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Introduction Smoking behaviors are partly heritable, yet the genetic and environmental mechanisms underlying smoking phenotypes are not fully understood. Developmental nicotine exposure (DNE) is a significant risk factor for smoking and leads to gene expression changes in mouse models; however, it is unknown whether the same genes whose expression is impacted by DNE are also those underlying smoking genetic liability. We examined whether genes whose expression in D1-type striatal medium spiny neurons due to DNE in the mouse are also associated with human smoking behaviors. Methods Specifically, we assessed whether human orthologs of mouse-identified genes, either individually or as a set, were genetically associated with five human smoking traits using MAGMA and S-LDSC while implementing a novel expression-based gene-SNP annotation methodology. Results We found no strong evidence that these genes sets were more strongly associated with smoking behaviors than the rest of the genome, but ten of these individual genes were significantly associated with three of the five human smoking traits examined (p Conclusions These results suggest the genes whose expression is impacted by DNE in mice are largely distinct from those contributing to smoking genetic liability in humans. However, examining a single mouse neuronal cell type may be too fine a resolution for comparison, suggesting that experimental manipulation of nicotine consumption, reward, or withdrawal in mice may better capture genes related to the complex genetics of human tobacco use. Implications Genes whose expression is impacted by DNE in mouse D1-type striatal medium spiny neurons were not found to be, as a whole, more strongly associated with human smoking behaviors than the rest of the genome, though ten individual mouse-identified genes were associated with human smoking traits. This suggests little overlap between the genetic mechanisms impacted by DNE and those influencing heritable liability to smoking phenotypes in humans. Further research is warranted to characterize how developmental nicotine exposure paradigms in mice can be translated to understand nicotine use in humans and their heritable effects on smoking.

Many complex human traits exhibit differences between sexes. While numerous factors likely contribute to this phenomenon, growing evidence from genome-wide studies suggest a partial explanation: that males and females from the same population possess differing genetic architectures. Despite this, mapping gene-by-sex (G×S) interactions remains a challenge likely because the magnitude of such an interaction is typically and exceedingly small; traditional genome-wide association techniques may be underpowered to detect such events, due partly to the burden of multiple test correction. Here, we developed a local Bayesian regression (LBR) method to estimate sex-specific SNP marker effects after fully accounting for local linkage-disequilibrium (LD) patterns. This enabled us to infer sex-specific effects and G×S interactions either at the single SNP level, or by aggregating the effects of multiple SNPs to make inferences at the level of small LD-based regions. Using simulations in which there was imperfect LD between SNPs and causal variants, we showed that aggregating sex-specific marker effects with LBR provides improved power and resolution to detect G×S interactions over traditional single-SNP-based tests. When using LBR to analyze traits from the UK Biobank, we detected a relatively large G×S interaction impacting bone mineral density within ABO, and replicated many previously detected large-magnitude G×S interactions impacting waist-to-hip ratio. We also discovered many new G×S interactions impacting such traits as height and body mass index (BMI) within regions of the genome where both male- and female-specific effects explain a small proportion of phenotypic variance (R2 < 1 × 10−4), but are enriched in known expression quantitative trait loci.

Genetic correlations suggest that the genetic relationship of alcohol use with internalizing psychopathology depends on the measure of alcohol use. Problematic alcohol use (PAU) is positively genetically correlated with internalizing psychopathology, whereas alcohol consumption ranges from not significantly correlated to moderately negatively correlated with internalizing psychopathology. To explore these different genetic relationships of internalizing psychopathology with alcohol use, we performed a multivariate genome-wide association study of four correlated factors (internalizing psychopathology, PAU, quantity of alcohol consumption, and frequency of alcohol consumption) and then assessed genome-wide and local genetic covariance between these factors. We identified 14 significant regions of local, largely positive, genetic covariance between PAU and internalizing psychopathology and 12 regions of significant local genetic covariance (including both positive and negative genetic covariance) between consumption factors and internalizing psychopathology. Partitioned genetic covariance among functional annotations suggested that brain tissues contribute significantly to positive genetic covariance between internalizing psychopathology and PAU but not to the genetic covariance between internalizing psychopathology and quantity or frequency of alcohol consumption. We hypothesize that genome-wide genetic correlations between alcohol use and psychiatric traits may not capture the more complex shared or divergent genetic architectures at the locus or tissue specific level. This study highlights the complexity of genetic architectures of alcohol use and internalizing psychopathology, and the differing shared genetics of internalizing disorders with PAU compared to consumption.

