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bioRxiv2025

Genomic resources for curimba Prochilodus lineatus reveal a fractal pattern of hierarchical genetic population structure in mixed stocks across fish segregated by dams.

Genomic resources, new microsatellite markers and a novel observation of a fractal pattern of the genetic population structure are presented for curimba Prochilodus lineatus, a suitable model organism for freshwater migratory species in South America. Our main goals were to investigate the presence of mixed fish stocks, the effects of isolation by dams and broodstocking over the genetic diversity for this species. We focused on the upper segment of the extremely fragmented Grande River, MG, Brazil, from the megadiverse continental La Plata Basin. Two main co-occurring genetically admixed stocks were identified by maximum likelihood estimation and iteratively unfolded with two further steps, through a hierarchical analysis of genetic structure. It consistently unveiled two newly defined internal groups, from the previously resolved clusters (23). We suggest this stratified pattern of mixed stocks from the main river channel may be attributed to the existence of different, well defined breeding grounds, nested within differential scales throughout this basin, arranged according to fractal geometry (1st order river, 2nd and 3rd order tributaries, and so on). This would imply in homing behaviour for this species. Our work also provides massive molecular data for this fish, including its first draft genome assembly and a valuable panel for the rapid and low-cost development of new microsatellite DNA markers. These findings will likely benefit researchers and environmental managers in tackling challenging issues regarding the conservation of Neotropical migratory fishes, as they support the hypothesis of the isolating effects of dams and broodstocking over genetic variability. More importantly, the results presented here point to the potential role of tributaries of different orders in harbouring genetically diverse populations of migratory freshwater fishes.

genetics↗

bioRxiv2025

Prioritization of Deleterious Mutations Improves Genomic Prediction and Increases the Rate of Genetic Gain in Common Bean (Phaseolus vulgaris L.), a Simulation Study

The study of mutations is fundamental to understanding evolution, domestication, and genetics. Characterizing mutations has the potential to accelerate breeding programs through selection and purging of deleterious mutations (DelMut). Here, we investigated how predicting DelMut in breeding populations can improve genomic prediction (GP) and inform strategies to increase the rate of genetic gain. DelMut were annotated in three independent common bean populations using a previously developed random forest (RF) model incorporating phylogenetic and protein information. Deleterious scores from the RF model were mostly around 0.25, with the top 1% (highly DelMut) of variants scoring between 0.78 - 0.82 among populations. All populations showed variation in the number of highly DelMut per line (max. 13 - 197) and in genetic load. We assessed the impact of incorporating a priori information for variant prioritization and weighting based on predicted deleteriousness in GP models for yield and flowering time. Stochastic simulations were conducted to evaluate how different mating schemes based variable numbers of DelMut per parent affect genetic gain. Variants with higher predicted scores had significantly different effect distributions compared to random or lower-scored markers. Yield predictions were 4.47-12.3% more accurate when markers were weighted by effect and deleterious score; no consistent improvement was observed for flowering time. Simulated breeding cycles showed that selecting parents with fewer highly DelMut consistently increases the rate of genetic gain. These results highlight the potential of DelMut information for variant prioritization and the optimization of common bean breeding programs. The approaches we developed can be assessed in other species to improve the efficacy of crop improvement. Key messages- Predicted deleterious mutations have different distributions of effects based on population composition. - Variant prioritization and differential weighing of markers based on effects and deleterious scores can improve the prediction of yield. - Favoring mating schemes between parents with fewer highly deleterious mutations can increase the rate of genetic gain.

genetics↗

bioRxiv2025

Development of an open-pollinated genetic mapping framework to facilitate the identification of QTL in apples

