Genome-wide association study of behavioral, physiological and gene expression traits in outbred CFW mice

HyperTRIBE uncovers increased MUSASHI-2 RNA binding activity and differential regulation in leukemic stem cells

The cell-context dependency for RNA binding proteins (RBPs) mediated control of stem cell fate remains to be defined. Here we adapt the HyperTRIBE method using an RBP fused to a Drosophila RNA editing enzyme (ADAR) to globally map the mRNA targets of the RBP MSI2 in mammalian adult normal and malignant stem cells. We reveal a unique MUSASHI-2 (MSI2) mRNA binding network in hematopoietic stem cells that changes during transition to multipotent progenitors. Additionally, we discover a significant increase in RNA binding activity of MSI2 in leukemic stem cells compared with normal hematopoietic stem and progenitor cells, resulting in selective regulation of MSI2's oncogenic targets. This provides a basis for MSI2 increased dependency in leukemia cells compared to normal cells. Moreover, our study provides a way to measure RBP function in rare cells and suggests that RBPs can achieve differential binding activity during cell state transition independent of gene expression.

Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity

There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.

Mouse Systems Genetics as a Prelude to Precision Medicine

Mouse models have been instrumental in understanding human disease biology and proposing possible new treatments. The precise control of the environment and genetic composition of mice allows more rigorous observations, but limits the generalizability and translatability of the results into human applications. In the era of precision medicine, strategies using mouse models have to be revisited to effectively emulate human populations. Systems genetics is one promising paradigm that may promote the transition to novel precision medicine strategies. Here, we review the state-of-the-art resources and discuss how mouse systems genetics helps to understand human diseases and to advance the development of precision medicine, with an emphasis on the existing resources and strategies.

A Genome-Wide Association Study Identifies Quantitative Trait Loci Affecting Hematological Traits in Camelus bactrianus

Simple Summary

Bactrian camels can adapt to harsh natural environments. This unique tolerance of camels is tightly linked to their hematological traits, which are related to their immune, metabolic, and disease status. Therefore, mapping genomic regions that affect blood cell traits can help identify genomic characteristics that can be used as biomarkers of immune, metabolic, and disease states. This knowledge will further our understanding of the camel’s tolerance mechanisms.

Abstract

Bactrian camels (Camelus bactrianus) are one of the few large livestock species that can survive in the Gobi Desert. Animal immunity and disease resistance are related to hematological traits, which are also associated with tolerance observed in Bactrian camels. However, no genome-wide association studies have examined the genetic mechanism of the immune capability of Bactrian camels. In the present study, we used genotyping-by-sequencing data generated from 366 Bactrian camel accessions to perform a genome-wide association study for 17 hematological traits. Of the 256,616 single-nucleotide polymorphisms (SNPs) obtained, 1,635 trait–SNP associations were among the top quantitative trait locus candidates. Lastly, 664 candidate genes associated with 13 blood traits were identified. The most significant were ZNF772, MTX2, ESRRG, MEI4, IL11, FRMPD4, GABPA, NTF4, CRYBG3, ENPP5, COL16A1, and CD207. The results of our genome-wide association study provide a list of significant SNPs and candidate genes, which offer valuable information for further dissection of the molecular mechanisms that regulate the camel’s hematological traits to ultimately reveal their tolerance mechanisms.

Genome-wide barebones regression scan for mixed-model association analysis

Based on the simplified FaST-LMM, wherein genomic variance is replaced with heritability, we have significantly improved computational efficiency by implementing rapid R/fastLmPure to statistically infer the genetic effects of tested SNPs and focus on large or highly significant SNPs obtained using the EMMAX algorithm. For a genome-wide mixed-model association analysis, we introduce a barebones linear model fitting function called fastLmPure from the R/RcppArmadillo package for the rapid estimation of single nucleotide polymorphism (SNP) effects and the maximum likelihood values of factored spectrally transformed linear mixed models (FaST-LMM). Starting from the estimated genomic heritability of quantitative traits under a null model without quantitative trait nucleotides, maximum likelihood estimations of the polygenic heritabilities of candidate markers consume the same time as approximately four rounds of genome-wide regression scans. When focusing only on SNPs with large effects or high significance levels, as estimated by the efficient mixed-model association expedited algorithm, the run time of genome-wide mixed-model association analysis is reduced to at most two rounds of genome-wide regression scans. We have developed a novel software application called Single-RunKing to transform nonlinear mixed-model association analyses into barebones linear regression scans. Based on a realised relationship matrix calculated using genome-wide markers, Single-RunKing saves significantly computation time, as compared with the FaST-LMM that optimises the variance ratios of polygenic variances to residual variances using the R/lm function.

Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2

Muscle bulk in adult healthy humans is highly variable even after height, age, and sex are accounted for. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-aged (aged 38-49 years) individuals from the UK Biobank (UKB), we found 182 loci associated with ALM (p < 5 × 10-8). We replicated associations for 78% of these loci (p < 5 × 10-8) with ALM in a population of 181,862 elderly (aged 60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J); this GWAS identified 23 quantitative trait loci. Thirty-eight positional candidates distributed across five loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.

Using Heterogeneous Stocks for Fine-Mapping Genetically Complex Traits

In this chapter we will review both the rationale and experimental design for using Heterogeneous Stock (HS) populations for fine-mapping of complex traits in mice and rats. We define an HS as an outbred population derived from an intercross between two or more inbred strains. HS have been used to perform genome-wide association studies (GWAS) for multiple behavioral, physiological, and gene expression traits. GWAS using HS require four key steps, which we review: selection of an appropriate HS population, phenotyping, genotyping, and statistical analysis. We provide advice on the selection of an HS, comment on key issues related to phenotyping, discuss genotyping methods relevant to these populations, and describe statistical genetic analyses that are applicable to genetic analyses that use HS.

Systems genetics applications in metabolism research

The common forms of metabolic diseases are highly complex, involving hundreds of genes, environmental and lifestyle factors, age-related changes, sex differences and gut-microbiome interactions. Systems genetics is a population-based approach to address this complexity. In contrast to commonly used 'reductionist' approaches, such as gain or loss of function, that examine one element at a time, systems genetics uses high-throughput 'omics' technologies to quantitatively assess the many molecular differences among individuals in a population and then to relate these to physiologic functions or disease states. Unlike genome-wide association studies, systems genetics seeks to go beyond the identification of disease-causing genes to understand higher-order interactions at the molecular level. The purpose of this review is to introduce the systems genetics applications in the areas of metabolic and cardiovascular disease. Here, we explain how large clinical and omics-level data and databases from both human and animal populations are available to help researchers place genes in the context of pathways and networks and formulate hypotheses that can then be experimentally examined. We provide lists of such databases and examples of the integration of reductionist and systems genetics data. Among the important applications emerging is the development of improved nutritional and pharmacological strategies to address the rise of metabolic diseases.

Heritable natural variation of light/dark preference in an outbred zebrafish population

Anxiety is a fear-like response to stimuli perceived to be threatening. Excessive or uncontrollable anxiety is a debilitating psychiatric disorder which affects many people throughout their lifetime. In unravelling the complex genetic and environmental regulations of anxiety-like phenotypes, models measuring the natural dark avoidance of larval zebrafish have shed light on the individual variation and heritability of this anxiety-related trait. Using the light/dark choice paradigm and selective breeding, this study aims to validate previous findings of the variable (VDA) and strong dark aversion (SDA) heritability in AB-WT larval zebrafish using the outbred zebrafish strain EK, which offers more genetic diversity to aid in future molecular mapping efforts. 190 larvae (6 days post fertilization [dpf] and 7 dpf) were tested across four trials and divided into variable (VDA), medium (MDA) and strong (SDA) dark aversion for further in-crosses. VDA and MDA larvae became more explorative with time, whereas SDA larvae rarely left the preferred light zone. The SDA and VDA in-crosses significantly increased the respective phenotypes in the second generation of larvae, whereas VDA × MDA inter-crosses did not. For the second-generation SDA cohort, dark aversion correlated with increased thigmotaxis, which reinforces SDA as an anxiety-like phenotype. Our finding that the dark aversion trait and SDA and VDA phenotypes are heritable in an outbred zebrafish population lays an important foundation for future studies of genetic underpinnings using whole-genome mapping methods. This conserved fear/anxiety-like response in a highly accessible model organism also allows for further pharmacological and behavioral studies to elucidate the etiology of anxiety and the search for novel therapeutics for anxiety disorders.

