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Results for “genetics”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

Genome improvement and genetic map construction for Aethionema arabicum, the first divergent branch in the Brassicaceae family

BackgroundThe genus Aethionema is a sister-group to the core-group of the Brassicaceae family that includes Arabidopsis thaliana and the Brassica crops. Thus, Aethionema is phylogenetically well-placed for the investigation and understanding of genome and trait evolution across the family. We aimed to improve the quality of the reference genome draft version of the annual species Aethionema arabicum. Secondly, we constructed the first Ae. arabicum genetic map. The improved reference genome and genetic map enabled the development of each other.\n\nResultsWe started with the initially published genome (version 2.5). PacBio and MinION sequencing together with genetic map v2.5 were incorporated to produce the new reference genome v3.0. The improved genome contains 203 MB of sequence, with approximately 94% of the assembly made up of called bases, assembled into 2,883 scaffolds. The N50 (10.3 MB) represents an 80-fold over the initial genome release. We generated a Recombinant Inbred Line (RIL) population that was derived from two ecotypes: Cyprus and Turkey (the reference genotype. Using a Genotyping by Sequencing (GBS) approach, we generated a high-density genetic map with 749 (v2.5) and then 632 SNPs (v3.0) was generated. The genetic map and reference genome were integrated, thus greatly improving the scaffolding of the reference genome into 11 linkage groups.\n\nConclusionsWe show that long-read sequencing data and genetics are complementary, resulting in an improved genome assembly in Ae. arabicum. They will facilitate comparative genetic mapping work for the Brassicaceae family and are also valuable resources to investigate wide range of life history traits in Aethionema.

genomics↗

bioRxiv2019

Security and Privacy Concerns Regarding Genetic Data in Mobile Health Record Systems: An Empirical Study from Turkey

With the increasing use of genetic testing and applications of bioinformatics in healthcare, genetic and genomic data needs to be integrated into electronic health systems. We administered a descriptive survey to 174 participants to elicit their views on the privacy and security of mobile health record systems and inclusion of their genetic data in these systems. A survey was implemented online and on site in two genetic diagnostic centres. Nearly half of the participants or their close family members had undergone genetic testing. Doctors constituted the only profession group that people trusted for the privacy of their health and genetic data; however, people chose to limit even their doctors access to their genetic/health records. The majority of the respondents preferred to keep full access for themselves. Several participants had negative experience or preconceptions about electronic health records: the medical reports of 9.7% of the respondents had been used or released without their consent, 15.1% stated that they avoided being tested due to violation risks, and 3.5% asked their doctors to enter a less embarrassing health status in their records. The participants wanted to see some regulations and security measurements before using any system for their health/genetic data. In addition, significantly more participants stating that storing genetic data in a mobile system was riskier compared to other health data. Furthermore, the comparative analysis revealed that being young, being a woman and having higher education were associated with having greater privacy concerns.

bioinformatics↗

bioRxiv2019

Genetic overlap between psychotic experiences in the community across age and with psychiatric disorders

BackgroundThis study explores the degree to which genetic influences on psychotic experiences are stable across adolescence and adulthood, and their overlap with psychiatric disorders.\n\nMethodsGenome-wide association results were obtained for adolescent psychotic experiences and negative symptom traits (N = 6,297-10,098), schizotypy (N = 3,967-4,057) and positive psychotic experiences in adulthood (N = 116,787-117,794), schizophrenia (N = 150,064), bipolar disorder (N = 41,653) and depression (N = 173,005). Linkage disequilibrium score regression was used to estimate genetic correlations. Implicated genes from functional and gene-based analyses were compared. Mendelian Randomization was performed on trait pairs with significant genetic correlations.\n\nResultsSubclinical auditory and visual hallucinations and believing in conspiracies during adulthood were significantly genetically correlated with schizophrenia (rg = .27-.67) and major depression (rg = .41-.96) after correction for multiple testing. Auditory and visual subclinical hallucinations were highly genetically correlated (rg = .95). Cross-age genetic correlations for psychotic experiences were not significant. Gene mapping and gene association analyses revealed 14 possible genes associated with psychotic experiences that overlapped across age for psychotic experiences or between psychotic experiences and psychiatric disorders. Mendelian Randomization indicated bidirectional associations between auditory and visual hallucinations in adults but did not support causal relationships between psychotic experiences and psychiatric disorders.\n\nConclusionsPsychotic experiences in adulthood may be more linked genetically to schizophrenia and major depression than psychotic experiences in adolescence. Our study implicated specific genes that are associated with psychotic experiences across development as well as genes shared between psychotic experiences and psychiatric disorders.

