Tmod2 Is a Regulator of Cocaine Responses through Control of Striatal and Cortical Excitability and Drug-Induced Plasticity.

Drugs of abuse induce neuroadaptations, including synaptic plasticity, that are critical for transition to addiction, and genes and pathways that regulate these neuroadaptations are potential therapeutic targets. Tropomodulin 2 (Tmod2) is an actin-regulating gene that plays an important role in synapse maturation and dendritic arborization and has been implicated in substance abuse and intellectual disability in humans. Here, we mine the KOMP2 data and find that Tmod2 knock-out mice show emotionality phenotypes that are predictive of addiction vulnerability. Detailed addiction phenotyping shows that Tmod2 deletion does not affect the acute locomotor response to cocaine administration. However, sensitized locomotor responses are highly attenuated in these knock-outs, indicating perturbed drug-induced plasticity. In addition, Tmod2 mutant animals do not self-administer cocaine indicating lack of hedonic responses to cocaine. Whole-brain MR imaging shows differences in brain volume across multiple regions, although transcriptomic experiments did not reveal perturbations in gene coexpression networks. Detailed electrophysiological characterization of Tmod2 KO neurons showed increased spontaneous firing rate of early postnatal and adult cortical and striatal neurons. Cocaine-induced synaptic plasticity that is critical for sensitization is either missing or reciprocal in Tmod2 KO nucleus accumbens shell medium spiny neurons, providing a mechanistic explanation of the cocaine response phenotypes. Combined, these data, collected from both males and females, provide compelling evidence that Tmod2 is a major regulator of plasticity in the mesolimbic system and regulates the reinforcing and addictive properties of cocaine.

Discovery and validation of genes driving drug-intake and related behavioral traits in mice.

Substance use disorders are heritable disorders characterized by compulsive drug use, the biological mechanisms for which remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference and sensation seeking, are predictive of drug-use phenotypes, thereby implicating shared genetic mechanisms. High-throughput behavioral screening in knockout (KO) mice allows efficient discovery of the function of genes. We used this strategy in two rounds of candidate prioritization in which we identified 33 drug-use candidate genes based upon predisposing drug-naïve phenotypes and ultimately validated the perturbation of 22 genes as causal drivers of substance intake. We selected 19/221 KO strains (8.5%) that had a difference from control on at least one drug-naïve predictive behavioral phenotype and determined that 15/19 (~80%) affected the consumption or preference for alcohol, methamphetamine or both. No mutant exhibited a difference in nicotine consumption or preference which was possibly confounded with saccharin. In the second round of prioritization, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15/401 KO strains (3.7%, which included one gene from the first cohort) that differed most from controls for the predisposing phenotypes. 8 of 15 gene deletions (53%) affected intake or preference for alcohol, methamphetamine or both. Using multivariate and bioinformatic analyses, we observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.

Evaluation of the diagnostic accuracy of exome sequencing and its impact on diagnostic thinking for patients with rare disease in a publicly funded health care system: A prospective cohort study.

PURPOSE: To evaluate the diagnostic utility of publicly funded clinical exome sequencing (ES) for patients with suspected rare genetic diseases. METHODS: We prospectively enrolled 297 probands who met eligibility criteria and received ES across 5 sites in Ontario, Canada, and extracted data from medical records and clinician surveys. Using the Fryback and Thornbury Efficacy Framework, we assessed diagnostic accuracy by examining laboratory interpretation of results and assessed diagnostic thinking by examining the clinical interpretation of results and whether clinical-molecular diagnoses would have been achieved via alternative hypothetical molecular tests. RESULTS: Laboratories reported 105 molecular diagnoses and 165 uncertain results in known and novel genes. Of these, clinicians interpreted 102 of 105 (97%) molecular diagnoses and 6 of 165 (4%) uncertain results as clinical-molecular diagnoses. The 108 clinical-molecular diagnoses were in 104 families (35% diagnostic yield). Each eligibility criteria resulted in diagnostic yields of 30% to 40%, and higher yields were achieved when >2 eligibility criteria were met (up to 45%). Hypothetical tests would have identified 61% of clinical-molecular diagnoses. CONCLUSION: We demonstrate robustness in eligibility criteria and high clinical validity of laboratory results from ES testing. The importance of ES was highlighted by the potential 40% of patients that would have gone undiagnosed without this test.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta.