Negr1 controls adult hippocampal neurogenesis and affective behaviors

Recent genome-wide association studies on major depressive disorder have implicated neuronal growth regulator 1 (Negr1), a GPI-anchored cell adhesion molecule in the immunoglobulin LON family. Although Negr1 has been shown to regulate neurite outgrowth and synapse formation, the mechanism through which this protein affects mood disorders is still largely unknown. In this research, we characterized Negr1-deficient (negr1^-/-) mice to elucidate the function of Negr1 in anxiety and depression. We found that anxiety- and depression-like behaviors increased in negr1^-/- mice compared with wild-type mice. In addition, negr1^-/- mice had decreased adult hippocampal neurogenesis compared to wild-type mice. Concurrently, both LTP and mEPSC in the dentate gyrus (DG) region were severely compromised in negr1^-/- mice. In our effort to elucidate the underlying molecular mechanisms, we found that lipocalin-2 (Lcn2) expression was decreased in the hippocampus of negr1^-/- mice compared to wild-type mice. Heterologous Lcn2 expression in the hippocampal DG of negr1^-/- mice rescued anxiety- and depression-like behaviors and restored neurogenesis and mEPSC frequency to their normal levels in these mice. Furthermore, we discovered that Negr1 interacts with leukemia inhibitory factor receptor (LIFR) and modulates LIF-induced Lcn2 expression. Taken together, our data uncovered a novel mechanism of mood regulation by Negr1 involving an interaction between Negr1 and LIFR along with Lcn2 expression.

Novel biomarkers to assess in utero effects of maternal opioid use: First steps toward understanding short- and long-term neurodevelopmental sequelae

Maternal opioid use disorder is common, resulting in significant neonatal morbidity and cost. Currently, it is not possible to predict which opioid-exposed newborns will require pharmacotherapy for neonatal abstinence syndrome. Further, little is known regarding the effects of maternal opioid use disorder on the developing human brain. We hypothesized that novel methodologies utilizing fetal central nervous system-derived extracellular vesicles isolated from maternal blood can address these gaps in knowledge. Plasma from opioid users and controls between 9 and 21 weeks was precipitated and extracellular vesicles were isolated. Mu opioid and cannabinoid receptor levels were quantified. Label-free proteomics studies and unbiased small RNA next generation sequencing was performed in paired fetal brain tissue. Maternal opioid use disorder increased mu opioid receptor protein levels in extracellular vesicles independent of opioid equivalent dose. Moreover, cannabinoid receptor levels in extracellular vesicles were upregulated with opioid exposure indicating cross talk with endocannabinoids. Maternal opioid use disorder was associated with significant changes in extracellular vesicle protein cargo and fetal brain micro RNA expression, especially in male fetuses. Many of the altered cargo molecules and micro RNAs identified are associated with adverse clinical neurodevelopmental outcomes. Our data suggest that assays relying on extracellular vesicles isolated from maternal blood extracellular vesicles may provide information regarding fetal response to opioids in the setting of maternal opioid use disorder. Prospective clinical studies are needed to evaluate the association between extracellular vesicle biomarkers, risk of neonatal abstinence syndrome and neurodevelopmental outcomes.

