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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2016

Assessing the relationship between height growth and molecular genetic variation in Douglas-fir (Pseudotsuga menziesii) provenances

Douglas-fir (Pseudotsuga menziesii) is a conifer tree native to western North America. In central Europe, it shows superior growth performance and is considered a suitable substitute for tree species impaired in vitality due to climate change. Maintenance and improvement of growth performance in a changing environment is a main challenge for forest tree breeders. In this context, genetic variation as a factor underlying phenotypic variation, but also as the basis for future adaptation, is of particular interest. The aims of this study were to analyse (i) genetic diversity of selected Douglas-fir provenances, (ii) variation in height growth among provenances, and (iii) to assess the link between genetic and phenotypic variation height growth. Genotyping was done on microsatellite loci. Effects of provenance, genotype, and site on height growth were assessed by fitting mixed linear models. The most significant genetic differentiation was observed between provenances of the coastal variety, versus a provenance of the interior variety originating from British Columbia. Although genetic differentiation among provenances of the coastal variety was lower, genetic structures within this variety were identified. Moreover, genetic diversity showed a latitudinal gradient with the southernmost provenances being more diverse, probably reflecting the species' evolutionary history. The modelling approach revealed that height growth differed significantly by provenance, site, and the interaction between site and provenance, demonstrating that height growth is under strong genetic control. Additionally, this analysis showed that genetic variation captured by the genotyped microsatellite loci was significantly related to variation in height growth, providing statistical evidence for a genetic component in the observed phenotypic variation.

Plant Biology↗
bioRxiv2016

Genome-wide analysis of ivermectin response by Onchocerca volvulus reveals that genetic drift and soft selective sweeps contribute to loss of drug sensitivity

BackgroundTreatment of onchocerciasis using mass ivermectin administration has reduced morbidity and transmission throughout Africa and Central/South America. Mass drug administration is likely to exert selection pressure on parasites, and phenotypic and genetic changes in several Onchocerca volvulus populations from Cameroon and Ghana - exposed to more than a decade of regular ivermectin treatment - have raised concern that sub-optimal responses to ivermectins anti-fecundity effect are becoming more frequent and may spread.\n\nMethodology/Principal FindingsPooled next generation sequencing (Pool-seq) was used to characterise genetic diversity within and between 108 adult female worms differing in ivermectin treatment history and response. Genome-wide analyses revealed genetic variation that significantly differentiated good responder (GR) and sub-optimal responder (SOR) parasites. These variants were not randomly distributed but clustered in ~31 quantitative trait loci (QTLs), with little overlap in putative QTL position and gene content between countries. Published candidate ivermectin SOR genes were largely absent in these regions; QTLs differentiating GR and SOR worms were enriched for genes in molecular pathways associated with neurotransmission, development, and stress responses. Finally, single worm genotyping demonstrated that geographic isolation and genetic change over time (in the presence of drug exposure) had a significantly greater role in shaping genetic diversity than the evolution of SOR.\n\nConclusions/SignificanceThis study is one of the first genome-wide association analyses in a parasitic nematode, and provides insight into the genomics of ivermectin response and population structure of O. volvulus. We argue that ivermectin response is a polygenically-determined quantitative trait in which identical or related molecular pathways but not necessarily individual genes likely determine the extent of ivermectin response in different parasite populations. Furthermore, we propose that genetic drift rather than genetic selection of SOR is the underlying driver of population differentiation, which has significant implications for the emergence and potential spread of SOR within and between these parasite populations.\n\nAuthor summaryOnchocerciasis is a human parasitic disease endemic across large areas of Sub-Saharan Africa, where more that 99% of the estimated 100 million people globally at-risk live. The microfilarial stage of Onchocerca volvulus causes pathologies ranging from mild itching to visual impairment and ultimately, irreversible blindness. Mass administration of ivermectin kills microfilariae and has an anti-fecundity effect on adult worms by temporarily inhibiting the development in utero and/or release into the skin of new microfilariae, thereby reducing morbidity and transmission. Phenotypic and genetic changes in some parasite populations that have undergone multiple ivermectin treatments in Cameroon and Ghana have raised concern that sub-optimal response to ivermectins anti-fecundity effect may increase in frequency, reducing the impact of ivermectin-based control measures. We used next generation sequencing of small pools of parasites to define genome-wide genetic differences between phenotypically characterised good and sub-optimal responder parasites from Cameroon and Ghana, and identified multiple genomic regions differentiating the response types. These regions were largely different between parasites from both countries but revealed common molecular pathways that might be involved in determining the extent of response to ivermectins anti-fecundity effect. These data reveal a more complex than previously described pattern of genetic diversity among O. volvulus populations that differ in their geography and response to ivermectin treatment.