BACKGROUND: Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. RESULTS: Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry-informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, as well as over very long placental processing times. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. CONCLUSIONS: This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. We further demonstrate the specific utility of epiphenotyping tools developed for use with placental DNAme data, and show that these variables (i) provide an independent check of clinically obtained data and (ii) provide a robust approach to compare variables across different datasets. Finally, we present a general framework for the processing and analysis of placental DNAme data, integrating the epiphenotype variables discussed here.

Gene expression genetics of the striatum of Diversity Outbred mice.

Brain transcriptional variation is a heritable trait that mediates complex behaviors, including addiction. Expression quantitative trait locus (eQTL) mapping reveals genomic regions harboring genetic variants that influence transcript abundance. In this study, we profiled transcript abundance in the striatum of 386 Diversity Outbred (J:DO) mice of both sexes using RNA-Seq. All mice were characterized using a behavioral battery of widely-used exploratory and risk-taking assays prior to transcriptional profiling. We performed eQTL mapping, incorporated the results into a browser-based eQTL viewer, and deposited co-expression network members in GeneWeaver. The eQTL viewer allows researchers to query specific genes to obtain allelic effect plots, analyze SNP associations, assess gene expression correlations, and apply mediation analysis to evaluate whether the regulatory variant is acting through the expression of another gene. GeneWeaver allows multi-species comparison of gene sets using statistical and combinatorial tools. This data resource allows users to find genetic variants that regulate differentially expressed transcripts and place them in the context of other studies of striatal gene expression and function in addiction-related behavior.

DISCOVERY AND VALIDATION OF GENES DRIVING DRUG-INTAKE AND RELATED BEHAVIORAL TRAITS IN MICE.

Substance use disorders (SUDs) are heritable disorders characterized by compulsive drug use, but the biological mechanisms driving addiction remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference, and sensation seeking, are predictive of drug-use phenotypes, implicating shared genetic mechanisms. Because of this relationship, high-throughput behavioral screening of predictive phenotypes in knockout (KO) mice allows efficient discovery of genes likely to be involved in drug use. We used this strategy in two rounds of screening in which we identified 33 drug-use candidate genes and ultimately validated the perturbation of 22 of these genes as causal drivers of substance intake. In our initial round of screening, we employed the two-bottle-choice paradigms to assess alcohol, methamphetamine, and nicotine intake. We identified 19 KO strains that were extreme responders on at least one predictive phenotype. Thirteen of the 19 gene deletions (68%) significantly affected alcohol use three methamphetamine use, and two both. In the second round of screening, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15 KO strains that were extreme responders across the predisposing drug-naïve phenotypes. Eight of the 15 gene deletions (53%) significantly affected intake or preference for three alcohol, eight methamphetamine or three both (3). We observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta.

Background : Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. Results : Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, but reassuringly were robust to placental processing time. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. Conclusions : This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. Further, we demonstrate that estimating epiphenotype variables from the DNAme data itself, when possible, provides both an independent check of clinically-obtained data and can provide a robust approach to compare variables across different datasets.

The Aryl Hydrocarbon Receptor, Epigenetics and the Aging Process.

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor, classically associated with the regulation of xenobiotic metabolism in response to environmental toxins. In recent years, transgenic rodent models have implicated AhR in aging and longevity. Moreover, several AhR ligands, such as resveratrol and quercetin, are compounds proven to extend the lifespan of model organisms. In this paper, we first review AhR biology with a focus on aging and highlight several AhR ligands with potential anti-aging properties. We outline how AhR-driven expression of xenobiotic metabolism genes into old age may be a key mechanism through which moderate induction of AhR elicits positive benefits on longevity and healthspan. Furthermore, via integration of publicly available datasets, we show that liver-specific AhR target genes are enriched among genes subject to epigenetic aging. Changes to epigenetic states can profoundly affect transcription factor binding and are a hallmark of the aging process. We suggest that the interplay between AhR and epigenetic aging should be the subject of future research and outline several key gaps in the current literature. Finally, we recommend that a broad range of non-toxic AhR ligands should be investigated for their potential to promote healthspan and longevity.

Gene expression genetics of the striatum of Diversity Outbred mice.

