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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits

BackgroundSweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years.\n\nResultsHigh broad-sense heritabilities of 0.83, 0.77, and 0.75 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic mode resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance.\n\nConclusionsPredicted breeding values and genetic values a measure revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone.

genetics↗

bioRxiv2019

Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: an application to maize flowering

When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred \"Flint-Dent\" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. The existence of directional epistasis was highlighted by comparing admixed with pure individuals and was consistent with epistatic interactions identified at the level of QTLs. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.\n\nAuthor summaryIdentification of genomic regions involved in genetic architecture of traits has become commonplace in quantitative genetics studies. Genetic structure is a common feature in human, animal and plant species and most current methods target genomic regions whose effects on traits are conserved between genetic groups. However, a heterogeneity of allele effects may be observed due to different factors: a group-specific correlation between the alleles of the tagged marker and those of the causal variant, a group-specific mutation at the causal variant or an epistatic interaction between the causal variant and the genetic background. We propose a new method adapted to structured populations including admixed individuals, which aims to identify these genomic regions and to unravel the previous factors. method was applied to a maize inbred diversity panel including lines from the dent and the flint genetic groups, as well as admixed lines, evaluated for flowering time. Several genomic regions were detected with various configurations of allele effects, with evidence of epistatic interactions between some of the loci and the genetic background.

genetics↗

bioRxiv2020

Developmental models reveal the role of phenotypic plasticity in explaining genetic evolvability

Biological evolution exhibits an extraordinary capability to adapt organisms to their environments. The explanation for this often takes for granted that random genetic variation produces at least some beneficial phenotypic variation for natural selection to act on. Such genetic evolvability could itself be a product of evolution, but it is widely acknowledged that the immediate selective gains of evolvability are small on short timescales. So how do biological systems come to exhibit such extraordinary capacity to evolve? One suggestion is that adaptive phenotypic plasticity makes genetic evolution find adaptations faster. However, the need to explain the origin of adaptive plasticity puts genetic evolution back in the driving seat, and genetic evolvability remains unexplained. To better understand the interaction between plasticity and genetic evolvability, we simulate the evolution of phenotypes produced by gene-regulation network-based models of development. First, we show that the phenotypic variation resulting from genetic and environmental change are highly concordant. This is because phenotypic variation, regardless of its cause, occurs within the relatively specific space of possibilities allowed by development. Second, we show that selection for genetic evolvability results in the evolution of adaptive plasticity and vice versa. This linkage is essentially symmetric but, unlike genetic evolvability, the selective gains of plasticity are often substantial on short, including within-lifetime, timescales. Accordingly, we show that selection for phenotypic plasticity is, in general, the most efficient and results in the rapid evolution of high genetic evolvability. Thus, without overlooking the fact that adaptive plasticity is itself a product of genetic evolution, this shows how plasticity can influence adaptive evolution and helps explain the genetic evolvability observed in biological systems.

evolutionary biology↗

bioRxiv2021

Drivers of genetic differentiation and recent evolutionary history of an Eurasian wild pea

Genetic diversity a major determinant for the capacity of species to persist and adapt to their environments. Unraveling the factors affecting genetic differentiation is crucial to understand how genetic diversity is shaped and species may react to changing environments. We employed genotyping by sequencing to test the influence of climate, space, latitude, altitude and land cover on genetic differentiation in a collection of 81 wild pea samples (Pisum sativum ssp. elatius) from across its distribution range from western Europe to central Asia. We also attempted to elucidate the species recent evolutionary history and its effect on the current distribution of genetic diversity. Association of single SNPs with climate variables were analyses to test for signatures of local adaptation. Genetic variation was geographically structured into six distinct genetic cluster. Two of which were associated with a taxonomic group (Pisum sativum ssp. humile) that according to some researchers does not qualify for a sub-species rank due to its alleged lack of genetic distinctness from other conspecific groups. The effect of the tested factors influencing genetic differentiation were rather variable among genetic clusters. The climate predictors were most important in all clusters. Land use was more important in clusters from areas strongly influenced by human land use, especially by agriculture. We found a statistically significant association of 3,623 SNPs (2.4 % of all SNPs) with one of the environmental predictors. Most of them were correlated with latitude followed by temperature, precipitation and altitude. Estimation of SNP effects of the candidates resulted in a missense to silent ratio of 0.45, suggesting many of the observed candidates SNPs may alter the encoded amino acid sequence. Wild peas went through a genetic bottleneck during the last glacial period followed by population recovery. Probably associated with this population recovery, we detected a range expansion, which may have led to an eastward range expansion of the European cluster to Turkey and thereof southwards and eastwards. Overall, the interplay of several environmental factors and the recent evolutionary history affected the distribution of genetic diversity in wild peas where each subpopulations were differently affected by those factors and processes.