genomics↗
bioRxiv2017

Evolution of genetic variance during adaptive radiation

Genetic correlations between traits can bias adaptation away from optimal phenotypes and constrain the rate of evolution. If genetic correlations between traits limit adaptation to contrasting environments, rapid adaptive divergence across a heterogeneous landscape may be difficult. However, if genetic variance can evolve and align with the direction of natural selection, then abundant allelic variation can promote rapid divergence during adaptive radiation. Here, we explored adaptive divergence among ecotypes of an Australian native wildflower by quantifying divergence in multivariate phenotypes of populations that occupy four contrasting environments. We investigated differences in multivariate genetic variance underlying morphological traits and examined the alignment between divergence in phenotype and divergence in genetic variance. We found that divergence in mean multivariate phenotype has occurred along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits, and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with most of the divergence in phenotype among ecotypes associated with a change in trait combinations that had substantial levels of genetic variance in each ecotype. Overall, our results suggest that divergent natural selection acting on high levels of standing genetic variation might fuel ecotypic differentiation during the early stages of adaptive radiation.

evolutionary biology↗
bioRxiv2017

A Map Of Genetic Interactions In Cancer Cells

Cancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and, as a side effect, create new vulnerabilities for potential therapeutic exploitation. To systematically identify genotype-dependent vulnerabilities and synthetic lethal interactions, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework that integrates CRISPR/Cas9 screens originating from many different libraries and laboratories to build genetic interaction maps. It builds on analytical approaches that were established for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cell lines combining functional data with information on genetic variants to explore the relationships of more than 2.1 million gene-background relationships. In addition to known dependencies, our analysis identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities associated with aberrant Wnt/{beta}-catenin signaling identified GANAB and PRKCSH as new positive regulators of Wnt/{beta}-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data is included.

systems biology↗
bioRxiv2017

The human oral microbiome is shaped by shared environment rather than genetics: evidence from a large family of closely-related individuals

The human microbiome is affected by multiple factors, including the environment and host genetics. In this study, we analyzed the oral microbiome of an extended family of Ashkenazi Jewish individuals living in several cities and investigated associations with both shared household and host genetic similarities. We found that environmental effects dominated over genetic ones. While there was weak evidence of geographic structuring at the level of cities, we observed a large and significant effect of shared household on microbiome composition, supporting the role of immediate shared environment in dictating the presence or absence of taxa. This effect was also seen when including adults who had grown up in the same household but moved out prior to the time of sampling, suggesting that the establishment of the oral microbiome earlier in life may affect its long-term composition. We found weak associations between host genetic relatedness and microbiome dissimilarity when using family pedigrees as proxies for genetic similarity. However this association disappeared when using more accurate measures of kinship based on genome-wide genetic markers, indicating that environment rather than host genetics is the dominant factor affecting the composition of the oral microbiome in closely-related individuals. Our results support the concept that there is a consistent core microbiome conserved across global scales, but that small-scale effects due to shared living environment significantly affect microbial community composition.\n\nIMPORTANCEPrevious research shows that relatives have a more similar oral microbiome composition than non-relatives, but it remains difficult to distinguish the effects of relatedness and shared household environment. Furthermore, pedigree measures may not accurately measure host genetic similarity. In this study, we include genetic relatedness based on genome-wide SNPs (rather than pedigree measures) and shared environment in the same analysis. We quantify the relative importance of these factors by studying the oral microbiome in members of a large extended Ashkenazi Jewish family who share a similar diet and lifestyle despite living in different locations. We find that host genetics plays no significant role and that the dominant factor is shared environment at the household level. We also find that this effect appears to persist in individuals who have moved out of the parental household, suggesting that the oral microbiome established earlier in life persists long-term.

microbiology↗
bioRxiv2017

Genetic Load Makes Cancer Cells More Sensitive To Common Drugs: Evidence From Cancer Cell Line Encyclopedia