The genetic architecture of numerous smoking behaviors is highly polygenic, but these genetic effects are heterogeneous and depend on moderating factors. Here, we used common SNPs from the UK Biobank to investigate heterogeneous genetic effects for smoking heaviness using cigarettes per day (CPD) records, smoking initiation (SI), and smoking cessation (SC). We assessed heterogeneous effects across levels of sex, age of smoking initiation, major depressive disorder (MDD) DSM-V-like diagnosis, generalized anxiety disorder (GAD) DSM-V-like diagnosis, and whether an individual has seen a psychiatrist for nerves, anxiety, tension, or depression. We observed suggestive evidence of heterogeneous genetic effects for CPD and SC, moderated by MDD and GAD, respectively [ (SE = 0.15) between MDD cases and controls, and (SE = 0.28) between GAD cases and controls, p < 0.05]. We detected 5 SNPs with genome-wide significant evidence of heterogeneous effects moderated by either MDD or GAD (p-value < 5×10-8) for CPD and SC. We also observed strong evidence for heterogeneous genetic effects for SI between sexes (between-sex , SE = 0.02). While we detected no individual SNPs that were moderated by sex at genome-wide significance (all p-value > 5×10-8), we observed evidence of novel genome-wide significant SI-SNP associations using sex-stratified GWAS; six loci were discovered in either men or women separately that were not identified in a previous smoking meta-analysis that had a 6-fold larger, sex-combined sample. Furthermore, using several independent testing samples, there was suggestive evidence that the prediction ability of a polygenic risk score (PRS) for smoking initiation improved through the utilization of sex-specific SNP effects. This work suggests that a more nuanced approach to GWAS analyses is warranted, as potential heterogeneous effects can complicate variant discovery and polygenic risk score accuracy.Author SummarySmoking imposes a heavy health burden and is highly polygenic in architecture. Consistent with most complex traits, many causal loci have yet to be identified, even when using the largest available samples. One possible reason for the difficulty in inferring genetic variants associated with such complex traits is that common genetic variants possess context-dependent (or heterogeneous) effects. Utilizing the UK Biobank, we find evidence for heterogeneous SNP effects on smoking initiation, heaviness, and cessation among psychiatric disorder cases and controls and between sexes. Failure to model such heterogeneity (when accounting for sample size) resulted in lower independent sample predictive ability. This work encourages a more nuanced approach to GWAS and polygenic risk prediction. The assumption that all genetic effects are homogeneous limits our understanding of complex traits when heterogeneous effects are present.

Anxiety disorders and alcohol use disorders are common psychiatric illnesses. Comorbidity of the two disorders can have a tremendous effect on treatment of one or both disorders, as well as an individual’s social, economic, and physical well-being. We estimated genome-wide genetic correlations between anxiety and alcohol use traits using linkage disequilibrium score regression (LDSC) and found strong and positive correlations of anxiety with problematic alcohol use (PAU), but not with most alcohol consumption (AC) measures. We observed strong, positive between-sex genetic correlations for all traits, but found suggestive evidence that the genetic correlation between alcohol use and anxiety might differ between males and females. Estimates of local genetic covariance demonstrated divergent genetic covariance profiles of PAU and AC with anxiety phenotypes and localized 12 specific genomic regions that likely contribute to both anxiety and alcohol use. Finally, partitioning the genetic covariance among functional annotations also identified the amygdala, caudate basal ganglia and frontal cortex as contributing significantly to positive genetic covariance between anxiety and PAU phenotypes. This study serves as a framework for an approach to be used in future analyses of the genetics of comorbid disorders.

Gene expression is controlled at transcriptional and post-transcriptional levels including decoding of messenger RNA (mRNA) into polypeptides via ribosome-mediated translation. Translational regulation has been intensively studied in the model dicot plant Arabidopsis thaliana, and in this study, we assessed the translational status [proportion of steady-state mRNA associated with ribosomes] of mRNAs by Translating Ribosome Affinity Purification followed by mRNA-sequencing (TRAP-seq) in rice (Oryza sativa), a model monocot plant and the most important food crop. A survey of three tissues found that most transcribed rice genes are translated whereas few transposable elements are associated with ribosomes. Genes with short and GC-rich coding regions are overrepresented in ribosome-associated mRNAs, suggesting that the GC-richness characteristic of coding sequences in grasses may be an adaptation that favors efficient translation. Transcripts with retained introns and extended 5' untranslated regions are underrepresented on ribosomes, and rice genes belonging to different evolutionary lineages exhibited differential enrichment on the ribosomes that was associated with GC content. Genes involved in photosynthesis and stress responses are preferentially associated with ribosomes, whereas genes in epigenetic regulation pathways are the least enriched on ribosomes. Such variation is more dramatic in rice than that in Arabidopsis and is correlated with the wide variation of GC content of transcripts in rice. Taken together, variation in the translation status of individual transcripts reflects important mechanisms of gene regulation, which may have a role in evolution and diversification.