evolutionary biology↗

bioRxiv2022

Modeling the genetic footprint of fluctuating balancing selection: From the local to the genomic scale

Natural selection not only affects the actual loci under selection but also leaves "footprints" in patterns of genetic variation in linked genetic regions. This offers exciting opportunities for inferring selection and for understanding the processes shaping levels of genetic variation in natural populations. Here we develop analytical approximations based on coalescent theory to characterize the genetic footprint of a complex, but potentially common type of natural selection: balancing selection with seasonally fluctuating allele frequencies. We show that seasonal allele frequency fluctuations can have important (and partly unexpected) consequences for the genetic footprint of balancing selection. As also confirmed by stochastic simulations, fluctuating balancing selection generally leads to an increase in genetic diversity close to the selected site, the effect of balancing selection, but reduces diversity further away from the selected site, which is a consequence of the allele-frequency fluctuations effectively producing recurrent bottlenecks of allelic backgrounds. This negative effect usually outweighs the positive effect when averaging diversity levels across the entire chromosome. Strong fluctuating balancing selection even induces a loss of genetic variation in unlinked regions, e.g. on different chromosomes. If many loci in the genome are simultaneously under fluctuating balancing selection this could lead to substantial genome-wide reductions in genetic diversity. This may be the case, even if allele-frequency fluctuations are so small that individual footprints are hard to detect. Thus, together with genetic drift, selective sweeps and background selection, fluctuating selection could be one of the major forces shaping levels of genetic diversity in natural populations. Article summaryIn some species with multiple generations per year, many loci in the genome experience strong seasonally fluctuating selection, in some cases with stable maintenance of polymorphism. Here we investigate the consequences for levels of genetic diversity at linked neutral sites. Using analytical approximations and stochastic simulations, we find a characteristic local genetic footprint with a diversity peak around the selected site and a diversity valley further away and a substantial reduction in diversity levels chromosome-wide and even genome-wide.

evolutionary biology↗

bioRxiv2022

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we dont yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift will be informative for parameterizing evolutionary models and studying potential mechanisms for increased drift. Author SummaryThe transmission of pathogens like SARS-CoV-2 is strongly affected by chance effects in the contact process between infected and susceptible individuals, collectively referred to as random genetic drift. We have an incomplete understanding of how genetic drift changes across time and locations. To address this gap, we developed a computational method that infers the strength of genetic drift from time series genomic data that corrects for non-biological noise and is computationally scalable to the large numbers of sequences available for SARS-CoV-2, overcoming a major challenge of existing methods. Using this method, we quantified the strength of genetic drift for SARS-CoV-2 transmission in England throughout time and across locations. These estimates constrain potential mechanisms and help parameterize models of SARS-CoV-2 evolution. More generally, the computational scalability of our method will become more important as increasingly large genomic datasets become more common.

evolutionary biology↗

bioRxiv2023

Shared Genetic Architecture between Muscle and Bone: Identification and Functional Implications of EPDR1, PKDCC, and SPTBN1

