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bioRxiv2023

Genetic diversity of North American popcorn germplasm and the effect of population structure on nicosulfuron response

Popcorn is an important crop in the United States; however, genetic analyses of popcorn are limited and tend to utilize relatively few markers that cannot capture the total genomic variation. To improve the genomic resources in popcorn, a panel of 362 popcorn accessions was evaluated using 417,218 single nucleotide polymorphisms generated using a genotyping-by-sequencing approach. Using this genomic data, a model-based clustering analysis identified two populations. The first comprised North American Yellow Pearl Popcorns and several accessions of the Chilean Curagua landrace. The second, the Pointed and Latin American Popcorns, included all remaining North American (pointed and early popcorns), Latin American, and global accessions. The two populations exhibited large differences in population structure and genetic diversity. The North American Yellow Pearl Popcorns constitute a highly inbred population with limited genetic diversity compared to the Pointed and Latin American Popcorns. Additionally, phenotypic differences between the two populations were observed in kernel color and nicosulfuron sensitivity. A filtered set of SNPs was curated and used for genome-wide association studies and popcorn-specific candidate genes for nicosulfuron tolerance were identified. The genomic characterization described here can be used by breeding programs to accelerate the rate of genetic gain and incorporate genetic diversity into elite popcorn germplasm. Core IdeasO_LINorth American Popcorn is composed of two distinct populations that differ genetically and phenotypically. C_LIO_LINorth American Yellow Pearl Popcorns contain limited genetic diversity and are highly inbred. C_LIO_LIPointed and Latin American Popcorns exhibit considerable genetic diversity and rapid linkage disequilibrium decay. C_LIO_LIKernel color does not affect nicosulfuron sensitivity and instead reflects differences between the populations. C_LIO_LIPopcorn-specific candidate genes for nicosulfuron tolerance are distinct from dent corn. C_LI

genetics↗

bioRxiv2023

Assessment of long-term trends in genetic mean and variance after the introduction of genomic selection in layers: a simulation study

Nucleus-based breeding programs are characterized by intense selection that results in high genetic gain, which inevitably means reduction of genetic variation in the breeding population. Therefore, genetic variation in such breeding systems is typically managed systematically, for example, by avoiding mating the closest relatives to limit progeny inbreeding. However, intense selection requires maximum effort to make such breeding programs sustainable in the long-term. The objective of this study was to use simulation to evaluate the long-term impact of genomic selection on genetic mean and variance in an intense layer chicken breeding program. We developed a large-scale stochastic simulation of an intense layer chicken breeding program to compare conventional truncation selection to genomic truncation selection optimized with either minimization of progeny inbreeding or full-scale optimal contribution selection. We compared the programs in terms of genetic mean, genic variance, conversion efficiency, rate of inbreeding, effective population size, and accuracy of selection. Our results confirmed that genomic truncation selection has immediate benefits compared to conventional truncation selection in all specified metrics. A simple minimization of progeny inbreeding after genomic truncation selection did not provide any significant improvements. Optimal contribution selection was successful in having better conversion efficiency and effective population size compared to genomic truncation selection, but it must be fine-tuned for balance between loss of genetic variance and genetic gain. In our simulation, we measured this balance using trigonometric penalty degrees between truncation selection and a balanced solution and concluded that the best results were between 45{degrees} and 65{degrees}. This balance is specific to the breeding program and depends on how much immediate genetic gain a breeding program may risk vs. save for the future. Furthermore, our results show that the persistence of accuracy is better with optimal contribution selection compared to truncation selection. In general, our results show that optimal contribution selection can ensure long-term success in intensive breeding programs using genomic selection.

genetics↗

bioRxiv2023

Genetic diversity of the Atacama Desert shrub Huidobria chilensis in the context of geography and climate