Epistasis regulates the developmental stability of the mouse craniofacial shape

Fluctuating asymmetry is a classic concept linked to organismal development. It has traditionally been used as a measure of developmental instability, which is the inability of an organism to buffer environmental fluctuations during development. Developmental stability has a genetic component that influences the final phenotype of the organism and can lead to congenital disorders. According to alternative hypotheses, this genetic component might be either the result of additive genetic effects or a by-product of developmental gene networks. Here we present a genome-wide association study of the genetic architecture of fluctuating asymmetry of the skull shape in mice. Geometric morphometric methods were applied to quantify fluctuating asymmetry: we estimated fluctuating asymmetry as Mahalanobis distances to the mean asymmetry, correcting first for genetic directional asymmetry. We applied the marginal epistasis test to study epistasis among genomic regions. Results showed no evidence of additive effects but several interacting regions significantly associated with fluctuating asymmetry. Among the candidate genes overlapping these interacting regions we found an over-representation of genes involved in craniofacial development. A gene network is likely to be associated with skull developmental stability, and genes originally described as buffering genes (e.g., Hspa2) might occupy central positions within these networks, where regulatory elements may also play an important role. Our results constitute an important step in the exploration of the molecular roots of developmental stability and the first empirical evidence about its genetic architecture.

Integrated analysis of population genomics, transcriptomics and virulence provides novel insights into Streptococcus pyogenes pathogenesis

Streptococcus pyogenes causes 700 million human infections annually worldwide, yet, despite a century of intensive effort, there is no licensed vaccine against this bacterium. Although a number of large-scale genomic studies of bacterial pathogens have been published, the relationships among the genome, transcriptome, and virulence in large bacterial populations remain poorly understood. We sequenced the genomes of 2,101 emm28 S. pyogenes invasive strains, from which we selected 492 phylogenetically diverse strains for transcriptome analysis and 50 strains for virulence assessment. Data integration provided a novel understanding of the virulence mechanisms of this model organism. Genome-wide association study, expression quantitative trait loci analysis, machine learning, and isogenic mutant strains identified and confirmed a one-nucleotide indel in an intergenic region that significantly alters global transcript profiles and ultimately virulence. The integrative strategy that we used is generally applicable to any microbe and may lead to new therapeutics for many human pathogens.

Replication and discovery of musculoskeletal QTLs in LG/J and SM/J advanced intercross lines

The genetics underlying variation in health‐related musculoskeletal phenotypes can be investigated in a mouse model. Quantitative trait loci (QTLs) affecting musculoskeletal traits in the LG/J and SM/J strain lineage remain to be refined and corroborated. The aim of this study was to map muscle and bone traits in males (n = 506) of the 50th filial generation of advanced intercross lines (LG/SM AIL) derived from the two strains. Genetic contribution to variation in all musculoskeletal traits was confirmed; the SNP heritability of muscle mass ranged between 0.46 and 0.56; and the SNP heritability of tibia length was 0.40. We used two analytical software, GEMMA and QTLRel, to map the underlying QTLs. GEMMA required substantially less computation and recovered all the QTLs identified by QTLRel. Seven significant QTLs were identified for muscle weight (Chr 1, 7, 11, 12, 13, 15, and 16), and two for tibia length, (Chr 1 and 13). Each QTL explained 4–5% of phenotypic variation. One muscle and both bone loci replicated previous findings; the remaining six were novel. Positional candidates for the replicated QTLs were prioritized based on in silico analyses and gene expression in muscle tissue. In summary, we replicated existing QTLs and identified novel QTLs affecting muscle weight, and replicated bone length QTLs in LG/SM AIL males. Heritability estimates substantially exceed the cumulative effect of the QTLs, hence a richer genetic architecture contributing to muscle and bone variability could be uncovered with a larger sample size.

Identification of a novel gene regulating amygdala-mediated fear extinction

Recent years have seen advances in our understanding of the neural circuits associated with trauma-related disorders, and the development of relevant assays for these behaviors in rodents. Although inherited factors are known to influence individual differences in risk for these disorders, it has been difficult to identify specific genes that moderate circuit functions to affect trauma-related behaviors. Here, we exploited robust inbred mouse strain differences in Pavlovian fear extinction to uncover quantitative trait loci (QTL) associated with this trait. We found these strain differences to be resistant to developmental cross-fostering and associated with anatomical variation in basolateral amygdala (BLA) perineuronal nets, which are developmentally implicated in extinction. Next, by profiling extinction-driven BLA expression of QTL-linked genes, we nominated Ppid (peptidylprolyl isomerase D, a member of the tetratricopeptide repeat (TPR) protein family) as an extinction-related candidate gene. We then showed that Ppid was enriched in excitatory and inhibitory BLA neuronal populations, but at lower levels in the extinction-impaired mouse strain. Using a virus-based approach to directly regulate Ppid function, we demonstrated that downregulating BLA-Ppid impaired extinction, while upregulating BLA-Ppid facilitated extinction and altered in vivo neuronal extinction encoding. Next, we showed that Ppid colocalized with the glucocorticoid receptor (GR) in BLA neurons and found that the extinction-facilitating effects of Ppid upregulation were blocked by a GR antagonist. Collectively, our results identify Ppid as a novel gene involved in regulating extinction via functional actions in the BLA, with possible implications for understanding genetic and pathophysiological mechanisms underlying risk for trauma-related disorders.