Brain transcriptional variation is a heritable trait that mediates complex behaviors, including addiction. Expression quantitative trait locus (eQTL) mapping reveals genomic regions harboring genetic variants that influence transcript abundance. In this study, we profiled transcript abundance in the striatum of 386 Diversity Outbred (J:DO) mice of both sexes using RNA-Seq. All mice were characterized using a behavioral battery of widely-used exploratory and risk-taking assays prior to transcriptional profiling. We performed eQTL mapping, incorporated the results into a browser-based eQTL viewer, and deposited co-expression network members in GeneWeaver. The eQTL viewer allows researchers to query specific genes to obtain allelic effect plots, analyze SNP associations, assess gene expression correlations, and apply mediation analysis to evaluate whether the regulatory variant is acting through the expression of another gene. GeneWeaver allows multi-species comparison of gene sets using statistical and combinatorial tools. This data resource allows users to find genetic variants that regulate differentially expressed transcripts and place them in the context of other studies of striatal gene expression and function in addiction-related behavior.

Effects of isolation housing stress and mouse strain on intravenous cocaine self-administration, sensory stimulus self-administration, and reward preference.

Sensory stimuli are natural rewards in mice and humans. Consequently, preference for a drug reward relative to a sensory reward may be an endophenotype of addiction vulnerability. In this study, we developed a novel behavioral assay to quantify the preference for intravenous drug self-administration relative to sensory stimulus self-administration. We used founder strains of the BXD recombinant inbred mouse panel (C57BL/6J, DBA/2J) and a model of stress (isolation vs enriched housing) to assess genetic and epigenetic effects. Following 10 weeks of differential housing, all mice were tested under three reward conditions: sensory rewards available, cocaine rewards available, both rewards available. When a single reward was available (sensory stimuli or cocaine; delivered using distinct levers), DBA/2J mice self-administered significantly more rewards than C57BL/6J mice. When both rewards were available, DBA/2J mice exhibited a significant preference for cocaine relative to sensory stimuli; in contrast, C57BL/6J mice exhibited no preference. Housing condition influenced sensory stimulus self-administration and strain-dependently influenced inactive lever pressing when both rewards were available. Collectively, these data reveal strain effects, housing effects, or both on reward self-administration and preference. Most importantly, this study reveals that genetic mechanisms underlying preference for a drug reward relative to a nondrug reward can be dissected using the full BXD panel.

Intravenous fentanyl self-administration in male and female C57BL/6J and DBA/2J mice.

The genetic mechanisms underlying fentanyl addiction, a highly heritable disease, are unknown. Identifying these mechanisms will lead to better risk assessment, early diagnosis, and improved intervention. To this end, we used intravenous fentanyl self-administration to quantify classical self-administration phenotypes and addiction-like fentanyl seeking in male and female mice from the two founder strains of the BXD recombinant inbred mouse panel (C57BL/6J and DBA/2J). We reached three primary conclusions from these experiments. First, mice from all groups rapidly acquired intravenous fentanyl self-administration and exhibited a dose-response curve, extinction burst, and extinction of the learned self-administration response. Second, fentanyl intake (during acquisition and dose response) and fentanyl seeking (during extinction) were equivalent among groups. Third, strain effects, sex effects, or both were identified for several addiction-like behaviors (cue-induced reinstatement, stress-induced reinstatement, escalation of intravenous fentanyl self-administration). Collectively, these data indicate that C57BL/6J and DBA/2J mice of both sexes were able to acquire, regulate, and extinguish intravenous fentanyl self-administration. Moreover, these data reveal novel strain and sex effects on addiction-like behaviors in the context of intravenous fentanyl self-administration in mice and indicate that the full BXD panel can be used to identify and dissect the genetic mechanisms underlying these effects.

Microbial glutamate metabolism predicts intravenous cocaine self-administration in diversity outbred mice.

