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bioRxiv2023

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

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

genomics↗

bioRxiv2023

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

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

microbiology↗

bioRxiv2023

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

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

evolutionary biology↗

bioRxiv2023

1LocusSim a mobile-friendly simulator for teaching population genetics

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

scientific communication and education↗

bioRxiv2023

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

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

evolutionary biology↗

bioRxiv2023

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

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

evolutionary biology↗

bioRxiv2023

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

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

evolutionary biology↗

bioRxiv2023

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

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

genomics↗

bioRxiv2023

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

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

evolutionary biology↗

bioRxiv2023

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

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

neuroscience↗

bioRxiv2023

A General Approach to Adjusting Genetic Studies for Assortative Mating

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

genomics↗

bioRxiv2023

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

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

genomics↗

bioRxiv2023

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

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

synthetic biology↗

bioRxiv2023

Polygenic barriers to gene flow: the role of dominance, haploid selection and heterogeneous genetic architectures

We consider how the genetic architecture underlying locally adaptive traits determines the strength of a barrier to gene flow in a mainland-island model. Assuming a general life cycle, we derive an expression for the effective migration rate when local adaptation is due to a polygenic trait under directional selection on the island, allowing for arbitrary fitness and dominance effects across loci. We show how the effective migration rate can be combined with classical single-locus diffusion theory to accurately predict multilocus differentiation between the mainland and island at migration-selection-drift equilibrium and determine the migration rate beyond which local adaptation collapses, while accounting for genetic drift and weak linkage. Using our efficient numerical tools, we then present a detailed study of the effects of dominance on barriers to gene flow, showing that when total selection is sufficiently strong, more recessive local adaptation generates stronger barriers to gene flow. We show that details of the haplodiplontic life cycle can be captured using a set of effective parameters, and consider how the relative strength of selection in the two phases affects barriers to gene flow. We then study how heterogeneous genetic architectures of local adaptation affect barriers to gene flow, characterizing adaptive differentiation at migration-selection balance for different distributions of fitness effects. We find that a more heterogeneous genetic architecture generally yields a stronger genome-wide barrier to gene flow and that the detailed genetic architecture underlying locally adaptive traits can have an important effect on observable differentiation when divergence is not too large. Lastly, we study the limits of our approach as loci become more tightly linked, showing that our predictions remain accurate over a large biologically relevant domain.

evolutionary biology↗

bioRxiv2023

Association of leaf spectral variation with functional genetic variants

The application of in-field and aerial spectroscopy to assess functional and phylogenetic variation in plants has led to novel ecological insights and supports global assessments of plant biodiversity. Understanding how plant genetic variation influences reflectance spectra will help harness this potential for biodiversity monitoring and improve understanding of why plants differ in functional responses to environmental change. Here, we use a well-resolved genetic mapping population derived from Multi-parent Advanced Generation Inter-cross (MAGIC) lines of Nicotiana attenuata to associate genetic differences with differences in leaf spectra between plants in a field experiment in their natural environment. We analyzed the leaf reflectance spectra using a hand-held spectroradiometer (350-2500 nm) on 616 fully genotyped plants of N. attenuata grown in a randomized block design. We tested three approaches to conducting Genome-Wide Association Studies on spectral variants. We introduce a new Hierarchical Spectral Clustering with Parallel Analysis (HSC-PA) method. This method efficiently captured the variation in our high-dimensional dataset and allowed us to discover a novel association, between a locus on chromosome 1 and the 734-1143 nm spectral range, spanning the red-edge and near-infrared regions that are sensitive to leaf structure and photosynthetic activity. This locus contains a candidate gene annotated as carbonic anhydrase, an enzyme involved in CO2 hydration and regulation of photosynthetic efficiency, suggesting a physiological link between variation in leaf optical properties and carbon assimilation. In contrast, an approach treating single wavelengths as phenotypes identified the same associations as HSC-PA, but without the statistical power to pinpoint significant associations. An index-based approach, which reduces complex spectra to a few dimensionless variables, detected two significant associations for ARDSI_Cw (a water-content-related index) with loci on chromosome 1 near genes annotated as a Zeta toxin domain-containing protein, and an Exocyst subunit Exo70 family protein. While these findings are biologically plausible, they represent a very narrow subset of the spectral variation captured by HSC-PA. The HSC-PA approach supports a comprehensive understanding of the genetic determinants of leaf spectral variation which is data-driven but human-interpretable, and lays a robust foundation for future research in linking plant genetics with biodiversity monitoring, large-scale ecological assessment and remote-sensing applications.