Many complex human traits exhibit differences between sexes. While numerous factors likely contribute to this phenomenon, growing evidence from genome-wide studies suggest a partial explanation: that males and females from the same population possess differing genetic architectures. Despite this, mapping gene-by-sex (G×S) interactions remains a challenge likely because the magnitude of such an interaction is typically and exceedingly small; traditional genome-wide association techniques may be underpowered to detect such events partly due to the burden of multiple test correction. Here, we developed a local Bayesian regression (LBR) method to estimate sex-specific SNP marker effects after fully accounting for local linkage-disequilibrium (LD) patterns. This enabled us to infer sex-specific effects and G×S interactions either at the single SNP level, or by aggregating the effects of multiple SNPs to make inferences at the level of small LD-based regions. Using simulations in which there was imperfect LD between SNPs and causal variants, we showed that aggregating sex-specific marker effects with LBR provides improved power and resolution to detect G×S interactions over traditional single-SNP-based tests. When using LBR to analyze traits from the UK Biobank, we detected a relatively large G×S interaction impacting bone-mineral density withinABOand replicated many previously detected large-magnitude G×S interactions impacting waist-to-hip ratio. We also discovered many new G×S interactions impacting such traits as height and BMI within regions of the genome where both male- and female-specific effects explain a small proportion of phenotypic variance (R2< 1×10−4), but are enriched in known expression quantitative trait loci. By combining biobank-level data and techniques to estimate sex-specific SNP effects after accounting for local-LD patterns, we are providing evidence that numerous small-magnitude G×S interactions exist to influence sex differences in a variety of complex traits.Author SummaryMany complex human traits are known to be influenced by an impressive number of causal variants each with very small effects, posing great challenges for genome-wide association studies (GWAS). To add to this challenge, many causal variants may possess context-dependent effects such as effects that are dependent on biological sex. While GWAS are commonly performed using specific methods in which one single nucleotide polymorphism (SNP) at a time is tested for association with a trait, alternatively we utilize methods more commonly observed in the genomic prediction literature. Such methods are advantageous in that they are not burdened by multiple test correction in the same way as traditional GWAS techniques are, and can fully account for linkage-disequilibrium patterns to accurately estimate the true effects of SNP markers. Here we adapt such methods to estimate genetic effects within sexes and provide a powerful means to compare sex-specific genetic effects.

All aerobic cells and organisms must synthesize heme from the amino acid glycine and the tricarboxylic acid cycle intermediate succinyl CoA for incorporation into hemoproteins, such as the cytochromes needed for oxidative phosphorylation. Most studies on heme regulation have been done in erythroid cells or hepatocytes; however, much less is known about heme metabolism in other cell types. The feline leukemia virus subgroup C receptor (FLVCR) is a 12-transmembrane domain surface protein that exports heme from cells, and it was shown to be required for erythroid development. In this article, we show that deletion of Flvcr in murine hematopoietic precursors caused a complete block in αβ T cell development at the CD4+CD8+ double-positive stage, although other lymphoid lineages were not affected. Moreover, FLVCR was required for the proliferation and survival of peripheral CD4+ and CD8+ T cells. These studies identify a novel and unexpected role for FLVCR, a major facilitator superfamily metabolite transporter, in T cell development and suggest that heme metabolism is particularly important in the T lineage.

Advances in pig genomic technologies enable implementation of new methods to estimate breed composition, allowing innovative and efficient ways to evaluate and ensure breed and line background. Existing methods to test for homozygosity at key loci involve test mating the animal in question and observing phenotypic patterns among offspring, requiring extensive resources. In this study, whole-genome pig DNA microarray data from over 8,000 SNP was used to profile the composition of U.S. registered purebred pigs using a refined linear regression method that enhances the interpretation of coefficients. In a simulation analysis, a strong correlation between true and estimated breed composition was observed (R2 = 0.94). Applying these methods to 930 Yorkshire animals registered with the National Swine Registry, 95% were estimated to have a “genome-wide” Yorkshire breed composition of at least 0.825 or 82.5%, with similar performance for evaluating datasets of registered Duroc (n = 88) Landrace (n = 129), and Hampshire (n = 17) breeds. We also developed new methods to evaluate locus-based breed probabilities. Such methods have been applied to multi-locus SNP genotypes flanking the KIT gene known to predominantly control coat color, thereby inferring the probability that an animal has haplotypes in the KIT region that are predominant in white breeds. These methods have been adopted by the National Swine Registry as a means to identify purebred Yorkshire animals.