Genetic alterations initiate tumors and enable the evolution of drug resistance. The pro-cancer view of mutations is however incomplete, and several studies show that mutational load can reduce tumor fitness. Given its negative effect, genetic load should make tumors more sensitive to anticancer drugs. Here, we test this hypothesis across all major types of cancer from the Cancer Cell Line Encyclopedia, that provides genetic and expression data of 496 cell lines together with their response to 24 common anticancer drugs. We found that the efficacy of 9 out of 24 drugs showed significant association with genetic load in a pan-cancer analysis. The associations for some tissue-drug combinations were remarkably strong with genetic load explaining up to 83% of the variance in the drug response. Overall, the role of genetic load depended on both the drug and the tissue type with 10 tissues being particularly vulnerable to genetic load. We also identified changes in gene expression associated with increased genetic load, which included cell-cycle checkpoints, DNA damage and apoptosis. Our results show that genetic load is an important component of tumor fitness and can predict drug sensitivity. Beyond being a biomarker, genetic load might be a new, unexplored vulnerability of cancer.

cancer biology↗
bioRxiv2020

Spatial Proximity Moderates Genotype Uncertainty in Genetic Tagging Studies

Accelerating declines of an increasing number of animal populations worldwide necessitate methods to reliably and efficiently estimate demographic parameters such as population density and trajectory. Standard methods for estimating demographic parameters from noninvasive genetic samples are inefficient because lower quality samples cannot be used, and they do not allow for errors in individual identification. We introduce the Genotype Spatial Partial Identity Model (SPIM), which integrates a genetic classification model with a spatial population model to combine both spatial and genetic information, thus reducing genotype uncertainty and increasing the precision of demographic parameter estimates. We apply this model to data from a study of fishers (Pekania pennanti) in which 37% of samples were originally discarded because of uncertainty in individual identity. The Genotype SPIM density estimate using all collected samples was 25% more precise than the original density estimate, and the model identified and corrected 3 errors in the original individual identity assignments. A simulation study demonstrated that our model increased the accuracy and precision of density estimates 63% and 42%, respectively, using 3 PCRs per genetic sample. Further, the simulations showed that the Genotype SPIM model parameters are identifiable with only one PCR per sample, and that accuracy and precision are relatively insensitive to the number of PCRs for high quality samples. Current genotyping protocols devote the majority of resources to replicating and confirming high quality samples, but when using the Genotype SPIM, genotyping protocols could be more efficient by devoting more resources to low quality samples. SignificanceWe present a new statistical framework for the estimation of animal demographic parameters, such as abundance, density, and growth rate, from noninvasive genetic samples (e.g., hair, scat). By integrating a genetic classification model with a spatial population model, we show that accounting for spatial proximity of samples reduces genotype uncertainty and improves parameter estimation. Our method produces a fundamentally different approach to genetic capture-recapture by sharing information between the normally disjunct steps of assigning individual identities to genetic samples and modeling population processes. Further, it leads to more efficient protocols for processing genetic samples, which can lower project costs and expand opportunities for applying noninvasive genetics to conservation and management problems.

ecology↗
bioRxiv2020

Clonality and inbreeding amplifies genetic isolation and mate limitation in a rare montane woody plant (Persoonia hindii; Proteaceae)

Small populations have genetic attributes that make them prone to extinction, including low effective population size (Ne), increased levels of inbreeding, and negative impacts from genetic drift. Some small populations are also clonal with low levels of genetic diversity, restricted seed dispersal, and high levels of genetic structure. Together, these attributes make species with small, isolated, clonal populations unlikely to persist under environmental change. We investigated an endangered woody plant species (Persoonia hindii) in eastern Australia to answer key questions about genetic differentiation, migration rates, population sizes, size of clones, mating system and Ne. We identified 587 single nucleotide polymorphisms. Of the 88 individual stems collected from 15 sites across the entire distribution of P. hindii, we identified 30 multi-locus genotypes (MLG). Additional fine-scale genotyping of two sites (49 and 47 stems) detected a dominant genet within each site occupying a minimum area of 20 m2. Global population differentiation was high (FST 0.22) with very low migration rates (0.048 - 0.064). We identified some population structure with variable site pairwise differentiation (0.015 - 0.32) with no detectable spatial autocorrelation. Species wide inbreeding coefficient was 0.42 (FIT), supporting the direct estimate of 82% selfing. Estimated Ne was extremely small (15), indicating that genetic drift may be reducing genetic diversity and increasing genetic load through fixation of deleterious alleles. Clonality and inbreeding combined with negligible gene flow suggests limited adaptive capacity to respond to climate challenges. Genetic rescue, through assisted gene migration and experimental translocations, would enhance the persistence of natural populations.