Recent studies suggest a shared genetic architecture between muscle and bone, yet the underlying molecular mechanisms remain elusive. This study aims to identify the functionally annotated genes with shared genetic architecture between muscle and bone using the most up-to-date genome-wide association study (GWAS) summary statistics from bone mineral density (BMD) and fracture-related genetic variants. We employed an advanced statistical functional mapping method to investigate shared genetic architecture between muscle and bone, focusing on genes highly expressed in muscle tissue. Our analysis identified three genes, EPDR1, PKDCC, and SPTBN1, highly expressed in muscle tissue and previously unlinked to bone metabolism. About 90% and 85% of filtered Single-Nucleotide Polymorphisms were located in the intronic and intergenic regions for the threshold at P [≤] 5 x 10-8 and P [≤] 5 x 10-100, respectively. EPDR1 was highly expressed in multiple tissues, including muscle, adrenal gland, blood vessels, and thyroid. SPTBN1 was highly expressed in all 30 tissue types except blood, while PKDCC was highly expressed in all 30 tissue types except the brain, pancreas, and skin. Our study provides a framework for using GWAS findings to highlight functional evidence of crosstalk between multiple tissues based on shared genetic architecture between muscle and bone. Further research should focus on functional validation, multi-omics data integration, gene-environment interactions, and clinical relevance in musculoskeletal disorders. Author SummaryOsteoporotic fractures in the aging population pose a significant health concern. They are often attributed to decreased bone strength and muscle loss. However, the underlying molecular connections between bone and muscle are not well understood. This lack of knowledge persists despite recent genetic discoveries linking certain genetic variants to bone mineral density and fracture risk. Our study aimed to uncover genes that share genetic architecture between muscle and bone. We utilized state-of-the-art statistical methods and the most recent genetic data related to bone mineral density and fractures. Our focus was on genes that are highly active in muscle tissue. Our investigation identified three new genes - EPDR1, PKDCC, and SPTBN1 - which are highly active in muscle tissue and influence bone health. These discoveries offer fresh insights into the interconnected genetic makeup of bone and muscle. Our work not only uncovers potential targets for therapeutic strategies to enhance bone and muscle strength but also provides a blueprint for identifying shared genetic structures across multiple tissues. This research represents a crucial step forward in our understanding of the interplay between our muscles and bones at a genetic level.

genomics↗

bioRxiv2023

Characterization of the genetic composition and establishment of a core collection for the INERA Robusta coffee (Coffea canephora) field genebank from the Democratic Republic of the Congo

Cultivation of Robusta coffee is likely to gain importance because of its high disease resistance and climate envelope, but substantial effort must be made to improve its cupping quality and other agronomic traits. Robusta coffee genetic resources conserved in field genebanks can play an important role in this context, but many of them are limited and poorly characterized. In this study, we aimed to characterize the genetic composition of the historically important but until recently neglected INERA Coffee Collection in Yangambi (Democratic Republic of the Congo) and to propose a Robusta core collection. We combined genome-wide GBS marker sets with a novel versatile multiplex amplicon sequencing (HiPlex) screening assay, for the genetic screening of the INERA Coffee Collection and created tools for future genetic screening. A set of 730 coffee shrubs in the collection were genotyped at 86 HiPlex loci and 263 unique genetic fingerprints were identified. Representative fingerprints were compared to Lula cultivars, Luki cultivars, Congolese subgroup A, and wild genotypes growing in the rainforest of the Yangambi region. The majority of the unique genetic fingerprints were identified as Lula cultivars but also four Congolese subgroup A and nine wild genotypes were found in the collection. Twenty-five percent of the unique genetic fingerprints had a hybrid identity which could result from seed-based propagation of the collection or natural cross-pollination. Moreover, eight unique genetic fingerprints were frequently identified as a parent and these may correspond to the ancient selected mother plants, or direct descendants thereof, of which seed material was widely distributed from 1930 to 1960 for the creation of coffee plantations. Finally, to delineate core collections we tested the maximization strategy and genetic distance method for the INERA Coffee Collection, and proposed i) a core collection conserving the loci diversity of the collection, i.e. 100 accessions and ii) a core collection holding the highest genetic distances between the accessions, i.e. 10 accessions. Our study provides a method for the genetic characterization of Robusta coffee collections in general and contributes to the revaluation and exploitation of the Robusta coffee genetic resources in the Democratic Republic of the Congo in particular.

plant biology↗

bioRxiv2023

Genetic drift vs natural selection affecting the evolution of spectral and functional traits of two key macrophytes: Phragmites australis and Nuphar lutea