Survival in hyperarid deserts is a major challenge for plant life, requiring the development of evolutionary strategies. The Atacama Desert presents harsh conditions such as limited rainfall, crusted soils, high soil salinity, high altitude, and intense solar radiation. These conditions, together with paleoclimatic variability since the past millions of years, have influenced the genetic structure and connectivity of plant populations, resulting in a diverse flora with high endemism. However, the diversification of most lineages appears to be relatively recent, in contrast to proposed age of the Atacama Desert and the onset, evolution and expansion of hyperarid conditions since the Late Oligocene and Early Miocene. A prominent exception is the Atacama paleoendemic Huidobria chilensis (Loasaceae), which is thought to be adapted to such conditions since the Eocene. Still, the environmental limits and thresholds for life in the Atacama remain poorly understood. To investigate the genetic structure in relation to the history of the Atacama Desert, we studied 186 individuals from 11 populations using genotyping-by-sequencing (GBS). Genome-wide single nucleotide polymorphisms (SNPs) were analyzed for population structure and genetic diversity. We identified three genetic clusters corresponding to geographic regions: the coastal region south of Tocopilla, the Coastal Cordillera around Chanaral, and the Copiapo watershed in the south. These clusters as well as genetic diversity were analyzed alongside rainfall, altitude, and landscape data. Although the genetic data generally supports isolation by distance as a major factor for genetic variation between populations, the study also reveals the influence of the topography on the distribution of H. chilensis and highlights the role of hydrologically connected watersheds and rivers in plant migration and colonization. This shapes the species evolutionary trajectory and genetic diversity. Understanding these patterns provides insights into the adaptation and survival strategies of plants in extreme desert environments such as the Atacama.

genetics↗

bioRxiv2024

Interleaved intersectional strategy enables genetic lineage tracing with enhanced specificity

BACKGROUNDDual recombinases have been increasingly employed for enhanced precision in genetic targeting. A recent study utilizing an intersectional genetic approach through dual recombinases (Dre + CreER) has revealed that endocardium-derived fibroblasts (EndoFbs) play a pivotal role in cardiac fibrosis after pressure overload. However, this intersectional strategy has limitations, primarily due to ectopic genetic labeling of non-target cells within the adult heart by the constitutively active Dre recombinase. METHODSTo address this issue, we have developed an advanced, interleaved and intersectional reporter (IIR) strategy in this study. This IIR strategy leverages an inducible CreER to prevent inadvertent Dre-rox recombination during development or disease progression by designing an interleaved reporter to allow for more specific tracing of EndoFbs. Moreover, our IIR system also incorporates Diphtheria Toxin Receptor (DTR) in targeted cells, enabling functional characterization of these cells after genetic ablation. RESULTSEndoFbs were regionally distributed in the heart during homeostasis and proliferated preferentially in response to pressure overload, leading to cardiac fibrosis in defined regions. The IIR strategy enables the tracing of EndoFbs with a more prominent regional pattern and facilitates genetic ablation of EndoFbs through DT injection. In addition, we have applied this IIR strategy to specifically target fibroblasts derived from the epicardium (EpiFbs). Genetic lineage tracing of EpiFb reveals that their distribution pattern is complementary to that of EndoFbs in the adult heart. When a substantial number of EpiFbs were genetically ablated, EndoFbs could replace the loss of EpiFbs in some specific regions of hearts. CONCLUSIONSThe IIR strategy refines the precision of genetic lineage tracing while still employing the constitutively active Dre recombinase in tandem with inducible Cre. EndoFbs and EpiFbs are complementary in their distribution pattern in the heart, where EndoFbs have the potential to replace the loss of EpiFbs in some regions.

genetics↗

bioRxiv2025

Genetic underpinnings of chills from art and music

Art can evoke strong emotional responses in humans. Here, we examine genetic contributions to chills, a marker of such responses. We gather self-reports from a genotyped sample of thousands of partly related individuals from the Netherlands (N =15,606). Using genomic relationships based on common single-nucleotide polymorphism (SNP) data, we find that up to 29% of the variation in proneness to aesthetic (visual art and poetry) and music chills can be explained by familial relatedness effects, one-fourth of which is attributed to SNP variation. Furthermore, we reveal a moderate genetic correlation of .58 between aesthetic and music chills, pointing to shared genetic variation affecting susceptibility to strong emotional responses across different art forms. Finally, we find that a polygenic index (PGI) capturing openness to experiences, including propensities towards art (N = 234,880), is associated with susceptibilities both to aesthetic and music chills. Our results show that additive genetic variation, but also familial relatedness beyond shared common SNPs, contributes to proneness to chills from artistic, poetic, and musical expressions. These results open up a promising path towards studying the human attitude towards art, via both state-of-the-art genomics and intergenerational models of transmission. Author SummaryMany people experience chills when listening to music, reading poetry, or viewing art. Yet not everyone feels these reactions in the same way. These differences provide a window into how our brains and bodies respond to art, revealing individual variation in emotional experiences. To investigate what drives these differences, we analysed data from over 15,000 participants with available genetic information, examining whether DNA variation could help explain why some people are more prone to these intense responses. We estimated that roughly 30% of the variation in chills is linked to family-related factors, of which about one fourth was attributable to common DNA variants. Some genetic influences appear to be shared across music, poetry, and art, and are associated with individual openness to experience and general artistic interests, while others may be unique to each domain. These results suggest that genetics contributes to how strongly people respond to cultural experiences and pave the way for future studies on the genetics of sensitivity to art and music experiences.