Abstract 2162 Heme is essential for every mammalian cell, however, free heme can induce free radical formation and cellular damage, therefore cells must carefully regulate heme levels. The feline leukemia virus subgroup C receptor (FLVCR) exports heme from cells. Conditional deletion of Flvcr was shown to cause progressive anemia in neonatal and adult mice (Science 319:825–8, 2008). Using a transplant model, we previously demonstrated that Flvcr-deleted thymocytes were blocked at the CD4+CD8+ double-positive (DP) stage (Blood [ASH Annual Meeting Abstracts] 114: 913, 2009). To characterize the temporal requirement for FLVCR in developing thymocytes, we crossed Flvcrflox/flox mice to thymocyte-specific cre recombinase strains: Lck-cre mice, which express cre in early CD4+CD8+ double-negative (DN) thymocytes, and CD4-cre mice, which turn on cre in late DN/early DP thymocytes. Flvcrflox/flox;Lck-cre mice had similar numbers of DN and DP thymocytes compared to controls, however, CD4+ and CD8+ single-positive (SP) thymocytes and peripheral T cells were nearly absent, similar to what we observed in our previous transplant model. In contrast, Flvcrflox/flox;CD4-cre mice had intact thymic development with normal numbers of SP, but there were few CD4+ and CD8+ T cells in the periphery. When we analyzed deletion efficiency of these T cells, CD8+ T cells showed only 50% Flvcr deletion and were nearly all CD44-high, implying that only incompletely-deleted CD8+ T cells survived and expanded. Taken together, these results show that FLVCR is required not only for T cell development beyond the DP stage, but also for the survival of mature T cells in the periphery. We next adoptively transferred thymocytes from Flvcrflox/flox;CD4-cre mice or controls into sub-lethally irradiated Rag1−/− mice. Normal SP thymocytes undergo homeostatic proliferation when transferred into an “empty” host. At day 12 and 20 post-adoptive transfer, few Flvcrflox/flox;CD4-cre CD4+ or CD8+ T cells were found, in contrast to mice that had received Flvcr+/flox;CD4-cre thymocytes. To determine whether Flvcr-deleted T cells failed to undergo homeostatic proliferation, we used carboxyfluorescein succinimidyl ester (CFSE) to label Flvcrflox/flox;CD4-cre or control thymocytes prior to adoptive transfer. At day 8, similar numbers of Flvcrflox/flox;CD4-cre and control T cell were found in the periphery and both had diluted CFSE equally, thus initial proliferation was not affected. However, by day 20, few Flvcr-deleted T cells were present compared to controls. Experiments are currently underway to understand how and why Flvcr-deleted T cells fail to persist long-term. The finding that FLVCR is required for T cell development and peripheral survival is intriguing because there is no known specific role for heme in T cell development or function. We carried out transcriptional profiling on sorted DP thymocytes from Rag1−/− mice transplanted with Flvcr-deleted or control bone marrow to determine whether FLVCR loss led to gene expression changes that might explain the block in T cell development. Surprisingly, there were few transcriptional changes, suggesting that FLVCR loss has an abrupt impact on T cell development late in the DP stage. This finding, together with the apparent normal development of Flvcr-deleted B lymphocytes and myeloid lineages, leads us to hypothesize that FLVCR plays a specific role in T cell development starting at the DP stage and persisting throughout T cell life. FLVCR is a member of the major facilitator superfamily of secondary active transporters. While FLVCR has been shown to export heme, it is not known whether it can import or export other small molecules or metabolites. We are now using a bioinformatics approach on published datasets to analyze metabolic gene expression during normal thymic development and in various mature T cell subsets to identify metabolic pathways that are specific for the DP-SP transition in thymocytes as well as in mature, peripheral T cells. We will then test whether these pathways are altered in Flvcr-deleted thymocytes and mature T cells. These studies may uncover a new role for heme in T cell metabolism, function, and survival, or a new non-heme role for FLVCR. Disclosures: No relevant conflicts of interest to declare.