genomics↗

bioRxiv2019

The effect of population bottleneck size and selective regime on genetic diversity and evolvability in bacteria

Population bottlenecks leading to a drastic reduction of the population size are common in the evolutionary dynamics of natural populations; their occurrence is known to have implications for genome evolution due to genetic drift, the consequent reduction in genetic diversity and the rate of adaptation. Nevertheless, an empirical characterization of the effect of population bottleneck size on evolutionary dynamics of bacteria is currently lacking. Here we show that selective conditions have a stronger effect on the evolutionary history of bacteria in comparison to genetic drift following population bottlenecks. We evolved Escherichia coli populations under three different population bottlenecks (small, medium, large) in two temperature regimes (37{degrees}C and 20{degrees}C). We find a high genetic diversity in the large in comparison to the small bottleneck size. Nonetheless, the cold temperature led to reduced genetic diversity in all bottleneck sizes, hence, the temperature has a stronger effect on the genetic diversity in comparison to the bottleneck size. A comparison of the fitness gain among the evolved populations reveals a similar pattern where the temperature has a significant effect on the fitness. Our study demonstrates that population bottlenecks are an important determinant of the evolvability in bacteria; their consequences depend on the selective conditions and are best understood via their effect on the standing genetic variation.

evolutionary biology↗

bioRxiv2019

Continent-wide effects of urbanization on bird and mammal genetic diversity

AbstractUrbanization and associated environmental changes are causing global declines in vertebrate populations. In general, population declines of the magnitudes now detected should lead to reduced effective population sizes for animals living in proximity to humans and disturbed lands. This is cause for concern because effective population sizes set the rate of genetic diversity loss due to genetic drift, the rate of increase in inbreeding, and the efficiency with which selection can act on beneficial alleles. We predicted that the effects of urbanization should decrease effective population size and genetic diversity, and increase population-level genetic differentiation. To test for such patterns, we repurposed and reanalyzed publicly archived genetic data sets for North American birds and mammals. After filtering, we had usable raw genotype data from 85 studies and 41,023 individuals, sampled from 1,008 locations spanning 41 mammal and 25 bird species. We used census-based urban-rural designations, human population density, and the Human Footprint Index as measures of urbanization and habitat disturbance. As predicted, mammals sampled in more disturbed environments had lower effective population sizes and genetic diversity, and were more genetically differentiated from those in more natural environments. There were no consistent relationships detectable for birds. This suggests that, in general, mammal populations living near humans may have less capacity to respond adaptively to further environmental changes, and be more likely to suffer from effects of inbreeding.

evolutionary biology↗

bioRxiv2019

Population genomic SNPs from epigenetic RADs: gaining genetic and epigenetic data from a single established next-generation sequencing approach