genetics↗

bioRxiv2025

Temperature and genetic background drive mobilization of diverse transposable elements in a critical human fungal pathogen

Transposable elements (TEs) are key agents of genome evolution across all domains of life. These mobile genetic elements can cause mutations through transposition or by promoting structural rearrangements. Stress conditions can amplify TE mobility, either by impairing TE suppression mechanisms or through stress-induced interactions between transcription factors and TE sequences, offering a route for rapid genetic change. As such, TEs represent an important source of adaptability within populations. To investigate the interplay between environmental stress and eukaryotic TE dynamics relevant to infectious disease, we examined how heat stress and host-mimicking medium (RPMI) affect TE mobility in the global human fungal pathogen Cryptococcus neoformans, using a collection of clinical and environmental isolates. Using a selection-based screen, we captured the mobilization of seven distinct mobile element families, encompassing diverse retrotransposons and DNA transposons, whose insertions conferred antifungal resistance. This includes a novel element, CNEST, which belongs to the CACTA, Mirage, Chapaev (CMC) supergroup. Heat stress at human body temperature (37{degrees}C) significantly increased the mobilization of a subset of these TEs, leading to higher rates of acquired antifungal resistance. Whole-genome assemblies revealed that, compared to retrotransposons, DNA transposons were hypomethylated and approximately uniformly distributed throughout the genome, features that may contribute to their frequent mobilization. We further assessed TE-driven genomic changes within hosts using serial isolates from patients with recurrent cryptococcal infections and from isolates passaged through mice. While we observed evidence of TE copy number changes near chromosome ends, we found no indication of TE-mediated alterations near gene-coding regions across any of the serial isolates. Finally, TE mobility was isolate- and strain-dependent, with significant variation even among clonally related strains collected from the same patient, emphasizing the role of genetic background in shaping TE activity. Together, these findings reveal a complex and dynamic relationship between environmental stress, genetic background, TE type-specific epigenetic regulation, and TE mobility, with important implications for adaptation and acquired antifungal resistance in C. neoformans. AUTHOR SUMMARYTransposable elements (TEs) are mobile segments of DNA that can "jump" from one place to another in a genome, causing genetic changes that can impact fitness and evolution. In this study, we investigate how different environmental conditions influence TE mobility in the pathogenic yeast Cryptococcus neoformans, which is globally distributed in the environment and causes life-threatening infections. We compared genetically diverse strains and found that growth at higher temperatures, specifically human body temperature (37{degrees}C), increases the mobility of some TEs. In contrast, other TEs were more active at lower temperatures (30{degrees}C), indicating distinct pathways of temperature regulation for different TE groups. By examining C. neoformans isolates from patients with recurrent infections, we observed genetic changes by one TE group that likely occurred during infection. We also found that TE groups are distributed differently across the genome and show varying levels of DNA methylation, a modification that can suppress their activity and control TE mobility in the cell. Overall, this work shows that environmental stresses, such as increased temperature, can accelerate genetic change by promoting TE mobilization. These changes may contribute to how C. neoformans adapts during infection or in the environment.

genetics↗

bioRxiv2025

Mapping of genotype-by-environment interaction loci for Metabolic Syndrome-like traits using the multi-parent Drosophila Synthetic Population Resource determines that main genetic effects are distinct from environment dependent plastic loci