evolutionary biology↗
bioRxiv2020

A unifying framework disentangles genetic, epigenetic, and stochastic sources of drug-response variability in an in vitro model of tumor heterogeneity

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability of targeted therapy response is observed. Additional genetic mutations can only partially explain this variability, leading to consideration of non-genetic factors, such as "stem-like" and "mesenchymal" phenotypic states, as critical contributors to tumor relapse and resistance. Here, we show that both genetic and non-genetic factors contribute to targeted drug-response variability in an experimental tumor heterogeneity model based on multiple versions and clonal sublines of PC9, the archetypal EGFR-mutant non-small cell lung cancer cell line. We observe significant drug-response variability across PC9 cell line versions, among sublines, and within sublines. To disentangle genetic, epigenetic, and stochastic components underlying this variability, we adopt a theoretical framework whereby distinct genetic states give rise to multiple epigenetic "basins of attraction", across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Using mutational impact analysis, single-cell differential gene expression, and semantic similarity of gene ontology terms to connect genomics and transcriptomics, we establish a baseline of genetic differences explaining drug-response variability across PC9 cell line versions. In contrast, with the same approach, we conclude that in all but one of the clonal sublines, drug-response variability is due to epigenetic rather than genetic differences. Finally, using a clonal drug-response assay and stochastic simulations, we attribute drug-response variability within sublines to intracellular stochastic fluctuations and confirm that one subline likely contains a genetic resistance mutation that emerged in the absence of selective pressures. We propose that a theoretical framework deconvolving the complex interplay among genetic, epigenetic, and stochastic sources of intratumoral heterogeneity will lead to novel therapeutic strategies to combat tumor relapse and resistance.

systems biology↗
bioRxiv2020

How does the strength of selection influence genetic correlations ?

Genetic correlations between traits can strongly impact evolutionary responses to selection, and may thus impose constraints on adaptation. Theoretical and empirical work has made it clear that, without strong linkage, genetic correlations at evolutionary equilibrium result from an interplay of correlated pleiotropic effects of mutations, and correlational selection favoring combinations of trait values. However, it is not entirely clear how the strength of stabilizing selection influences this compromise between mutation and selection effects on genetic correlations. Here, we show that the answer to this question crucially depends on the intensity of genetic drift. In large, effectively infinite populations, genetic correlations are unaffected by the strength of selection, regardless of whether the genetic architecture involves common small-effect mutations (Gaussian regime), or rare large-effect mutations (House-of-Cards regime). In contrast in finite populations, the strength of selection does affect genetic correlations, by shifting the balance from drift-dominated to selection-dominated evolutionary dynamics. The transition between these domains depends on mutation parameters to some extent, but with a similar dependence of genetic correlation on the strength of selection. Our results are particularly relevant for understanding how senescence shapes patterns of genetic correlations across ages, and genetic constraints on adaptation during colonization of novel habitats.

evolutionary biology↗
bioRxiv2020

Sex-Specific Genetic Architecture Of Behavioral Traits In A Spider

Sex differences in behavioral traits are common, but we know little about the role of sexual selection in shaping these traits. Estimating sex-specific genetic effects and cross-sex genetic correlations can provide insights into sex-specific selection and on whether evolution can shape independent expression of behavioral traits across the sexes. We conducted a quantitative genetic study in a sexually-size-dimorphic spider, Larinioides sclopetarius, which exhibits sex differences in adult life-styles. We observed pedigreed spiders for aggression, activity, exploration and boldness, and used animal models to disentangle genetic and environmental influences on these behaviors. We detected higher additive genetic variances in activity and aggression in males compared to females, but no sex differences in quantitative genetic estimates for exploration and boldness. The estimated mean cross-sex genetic correlation in all traits were close to zero suggesting these traits could have flexibility for sex-independent evolution. We note however, that the 95% credible intervals of cross-sex genetic correlation are large, and thus estimates uncertain. Our results imply that individual variation in aggression and activity might stem from sex-specific selection acting on these traits. The estimates of sex-specific additive genetic variation and cross-sex genetic correlation suggests their further sex-independent evolution. Taken together, our results support the notion that sexual selection can play an important role shaping behavioral traits.