Genome wide association analysis in a mouse advanced intercross line

The LG/J x SM/J advanced intercross line of mice (LG x SM AIL) is a multigenerational outbred population. High minor allele frequencies, a simple genetic background, and the fully sequenced LG and SM genomes make it a powerful population for genome-wide association studies. Here we use 1,063 AIL mice to identify 126 significant associations for 50 traits relevant to human health and disease. We also identify thousands of cis- and trans-eQTLs in the hippocampus, striatum, and prefrontal cortex of ~200 mice. We replicate an association between locomotor activity and Csmd1, which we identified in an earlier generation of this AIL, and show that Csmd1 mutant mice recapitulate the locomotor phenotype. Our results demonstrate the utility of the LG x SM AIL as a mapping population, identify numerous novel associations, and shed light on the genetic architecture of mammalian behavior.

Decoding the transcriptional programs activated by psychotropic drugs in the brain

Analysis of drug-induced gene expression in the brain has long held the promise of revealing the molecular mechanisms of drug actions as well as predicting their long-term clinical efficacy. However, despite some successes, this promise has yet to be fulfilled. Here, we present an overview of the current state of understanding of drug-induced gene expression in the brain and consider the obstacles to achieving a robust prediction of the properties of psychoactive compounds based on gene expression profiles. We begin with a comprehensive overview of the mechanisms controlling drug-inducible transcription and the complexity resulting from expression of noncoding RNAs and alternative gene isoforms. Particular interest is placed on studies that examine the associations within drug classes with regard to the effects on gene transcription, alterations in cell signaling and neuropharmacological drug properties. While the ability of gene expression signatures to distinguish specific clinical classes of psychotropic and addictive drugs remains unclear, some reports show that under specific constraints, drug properties can be predicted based on gene expression. Such signatures offer a simple and effective way to classify psychotropic drugs and screen novel psychoactive compounds. Finally, we note that the amount of data regarding molecular programs activated in the brain by drug treatment has grown exponentially in recent years and that future advances may therefore come in large part from integrating the currently available high-throughput data sets.

A Methodological Assessment and Characterization of Genetically-Driven Variation in Three Human Phosphoproteomes

Phosphorylation of proteins on serine, threonine, and tyrosine residues is a ubiquitous post-translational modification that plays a key part of essentially every cell signaling process. It is reasonable to assume that inter-individual variation in protein phosphorylation may underlie phenotypic differences, as has been observed for practically any other molecular regulatory phenotype. However, we do not know much about the extent of inter-individual variation in phosphorylation because it is quite challenging to perform a quantitative high throughput study to assess inter-individual variation in any post-translational modification. To test our ability to address this challenge with SILAC-based mass spectrometry, we quantified phosphorylation levels for three genotyped human cell lines within a nested experimental framework, and found that genetic background is the primary determinant of phosphoproteome variation. We uncovered multiple functional, biophysical, and genetic associations with germline driven phosphopeptide variation. Variants affecting protein levels or structure were among these associations, with the latter presenting, on average, a stronger effect. Interestingly, we found evidence that is consistent with a phosphopeptide variability buffering effect endowed from properties enriched within longer proteins. Because the small sample size in this 'pilot' study may limit the applicability of our genetic observations, we also undertook a thorough technical assessment of our experimental workflow to aid further efforts. Taken together, these results provide the foundation for future work to characterize inter-individual variation in post-translational modification levels and reveal novel insights into the nature of inter-individual variation in phosphorylation.