Genetic mapping of traits in apples (Malus domestica), a temperate woody perennial, is challenging due to high heterozygosity, long juvenility, and extensive spatial maintenance requirements for the populations. These factors limit the effective use of traditional quantitative trait locus (QTL) mapping methods in identifying the genetic basis of traits critical for apple production, marketability and sustainability. We explored the use of open-pollinated (OP) genetic mapping as an alternative to conventional bi-parental QTL mapping and genome wide association studies (GWAS). A QTL was simulated and the performance of a mixed linear model (MLM) and a multi-locus mixed model (MLMM) in QTL mapping accuracy was compared using a genotyping-by-sequencing (GBS) dataset of seven interspecific Royal Gala x M. sieversii bi-parental F1 populations. The simulation results show that the MLMM outperformed the MLM by accurately identifying the simulated QTL. Analysis of power indicated that a population size of 137 individuals is required to reach an = 0.8 for a simulated major effect QTL. Mapping resolution analysis showed that a population size of 470-600 individuals, depending on local recombination rates, is necessary to achieve high resolution within the OP population. Simulations demonstrate the potential of OP-based genetic mapping for identifying QTL in apples, reducing the logistical challenges associated with traditional QTL mapping methods. Our results show that OP-based genetic mapping could be used to speed up the identification of novel alleles directly from diverse germplasm collections in apples. Core IdeasBi-parental QTL mapping in apples is constrained by limited diversity, high costs, and long-term orchard space. OP-based mapping avoids controlled pollination, clonal propagation, and large-scale F1 orchard requirements. OP-based mapping offers an alternative to bi-parental mapping by leveraging existing germplasm and natural crosses. OP-mapping enables QTL discovery absent full pedigree information to strategically capture broad genetic diversity. OP F1 populations support fast QTL detection, aiding rapid breeding against emerging pathogens.

genetics↗

bioRxiv2025

Spatiotemporal variation in abundance and genetic structure across the urban-rural landscape gradient: Aedes albopictus (Skuse, 1894) (Diptera: Culicidae) in Wake County, NC

Since its invasion of the United States in the 1980s, Aedes albopictus (Skuse, 1894) has become a major pest and a significant public health threat in the Southeastern USA. Despite its importance, we know little about its population genetics at fine spatial scales. To remedy this lack of information, we analyzed Ae. albopictus spatial variation in mosquito abundance and genetic structure in an urban-rural landscape over two years (2016 and 2018) in Wake County, NC, USA. We used a reduced representation sequencing method to generate between 11,00 to 30,000 SNPs that were used for population genetic analyses. We found spatial variation in both the abundance, genetic diversity, and significant differences in genetic divergence among sites that varied between the two years. The year-to-year variation in the population genetic patterns at the within county scale suggests a dynamic system which requires extensive geographic, temporal, and genomic sampling to resolve. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/659333v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1158719org.highwire.dtl.DTLVardef@58ba77org.highwire.dtl.DTLVardef@139e303org.highwire.dtl.DTLVardef@166f334_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2025

Optimizing core collections for genetic studies: a worldwide flax germplasm case study

Core collections provide a strategic approach to reducing population size while retaining genetic diversity and allele frequencies, serving as key resources for genetic research. Although various sampling and selection strategies have been proposed, most of them focused on either diversity or representativeness, rarely both, and none fully integrated these with QTL detection optimization. The first part of our study focuses on a genetic diversity analysis of a flax germplasm (Linum usitatissimum L.), a prerequisite for the development of core collections. This germplasm, maintained by the Arvalis Institute, is a worldwide flax collection comprising 1,593 accessions originating from 42 countries, encompassing all major flax-growing regions. It includes both spring- and winter-type lines, as well as oilseed and fiber types. The results revealed a pronounced genetic structure within the germplasm, strongly influenced by cultivation purposes (fiber vs. oilseed flax), growth cycle (winter vs. spring), and geographic origin. A K-means clustering procedure identified six clusters as the optimal structuration, which aligns with our knowledge of this germplasm. Overall genetic diversity was moderate (H = 0.22), with oilseed flax clusters displaying greater diversity than fiber flax, likely due to the broader selection history and wider geographic distribution, findings consistent with previous studies. In a second step we evaluated twenty distinct strategies for core-collection development. Some approaches were originally developed for core-collection construction while others were developed for optimizing genomic-selection calibration panels. QTL detection performance was assessed via extensive simulations of QTLs distributed across the genome. We observed a fundamental trade-off between maximizing diversity and ensuring representativeness in core collection design. Diversity-oriented approaches may overemphasize rare or outlier genotypes, compromising representativeness, while representativeness-focused strategies leaded to overlooking rare alleles, thus limiting diversity. In our results we have found that particular combinations of selection criteria achieved a favorable balance between genetic diversity and representativeness, while concurrently maintaining a robust capacity to capture QTL signals across the genome. We demonstrated that using the Shannon index combined with the allelic coverage led to optimal core-collection design adapted for GWAS applications in a structured population. These results provide knowledge for the development of optimized core collections tailored to GWAS applications.

genetics↗

bioRxiv2025

Sex-specific disease association and genetic architecture of retinal vascular traits

