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Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. Results We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. Conclusions We show that PTRS has a significantly higher portability (Wilcoxon p =0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

Rationale Caffeine is widely consumed in foods and beverages and is also used for a variety of medical purposes. Despite its widespread use, relatively little is understood regarding how genetics affects consumption, acute response, or the long-term effects of caffeine. Objective This paper reviews the literature on the genetics of caffeine from the following: (1) twin studies comparing heritability of consumption and of caffeine-related traits, including withdrawal symptoms, caffeine-induced insomnia, and anxiety, (2) association studies linking genetic polymorphisms of metabolic enzymes and target receptors to variations in caffeine response, and (3) case-control and prospective studies examining relationship between polymorphisms associated with variations in caffeine response to risks of Parkinson’s and cardiovascular diseases in habitual caffeine consumers. Results Twin studies find the heritability of caffeine-related traits to range between 0.36 and 0.58. Analysis of polysubstance use shows that predisposition to caffeine use is highly specific to caffeine itself and shares little common disposition to use of other substances. Genome association studies link variations in adenosine and dopamine receptors to caffeine-induced anxiety and sleep disturbances. Polymorphism in the metabolic enzyme cytochrome P-450 is associated with risk of myocardial infarction in caffeine users. Conclusion Modeling based on twin studies reveals that genetics plays a role in individual variability in caffeine consumption and in the direct effects of caffeine. Both pharmacodynamic and pharmacokinetic polymorphisms have been linked to variation in response to caffeine. These studies may help guide future research in the role of genetics in modulating the acute and chronic effects of caffeine.

The JAX Diversity Outbred population is a new mouse resource derived from partially inbred Collaborative Cross strains and maintained by randomized outcrossing. As such, it segregates the same allelic variants as the Collaborative Cross but embeds these in a distinct population architecture in which each animal has a high degree of heterozygosity and carries a unique combination of alleles. Phenotypic diversity is striking and often divergent from phenotypes seen in the founder strains of the Collaborative Cross. Allele frequencies and recombination density in early generations of Diversity Outbred mice are consistent with expectations based on simulations of the mating design. We describe analytical methods for genetic mapping using this resource and demonstrate the power and high mapping resolution achieved with this population by mapping a serum cholesterol trait to a 2-Mb region on chromosome 3 containing only 11 genes. Analysis of the estimated allele effects in conjunction with complete genome sequence data of the founder strains reduced the pool of candidate polymorphisms to seven SNPs, five of which are located in an intergenic region upstream of the Foxo1 gene.

RNA sequencing has the potential to reveal many modalities of transcriptional regulation, such as various splicing phenotypes, but studies on gene regulation are often limited to gene expression due to the complexity of extracting and analyzing multiple RNA phenotypes. Here, we present Pantry, a framework to efficiently generate diverse RNA phenotypes from RNA sequencing data and perform downstream integrative analyses with genetic data. Pantry generates phenotypes from six modalities of transcriptional regulation (gene expression, isoform ratios, splice junction usage, alternative TSS/polyA usage, and RNA stability) and integrates them with genetic data via QTL mapping, TWAS, and colocalization testing. We apply Pantry to Geuvadis and GTEx data, finding that 4768 of the genes with no identified eQTL in Geuvadis have QTL in at least one other transcriptional modality, resulting in a 66% increase in genes over eQTL mapping. We further found that the QTL exhibit modality-specific functional properties that are further reinforced by joint analysis of different RNA modalities. We also show that generalizing TWAS to multiple RNA modalities approximately doubles the discovery of unique gene-trait associations, and enhances identification of regulatory mechanisms underlying GWAS signal in 42% of previously associated gene-trait pairs. Here, the authors present the Pantry framework, which extracts features from RNA sequencing data and performs multimodal genetic analyses. This type of analysis can increase gene-trait associations identified compared to using only expression levels.

Loneliness is a complex biological trait that has been associated with numerous negative health outcomes. The measurement and environmental determinants of loneliness are well understood, but its genetic basis is not. Previous studies have estimated the heritability of loneliness between 37 and 55% using twins and family-based approaches, and have explored the role of specific candidate genes. We used genotypic and phenotypic data from 10 760 individuals aged ⩾50 years that were collected by the Health and Retirement Study (HRS) to perform the first genome-wide association study of loneliness. No associations reached genome-wide significance (p>5 × 10 ). Furthermore, none of the previously published associations between variants within candidate genes (BDNF, OXTR, RORA, GRM8, CHRNA4, IL-1A, CRHR1, MTHFR, DRD2, APOE) and loneliness were replicated (p>0.05), despite our much larger sample size. We estimated the chip heritability of loneliness and examined coheritability between loneliness and several personality and psychiatric traits. Our estimates of chip heritability (14-27%) support a role for common genetic variation. We identified strong genetic correlations between loneliness, neuroticism, and a scale of 'depressive symptoms.' We also identified weaker evidence for coheritability with extraversion, schizophrenia, bipolar disorder, and major depressive disorder. We conclude that loneliness, as defined in this study, is a modestly heritable trait that has a highly polygenic genetic architecture. The coheritability between loneliness and neuroticism may reflect the role of negative affectivity that is common to both traits. Our results also reflect the value of studies that probe the common genetic basis of salutary social bonds and clinically defined psychiatric disorders.

