundamental requirement of genomic selection models. Here, we employed 272 single nucleotide polymorphisms from 208 Mangifera indica cultivars to explore whether the genetic structure of the Australian mango gene pool explained variation in tree size, fruit blush colour and intensity. Our results show that genetic structure is weak, but cultivars imported from Southeast Asia (mainly those from Thailand) were genetically differentiated across multiple population genetic analyses. We find that genetic structure was strongly associated with phenotypic diversity in M. indica, suggesting that the history of these cultivars could drive spurious associations between loci and key mango phenotypes in the Australian mango gene pool. Incorporating such genetic structure in associations between genotype and phenotype has the potential to improve the accuracy of genomic selection, which can assist the development of new cultivars.

evolutionary biology↗
bioRxiv2022

Systematic analysis of transcriptional and epigenetic effects of genetic variation in Kupffer cells enables discrimination of cell intrinsic and environment-dependent mechanisms

Noncoding genetic variation is a major driver of phenotypic diversity but determining the underlying mechanisms and the cell types in which it acts remain challenging problems. Here, we investigate the impact of natural genetic variation provided by phenotypically diverse inbred strains of mice on gene expression and epigenetic landscapes of Kupffer cells. Analysis of gene expression in Kupffer cells and other liver cell types derived from C57BL/6J, BALB/cJ and A/J mice provided evidence for strain-specific differences in environmental factors influencing Kupffer cell phenotypes, including preferential Leptin signaling in BALB/cJ Kupffer cells. Systematic analysis of transcriptomic and epigenetic data from F1 hybrids of these mice, and transcriptomic data from strain-specific Kupffer cells engrafted into a common host enabled quantitative assessment of cis versus trans effects of genetic variation on gene expression and an estimate of cell autonomous versus non cell autonomous effects. Under homeostatic conditions, trans effects of genetic variation were dominant, with the majority of trans regulation being non cell autonomous. In contrast, strain specific responses to acutely administered LPS were primarily associated with genetic variation acting in cis to modify response elements for lineage determining and signal dependent transcription factors. Collectively, these findings reveal cell intrinsic and environmental effects of natural genetic variation on gene expression, demonstrate the use of enhancers as detectors of trans effects of genetic variation, and provide a new resource for understanding the impact of genetic variation on gene expression in Kupffer cells.

genomics↗