Both genetic and phenotypic intraspecific diversity play a crucial role in the ecological and evolutionary dynamics of organisms. Several studies have compared phenotypic divergence (Pst) and differentiation of neutral loci (Fst) to infer the relative roles of genetic drift and natural selection in population differentiation (Pst - Fst comparison). For the first time, we assessed and compared the genetic variation and differentiation at the leaf trait level in two key macrophytes, Phragmites australis and Nuphar lutea. To this aim, we quantified and described the genetic structure and phenotypic diversity of both species in five lake systems in north-central Italy. We then investigated the relative roles of genetic drift and natural selection on leaf trait differentiation (Pst - Fst), assuming that Fst reflects divergence caused only by genetic drift while Pst also incorporates the effects of selective dynamics on the phenotype. In terms of genetic structure, the results for P. australis were in line with those observed for other Italian and European conspecific populations. Conversely, N. lutea showed a more complex genetic structure than expected at the site level, likely due to the combined effect of genetic isolation and its mixed mating system. Both species exhibited high variability in leaf functional traits within and among sites, highlighting a high degree of phenotypic plasticity. Pst - Fst comparisons showed a general tendency towards directional selection in P. australis and a more complex pattern in N. lutea. Indeed, the drivers of phenotypic differentiation in N. lutea showed a variable mix of stabilizing and directional selection or neutral divergence at most sites. The prevalence of vegetative over generative reproduction leads P. australis populations to be dominated by a few clones that are well adapted to local conditions, including phenotypes that respond plastically to the environment. In contrast, in N. lutea the interaction of a mixed mating system and geographical isolation among distant sites tends to reduce the effect of outbreeding depression and provides the genetic basis for adaptive capacity. The first joint analysis of the genetic structure of these two key macrophytes allowed a better understanding of the relative roles of genetic drift and natural selection in the diversification of phenotypic traits within habitats dominated by P. australis and N. lutea.

ecology↗

bioRxiv2024

Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond

Deciphering cellular responses to genetic perturbations is fundamental for a wide array of biomedical applications, ranging from uncovering gene roles and interactions to unraveling effective therapeutics. Accurately predicting the transcriptional outcomes of genetic perturbations is indispensable for optimizing experimental perturbations and deciphering cellular response mechanisms; however, three scenarios present principal challenges, i.e., predicting single genetic perturbation outcomes, predicting multiple genetic perturbation outcomes and predicting genetic outcomes across cell lines. In this study, we introduce SubTAsk decomposition Modeling for genetic Perturbation prediction (STAMP), a conceptually novel computational strategy for genetic perturbation outcome prediction and downstream applications. STAMP innovatively formulates genetic perturbation prediction as a subtask decomposition (STD) problem by resolving three progressive subtasks in a divide-and-conquer manner, i.e., identifying differentially expressed gene (DEG) postperturbations, determining the regulatory directions of DEGs and finally estimating the magnitudes of gene expression changes. In addition to facilitating perturbation prediction, STAMP also serves as a robust and generalizable benchmark guide for evaluating various genetic perturbation prediction models. As a result, STAMP exhibits a substantial improvement in terms of its genetic perturbation prediction ability over the existing approaches on three subtasks and beyond, including revealing the ability to identify key regulatory genes and pathways on small samples and to reveal precise genetic interactions. Overall, STAMP serves as a fundamentally novel and effective prediction and generalizable benchmarking strategy that can facilitate genetic perturbation prediction, guide the design of perturbation experiments, and broaden the understanding of perturbation mechanisms.

bioinformatics↗

bioRxiv2024

Under the name of "Lua": Revisiting Genetic Heterogeneity and Population Ancestry of Austroasiatic speakers in Northern Thailand Through Genomic Analysis