O_LIEpigenetics is increasingly recognised as an important molecular mechanism underlying phenotypic variation. To study DNA methylation in ecological and evolutionary contexts, epiRADseq is a cost-effective next-generation sequencing technique based on reduced representation sequencing of genomic regions surrounding non-/methylated sites. EpiRADseq for genome-wide methylation abundance and ddRADseq for genome-wide SNP genotyping follow very similar library and sequencing protocols, but to date these two types of dataset have been handled separately. Here we test the performance of using epiRADseq data to generate SNPs for population genomic analyses.\nC_LIO_LIWe tested the robustness of using epiRADseq data for population genomics with two independent datasets: a newly generated single-end dataset for the European whitefish Coregonus lavaretus, and a re-analysis of publicly available, previously published paired-end data on corals. Using standard bioinformatic pipelines with a reference genome and without (i.e. de novo catalogue loci), we compared the number of SNPs retained, population genetic summary statistics, and population genetic structure between data drawn from ddRADseq and epiRADseq library preparations.\nC_LIO_LIWe find that SNPs drawn from epiRADseq are similar in number to those drawn from ddRADseq, with a 55-83% of SNPs being identified by both methods. Genotyping error rate was <5% in both approaches. For summary statistics such as heterozygosity and nucleotide diversity, there is a strong correlation between methods (Spearmans rho > 0.88). Furthermore, identical patterns of population genetic structure were recovered using SNPs from epiRADseq and ddRADseq approaches.\nC_LIO_LIWe show that SNPs obtained from epiRADseq are highly similar to those from ddRADseq and are equivalent for estimating genetic diversity and population structure. This finding is particularly relevant to researchers interested in genetics and epigenetics on the same individuals because using a single epigenomic approach to generate two datasets greatly reduces the time and financial costs compared to using these techniques separately. It also efficiently enables correction of epigenetic estimates with population genetic data. Many studies will benefit from a combinatorial approach with genetic and epigenetic markers and this demonstrates a single, efficient method to do so.\nC_LI

genomics↗

bioRxiv2019

Genetic perturbations of disease risk genes in mice capture transcriptomic signatures of late-onset Alzheimer’s disease

BackgroundNew genetic and genomic resources have identified multiple genetic risk factors for late-onset Alzheimers disease (LOAD) and characterized this common dementia at the molecular level. Experimental studies in model organisms can validate these associations and elucidate the links between specific genetic factors and transcriptomic signatures. Animal models based on LOAD-associated genes can potentially connect common genetic variation with LOAD transcriptomes, thereby providing novel insights into basic biological mechanisms underlying the disease.\n\nMethodsWe performed RNA-Seq on whole brain samples from a panel of six-month-old female mice, each carrying one of the following mutations: homozygous deletions of Apoe and Clu; hemizygous deletions of Bin1 and Cd2ap; and a transgenic APOE{varepsilon}4. Similar data from a transgenic APP/PS1 model was included for comparison to early-onset variant effects. Weighted gene co-expression network analysis (WGCNA) was used to identify modules of correlated genes and each module was tested for differential expression by strain. We then compared mouse modules with human postmortem brain modules from the Accelerating Medicines Partnership for AD (AMP-AD) to determine the LOAD-related processes affected by each genetic risk factor.\n\nResultsMouse modules were significantly enriched in multiple AD-related processes, including immune response, inflammation, lipid processing, endocytosis, and synaptic cell function. WGCNA modules were significantly associated with Apoe-/-, APOE{varepsilon}4, Clu-/-, and APP/PS1 mouse models. Apoe-/-, GFAP-driven APOE{varepsilon}4, and APP/PS1 driven modules overlapped with AMP-AD inflammation and microglial modules; Clu-/- driven modules overlapped with synaptic modules; and APP/PS1 modules separately overlapped with lipid-processing and metabolism modules.\n\nConclusionsThis study of genetic mouse models provides a basis to dissect the role of AD risk genes in relevant AD pathologies. We determined that different genetic perturbations affect different molecular mechanisms comprising AD, and mapped specific effects to each risk gene. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants.

neuroscience↗

bioRxiv2019

Loss of diversity and accumulation of genetic load in doubled-haploid lines from European maize landrace