The gut microbiome is thought to play a critical role in the onset and development of psychiatric disorders, including depression and substance use disorder (SUD). To test the hypothesis that the microbiome affects addiction predisposing behaviors and cocaine intravenous self-administration (IVSA) and to identify specific microbes involved in the relationship, we performed 16S rRNA gene sequencing on feces from 228 diversity outbred mice. Twelve open field measures, two light-dark assay measures, one hole board and novelty place preference measure significantly differed between mice that acquired cocaine IVSA (ACQ) and those that failed to acquire IVSA (FACQ). We found that ACQ mice are more active and exploratory and display decreased fear than FACQ mice. The microbial abundances that differentiated ACQ from FACQ mice were an increased abundance of Barnesiella, Ruminococcus, and Robinsoniella and decreased Clostridium IV in ACQ mice. There was a sex-specific correlation between ACQ and microbial abundance, a reduced Lactobacillus abundance in ACQ male mice, and a decreased Blautia abundance in female ACQ mice. The abundance of Robinsoniella was correlated, and Clostridium IV inversely correlated with the number of doses of cocaine self-administered during acquisition. Functional analysis of the microbiome composition of a subset of mice suggested that gut-brain modules encoding glutamate metabolism genes are associated with the propensity to self-administer cocaine. These findings establish associations between the microbiome composition and glutamate metabolic potential and the ability to acquire cocaine IVSA thus indicating the potential translational impact of targeting the gut microbiome or microbial metabolites for treatment of SUD. This article is part of the Special Issue on "Microbiome & the Brain: Mechanisms & Maladies".

Development and Biodistribution of a Nerve Growth Factor Radioactive Conjugate for PET Imaging.

PURPOSE: The purpose of these studies was to develop a nerve growth factor (NGF) radiometal-chelator conjugate to determine the biodistribution and brain uptake of NGF by positron emission tomography/computerized tomography (PET-CT). PROCEDURES: Purified NGF from llama seminal plasma was conjugated with FITC, and the chelator NOTA or DFO. NGF conjugates were evaluated for bioactivity. NOTA- and DFO-conjugated NGF were radiolabeled with gallium-68 or zirconium-89 ([68 Ga]GaCl3, half-life = 68 min; [89Zr]Zr(oxalate)4, half-life = 3.3 days). [89Zr]Zr-NGF was evaluated for biodistribution (0.5, 1, or 24 h), PET imaging (60 min), and brain autoradiography in mice. RESULTS: Cell-based in vitro assays confirmed that the NGF conjugates maintained NGF receptor-binding and biological activity. Zirconium-89 and gallium-68 radiolabeling showed a high efficiency; however, only[89Zr]Zr-NGF was stable in vitro. Biodistribution studies showed that, as with most small proteins < 70 kDa, [89Zr]Zr-NGF uptake was predominantly in the kidney and was cleared rapidly with almost complete elimination of NGF at 24 h. Dynamic PET imaging from 0-60 min showed a similar pattern to ex vivo biodistribution with some transient liver uptake. Interestingly, although absolute brain uptake was very low, at 24 h after treatment, cerebral cortex uptake was higher than any other brain area examined and blood. CONCLUSIONS: We conclude that conjugation of DFO to NGF through a thiourea linkage allows effective radiolabeling with zirconium-89 while maintaining NGF bioactivity. Following intravenous administration, the radiolabeled NGF targets non-neuronal tissues (e.g., kidney, liver), and although absolute brain uptake was very low, the brain uptake that was observed was restricted to the cortex.

Bridging clinical care and research in Ontario, Canada: Maximizing diagnoses from reanalysis of clinical exome sequencing data.

We examined the utility of clinical and research processes in the reanalysis of publicly-funded clinical exome sequencing data in Ontario, Canada. In partnership with eight sites, we recruited 287 families with suspected rare genetic diseases tested between 2014 and 2020. Data from seven laboratories was reanalyzed with the referring clinicians. Reanalysis of clinically relevant genes identified diagnoses in 4% (13/287); four were missed by clinical testing. Translational research methods, including analysis of novel candidate genes, identified candidates in 21% (61/287). Of these, 24 families have additional evidence through data sharing to support likely diagnoses (8% of cohort). This study indicates few diagnoses are missed by clinical laboratories, the incremental gain from reanalysis of clinically-relevant genes is modest, and the highest yield comes from validation of novel disease-gene associations. Future implementation of translational research methods, including continued reporting of compelling genes of uncertain significance by clinical laboratories, should be considered to maximize diagnoses.

Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy.

Selective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood.  In utero exposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression. Chorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score > 8 to indicate symptomatic depressed mood ("maternally-depressed"), and we further classified cases into SSRI-exposed, maternally-depressed (n = 14); SSRI-exposed, not maternally-depressed (n = 6); SSRI non-exposed, maternally-depressed (n = 20); and SSRI non-exposed, not maternally-depressed (n = 24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n = 17 SSRI-exposed, n = 17 SSRI non-exposed). No CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δß| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n = 31; males n = 33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off. We did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment, as compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.