Metabolic Syndrome (MetS) risk, driven by genotype-environment interactions like diet, is rising globally. Due to its genetic and environmental complexity, the genetic architecture and interconnected traits underlying MetS is poorly understood. In Drosophila, genotype-by-diet interactions significantly influence MetS-like traits. This study used the Drosophila Synthetic Population Resource to dissect the genetic architecture of both genotypic and genotype-by-diet interaction effects underlying trait variation. The study hypotheses were: 1) Loci responsible for metabolic phenotypic variation should be shared across traits. 2) Genetic loci responsible for plasticity and epistatic interactions for metabolic traits should also be the loci responsible for the main effects. 3) Genes responsible for variation in metabolic traits should share common functions. Using a round-robin crossing scheme and novel analyses, we mapped additive, dominance, and epistatic loci--some diet-specific, others diet-independent. Main-effect and plastic loci were largely distinct, as were epistatic loci from main-effect loci, highlighting that main genetic effects alone will not explain how genetic variants interact with the environment or the genome to influence disease risk. gene-by-diet or gene-by-gene interactions influencing MetS risk. Further, tremendous cryptic genetic variation for metabolic traits is lurking in natural populations. We explored the function of candidate genes from our study empirically and with bioinformatics. While some of the candidate genes might have been expected, most would not have been identified a priori, thus with this study we have identified many new candidate mechanisms contributing to the genetic and genotype-by-diet interaction effects on MetS variance.

genetics↗

bioRxiv2025

On the analysis of genetic association with long-read sequencing data

Long-read sequencing (LRS) technologies have enhanced the ability to resolve complex genomic architecture and determine the phase relationships of genetic variants over long distances. Although genome-wide association studies (GWAS) identify individual variants associated with complex traits, they do not typically account for whether multiple associated signals at a locus may act in cis or trans, or whether they reflect allelic heterogeneity. As a result, effects that arise specifically from phase relationships may remain hidden in analyses using short-read and microarray data. While the advent of LRS has enabled accurate measurement of phase in population cohorts, statistical methods that leverage phase in genetic association analysis remain underdeveloped. Here, we introduce the Regression on Phase (RoP) method, which directly models cis and trans phase effects between variants under a regression framework. In simulations, RoP outperforms genotype interaction tests that detect phase effects indirectly, and distinguishes in-cis from in-trans phase effects. We implemented RoP at two cystic fibrosis (CF) modifier loci discovered by GWAS. At the chromosome 7q35 trypsinogen locus, RoP confirmed that two variants contributed independently (allelic heterogeneity). At the SLC6A14 locus on chromosome X, phase analysis uncovered a coordinated regulatory mechanism in which a promoter variant modulates lung phenotypes in individuals with CF when acting in cis with a lung-specific enhancer (E2765449/enhD). This coordinated regulation was confirmed in functional studies. These findings highlight the potential of leveraging phase information from LRS in genetic association studies. Analyzing phase effects with RoP can provide deeper insights into the complex genetic architectures underlying disease phenotypes, ultimately guiding more informed functional investigations and potentially revealing new therapeutic targets. Author summaryTraditional genetic association studies typically link individual genetic variants to diseases but often neglect how variants may jointly affect outcomes based on their arrangement across maternal and paternal chromosomes, known as phase relationships. Understanding phase effects is essential for uncovering the mechanisms underlying complex diseases. Recent advances in long-read sequencing technology allow precise measurement of phase relationships over extensive chromosome regions; however, statistical methods for analyzing these effects remain limited. We developed a novel statistical approach called Regression on Phase (RoP) to directly assess these complex genetic interactions. Our simulation studies demonstrated that RoP effectively identifies effects dependent on specific phase arrangements. Applying RoP to genetic variants contributing to cystic fibrosis (CF) revealed phase-dependent mechanisms affecting CF-related lung disease, which were missed by traditional methods. Analyzing phase effects with RoP can advance our understanding of disease mechanisms, guide future functional studies, and ultimately support the development of personalized medicine.

genetics↗

bioRxiv2025

Impact of genomic selection on genetic diversity in five local European cattle breeds