Austroasiatic (AA)-speaking populations in northern Thailand are of significant interest due to their status as indigenous descendants and their location at the crossroads of AA prehistoric distribution across Southern China, the Indian Subcontinent, and Mainland Southeast Asia. However, the complexity of ethnic identification can result in inaccuracies regarding the origin and migration history of these populations. To address this, we conducted a genome-wide SNP analysis on 89 individuals from two Lavue- and three Lwa-endonym populations and combined them with previously published data to elucidate the genetic diversity and clustering of AA groups in northern Thailand. Our findings align with linguistic classifications, revealing distinct genetic structure among the three branches of the Mon-Khmer subfamily within the AA family: Monic, Khmuic, and Palaungic. Although the term "Lua" ethnicity is used confusingly to identify ethnic groups belonging to both Khmuic and Palaungic branches, our genomic data clarifies that the Khmuic-speaking Lua living on the eastern side of the region show genetic differentiation from the Palaungic-speaking Lavue and Lwa populations living on the western side. Within the Palaungic branch, the Dara-ang population stands out as genetically distinct, reflecting remnants of ancient ancestry. The Lavue populations, mainly inhabiting mountainous areas, exhibit a genetic makeup unique to the AA family, with a close genetic relationship to the Karenic subgroup of the ST family. Conversely, the Lwa and Blang populations, residing in lowland river valleys, display genetic signatures resulting from admixture with Tai-Kadai-speaking ethnic groups. Author summaryIn the past, many Austroasiatic speakers in northern Thailand concealed their identity due to perceptions of inferiority compared to the majority Tai-Kadai-speaking group in the region. However, attitudes have shifted in the modern era, with a greater appreciation for ethnic diversity and the unique aspects of different valuable cultures. This scenario provides an opportunity for us to use genetic insights to untangle the complexities of ethnic identification among these indigenous inhabitants of Mainland Southeast Asia. Through our genetic analysis, we aimed to shed light on the ancestry and diversity of the Austroasiatic people in northern Thailand, often collectively referred to as "Lua" or "Lawa", which is an exonym (a name of the ethnic group created by another group of people) commonly used in prior scientific reports. Our findings clearly indicate genetic distinctions among the Lua, Lavue, and Lwa ethnic groups. The intricate interplay of genetics, cultural heritage, and historical influences has shaped these ethnic communities. Our study underscores the importance of accurate ethnic classifications, emphasizing the use of self-identified endonyms, names created and used by the ethnic group themselves. This approach respects the Austroasiatic communities in northern Thailand and acknowledges their significant contributions to advancing our understanding of genetic anthropology.

evolutionary biology↗

bioRxiv2024

Contrasting patterns of spatial genetic structure in endangered southern damselfly (Coenagrion mercuriale) populations facing habitat fragmentation and urbanisation.

AimHuman-induced environmental changes result in habitat loss and fragmentation, impacting wildlife population genetic structure and evolution. Urbanised and geographically peripheral areas often represent unfavourable environments, reducing connectivity among populations and causing higher population genetic differentiation and lower intra-population genetic diversity. We examined how geographic peripherality and anthropogenic pressures affect genetic diversity and genetic differentiation in the protected southern damselfly (Coenagrion mercuriale, Odonata), which has low dispersal capabilities and specific habitat requirements and whose populations are declining. LocationWe studied two areas: one in semi-natural habitats at the periphery of the species geographic range (northern France) and the other more central to the species range, in an urbanised area surrounding the city of Strasbourg (Alsace, eastern France). MethodsWe genotyped 2743 individuals from 128 populations using eleven microsatellite loci. We analysed the spatial distribution of neutral genetic diversity (allelic richness, heterozygosity, levels of inbreeding, genetic relatedness), the extent of genetic differentiation, and population affiliations (sPCA analyses) within the two areas. We also examined fine-scale patterns of gene flow in the urbanised area of Alsace by investigating patterns of isolation by distance and estimating effective migration surfaces (EEMS method). ResultsNorthern peripheral populations showed lower levels of genetic diversity and higher levels of genetic differentiation than central Alsacian populations. Although located in anthropised habitats, geographically central Alsacian populations showed high levels of gene flow, with dispersal events mainly occurring overland and not restricted to watercourses. However, the highly urbanised city of Strasbourg negatively impacted nearby populations by reducing levels of genetic diversity and increasing population genetic differentiation. Main conclusionsThese results showed the need for management action by restoring breeding sites and creating migratory corridors for peripheral southern damselfly populations. However, our results also highlighted the resilience of southern damselfly in central range populations facing strong urbanisation pressures.

evolutionary biology↗

bioRxiv2025

On the edge of extinction: Delayed plant genetic response to forest edge dynamics