Collective interaction effects associated with mammalian behavioral traits reveal genetic factors connecting fear and hemostasis

BACKGROUND

Investigation of the genetic architectures that influence the behavioral traits of animals can provide important insights into human neuropsychiatric phenotypes. These traits, however, are often highly polygenic, with individual loci contributing only small effects to the overall association. The polygenicity makes it challenging to explain, for example, the widely observed comorbidity between stress and cardiac disease.

METHODS

We present an algorithm for inferring the collective association of a large number of interacting gene variants with a quantitative trait. Using simulated data, we demonstrate that by taking into account the non-uniform distribution of genotypes within a cohort, we can achieve greater power than regression-based methods for high-dimensional inference.

RESULTS

We analyzed genome-wide data sets of outbred mice and pet dogs, and found neurobiological pathways whose associations with behavioral traits arose primarily from interaction effects: γ-carboxylated coagulation factors and downstream neuronal signaling were highly associated with conditioned fear, consistent with our previous finding in human post-traumatic stress disorder (PTSD) data. Prepulse inhibition in mice was associated with serotonin transporter and platelet homeostasis, and noise-induced fear in dogs with hemostasis.

CONCLUSIONS

Our findings suggest a novel explanation for the observed comorbidity between PTSD/anxiety and cardiovascular diseases: key coagulation factors modulating hemostasis also regulate synaptic plasticity affecting the learning and extinction of fear.

Genome-wide association for testis weight in the diversity outbred mouse population

Testis weight is a genetically mediated trait associated with reproductive efficiency across numerous species. We sought to evaluate the genetically diverse, highly recombinant Diversity Outbred (DO) mouse population as a tool to identify and map quantitative trait loci (QTLs) associated with testis weight. Testis weights were recorded for 502 male DO mice and the mice were genotyped on the GIGAMuga array at ~ 143,000 SNPs. We performed a genome-wide association analysis and identified one significant and two suggestive QTLs associated with testis weight. Using bioinformatic approaches, we developed a list of candidate genes and identified those with known roles in testicular size and development. Candidates of particular interest include the RNA demethylase gene Alkbh5, the cyclin-dependent kinase inhibitor gene Cdkn2c, the dynein axonemal heavy chain gene Dnah11, the phospholipase D gene Pld6, the trans-acting transcription factor gene Sp4, and the spermatogenesis-associated gene Spata6, each of which has a human ortholog. Our results demonstrate the utility of DO mice in high-resolution genetic mapping of complex traits, enabling us to identify developmentally important genes in adult mice. Understanding how genetic variation in these genes influence testis weight could aid in the understanding of mechanisms of mammalian reproductive function.

Genetic mapping of species differences via in vitro crosses in mouse embryonic stem cells

Discovering the genetic changes underlying species differences is a central goal in evolutionary genetics. However, hybrid crosses between species in mammals often suffer from hybrid sterility, greatly complicating genetic mapping of trait variation across species. Here, we describe a simple, robust, and transgene-free technique to generate "in vitro crosses" in hybrid mouse embryonic stem (ES) cells by inducing random mitotic cross-overs with the drug ML216, which inhibits the DNA helicase Bloom syndrome (BLM). Starting with an interspecific F1 hybrid ES cell line between the Mus musculus laboratory mouse and Mus spretus (∼1.5 million years of divergence), we mapped the genetic basis of drug resistance to the antimetabolite tioguanine to a single region containing hypoxanthine-guanine phosphoribosyltransferase (Hprt) in as few as 21 d through "flow mapping" by coupling in vitro crosses with fluorescence-activated cell sorting (FACS). We also show how our platform can enable direct study of developmental variation by rederiving embryos with contribution from the recombinant ES cell lines. We demonstrate how in vitro crosses can overcome major bottlenecks in mouse complex trait genetics and address fundamental questions in evolutionary biology that are otherwise intractable through traditional breeding due to high cost, small litter sizes, and/or hybrid sterility. In doing so, we describe an experimental platform toward studying evolutionary systems biology in mouse and potentially in human and other mammals, including cross-species hybrids.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www.