Sex as a biological variable (SABV) remains underemphasized in biomedical research, despite its well-established impact on disease prevalence, progression, and genetic architecture. Here, we investigated sex differences in retinal vascular phenotypes, which are emerging as non-invasive biomarkers for ocular, cardiovascular, and neurodegenerative diseases. We used both interaction and sex-stratified analyses in disease association and genome-wide association studies (GWAS), including the X chromosome. Our analyses revealed sex-specific differences in associations between retinal traits, cardiometabolic risk factors, and disease outcomes. Several phenotypes showed prognostic value for mortality and cardiovascular endpoints, predominantly in one sex, illustrating the limitations of sex-agnostic analyses. Genetic analyses revealed differences in genetic architectures, with females exhibiting higher heritability and a greater number of associated loci, as well as sex-specific trait-gene associations. Notably, we report the first genetic association on the X chromosome for retinal vascular phenotypes. These findings suggest sex-differential genetic and environmental contributions to microvascular morphology, possibly reflecting divergent biological pathways and risk profiles. Our study underscores the necessity of integrating SABV and sex-aware approaches in genetic and prognostic research to advance precision medicine and improve tailored risk stratification.

genetics↗

bioRxiv2025

Inflammation-Induced Alternative Splicing in Human Endothelial Cells Reveals Genetic Mechanisms of Cardiovascular Disease Risk

Alternative splicing modulates mRNA protein-coding sequence, stability, and translation rates, although it has not been comprehensively annotated in human endothelial cells (ECs). EC dysfunction is a hallmark of complex inflammatory diseases, including cancer and atherosclerosis. Therefore, this study modeled acute inflammation in vitro using 53 genetically distinct human aortic EC lines exposed to interleukin-1{beta} (IL-1{beta}) or control media. This approach identified 1,224 differentially spliced transcripts (DSTs) between IL-1{beta} and control conditions. DSTs were enriched for alternative first (AF) exons, including several novel mRNA isoforms of disease-associated and metabolic genes. It was hypothesized and confirmed that AF splicing was driven by alternative promoters using ATAC-seq and ChIP-seq data. To identify alternative promoters driving IL-1{beta}-dependent AF isoforms, a quantitative measure of promoter activity ratios was defined, and analysis found that histone 3 lysine 27 acetylation and binding of the transcription factors ERG and RELA often correlated with alternative promoter usage. Finally, the effect of common genetic variants on alternative first exon usage was interrogated through splicing quantitative trait locus (sQTL) analysis. Significant sQTLs were next submitted to genetic colocalization analysis with cardiovascular-related associations identified by genome-wide association studies (GWAS), finding colocalized signals at 66 human disease loci corresponding to 30 genes and 39 variants. These genetically regulated splicing differences provide plausible mechanisms explaining some of the genetic risk for cardiovascular-related diseases. Among the top signals are novel isoforms of Endothelial Protein C Receptor (PROCR) and Distal Membrane Arm Assembly Component 2 (DMAC2), whose splicing patterns colocalize with risk for coronary artery disease (CAD). This study demonstrates the prevalence of inducible alternative promoters and supports that ECs express numerous novel transcripts regulated by genetics and inflammation that are consistent with driving individual risk for cardiovascular disease. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=66 SRC="FIGDIR/small/667484v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1a702c6org.highwire.dtl.DTLVardef@1a71602org.highwire.dtl.DTLVardef@961cbaorg.highwire.dtl.DTLVardef@13802eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2025

Genetic parameters and genome-wide association analysis of service sire effect on litter size and its relationship with boar semen quality in three terminal sire lines

This study aimed to estimate the genetic parameters for service sire effects on the number born alive (NBA) and its relationship with semen quality traits. Data of 6,416, 23,188, and 48,890 litter size records collected between 2020 and 2024 from three purebred terminal sire lines were analyzed. The number of sows was 3,071, 11,819, and 24,089, with 197, 554, and 891 service sires for the three respective lines. There were 1,424,858, 4,344,630, and 2,146,583 animals in the pedigree of which 67,990, 259,250, and 365,392 were genotyped and imputed up to 50K SNPs. The service sire and dam effects were modeled as additive genetic effects, considering a covariance structure among them, given by the relationship matrix. The model also included fixed effects of contemporary group and parity group with random permanent environmental effects for service sire and dam. Genetic parameters were estimated using the AIREML option in the BLUPF90+ software, and GEBVs were generated by ssGBLUP with the algorithm for proven and young (APY). Heritability for the service sire effect ranged from 0.01 to 0.03, and the heritability for the dam effect ranged from 0.09 to 0.15, with genetic correlations ranging from -0.20 to 0.37. A single-step genome-wide association study (ssGWAS) was also performed, and no strong signals were detected for service sire effects on NBA. Sperm motility (MOT) and total abnormal morphology (ABN_MOR) GEBVs from the three lines were estimated based on about 57,500 to 608,996 ejaculates recorded using the computer-assisted semen analysis (CASA) system from 1,698 to 29,095 boars collected from 2013 to 2025. Heritability estimates ranged from 0.10 to 0.12 for motility and from 0.17 to 0.28 for total abnormal morphology. The correlations between service sire GEBV for NBA and semen quality were low but in the favorable direction. Results suggest that although paternal genetic contributions to litter size were small compared to maternal genetic contributions, selecting on service sire effects on litter size in addition to semen quality traits will improve overall reproductive success.