Understanding genetic responses to forest dynamics is essential for predicting the long-term viability of understory plant populations and for developing effective conservation strategies. This study investigates genetic extinction debt and colonization credit in Circaea lutetiana, a clonal forest understory species, across its European range. Using pooled genotype-by-sequencing data from 40 forest edge and core populations, we examined to what extent population size, latitude and historical changes in forest configuration predict genetic diversity. Our findings reveal that the historical forest configuration profoundly shapes present-day genetic diversity. Long-established forest edge populations exhibit significantly reduced allelic richness (-9%) compared to core populations, indicating the partial pay-off of a genetic extinction debt. In contrast, populations from recently established forest edges maintain comparable allelic richness to core populations, suggesting delayed population genetic responses to land use changes. Finally, populations established in areas that were afforested during the past 250 years exhibit lower genetic diversity than historical forest core populations, indicating a delay in genetic recovery and thus a potential genetic colonization credit. Our results highlight that C. lutetiana populations are not at equilibrium with the current forest configuration, underscoring the role of lagged genetic responses across very long time scales. Connectivity and population size further moderate genetic diversity, with smaller, isolated populations particularly vulnerable to genetic erosion. Given the limited research on delayed evolution in forest understory species, our results improve the understanding of extinction risk dynamics and underscore the need for history-informed restoration efforts.

ecology↗

bioRxiv2018

Genetic variability and potential effects on clinical trial outcomes: perspectives in Parkinson’s disease

BackgroundImproper randomization in clinical trials can result in the failure of the trial to meet its primary end-point. The last [~]10 years have revealed that common and rare genetic variants are an important disease factor and sometimes account for a substantial portion of disease risk variance. However, the burden of common genetic risk variants is not often considered in the randomization of clinical trials and can therefore lead to additional unwanted variance between trial arms. We simulated clinical trials to estimate false negative and false positive rates and investigated differences in single variants and mean genetic risk scores (GRS) between trial arms to investigate the potential effect of genetic variance on clinical trial outcomes at different sample sizes.\n\nMethodsSingle variant and genetic risk score analyses were conducted in a clinical trial simulation environment using data from 5851 Parkinsons Disease patients as well as two simulated virtual cohorts based on public data. The virtual cohorts included a GBA variant cohort and a two variant interaction cohort. Data was resampled at different sizes (n = 200-5000 for the Parkinsons Disease cohort) and (n = 50-800 and n = 50-2000 for virtual cohorts) for 1000 iterations and randomly assigned to the two arms of a trial. False negative and false positive rates were estimated using simulated clinical trials, and percent difference in genetic risk score and allele frequency was calculated to quantify disparity between arms.\n\nFindingsSignificant genetic differences between the two arms of a trial are found at all sample sizes. Approximately 90% of the iterations had at least one statistically significant difference in individual risk SNPs between each trial arm. Approximately 10% of iterations had a statistically significant difference between trial arms in polygenic risk score mean or variance. For significant iterations at sample size 200, the average percent difference for mean GRS between trial arms was 130.87%, decreasing to 29.87% as sample size reached 5000. In the GBA only simulations we see an average 18.86% difference in GRS scores between trial arms at n = 50, decreasing to 3.09% as sample size reaches 2000. Balancing patients by genotype reduced mean percent difference in GRS between arms to 36.71% for the main cohort and 2.00% for the GBA cohort at n = 200. When adding a drug effect to the simulations, we found that unbalanced genetics with an effect on the chosen measurable clinical outcome can result in high false negative rates among trials, especially at small sample sizes. At a sample size of n = 50 and a targeted drug effect of -0.5 points in UPDRS per year, we discovered 33.9% of trials resulted in false negatives.\n\nInterpretationsOur data support the hypothesis that within genetically unmatched clinical trials, particularly those below 1000 participants, heterogeneity could confound true therapeutic effects as expected. This is particularly important in the changing environment of drug approvals. Clinical trials should undergo pre-trial genetic adjustment or, at the minimum, post-trial adjustment and analysis for failed trials. Clinical trial arms should be balanced on genetic risk variants, as well as cumulative variant distributions represented by GRS, in order to ensure the maximum reduction in trial arm disparities. The reduction in variance after balancing allows smaller sample sizes to be utilized without risking the large disparities between trial arms witnessed in typical randomized trials. As the cost of genotyping will likely be far less than greatly increasing sample size, genetically balancing trial arms can lead to more cost-effective clinical trials as well as better outcomes.

genomics↗

bioRxiv2019

The genetic structure of the European black pine (Pinus nigra Arnold) is shaped by its recent Holocene demographic history.