Genomic selection (GS) has revolutionised animal breeding and accelerated genetic gains in breeding programs. While GS has become common in major dairy cattle breeds, its implementation in local breeds has begun only more recently or is still in progress. However, the introduction of GS in some major breeds has also been associated with increased inbreeding rates, raising concerns about the potential effects of GS on the genetic diversity in smaller or local breeds. Our aim was to investigate the impact of GS on genetic diversity in five (small) local cattle breeds from three European countries. The five breeds evaluated were: MRY (from the Netherlands), Norwegian Red (from Norway), Abondance, Tarentaise, and Vosgienne (from France). We investigated changes in population demographic structure, as well as trends and rates of kinship and inbreeding, using both pedigree- and genomic-based measures. The population size varied depending on the breed, with Vosgienne being the smallest and Norwegian Red being the largest. The dataset included 4,645 MRY, 193,489 Norwegian Red, 16,427 Abondance, 8,882 Tarentaise, and 4,466 Vosgienne genotyped animals for more than 40,000 single-nucleotide polymorphisms. Overall, following the implementation of GS in these breeds, we observed a reduction in generation intervals for sires, fewer calves that later became sires, and, for the French breeds, a broader sire usage. Such changes were likely due to GS enabling the preselection and screening of more young bulls. Additionally, we observed a more balanced contribution of the top ten sires after the introduction of GS. Although changes in inbreeding and kinship rates occurred after the introduction of GS, there was no consistent pattern across breeds: rates increased in MRY and Tarentaise, but decreased in Norwegian Red, Abondance, and Vosgienne. Our study suggests that changes and increases in inbreeding rates may occur after the introduction of GS, although they may not be directly due to the introduction of GS per se, but rather due to population management strategies, such as optimal contribution selection or other breeding practices implemented at the nucleus level. Our findings emphasise the importance of monitoring changes in both genetic diversity and population demographic structure after implementing GS in local breeds, as well as adjusting breeding strategies when needed to ensure long-term sustainability. Interpretive SummaryGenomic selection (GS) has transformed cattle breeding. We investigated changes in population demographic structure and genetic diversity in five European breeds after the introduction of GS. Changes in inbreeding and kinship rates were not consistent across breeds, with both increases and decreases observed. Genetic management strategies, such as optimal contribution selection, had a greater impact on maintaining genetic diversity than the introduction of GS per se. These findings highlight the need to monitor changes in genetic diversity and population demographic structure after the implementation of GS and, when needed, to adapt management strategies to ensure long-term sustainability.

genetics↗

bioRxiv2025

Pervasive context-dependent effects in the genetic architecture of complex and quantitative traits revealed by a powerful multiparent mapping population in yeast

The genetic dissection of complex traits remains a major challenge in basic and biomedical research, but is essential for understanding the molecular pathways that shape phenotypic variation and for developing predictive models of trait and disease susceptibility. Here, we leverage a novel multiparent mapping population of budding yeast, CYClones, comprising 9,344 haploid strains derived from eight genetically diverse founders, to identify quantitative trait loci (QTL) and systematically investigate the genetic architecture of growth rates across ten environmental conditions. In total, we identified 349 QTL (ranging from 19 to 49 QTL per growth condition) that explained between 61% and 100% of narrow sense heritability across traits. The high power and resolution of CYClones revealed that growth traits exhibited distinct, condition-specific genetic architectures with extensive allelic heterogeneity, where a QTL was the result of multiple tightly linked causal variants. We also observed pleiotropy among QTL with complex, trait-dependent allele effects that are also consistent with allelic heterogeneity. Genetic complexity varied widely, with some traits showing nearly Mendelian architectures, while others were highly polygenic. Introgressed loci played a prominent role in the landscape of growth rate QTL, including one that is localized to a 2.4 kb interval in the PCA1 cadmium transporter and explains 72% of variation in cadmium resistance and another large-effect QTL that alters growth on galactose via complex non-additive interactions with the transcriptional regulator GAL3. In both cadmium and galactose conditions, we show that allelic variation at a small number of loci stratifies the population into regulatory or physiological subgroups, each with distinct genetic architectures, a phenomenon we term allele-dependent stratification. Collectively, our results provide novel insights into the genetics of growth rates in budding yeast, the architectural features of genetic complexity, and demonstrate that CYClones is a powerful platform for revealing the molecular basis of complex trait variation.