Maize landraces are well adapted to their local environments and present valuable sources of genetic diversity for breeding and conservation. But the maintenance of open-pollinated landraces in ex-situ programs is challenging, as regeneration of seed can often lead to inbreeding depression and the loss of diversity due to genetic drift. Recent reports suggest that the production of doubled-haploid (DH) lines from landraces may serve as a convenient means to preserve genetic diversity in a homozygous form that is immediately useful for modern breeding. The production of doubled-haploid (DH) lines presents an extreme case of inbreeding which results in instantaneous homozygosity genome-wide. Here, we analyzed the effect of DH production on genetic diversity, using genome-wide SNP data from hundreds of individuals of five European landraces and their related DH lines. In contrast to previous findings, we observe a dramatic loss of diversity at both the haplotype level and that of individual SNPs. We identify thousands of SNPs that exhibit allele frequency differences larger than expected under models of neutral genetic drift and document losses of shared haplotypes. We find evidence consistent with selection at functional sites that are potentially involved in the diversity differences between landrace and DH populations. Although we were unable to uncover more details about the mode of selection, we conclude that landrace DH lines may be a valuable tool for the introduction of variation into maize breeding programs but come at the cost of decreased genetic diversity and increased genetic load.

evolutionary biology↗

bioRxiv2019

Extending the genotype in Brachypodium by including DNA methylation reveals a joint contribution with genetics on adaptive traits

Epigenomic changes have been considered a potential missing link underlying phenotypic variation in quantitative traits but is potentially confounded with the underlying DNA sequence variation. Although the concept of epigenetic inheritance has been discussed in depth, there have been few studies attempting to directly dissect the amount of epigenomic variation within inbred natural populations while also accounting for genetic diversity. By using known genetic relationships between Brachypodium lines, multiple sets of nearly identical accession families were selected for phenotypic studies and DNA methylome profiling to investigate the dual role of (epi)genetics under simulated natural seasonal climate conditions. Despite reduced genetic diversity, appreciable phenotypic variation was still observable in the measured traits (height, leaf width and length, tiller count, flowering time, ear count) between as well as within the inbred accessions. However, with reduced genetic diversity there was diminished variation in DNA methylation within families. Mixed-effects linear modelling revealed large genetic differences between families and a minor contribution of epigenomic variation on phenotypic variation in select traits. Taken together, this analysis suggests a limited but significant contribution of DNA methylation towards heritable phenotypic variation relative to genetic differences.

plant biology↗

bioRxiv2019

Cultural variation in voting patterns reflects the landscape of US genetic diversity: A test of the cultural niche hypothesis.

Humans are unique in the animal world in the extent to which we have the potential to affect our own biological evolution through culturally mediated behavioural variation. However, there is scant clear evidence of the phenomenon. Here, I estimate genetic diversity for every county in the US by merging demographic data from the 2010 US Census with genomic reference populations and show that genetic diversity is predicted by cultural variation as reflected by the 2016 Presidential Election. Remarkably, the 2016 Election alone explains 18% of US county-level variation in genetic diversity, with diversity decreasing as Trump support increases. When state level variation is included in the model, 71% of variation is explained. Within states, genetic segregation increases with cultural segregation. I then tested whether the observed genetic patterns might be explained by culture acting on race and ethnicity and found that genetic diversity tends to increase with racial and ethnic diversity, and that the 2016 Election is an even better predictor of the US landscape of ethnic diversity. Finally, I measured patterns of ethnic assortative mating nationwide from the Census data, and found that ethnic assortment is primarily explained by the proportion of minorities in each county, and that the most diverse counties are the most assortative. Overall, regional variation in cultural tolerance appears to be structuring biological diversity on a massive scale. Also, assortative mating is maintaining ethnic and genetic diversity within the most diverse and tolerant areas. Culture is a primary driver of biological evolution across the US.

evolutionary biology↗

bioRxiv2019

Understanding the genetic risks of complex diseases using the additive epistatic interaction model: a simulation study

Thousands of Genome-Wide Association Studies (GWAS) have been carried out to pinpoint genetic variants associated with complex diseases. However, the proportion of phenotypic variance which can be explained by the identified genetic variants is relatively low, leading to the "missing heritability" problem. This problem may be partly caused by the inadequate understanding of the genetic mechanisms of complex diseases. Here, we propose the additive epistatic interaction model, consisting of widespread pure epistatic interactions whose effects are additive and can be summarized by a genetic risk score. Based on a simulated genotype dataset, the additive epistatic interaction model well depicted genetic risks and hereditary patterns of complex diseases. Based on the 1000 Genomes Project data, the additive epistatic interaction model accurately classified human populations. Moreover, the models genetic risk score can be replaced by a deep learning model which is more resistant to noises. We suggest that the additive epistatic interaction model may help to understand the genetic mechanisms and risks of complex diseases.