genetics↗

bioRxiv2025

Early-stage sparse testing strategies to increase genetic gain in plant breeding programmes

Early-stage sparse testing can significantly increase genetic gain in plant breeding programmes, facilitating the development of varieties with high and stable performance across farmers fields. This is achieved through (1) increased selection accuracy, enabled by broader sampling of trial sites across the Target Population of Environments (TPE), and (2) increased selection intensity by testing more selection candidates at a reduced replication rate. Early-stage agronomic testing typically involves evaluating a large number of selection candidates at one or a few experimental sites. Although these sites may poorly represent the TPE, strong selection pressure is generally applied. However, if the genetic correlation between performance at the experimental sites and in the TPE is low, most of the genetic gain achieved through selection will not be expressed under farmers conditions. Sparse testing addresses this challenge by using farm-as-incomplete-block designs, in which different subsets of selection candidates are evaluated across sites. By leveraging a genomic relationship matrix (GRM) to connect genotypes across environments, sparse testing enables early-stage multi-environment trials with broader coverage of the TPE. Here, we used stochastic simulation to compare various partially replicated sparse testing strategies to three fully replicated conventional early-stage testing strategies, with and without GRM. All sparse testing strategies achieved substantially higher and more stable genetic gain than the conventional strategies. Our results show that sparse testing provides breeders with a powerful and flexible framework to rethink early-stage trials and design cost-effective, multi-location experiments that lay the foundation for increased genetic gains in farmers fields. Key messageEarly-stage sparse testing can significantly increase genetic gain by (1) improving selection accuracy through broader sampling of the Target Population of Environments (TPE), and (2) increasing selection intensity.

genetics↗

bioRxiv2025

Genetic regulation of fasting-induced longevity effects

Research methods for the investigation of the biology of aging have often implicitly generalized strain-specific results. Dietary interventions, such as caloric restriction and periodic fasting, have been shown to enhance metabolic health and extend lifespan in preclinical models. However, inter-individual variation in physiological responses to these interventions, which affects their safety and efficacy when translated to humans, remains poorly understood despite being observed in multiple studies. In this study, we implemented intermittent fasting (IF) for two days per week in 10 inbred strains (n = 800 mice) from the Collaborative Cross (CC). The CC is a multiparent recombinant inbred strain panel that offers a diverse collection of reproducible models to study the genetic control of heterogeneous intervention responses. We conducted longitudinal phenotyping to characterize hundreds of traits, including lifespan, in the CC mice. We demonstrate that sex and genetic background induce variable responses to intermittent fasting across multiple physiological outcomes, including metabolic, hematologic, and immunologic health. Effects of IF on lifespan were sex-specific and variable across genetic backgrounds. Thus we establish that response to IF is genetically determined in an animal model with physiological features similar to humans. We compared our findings in the CC with those from a parallel study of Diversity Outbred (DO) mice, highlighting common predictors of health and lifespan, as well as key differences between the genetically diverse inbred and outbred models. These findings underscore the importance of genetic factors in dietary intervention responses, offering valuable insights for translating intermittent fasting benefits to human health and longevity. Keywords: multiparental populations; gene-by-treatment interaction

genetics↗

bioRxiv2025

Comparing the genetic diversity of two threatened Rhyticeros hornbill species with contrasting geographic range sizes