genetics↗

bioRxiv2018

The Shared Genetic Basis of Human Fluid Intelligence and Brain Morphology

Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses reveal the genetic overlap between cognitive ability and cortical thickness measurements in bilateral primary motor cortex and predominantly left superior temporal cortex and proximal regions. These findings may contribute to our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.

genetics↗

bioRxiv2018

The Limits to Parapatric Speciation II: Strengthening a Preexisting Genetic Barrier to Gene Flow in Parapatry

Parapatric speciation has recently received a lot of attention. By encompassing the whole continuum between allopatric and sympatric scenarios, it includes many potential scenarios for the evolution of new species. Building upon previous work, we investigate how a genetic barrier to gene flow, that relies on a single postzygotic genetic incompatibility, may further evolve. We consider a continent island model with three loci involved in pairwise Dobzhansky-Muller incompatibilities (DMIs). Using a deterministic and analytic approach, we derive the conditions for invasion of a new mutation and its consequences on an already existing genetic barrier to gene flow. We focus on quantifying the impact of the epistasis generated by the new mutation on the genetic barrier. We show that the accumulation of genetic incompatibilities in the presence of gene flow is a complex process, where new mutations can either strengthen or destroy a preexisting barrier. In particular, preexisting polymorphism and incompatibilities do not always facilitate the growth of the genetic barrier by accumulation of further barrier genes. Migration may disrupt the snowball effect (the accelerating rate of DMI accumulation in allopatry) because incompatibilities are directly tested by selection. Our results also show an ambiguous role of gene flow, which can either impede or facilitate the strengthening of the genetic barrier. Overall, our results illustrate how the inclusion of gene flow renders the building of a genetic barrier difficult to analyze.

genetics↗

bioRxiv2018

A High-Resolution Genetic Map for the Laboratory Rat

An accurate and high-resolution genetic map is critical for mapping complex traits, yet the resolution of the current rat genetic map is far lower than human and mouse, and has not been updated since the original ensen-Seaman map in 2004. For the first time, we have refined the rat genetic map to sub-centimorgan (cM) r solution (<0.02 cM) by using 95,769 genetic markers and 870 informative meioses from a cohort of 528 heterogeneous stock (HS) rats. Global recombination rates in the revised sex-averaged map (0.66 cM/Mb) did not difeer compared to the historical map (0.65 cM/Mb); however, substantial refinement was made to the localization of highly recombinant regions within the revised map. Also for the first time, sex-specific rat genetic maps were generated, which revealed both genomewide and fine-scale variation in recombination rates between male and female rats. Reanalysis of multiple quantitative trait loci (QTL) using the historical and refined rat genetic maps demonstrated marked changes to QTL localization, shape, and effect size. As a resource to the rat research community, we have provided revised centimorgan positions for all physical positions within the rat genome and commonly used genetic markers for trait mapping, including 44,828 SSLP markers and the RATDIV genotyping array. Collectively, this study provides a substantial improvement to the rat genetic map and an unprecedented resource for analysis of complex traits and recombination in the rat.

genetics↗

bioRxiv2018

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Sprague Dawley (SD) rats are among the most widely used outbred laboratory rat populations. Despite this, the genetic characteristics of SD rats have not been clearly described, and SD rats are rarely used for experiments aimed at exploring genotype-phenotype relationships. In order to use SD rats to perform a genome-wide association study (GWAS), we collected behavioral data from 4,625 SD rats that were predominantly obtained from two commercial vendors, Charles River Laboratories and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we obtained dense, high-quality genotypes at 291,438 SNPs across 4,061 rats. This genetic data allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that the two populations are highly diverged (FST > 0.4). Furthermore, even for rats obtained from the same vendor, there was strong population structure across breeding facilities and even between rooms at the same facility. We performed multiple separate GWAS by fitting a linear mixed model that accounted population structure and using meta-analysis to jointly analyze all cohorts. Our study examined Pavlovian conditioned approach (PavCA) behavior, which assesses the propensity for rats to attribute incentive salience to reward-associated cues. We identified 46 significant associations for the various metrics used to define PavCA. The surprising degree of population structure among SD rats from different sources has important implications for their use in both genetic and non-genetic studies. Author SummaryOutbred Sprague Dawley rats are among the most commonly used rats for neuroscience, physiology and pharmacological research; in the year 2020, 4,188 publications contained the keyword "Sprague Dawley". Rats identified as "Sprague Dawley" are sold by several commercial vendors, including Charles River Laboratories and Harlan Sprague Dawley Inc. (now Envigo). Despite their widespread use, little is known about the genetic diversity of SD. We genotyped more than 4,000 SD rats, which we used for a genome-wide association study (GWAS) and to characterize genetic differences between SD rats from Charles River Laboratories and Harlan. Our analysis revealed extensive population structure both between and within vendors. The GWAS for Pavlovian conditioned approach (PavCA) identified a number of genome-wide significant loci for that complex behavioral trait. Our results demonstrate that, despite sharing an identical name, SD rats that are obtained from different vendors are very different. Future studies should carefully define the exact source of SD rats being used and may exploit their genetic diversity for genetic studies of complex traits.