bioinformatics↗

bioRxiv2025

Rapamycin Differentially Impacts Germline Stem Cell Quiescence Across Diverse Genetic Backgrounds of Drosophila Melanogaster

In response to ionizing radiation, stem cells enter a state of temporary quiescence, safeguarding the stem cell pool for tissue regeneration. Quiescence requires the inhibition of mTORC1, a kinase complex that promotes growth and suppresses autophagy, and cell cycle re-entry requires the reactivation of mTORC1. The pharmacological inhibition of mTORC1 in quiescent stem cells by rapamycin prevents cell cycle re-entry and subsequent tissue regeneration. It is well established that pharmacological responses can vary across genetic backgrounds, however, the extent to which genetic variation can impact the quiescence response to rapamycin is unclear. Here, we tested the sensitivity of stem cell quiescence to rapamycin in different genetic backgrounds within the Drosophila Genetic Reference Panel. These analyses revealed substantial variation across different genetic backgrounds, indicating that genetic variation can modulate drug-induced effects on stem cell dynamics. Our analyses suggest that mitophagy, rather than DNA damage response, is associated with the persistence of quiescence and delayed tissue regeneration by rapamycin. This work underscores the critical role of genetic background in determining drug efficacy, highlighting important implications for the therapeutic application of rapamycin.

developmental biology↗

bioRxiv2025

From storms to warming seas: a long-term metabarcoding survey in port communities unveils high genetic diversity and ecological resilience of non-indigenous species

Ports are key gateways for the introduction and spread of non-indigenous species (NIS), yet the ecological and genetic temporal dynamics of these introductions remain poorly understood. Long term temporal monitoring is essential to unravel invasion processes, anticipate biodiversity shifts, and inform effective management and biosecurity strategies. In this study, we conducted a five-year (2019-2024) monthly metabarcoding survey in a northwestern Mediterranean port using artificial collectors. By sequencing a fragment of the Cytochrome Oxidase I gene, we identified 2,225 Molecular Operational Taxonomic Units (MOTUs), including 93 NIS. In addition, we examined both interspecific temporal patterns and intraspecific trends of genetic diversity over time. Although NIS accounted for only 4% of total species richness, they represented over 26% of total read abundance, underscoring their strong influence on community structure. Interestingly, NIS had a significantly more homogeneous species composition through time than native species. In 2020, the passage of the Gloria storm reshaped community dynamics, triggering a temporary rise in species richness and MOTU counts, likely due to an influx of native taxa and a gradual decline and increased NIS dominance. Genetic analyses revealed that NIS exhibited higher haplotypic diversity and lower genetic differentiation than native taxa, suggesting sustained gene flow, likely facilitated by maritime transport. MOTUs with longer temporal persistence, particularly among NIS, also showed greater intraspecific diversity, supporting the "insurance hypothesis" and highlighting the role of genetic variability in resilience and invasion success. Overall, our findings showed that NIS, despite their low species richness, maintain high abundances, connectivity, and genetic diversity over time. These attributes likely enhance the NIS ability to persist in dynamic and disturbed port environments, and provide key information for understanding the invasion process. This study highlights the need to integrate genetic diversity metrics into marine biomonitoring assessments and management.