Island endemics exhibit low genetic diversity due to founder effects and geographical isolation, increasing their vulnerability to inbreeding depression. The Narcondam Hornbill (Rhyticeros narcondami), restricted to the 6.8 km2 Narcondam island in the Andaman archipelago, has the smallest range size among hornbills, a globally threatened group of birds. We compared the genetic diversity of the Narcondam Hornbill with the Wreathed Hornbill (Rhyticeros undulatus) distributed from the Eastern Himalaya to Bali. We generated DNA sequences for four mitochondrial markers ; Cytochrome B (Cytb), cytochrome c oxidase subunit I (COI), NADH dehydrogenase subunit 2 (ND2) and displacement loop (D-loop) regions) from 14 Narcondam Hornbill faecal samples and for three markers (Cytb, COI and ND2) from 19 Wreathed Hornbill tissue samples from north-east India. Our results suggest markedly lower genetic diversity in the island endemic Narcondam Hornbill compared to the Wreathed Hornbill. Specifically, Cytb and COI showed no genetic variation in the island endemic, compared to three to five haplotypes in the Wreathed Hornbills. In the ND2 region, Narcondam Hornbills showed seven haplotypes among 13 samples compared to the Wreathed Hornbills six haplotypes among eight samples. The observed genetic diversity in the D-loop in the Narcondam Hornbill was lower than other island-endemic hornbill species in the Philippines. The extremely low genetic diversity in the Narcondam Hornbill likely stems from a small founder population and/or past hunting pressures that reduced its numbers to approximately 30% of its current population of 1000 birds, rendering the Narcondam Hornbill susceptible to environmental and human-driven changes.

genetics↗

bioRxiv2025

The historical patterns that have shaped contemporary genetic differentiation across populations of Arctic charr in Scotland

Glacial history is an important contributor to contemporary biogeographic patterns because it caused population fragmentation and consequently diversification. The Arctic charr (Salvelinus alpinus) is a highly diverse non-anadromous salmonid fish species in Britain and Ireland, which likely was anadromous when it colonised around the end of the last ice age. Colonisation history of the species remains largely unexplored and so the potential impact on contemporary patterns of genetic differentiation remains unclear. To address this, we conducted a national-scale genetic study of Arctic charr using a genome-wide dataset of SNPs (24,878 SNPs and 410 individuals) and mitochondrial ND1 sequences (238 sequences). We found several mitochondrial haplotypes were shared across Britain, Ireland, and the wider Holarctic suggesting colonisation by multiple sub-lineages of the Atlantic lineage of the species. Genetic differentiation was not correlated with geographic distance among river catchments, highlighting the effect of spatial isolation and genetic drift. Several populations across different river catchments showed atypical ancestries and evidence for genetic mixing, which we speculate are due to asynchronous ice coverage and the presence of ice-dammed lakes. Our results highlight how glacial history can impact colonisation history and subsequently contemporary patterns of genetic differentiation in this widespread species.

genetics↗

bioRxiv2025

Quantitative genetics of trauma induced mortality in Drosophila melanogaster

Traumatic brain injury is a major cause of chronic neurological impairment worldwide, and there is evidence that both genetic and environmental variation contribute to the likelihood of recovery. Using an insect model of traumatic brain injury, we examined variation in the risk of mortality using quantitative genetic approaches applied previously for life history traits in Drosophila melanogaster. We quantified additive genetic variance for mortality risk using a controlled breeding design and found levels of variation consistent with existing data on major fitness components. We found no evidence for inbreeding effects on mortality risk, suggesting that dominance genetic variance makes little contribution to this trait. To explain the high level of standing genetic variation, we considered whether mortality risk depends on the metabolic resources available to an individual, also known as "condition". We manipulated condition by inducing random mutations and by restricting calories during larval development. We found that reduced condition due to both random mutations and resource limitation significantly increased the risk of mortality following trauma. Among inbred lines, greater mortality risk was associated with lower viability, fecundity and longevity, consistent with an effect of genome-wide genetic quality. Our results suggest that further consideration of individual condition would be valuable for understanding and predicting variation in the outcomes of traumatic brain injury.

genetics↗

bioRxiv2017

The molecular genetics of participation in the Avon Longitudinal Study of Parents and Children