ecology↗

bioRxiv2023

Distribution theories for genetic line of least resistance and evolvability measures

Quantitative genetic theory on multivariate character evolution predicts that a populations response to directional selection tends to happen around the major axis of the genetic covariance matrix G--the so-called genetic line of least resistance. Inferences on the genetic constraints in this sense have traditionally been made by measuring the angle of deviation of evolutionary trajectories from the major axis, or more recently by calculating the amount of genetic variance--the Hansen-Houle evolvability--available along the trajectories. However, there have not been clear practical guidelines on how these quantities can be interpreted, especially in a high-dimensional space. This study summarizes pertinent distribution theories for relevant quantities, pointing out that they can be written as ratios of quadratic forms in evolutionary trajectory vectors by taking G as a parameter. For example, a beta distribution with appropriate parameters can be used as a null distribution for squared cosine of the angle of deviation from a major axis or subspace. More general cases can be handled with the probability distribution of ratios of quadratic forms in normal variables. Apart from its use in hypothesis-testing, this latter approach could potentially be used as a heuristic tool for looking into various selection scenarios like directional and/or correlated selection as parameterized with mean and covariance of selection gradients.

evolutionary biology↗

bioRxiv2023

High genetic diversification in a symbiotic marine annelid is driven by microgeography and glaciation

Marine invertebrates with limited dispersal abilities exhibit high levels of genetic divergence among populations. However, the spatial extent of genetic differentiation in these species remains poorly understood because identifying natural barriers to gene flow can be challenging in the marine environment. In this study, we investigated the population genetic structure of the interstitial annelid Olavius algarvensis, a species that lays eggs in its immediate surroundings and does not have an active dispersal phase. We analyzed the mitochondrial and nuclear genome sequences of hundreds to thousands of individuals from eleven sites in the Mediterranean, spanning microgeographic scales of < 5 km to macrogeographic scales of 800 km. Comparisons of single nucleotide polymorphisms (SNPs) in mitochondrial genomes revealed a complex history of introgression events, with as many as six mitochondrial lineages co-occurring in individuals from the same site. In contrast, SNP analyses of nuclear genomes revealed clear genetic differentiation at micro- and macrographic scales, characterised by a significant isolation by distance pattern (IBD). IBD patterns further indicated the presence of a historical physical barrier to gene flow on the east coast of the island of Elba corresponding to the historical shoreline around Elba during the Last Glacial Maximum in the Late Pleistocene, and highlighting the influence of geological forces in shaping population genetic structuring in the species today. Overall, our results provide strong empirical evidence for the high genomic diversification across spatial scales in marine interstitial fauna.

evolutionary biology↗

bioRxiv2023

Epigenetic context predicts gene expression variation and reproductive traits across genetically identical individuals

In recent decades, genome-wide association studies (GWAS) have been the major approach to understand the biological basis of individual differences in traits and diseases. However, GWAS approaches have limited predictive power to explain individual differences, particularly for complex traits and diseases in which environmental factors play a substantial role in their etiology. Indeed, individual differences persist even in genetically identical individuals, although fully separating genetic and environmental causation is difficult in most organisms. To understand the basis of individual differences in the absence of genetic differences, we measured two quantitative reproductive traits in 180 genetically identical young adult Caenorhabditis elegans roundworms in a shared environment and performed single-individual transcriptomics on each worm. We identified hundreds of genes for which expression variation was strongly associated with reproductive traits, some of which depended on individuals historical environments and some of which was random. Multiple small sets of genes together were highly predictive of reproductive traits, explaining on average over half and over a quarter of variation in the two traits. We manipulated mRNA levels of predictive genes to identify a set of causal genes, demonstrating the utility of this approach for both prediction and understanding underlying biology. Finally, we found that the chromatin environment of predictive genes was enriched for H3K27 trimethylation, suggesting that gene expression variation may be driven in part by chromatin structure. Together, this work shows that individual, non-genetic differences in gene expression are both highly predictive and causal in shaping reproductive traits.

genomics↗

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