molecular biology↗

bioRxiv2026

RAREsim2: Flexible simulation of rare variant genetic data using real haplotypes

SummaryRealistic simulated data is critical for advancing methodological development and optimizing study design in genetics research. However, many genetic simulation tools are unable to replicate the distribution of rare variants or incorporate key genetic information, such as functional annotations and linkage disequilibrium. RAREsim, an accurate rare-variant simulation algorithm that uses real genetic haplotypes, was developed to address these limitations. Here, we introduce RAREsim2, an update that provides both streamlined software and new functionalities for simulating individual-level differences (e.g., cases vs controls, technological or batch effects) and variant-level differences to represent a variety of causal models. We demonstrate RAREsim2s utility with three rare variant association methods (Burden, SKAT, and SKAT-O) across several simulation scenarios: causal variants only in cases, causal variants in both cases and controls, and no causal variants. Type I Error was maintained and the optimal test matched previously known patterns: Burden performed best given a large amount of causal variants with the same direction of effect; SKAT performed best given causal variants with opposite directions of effect. SKAT-O was powerful across all simulation scenarios. We highlight RAREsim2s capabilities to simulate various genetic ancestries (African, East Asian, Non-Finnish European, and South Asian), gene sizes (~20-80 functional rare variants per gene), strengths of association (20%, 40%, 60% functional variants), and proportions of risk variants (1, 0.75, 0.5). Importantly, real genetic regions can be simulated to include known variant functions and disease associations. Ultimately, RAREsim2 offers additional flexibility and ease in simulating a multitude of realistic genetic scenarios. Availability and implementationThe RAREsim2 python package is available at https://github.com/Hendricks-Research-Team/RAREsim2 and the code for the example demonstration is available at https://github.com/JessMurphy/RAREsim2_demo. Contactjessica.murphy@cuanschutz.edu

bioinformatics↗

bioRxiv2026

Revisiting the genetics of Lake Constance Coregonids using lake-wide whole genome sequencing

Anthropogenic pressures can have detrimental impacts on fish populations, with their effective management and conservation requiring accurate monitoring tools. Yet, this is not straightforward for closely-related, co-existing species that are difficult to distinguish using simple phenotypic or genetic approaches. Coregonids are of cultural and economic importance across Europe but have faced a multitude of pressures over the last century. Yet genomic management tools are lacking. In Lake Constance, a large pre-alpine lake, stocks have drastically collapsed due to a multitude of pressures, leading to a fishery closure. Here, we adopt a cost-effective, whole genome sequencing approach for lake-wide assessment of stock composition, spatial distribution and genetic diversity of highly admixed Lake Constance whitefish (Coregonus spp.). By sequencing 983 adult and larval genomes, we show that nearly 90% of the stock is made up by one of three species, the Gangfisch (C. macrophthalmus), and define the genetic relationship between Upper and Lower Lake Constance whitefish stocks. We also identified strong mixing between Gangfisch and Blaufelchen (C. wartmanni) on traditionally specific-specific spawning grounds, and detected strong admixture in larvae, with potentially drastic impacts on the effectiveness of hatchery supplementation and stocking. Despite the collapse and admixture, species still exhibit low to moderate levels of genetic diversity, maintain ecologically-relevant genetic differences, and seem to show differences in habitat use. Overall, we present a cost-effective, translatable tool for stock-wide sequencing and genetically-informed fisheries management, with our results calling for the re-evaluation of current management practices to avoid the potential genetic mixing between species.

ecology↗

bioRxiv2026

Establishing genetically controlled, closed 1 colonies of an ascidian

Recent technological advances have made many "non-model" organisms accessible for experimental studies. However, reference inbred strains were not necessarily available, especially in marine invertebrates, and genetic background of organisms used for experiments are often non-uniform. This situation potentially affects experimental reproducibility. Although ascidians, Ciona intestinalis (type A, or C. robusta), are a widely used marine animal for many areas of experimental biology including developmental studies, no reference strains have been obtained despite extensive efforts. As an alternative way to improve reproducibility, we have established and maintained ascidian colonies through intra-population breeding every year from 2016 to 2020, and monitored genomic variants of these colonies. This method does not reduce genetic variations but instead manages and monitors genetic variations in the colonies, providing an easy and cost-effective way of increasing experimental reproducibility. Furthermore, we recently upgraded these genetically isolated, closed colonies that were re-established every year, and have maintained them for more than three years only through intra-population breeding and occasional back-cross using cryopreserved sperm. Genetic variants that we revealed using 3.7 tera-bases of sequence data will help to design future experiments in this species. Our data also show that two wild-populations, which were used to establish the colonies, have maintained distinct genetic backgrounds, although their habitats are directly linked to the Pacific Ocean and only 170 km apart. More importantly, genetic information regarding these colonies will undoubtedly improve experimental reproducibility and traceability, and our method will provide a realistic solution for performing reproducible experiments using non-model organisms.