BackgroundIt is often assumed that selection (including participation and dropout) does not represent an important source of bias in genetic studies. However, there is little evidence to date on the effect of genetic factors on participation.\n\nMethodsUsing data on mothers (N=7,486) and children (N=7,508) from the Avon Longitudinal Study of Parents and Children, we 1) examined the association of polygenic risk scores for a range of socio-demographic, lifestyle characteristics and health conditions related to continued participation, 2) investigated whether associations of polygenic scores with body mass index (BMI; derived from self-reported weight and height) and self-reported smoking differed in the largest sample with genetic data and a sub-sample who participated in a recent follow-up and 3) determined the proportion of variation in participation explained by common genetic variants using genome-wide data.\n\nResultsWe found evidence that polygenic scores for higher education, agreeableness and openness were associated with higher participation and polygenic scores for smoking initiation, higher BMI, neuroticism, schizophrenia, ADHD and depression were associated with lower participation. Associations between the polygenic score for education and self-reported smoking differed between the largest sample with genetic data (OR for ever smoking per SD increase in polygenic score:0.85, 95% CI:0.81,0.89) and sub-sample (OR:0.95, 95% CI:0.88,1.02). In genome-wide analysis, single nucleotide polymorphism based heritability explained 17-31% of variability in participation.\n\nConclusionsGenetic association studies, including Mendelian randomization, can be biased by selection, including loss to follow-up. Genetic risk for dropout should be considered in all analyses of studies with selective participation.

genetics↗

bioRxiv2017

Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

BackgroundStressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable traits that are correlated with genetic risk for MDD. In the current study, we sought to investigate the genetic and environmental contributions to SLEs in a large family-based sample, and quantify any genetic overlap with MDD and neuroticism.\n\nMethodsA subset of Generation Scotland: the Scottish Family Health Study, consisting of 9618 individuals comprise the present study. We estimated the heritability of SLEs using pedigree-based and molecular genetic data. The environment was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression we analysed the genetic overlap between MDD, neuroticism and SLEs.\n\nResultsPast 6-month life events were positively correlated with lifetime MDD status ({beta}=0.21, r2=1.1%, p=2.5 x 10-25) and neuroticism ({beta} =0.13, r2=1.9%, p=1.04 x 10-37). Common SNPs explained 8% of the variance in personal life events (those directly affecting the individual) (S.E.=0.03, p=9 x 10-4). A significant effect of couple environment accounted for 13% (S.E.=0.03, p=0.016) of variation in SLEs. PRS analyses found that individuals with higher PRS for MDD reported more SLEs ({beta} =0.05, r2=0.3%, p=3 x 10-5). LD score regression demonstrated genetic correlations between MDD and both SLEs (rG=0.33, S.E.=0.08) and neuroticism (rG=0.15, S.E.=0.07).\n\nConclusionsThese findings suggest that SLEs are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work should determine the causal direction and source of these associations.

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bioRxiv2017

Genetic structure of a patchily-distributed philopatric migrant: implications for management and conservation

Significant demographic fluctuations can have major genetic consequences in wild populations. The Lesser Kestrel (Falco naumanni) has suffered from both population declines and range fragmentation during the second half of the 20th century. In this study we analysed multilocus microsatellite data to assess the genetic structure of the species. Our analysis revealed significant genetic structuring of Lesser Kestrel populations, not only at cross-continental scale, but also regionally within Central and Eastern (CE) Mediterranean. We detected signs of genetic bottlenecks in some of the peripheral populations coupled with small effective population sizes. Values of genetic differentiation among the largest populations were low, albeit significant, whereas the small peripheral CE Mediterranean populations showed higher levels of differentiation from all other populations. Gene flow levels were relatively low among the discontinuously distributed populations of the CE Mediterranean region. We argue that the observed spatial genetic structure can be attributed at some level to the past demographic decline experienced by the species. Finally, we identify management units in the region, and inform the design of conservation actions aiming at the increase of population sizes and dispersal rates among peripheral populations.

genetics↗

bioRxiv2017

Examination of the Shared Genetic Basis of Anorexia Nervosa and Obsessive-Compulsive Disorder

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a crossdisorder GWAS meta-analysis of 3,495 AN cases, 2,688 OCD cases and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (rg = 0.49 {+/-} 0.13, p = 9.07x10-7) and a sizable SNP heritability (SNP h2 = 0.21 {+/-} 0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., bipolar disorder, schizophrenia, neuroticism) and negative correlations with metabolic phenotypes (e.g., BMI, triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN/OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.

genetics↗

bioRxiv2017

A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest

BackgroundSudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. While several risk factors are observationally associated with SCA, the genetic architecture of SCA in the general population remains unknown. Furthermore, understanding which risk factors are causal may help target prevention strategies.\n\nMethodsWe carried out a large genome-wide association study (GWAS) for SCA (n=3,939 cases, 25,989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA.\n\nResultsNo variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (1) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (2) height and BMI, and (3) electrical instability traits (QT and atrial fibrillation), suggesting etiologic roles for these traits in SCA risk.\n\nConclusionsOur findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in highrisk populations and the general community.

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