RESEARCH

va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

AZI23'UTR Is a New SLC6A3 Downregulator Associated with an Epistatic Protection Against Substance Use Disorders

Regulated activity of SLC6A3, which encodes the human dopamine transporter (DAT), contributes to diseases such as substance abuse disorders (SUDs); however, the exact transcription mechanism remains poorly understood. Here, we used a common genetic variant of the gene, intron 1 DNP1B sequence, as bait to screen and clone a new transcriptional activity, ^AZI23'UTR, for SLC6A3. ^AZI23'UTR is a 3' untranslated region (3'UTR) of the human 5-Azacytidine Induced 2 gene (AZI2) but appeared to be transcribed independently of AZI2. Found to be present in both human cell nuclei and dopamine neurons, this RNA was shown to downregulate promoter activity through a variant-dependent mechanism in vitro. Both reduced RNA density ratio of ^AZI23'UTR/AZI2 and increased DAT mRNA levels were found in ethanol-naive alcohol-preferring rats. Secondary analysis of dbGaP GWAS datasets (Genome-Wide Association Studies based on the database of Genotypes and Phenotypes) revealed significant interactions between regions upstream of ^AZI23'UTR and SLC6A3 in SUDs. Jointly, our data suggest that ^AZI23'UTR confers variant-dependent transcriptional regulation of SLC6A3, a potential risk factor for SUDs.

Viewing RNA-seq data on the entire human genome

RNA-Seq Viewer is a web application that enables users to visualize genome-wide expression data from NCBI’s Sequence Read Archive (SRA) and Gene Expression Omnibus (GEO) databases. The application prototype was created by a small team during a three-day hackathon facilitated by NCBI at Brandeis University. The backend data pipeline was developed and deployed on a shared AWS EC2 instance. Source code is available at https://github.com/NCBI-Hackathons/rnaseqview.

Identifying genes for neurobehavioural traits in rodents: progress and pitfalls

Identifying genes and pathways that contribute to differences in neurobehavioural traits is a key goal in psychiatric research. Despite considerable success in identifying quantitative trait loci (QTLs) associated with behaviour in laboratory rodents, pinpointing the causal variants and genes is more challenging. For a long time, the main obstacle was the size of QTLs, which could encompass tens if not hundreds of genes. However, recent studies have exploited mouse and rat resources that allow mapping of phenotypes to narrow intervals, encompassing only a few genes. Here, we review these studies, showcase the rodent resources they have used and highlight the insights into neurobehavioural traits provided to date. We discuss what we see as the biggest challenge in the field - translating QTLs into biological knowledge by experimentally validating and functionally characterizing candidate genes - and propose that the CRISPR/Cas genome-editing system holds the key to overcoming this obstacle. Finally, we challenge traditional views on inbred versus outbred resources in the light of recent resource and technology developments.

Genetic polymorphisms and their association with brain and behavioural measures in heterogeneous stock mice

Although the search for quantitative trait loci for behaviour remains a considerable challenge, the complicated genetic architecture of quantitative traits is beginning to be understood. The current project utilised heterogeneous stock (HS) male mice (n = 580) to investigate the genetic basis for brain weights, activity, anxiety and cognitive phenotypes. We identified 126 single nucleotide polymorphisms (SNPs) in genes involved in regulation of neurotransmitter systems, nerve growth/death and gene expression, and subsequently investigated their associations with changes in behaviour and/or brain weights in our sample. We found significant associations between four SNP-phenotype pairs, after controlling for multiple testing. Specificity protein 2 (Sp2, rs3708840), tryptophan hydroxylase 1 (Tph1, rs262731280) and serotonin receptor 3A (Htr3a, rs50670893) were associated with activity/anxiety behaviours, and microtubule-associated protein 2 (Map2, rs13475902) was associated with cognitive performance. All these genes except for Tph1 were expressed in the brain above the array median, and remained significantly associated with relevant behaviours after controlling for the family structure. Additionally, we found evidence for a correlation between Htr3a expression and activity. We discuss our findings in the light of the advantages and limitations of currently available mouse genetic tools, suggesting further directions for association studies in rodents.