Abraham Palmer and colleagues use genotyping by sequencing to perform genome-wide association studies on CFW mice for behavioral, physiological and gene expression traits. They find many QTLs and incorporate expression QTL analysis to prioritize specific genes at loci of interest that underlie different complex traits. Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice.

Even when trained under exactly the same conditions outbred male Sprague-Dawley (SD) rats vary in the form of the Pavlovian conditioned approach response (CR) they acquire. The form of the CR (i.e. sign-tracking vs. goal-tracking) predicts to what degree individuals attribute incentive salience to cues associated with food or drugs. However, we have noticed variation in the incidence of these two phenotypes in rats obtained from different vendors. In this study, we quantified sign- and goal-tracking behavior in a reasonably large sample of SD rats obtained from two vendors (Harlan or Charles River), as well as from individual colonies operated by both vendors. Our sample of rats acquired from Harlan had, on average, more sign-trackers than goal-trackers, and vice versa for our sample of rats acquired from Charles River. Furthermore, there were significant differences among colonies of the same vendor. Although it is impossible to rule out environmental variables, SD rats at different vendors and barriers may have reduced phenotypic heterogeneity as a result of genetic variables, such as random genetic drift or population bottlenecks. Consistent with this hypothesis, we identified marked population structure among colonies from Harlan. Therefore, despite sharing the same name, investigators should be aware that important genetic and phenotypic differences exist among SD rats from different vendors or even from different colonies of the same vendor. If used judiciously this can be an asset to experimental design, but it can also be a pitfall for those unaware of the issue.

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 (F ST > 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 for 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.

Background The phenotype of an individual can be affected not only by the individual’s own genotypes, known as direct genetic effects (DGE), but also by genotypes of interacting partners, indirect genetic effects (IGE). IGE have been detected using polygenic models in multiple species, including laboratory mice and humans. However, the underlying mechanisms remain largely unknown. Genome-wide association studies of IGE (igeGWAS) can point to IGE genes, but have not yet been applied to non-familial IGE arising from “peers” and affecting biomedical phenotypes. In addition, the extent to which igeGWAS will identify loci not identified by dgeGWAS remains an open question. Finally, findings from igeGWAS have not been confirmed by experimental manipulation. Results We leverage a dataset of 170 behavioral, physiological, and morphological phenotypes measured in 1812 genetically heterogeneous laboratory mice to study IGE arising between same-sex, adult, unrelated mice housed in the same cage. We develop and apply methods for igeGWAS in this context and identify 24 significant IGE loci for 17 phenotypes (FDR < 10%). We observe no overlap between IGE loci and DGE loci for the same phenotype, which is consistent with the moderate genetic correlations between DGE and IGE for the same phenotype estimated using polygenic models. Finally, we fine-map seven significant IGE loci to individual genes and find supportive evidence in an experiment with a knockout model that Epha4 gives rise to IGE on stress-coping strategy and wound healing. Conclusions Our results demonstrate the potential for igeGWAS to identify IGE genes and shed light into the mechanisms of peer influence.

The vertebrate cranium is a prime example of the high evolvability of complex traits. While evidence of genes and developmental pathways underlying craniofacial shape determination is accumulating, we are still far from understanding how such variation at the genetic level is translated into craniofacial shape variation. Here we used 3D geometric morphometrics to map genes involved in shape determination in a population of outbred mice (Carworth Farms White, or CFW). We defined shape traits via principal component analysis of 3D skull and mandible measurements. We mapped genetic loci associated with shape traits at ~80,000 candidate single nucleotide polymorphisms in ~700 male mice. We found that craniofacial shape and size are highly heritable, polygenic traits. Despite the polygenic nature of the traits, we identified 17 loci that explain variation in skull shape, and 8 loci associated with variation in mandible shape. Together, the associated variants account for 11.4% of skull and 4.4% of mandible shape variation, however, the total additive genetic variance associated with phenotypic variation was estimated in ~45%. Candidate genes within the associated loci have known roles in craniofacial development; this includes 6 transcription factors and several regulators of bone developmental pathways. One gene, Mn1, has an unusually large effect on shape variation in our study. A knockout of this gene was previously shown to affect negatively the development of membranous bones of the cranial skeleton, and evolutionary analysis shows that the gene has arisen at the base of the bony vertebrates (Eutelostomi), where the ossified head first appeared. Therefore, Mn1 emerges as a key gene for both skull formation and within-population shape variation. Our study shows that it is possible to identify important developmental genes through genome-wide mapping of high-dimensional shape features in an outbred population.