Fragmentation acting over geological times confers wide, biogeographical scale, genetic diversity patterns to species, through demographic and natural selection processes. To test the effects of historical fragmentation on the genetic diversity and differentiation of a major European forest tree and to resolve its demographic history, we describe and model its spatial genetic structure and gene genealogy. We then test which Pleistocene event, whether recent or ancient, could explain its widespread but patchy geographic distribution using population genetic data, environmental data and realistic demographic timed scenarios. The taxon of interest is a conifer forest tree, Pinus nigra (Arnold), the European black pine, whose populations are located in the mountains of southern Europe and North Africa, most frequently at mid-elevation. We used a set of different genetic markers, both neutral and potentially adaptive, and either bi-parentally or paternally inherited, and we sampled natural populations across the entire range of the species. We analysed the data using frequentist population genetic methods as well as Bayesian inference methods to calibrate realistic, demographic timed scenarios. Species with geographically fragmented distribution areas are expected to display strong among-population genetic differentiation and low within-population genetic diversity. Contrary to these expectations, we show that the current diversity of Pinus nigra and its weak genetic spatial structure are best explained as resulting from late Pleistocene or early Holocene fragmentation of one ancestral population into seven genetic lineages, which we found to be the main biogeographical contributors of the natural black pine forests of today. Gene flow among the different lineages is strong across forests and many current populations are admixed between lineages. We propose to modify the currently accepted international nomenclature made of five subspecies and name these seven lineages using regionally accepted subspecies-level names. HighlightsO_LIThe European black pine, Pinus nigra (Arnold), has a weak spatial genetic structure. C_LIO_LIGene flow among populations is frequent and populations are often of admixed origin. Current genealogies result from recent, late Pleistocene or Holocene events. C_LIO_LISeven modern genetic lineages emerged from divergence and demographic contractions. C_LIO_LIThese seven lineages warrant a revision of subspecies taxonomic nomenclature. C_LI

ecology↗

bioRxiv2019

Assortative mating and the dynamical decoupling of genetic admixture levels from phenotypes that differ between source populations

Source populations for an admixed population can possess distinct patterns of genotype and pheno-type at the beginning of the admixture process. Such differences are sometimes taken to serve as markers of ancestry--that is, phenotypes that are initially associated with the ancestral background in one source population are taken to reflect ancestry in that population. Examples exist, however, in which genotypes or phenotypes initially associated with ancestry in one source population have decoupled from overall admixture levels, so that they no longer serve as proxies for genetic ancestry. We develop a mechanistic model for describing the joint dynamics of admixture levels and phenotype distributions in an admixed population. The approach includes a quantitative-genetic model that relates a phenotype to underlying loci that affect its trait value. We consider three forms of mating. First, individuals might assort in a manner that is independent of the overall genetic admixture level. Second, individuals might assort by a quantitative phenotype that is initially correlated with the genetic admixture level. Third, individuals might assort by the genetic admixture level itself. Under the model, we explore the relationship between genetic admixture level and phenotype over time, studying the effect on this relationship of the genetic architecture of the phenotype. We find that the decoupling of genetic ancestry and phenotype can occur surprisingly quickly, especially if the phenotype is driven by a small number of loci. We also find that positive assortative mating attenuates the process of dissociation in relation to a scenario in which mating is random with respect to genetic admixture and with respect to phenotype. The mechanistic framework suggests that in an admixed population, a trait that initially differed between source populations might be a reliable proxy for ancestry for only a short time, especially if the trait is determined by relatively few loci. The results are potentially relevant in admixed human populations, in which phenotypes that have a perceived correlation with ancestry might have social significance as ancestry markers, despite declining correlations with ancestry over time.\n\nAuthor SummaryAdmixed populations are populations that descend from two or more populations that had been separated for a long time at the beginning of the admixture process. The source populations typically possess distinct patterns of genotype and phenotype. Hence, early in the admixture process, phenotypes of admixed individuals can provide information about the extent to which these individuals possess ancestry in a specific source population. To study correlations between admixture levels and phenotypes that differ between source populations, we construct a genetic and phenotypic model of the dynamical process of admixture. Under the model, we show that correlations between admixture levels and these phenotypes dissipate over time--especially if the genetic architecture of the phenotypes involves only a small number of loci, or if mating in the admixed population is random with respect to both the admixture levels and the phenotypes. The result has the implication that a trait that once reflected ancestry in a specific source population might lose this ancestry correlation. As a consequence, in human populations, after a sufficient length of time, salient phenotypes that can have social meaning as ancestry markers might no longer bear any relationship to genome-wide genetic ancestry.