evolutionary biology↗
bioRxiv2020

Examining the genetic influences of migratory status on island colonisation by naturally and recently established populations of a bird species

AimFounder effects and recurrent immigration are two major factors that potentially contribute to genetic differentiation and population persistence in the early-stage of remote island colonization. However, their relative importance remains controversial. By conducting population genetics analyses of multiple remote island populations of the bull-headed shrike established naturally within several decades, we examined the relative contributions of founder effects and recurrent immigration on these island populations. LocationJapan TaxonLanius bucephalus MethodsWe used 15 microsatellite loci to analyze the population genetics of four newly established island populations and five Japanese mainland populations. Allelic richness, heterozygosity, genetic differentiation, and the strength of the genetic bottleneck were compared among the islands. Two analyses, STRUCTURE and the DAPC, were conducted to assess the relative influence of founder effects and recurrent immigration on genetic differentiation. Temporal samples collected over eight years on Minami-Daito Island were used to detect any change in genetic structure due to recurrent immigration. ResultsThe founder effect strongly influenced genetic differentiation on the most remote oceanic island, Chichi-jima Island. However, this population became extinct 20 years after colonization, possibly owing to a lack of recurrent immigration. The founder effect moderately influenced a land-bridge island, Kikai-jima Island, indicating the presence of a relatively large founder population without recurrent immigration. Surprisingly, another distant oceanic island, Minami-Daito Island, was likely subject to multiple recurrent immigration events from the mainland, which obscured any genetic differentiation previously established by the founder effect. Main conclusionUnderlying the island-specific population dynamics of colonization, founder effects contributed to the genetic differentiation among the three studied island populations. Importantly, however, recurrent immigration strongly affected the population persistence and subsequent evolutionary processes of remote island populations, potentially overwhelming the founder effect. We argue the importance of recurrent immigration in highly remote island colonization, which has been previously overlooked.

ecology↗
bioRxiv2021

A Method for Cost-Effective and Rapid Characterization of Genetic Parts

Characterizing and cataloging genetic parts are critical to the design of useful genetic circuits. Having well-characterized parts allows for the fine-tuning of genetic circuits, such that their function results in predictable outcomes. With the growth of synthetic biology as a field, there has been an explosion of genetic circuits that have been implemented in microbes to execute functions pertaining to sensing, metabolic alteration, and cellular computing. Here, we show a cost-effective and rapid method for characterizing genetic parts. Our method utilizes cell-free lysate, prepared in-house, as a medium to evaluate parts via the expression of a reporter protein. Template DNA is prepared by PCR-amplification using inexpensive primers to add variant parts to the reporter gene, and the template is added to the reaction as linear DNA without cloning. Parts that can be added in this way include promoters, operators, ribosome binding sites, insulators, and terminators. This approach, combined with the incorporation of an acoustic liquid handler and 384-well plates, allows the user to carry out high-throughput evaluations of genetic parts in a single day. By comparison, cell-based screening approaches require time-consuming cloning and have longer testing times due to overnight culture and culture density normalization steps. Further, working in cell-free lysate allows the user to exact tighter control over the expression conditions through the addition of exogenous components, or by titrating DNA concentrations rather than relying on limited plasmid copy numbers. Because this method retains a cell-like environment, the function of the genetic part will typically mimic its function in whole cells. SUMMARYWell-characterized genetic parts are necessary for the design of novel genetic circuits. Here we describe a cost-effective, high-throughput method for rapidly characterizing genetic parts. Our method reduces cost and time by combining cell-free lysates, linear DNA to avoid cloning, and acoustic liquid handling to increase throughput and reduce reaction volumes.

synthetic biology↗
bioRxiv2021

Population bottlenecks constrain microbiome diversity and host genetic variation impeding fitness