genetics↗

bioRxiv2018

Novel insights into the genetic relationship between growth and disease resistance in Pacific salmon

BackgroundBreeding for disease resistance has become a highly desirable strategy for mitigating infectious disease problems in aquaculture. However, knowledge of the genetic relationship between resistance and other economically important traits, such as growth, is important to assess prior to including disease resistance into the breeding goal. Our study assessed the genetic correlations between growth and survival traits in a large bacterial infection challenge experiment. A population of 2,606 coho salmon individuals from 107 full-sibling families were challenged with the bacteria Piscirickettsia salmonis. Growth was measured as average daily gain prior (ADG0) and during (ADGi) the experimental infection and as harvest weight (HW). Resistance was measured as Survival time (ST) and binary survival (BS). Furthermore, individual measures of bacterial load (BL) were assessed as new resistance phenotypes and to provide an indication of genetic variation in tolerance in salmonid species.\n\nResultsSignificant moderate heritabilities were estimated for ADG0 (0.30 {+/-} 0.05), HW (0.38 {+/-} 0.03), and for the survival traits ST (0.16 {+/-} 0.03) and BS (0.18 {+/-} 0.03). In contrast, heritabilities for ADGi and log-transformed BL were low (0.07 {+/-} 0.02 (significant) and 0.04 {+/-} 0.03, respectively), although these increased to moderate significant levels (0.20 {+/-} 0.09 and 0.12 {+/-} 0.05, respectively) when traits were assessed in survivors only. Significant and favorable genetic correlations were found between ADG0 and the growth traits ADGi (0.40 {+/-} 0.16) and HW (0.64 {+/-} 0.09), as well as with resistance as ST (0.43 {+/-} 0.18), indicating that fish with higher genetic growth rate early on and prior to infection not only tend to maintain their genetic growth advantage until harvest, but also tend to grow faster and survive longer during infection. Furthermore, no robust unfavorable genetic correlations between ADG0 and any of the other traits considered in this study, in particular BL, was identified. Adding log BL as covariates into the models for growth under infection and survival provided an indication for genetic variation in tolerance.\n\nConclusionsThese results suggest that selective breeding for early growth would be expected to simultaneously increase survival time and growth performance during an infection with Piscirickettsia salmonis after accounting for variation in bacterial load, and harvest weight in this coho salmon population, without negatively impacting on pathogen burden.