developmental biology↗

bioRxiv2026

Genetic differentiation between two locations along an ocean/river gradient captures the signature of intragenerational selection in the European eel (Anguilla anguilla)

AO_SCPLOWBSTRACTC_SCPLOWMigration events can act as strong selective filters by spatially sorting individuals according to their migration ability, behaviour, and associated functional traits. The European eel, a panmictic and threatened fish, presents various estuarine migration patterns at juvenile stage (glass eel), ranging from sedentarization in brackish/saltwater of the estuary (non-migrant phenotype) to upstream colonisation of freshwater ecosystems (migrant phenotype). We hypothesize that migration propensity is partly genetically determined in glass eel, and that migration-related genotypes are spatially sorted during estuarine migration. To test these hypotheses, we first collected six pools of individuals over three years at two extreme sites along a gradient from ocean to Adour River tidal limit (Ocean vs. Upstream). Secondly, we collected additional glass eels and phenotypically sorted migrant vs. non-migrant individuals using an experimental device mimicking alternating tidal currents, producing two other pools. Whole genome pool sequencing and analysis of these eight pools generated 18.99 106 SNP variants. Controlling for linked selection through a local score approach, we found five best outlier SNPs with a significant genetic differentiation between Ocean vs. Upstream sites (average FST = 0.21) compared to the pangenomic estimate (FST = 0.0086). These five SNPs were all found in the same gene (gpb2), involved in interferon-mediated antiviral immune responses. We also found 28 best outlier SNPs with a significant genetic differentiation between migrant vs. non-migrant phenotypes (average FST = 0.51). They were located in genes mainly involved in neuronal development, cell migration and tissue remodelling, transcriptional regulation, and metabolic or stress-related processes. Our results support that variation in eel migration propensity is partly genetically determined and that, while panmixia maintains high level of genetic diversity, spatial sorting could promote intra-generational genetic divergence between habitats of European eels. However, the absence of shared genes among the best outliers between in-situ and experimental contrasts suggests a complex and context-dependent genetic control of migration.

evolutionary biology↗

bioRxiv2026

A mathematical synthesis of genetics, development, and evolution

Mathematically integrating genetics, development, and evolution is a longstanding challenge. A prevalent approach is quantitative genetics underpinned by the infinitesimal model, which considers a simplification of development, where phenotypes are described as the sum of many independent gene contributions. While this approach enjoys predictive success under controlled conditions, it is of interest to relax the model to consider more realistic development. Here I develop general mathematical theory that integrates sexual, discrete, multilocus genetics, developmental dynamics, and evolution. This yields an exact method to describe the evolutionary dynamics of allele frequencies and linkage disequilibria in multilocus systems and the associated evolutionary dynamics of mean phenotypes constructed via arbitrarily complex developmental dynamics. The theory shows that development affects evolution under realistic genetics by shaping the fitness landscape of allele frequencies and linkage disequilibria and by constraining adaptation to an admissible evolutionary manifold where mean phenotypes and phenotype (co-)variances can be developed. I derive a first-order approximation of this exact method, which yields equations in gradient form describing change in allele frequency, linkage disequilibria, and mean phenotypes as constrained, sometimes-adaptive topographies. Both the exact and approximated equations describe long-term phenotypic and genetic evolution. I provide worked examples to illustrate the methods. The theory obtained can be interpreted as an extension of population genetics, with some similarities with quantitative genetics under the infinitesimal model but with fundamental differences. The theory may improve prediction accuracy and shed light on empirical observations that have been paradoxical under previous theory, but appear less paradoxical in this theory.

evolutionary biology↗