It is becoming increasingly clear that microbial symbionts influence key aspects of their hosts fitness, and vice versa. This may fundamentally change our thinking about how microbes and hosts interact in influencing fitness and adaptation to changing environments. Here we explore how reductions in population size commonly experienced by threatened species influence microbiome diversity. Consequences of such reductions are normally interpreted in terms of a loss of genetic variation, increased inbreeding and associated inbreeding depression. However, fitness effects of population bottlenecks might also be mediated through microbiome diversity, such as through loss of functionally important microbes. Here we utilise 50 Drosophila melanogaster lines with different histories of population bottlenecks to explore these questions. The lines were phenotyped for egg-to-adult viability and their genomes sequenced to estimate genetic variation. The bacterial 16S rRNA gene was amplified in these lines to investigate microbial diversity. We found that 1) host population bottlenecks constrained microbiome richness and diversity, 2) core microbiomes of hosts with low genetic variation were constituted from subsets of microbiomes found in flies with higher genetic variation, 3) both microbiome diversity and host genetic variation contributed to host population fitness, 4) connectivity and robustness of bacterial networks was low in the inbred lines regardless of host genetic variation, 5) reduced microbial diversity was associated with weaker evolutionary responses of hosts in stressful environments, and 6) these effects were unrelated to Wolbachia density. These findings suggest that population bottlenecks reduce hologenomic variation (combined host and microbial genetic variation). Thus, while the current biodiversity crisis focuses on population sizes and genetic variation of eukaryotes, an additional focal point should be the microbial diversity carried by the eukaryotes, which in turn may influence host fitness and adaptability with consequences for the persistence of populations. Author summaryIt is becoming increasingly clear that organisms and the microbes that live on or in them - their microbiome - affect each other in profound ways that we are just beginning to understand. For instance, a diverse microbiome can help maintain metabolic functions or fight pathogens causing diseases. A disrupted microbiome may be especially critical for animals and plants that occur in low numbers because of threats from e.g. human exploitation or climate change, as they may already suffer from genetic challenges such as inbreeding and reduced evolutionary potential. The importance of such a reduction in population size, called a bottleneck, on the microbial diversity and the potential interactive effects on host health remains unexplored. Here we experimentally test these associations by investigating the microbiomes of 50 inbred or non-inbred populations of vinegar flies. We found that restricting the population size constrain the hosts genetic variation and simultaneously decreases the diversity of the microbiome that they harbor, and that both effects were detrimental to host fitness. The microbial communities in inbred host populations were less robust than in their non-inbred counterparts, suggesting that we should increasingly consider the microbiome diversity, which may ultimately influence the health and persistence of threatened species.

evolutionary biology↗
bioRxiv2021

Genetic compensation of triacylglycerol biosynthesis in the green microalga Chlamydomonas reinhardtii

Genetic compensation through transcriptional adaptation has been proposed to explain phenotypic differences between gene knockouts and knockdowns. With the rapid development of reverse genetic tools such as CRISPR/Cas9 and RNAi in microalgae, it is increasingly important to assess whether genetic compensation affects the phenotype of engineered algal mutants. While exploring triacylglycerol (TAG) biosynthesis pathways in Chlamydomonas reinhardtii, it was discovered that knockout of certain genes catalyzing rate-limiting steps of TAG biosynthesis, type-2 diacylglycerol acyltransferase genes (DGTTs), triggered genetic compensation under abiotic stress conditions. Genetic compensation of a DGTT1 null mutation by a related PDAT gene was observed regardless of the strain background or mutagenesis approach, e.g., CRISPR/Cas 9 or insertional mutagenesis. However, no compensation was found in the PDAT knockout mutant. The effect of PDAT knockout was evaluated in a {Delta}vtc1 mutant, in which PDAT was up-regulated under stress. Knockout of PDAT in the {Delta}vtc1 background induced a 12.8-fold upregulation of DGTT1 and a 272.3% increase in TAG content in {Delta}vtc1/pdat1 cells, while remaining viable. These data suggest that genetic compensation contributes to the genetic robustness of microalgal TAG biosynthetic pathways, maintaining lipid and redox homeostasis in the knockout mutants under abiotic stress with a mechanism distinct from that found in plants. This work demonstrates examples of genetic compensation in microalgae, implies the physiological relevance of genetic compensation in TAG biosynthesis, and provides guidance for future genetic engineering and mutant characterization efforts.

plant biology↗
bioRxiv2021

Extreme climatic events but not environmental heterogeneity shape within-population genetic variation in maritime pine