genetics↗

bioRxiv2019

Genetic interactions affect lung function in patients with systemic sclerosis

Scleroderma, or systemic sclerosis (SSc), is an autoimmune disease characterized by progressive fibrosis of the skin and internal organs. The most common cause of death in people with SSc is lung disease, but the pathogenesis of lung disease in SSc is insufficiently understood to devise specific treatment strategies. Developing targeted treatments requires not only the identification of molecular processes involved in SSc-associated lung disease, but also understanding of how these processes interact to drive pathology. One potentially powerful approach is to identify alleles that interact genetically to influence lung outcomes in patients with SSc. Analysis of interactions, rather than individual allele effects, has the potential to delineate molecular interactions that are important in SSc-related lung pathology. However, detecting genetic interactions, or epistasis, in human cohorts is challenging. Large numbers of variants with low minor allele frequencies, paired with heterogeneous disease presentation, reduce power to detect epistasis. Here we present an analysis that increases power to detect epistasis in human genome-wide association studies (GWAS). We tested for genetic interactions influencing lung function and autoantibody status in a cohort of 416 SSc patients. Using Matrix Epistasis to filter SNPs followed by the Combined Analysis of Pleiotropy and Epistasis (CAPE), we identified a network of interacting alleles influencing lung function in patients with SSc. In particular, we identified a three-gene network comprising WNT5A, RBMS3, and MSI2, which in combination influenced multiple pulmonary pathology measures. The associations of these genes with lung outcomes in SSc are novel and high-confidence. Furthermore, gene coexpression analysis suggested that the interactions we identified are tissue-specific, thus differentiating SSc-related pathogenic processes in lung from those in skin.\n\nAuthor summarySystemic sclerosis (SSc), or scleroderma, is a devastating autoimmune disease. Patients experience progressive fibrosis of their skin and internal organs, reduced quality of life, and increased risk of death. Lung disease associated with SSc is particularly dangerous and is currently the leading cause of death in SSc patients. There are no specific treatments for SSc or SSc-related lung disease, but promising work in the genetics of this disease has identified more than 200 genetic variants that influence SSc [1]. Piecing together how genetic variants interact with each other to influence disease may provide clues for targeted therapies. Here we present a novel analytical approach for identifying genetic interactions in a human disease cohort. In this approach we first filtered SNPs to those that are most likely to interact to influence the disease traits. We then applied the Combined Analysis of Pleiotropy and Epistasis (CAPE), which combines information across multiple traits to increase power to detect genetic interactions. Using this approach, we identified a three-gene network among MSI2, WNT5A, and RBMS3 that influenced autoantibody status and lung function in a cohort of 416 SSc patients. Gene expression data suggest that this interaction network is tissue- and disease-specific, and may thus provide a specific target for SSc therapy.

genetics↗

bioRxiv2019

Genetic Testing Preferences and Intentions in U.S. Patients with Clinically Diagnosed Familial Hypercholesterolemia

PurposeFamilial Hypercholesterolemia (FH) is a common Mendelian disorder characterized by elevated LDL cholesterol levels, which if untreated can cause premature heart disease. Less than 10% of cases in the US are diagnosed, and uptake of genetic testing is suboptimal. This study investigates decisionmaking factors associated with intentions to have FH genetic testing among patients clinically diagnosed with FH.\n\nMethodsClinically diagnosed adults with FH and no genetic testing were recruited through the FH Foundation and lipid clinics. Participants completed a survey containing items capturing various reasons to engage in genetic testing.\n\nResultsExploratory factor analysis of survey items identified three factors: (1) aversion to FH genetic information, (2) curiosity regarding medical/family history, (3) and psychological reassurance. Psychological reassurance was, in turn, the only significant predictor of genetic testing intentions. The effect of reassurance was qualified by aversion such that the inverse association between aversion and genetic testing intentions was greater among those with low perceived reassurance.\n\nConclusionFindings suggest that clinically diagnosed patients decisions about FH genetic testing are driven principally by psychological reassurance.

genetics↗

bioRxiv2019

Improving short and long term genetic gain by accounting for within family variance in optimal cross selection

The implementation of genomic selection in recurrent breeding programs raised several concerns, especially that a higher inbreeding rate could compromise the long term genetic gain. An optimized mating strategy that maximizes the performance in progeny and maintains diversity for long term genetic gain on current and yet unknown future targets is essential. The optimal cross selection approach aims at identifying the optimal set of crosses maximizing the expected genetic value in the progeny under a constraint on diversity in the progeny. Usually, optimal cross selection does not account for within family selection, i.e. the fact that only a selected fraction of each family serves as candidate parents of the next generation. In this study, we consider within family variance accounting for linkage disequilibrium between quantitative trait loci to predict the expected mean performance and the expected genetic diversity in the selected progeny of a set of crosses. These predictions rely on the method called usefulness criterion parental contribution (UCPC). We compared UCPC based optimal cross selection and optimal cross selection in a long term simulated recurrent genomic selection breeding program considering overlapping generations. UCPC based optimal cross selection proved to be more efficient to convert the genetic diversity into short and long term genetic gains than optimal cross selection. We also showed that using the UCPC based optimal cross selection, the long term genetic gain can be increased with only limited reduction of the short term commercial genetic gain.

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