evolutionary biology↗

bioRxiv2026

Establishing a baseline for standardised genetic monitoring of Atlantic cod (Gadus morhua) in Sweden

Protecting populations and genetic diversity within them is critical to conserving the resilience and adaptive potential of species. Fisheries management has long had the ambition of managing species at the population level, but mainly define "fish stocks" based on geographical limits, which can lead to overfishing of sensitive populations in areas where many different populations coexist. Modern genetic methods are now sufficiently cost-effective, fast, and accurate to be integrated into fisheries management, enabling genetic identification and monitoring of fish populations. Here, we establish a genetic baseline for the commercially important fish Atlantic cod (Gadus morhua) in the waters surrounding Sweden, by using standardised sampling procedures and developing a genetic panel of 4000 single nucleotide polymorphisms (SNPs) for cost-effective assignment of population-of-origin and inversion genotypes. Using the SNP panel, we resolve the geographical distribution of three genetically distinct cod populations in the region: offshore, coastal/Western Baltic, and Eastern Baltic cod. While there is considerable spatial overlap between the three populations, they are genetically differentiated across the entire genome, as well as in genomic regions associated with chromosomal inversions. In addition, heterozygosity and effective population size estimates suggest differences in genetic diversity and rates of genetic erosion, underscoring the need to monitor the genetic diversity within each population separately. Repeating this methodology across years provides a first suggestion for establishing spatiotemporally resolved genetic monitoring of Atlantic cod in Sweden - simultaneously accounting for both population structure within the species and the genetic diversity within populations.

genomics↗

bioRxiv2026

Socotra Cormorants in the Arabian Gulf represent a large, but isolated population with low genetic diversity

The Socotra Cormorant (Phalacrocorax nigrogularis) is a threatened seabird endemic to the coastal areas of the Arabian Gulf and the Arabian Sea, two regions separated by the Strait of Hormuz. Conserving threatened species requires clear delineation of population boundaries and the evaluation of genetic diversity. However, information on population structure and genetic variation, necessary for such an assessment, is lacking for the Socotra Cormorants. In this study, we assessed population structure and genetic diversity of Socotra Cormorants using two contrasting genetic markers: (1) maternally inherited mtDNA cytochrome oxidase 1 (COI) and (2) a nuclear non-coding region, {beta}-fibrinogen intron 7 (FIB7). A total of 279 individuals were sampled from four colonies in the Arabian Gulf and one colony on Hasikiyah Island in the Arabian Sea. Findings based on COI-variation suggest that the Arabian Gulf colonies represent one large population with extensive gene flow between Gulf colonies--except for the most distant pair of colonies--but isolated from Hasikiyah in the Arabian Sea. COI-variation indicated significant differentiation between the colonies inside the Gulf and the Hasikiyah colony. This is consistent with the reported distribution patterns, and may reflect phylogeographic processes of the region. The Gulf population showed substantially lower COI-diversity, with significantly lower nucleotide and haplotype diversity compared to Hasikiyah. In contrast, FIB7 results indicated extensive connectivity among colonies, with no detectable population structure or significant differences between the Gulf population and Hasikiyah. This study presents the first characterization of population structure and genetic diversity of Socotra Cormorants. The low genetic diversity coupled with relative isolation of the Gulf Socotra Cormorants raises conservation concerns regarding their long-term viability by potentially reducing fitness and eroding their evolutionary capacity to adapt to environmental change. LAY SUMMARYO_LIThe Socotra Cormorant is a threatened seabird found in the Arabian Gulf and Arabian Sea, but little was previously known about its population structure and genetic diversity. C_LIO_LIWe analyzed 279 birds from five nesting colonies (4 in the Gulf and 1 in the Arabian Sea), using two genetic markers to assess population connectivity and variation. C_LIO_LIWe found that the Socotra cormorants inside the Gulf appear to form a large, genetically isolated population with relatively low genetic diversity. C_LIO_LIThis is the first study that evaluates population structure and genetic diversity of this endangered seabird. C_LIO_LIThis is important information for the conservation of the Gulf Socotra cormorants because low genetic diversity, coupled with relative isolation, is associated with reduced fitness, and suggests that they may have a lower chance to adapt to environmental changes. C_LI

ecology↗