How evolutionary forces interact to maintain quantitative genetic variation within populations has been a matter of extensive theoretical debates. While mutation and migration increase genetic variation, natural selection and genetic drift are expected to deplete it. To date, levels of genetic variation observed in natural populations are hard to predict without accounting for other processes, such as balancing selection in heterogeneous environments. We aimed to empirically test three hypotheses: (i) admixed populations have higher quantitative genetic variation due to introgression from other gene pools, (ii) quantitative genetic variation is lower in populations from harsher environments (i.e. experiencing stronger selection), and (iii) quantitative genetic variation is higher in populations from spatially heterogeneous environments. We used phenotypic measurements of five growth, phenological and functional traits from three clonal common gardens, consisting of 523 clones from 33 populations of maritime pine (Pinus pinaster Aiton). Populations from harsher climates (mainly colder areas) showed lower genetic variation for height in the three common gardens. Surprisingly, we did not find any association between within-population genetic variation and environmental heterogeneity or population admixture for any trait. Our results suggest a predominant role of natural selection in driving within-population genetic variation, and therefore indirectly their adaptive potential.

evolutionary biology↗
bioRxiv2021

Genomic estimation of quantitative genetic parameters in wild admixed populations

O_LIHeritable genetic variation among free-living animals or plants is essential for populations to respond to selection and adapt. It is therefore important to be able to estimate additive genetic variance VA, which can be obtained using a generalized linear mixed model known as the animal model. An underlying assumption of the standard animal model is that the study population is genetically unstructured, which is often unrealistic. In fact, admixture might be the norm rather than the exception in the wild, like in geographically structured populations, in the presence of (im)migration, or in re-introduction and conservation contexts. Unfortunately, animal model estimators may be biased in such cases. So-called genetic group animal models that account for genetically differentiated subpopulations have recently become popular, but methodology is currently only available for cases where relatedness among individuals can be estimated from pedigrees. C_LIO_LITo ensure that genetic group animal models with heterogeneous VA remain applicable to populations with genomic data but no pedigrees, there is a clear need to generalize these models to the case when exclusively genomic data is available. We therefore introduce such methodology for wild admixed systems by extending methods that were recently suggested in the context of plant breeding. Our extension relaxes the limiting assumptions that currently restrict their use to artificial breeding setups. C_LIO_LIWe illustrate the usefulness of the extended genomic genetic groups animal model on a wild admixed population of house sparrows resident in an island system in Northern Norway, where genome-wide data on more than 180 000 single nucleotide polymorphisms (SNPs) is available to derive genomic relatedness. We compare our estimates of quantitative genetic parameters to those derived from a corresponding pedigree-based genetic groups animal model. The satisfactory agreement indicates that the new method works as expected. C_LIO_LIOur extension of the very popular animal model ensures that the upcoming challenges with increasing availability of genomic data for quantitative genetic studies of wild admixed populations can be handled. To make the method widely available to the scientific community, we offer guidance in the form of a tutorial including step-by-step instructions to facilitate implementation. C_LI

evolutionary biology↗
bioRxiv2022

Spatiotemporal changes in genetic diversity and structure of a recent fish invasion in eastern North America

Introduced and geographically expanding populations experience similar eco-evolutionary challenges, including founder events, genetic bottlenecks, and novel environments. Theory predicts that reduced genetic diversity resulting from such genetic phenomena limits the colonization success of introduced populations. We examined an invasive population of a Eurasian freshwater fish, Tench (Tinca tinca), that has been expanding geographically in eastern North America for three decades. Using genomic data, we evaluated evidence for single versus multiple introductions and the connectivity of the population across the entire range in which it has been spreading. Tench exhibited low levels of genetic diversity, a lack of marked population subdivision across time and space, and evidence of a recent genetic bottleneck. These results suggest that the invasion stemmed from a single introduction, consistent with the reported invasion history. Furthermore, the large genetic neighbourhood size and weak within-population genetic substructure suggest high connectivity across the invaded range, despite the large area occupied, and no evidence of substantial diminution of genetic diversity from the invasion core to the margins. As eradicating the species within a ~112 km radius would be necessary to prevent recolonization, eradicating Tench is likely not feasible at watershed--and possibly local--scales. Management should instead focus on reducing abundance in priority conservation areas to mitigate adverse impacts. Our study supports the argument that introduced populations can thrive despite recent bottlenecks and low levels of genetic diversity, and it suggests that landscape heterogeneity and population demographics can generate variability in spatial patterns of genetic diversity within a single range expansion.

genomics↗