Comparing genome sequencing technologies to improve rare disease diagnostics: a protocol for the evaluation of a pilot project, Genome-wide Sequencing Ontario.

BACKGROUND: Genome-wide sequencing has emerged as a promising strategy for the timely diagnosis of rare diseases, but it is not yet available as a clinical test performed in Canadian diagnostic laboratories. We describe the protocol for evaluating a 2-year pilot project, Genome-wide Sequencing Ontario, to offer high-quality clinical genome-wide sequencing in Ontario, Canada. METHODS: The Genome-wide Sequencing Ontario protocol was codesigned by the Ontario Ministry of Health, the Hospital for Sick Children in Toronto and the Children's Hospital of Eastern Ontario in Ottawa. Enrolment of a prospective cohort of patients began on Apr. 1, 2021. Eligible cases with blood samples available for the index case and both parents (i.e., trios) are randomized to receive exome sequencing or genome sequencing. We will collect patient-level data and ascertain costs associated with the laboratory workflow for exome sequencing and genome sequencing. We will compare point estimates for the diagnostic utility and timeliness of exome sequencing and genome sequencing, and we will determine an incremental cost-effectiveness ratio (expressed as the incremental cost of genome sequencing versus exome sequencing per additional patient with a causal variant detected). INTERPRETATION: Findings from this work will provide robust evidence for the diagnostic utility, cost-effectiveness and timeliness of exome sequencing and genome sequencing, and will be disseminated via academic publications and policy briefs. Findings will inform provincial and cross-provincial policy related to the long-term organization, delivery and reimbursement of clinical-grade genome diagnostics for rare disease.

Genomics4RD: An integrated platform to share Canadian deep-phenotype and multiomic data for international rare disease gene discovery.

Despite recent progress in the understanding of the genetic etiologies of rare diseases (RDs), a significant number remain intractable to diagnostic and discovery efforts. Broad data collection and sharing of information among RD researchers is therefore critical. In 2018, the Care4Rare Canada Consortium launched the project C4R-SOLVE, a subaim of which was to collect, harmonize, and share both retrospective and prospective Canadian clinical and multiomic data. Here, we introduce Genomics4RD, an integrated web-accessible platform to share Canadian phenotypic and multiomic data between researchers, both within Canada and internationally, for the purpose of discovering the mechanisms that cause RDs. Genomics4RD has been designed to standardize data collection and processing, and to help users systematically collect, prioritize, and visualize participant information. Data storage, authorization, and access procedures have been developed in collaboration with policy experts and stakeholders to ensure the trusted and secure access of data by external researchers. The breadth and standardization of data offered by Genomics4RD allows researchers to compare candidate disease genes and variants between participants (i.e., matchmaking) for discovery purposes, while facilitating the development of computational approaches for multiomic data analyses and enabling clinical translation efforts for new genetic technologies in the future.

Working memory and pattern separation in founder strains of the BXD recombinant inbred mouse panel.

Working memory and pattern separation are fundamental cognitive abilities which, when impaired, significantly diminish quality of life. Discovering genetic mechanisms underlying innate and disease-induced variation in these cognitive abilities is a critical step towards treatments for common and devastating neurodegenerative conditions such as Alzheimer's disease. In this regard, the trial-unique nonmatching-to-location assay (TUNL) is a touchscreen operant conditioning procedure allowing simultaneous quantification of working memory and pattern separation in mice and rats. In the present study, we used the TUNL assay to quantify these cognitive abilities in C57BL/6J and DBA/2J mice. These strains are the founders of the BXD recombinant inbred mouse panel which enables discovery of genetic mechanisms underlying phenotypic variation. TUNL testing revealed that pattern separation was significantly influenced by mouse strain, whereas working memory was not. Moreover, horizontal distance and vertical distance between choice-phase stimuli had dissociable effects on TUNL performance. These findings provide novel data on mouse strain differences in pattern separation and support previous findings of equivalent working memory performance in C57BL/6J and DBA/2J mice. Although working memory of the BXD founder strains was equivalent in this study, working memory of BXD strains may be divergent because of transgressive segregation. Collectively, data presented here indicate that pattern separation is heritable in the mouse and that the BXD panel can be used to identify mechanisms underlying variation in pattern separation.

Strain and sex dependent effects of isolation housing relative to environmental enrichment on operant sensation seeking in mice.

Sensation seeking is a multidimensional phenotype that predicts the development of drug addiction in humans and addiction-like drug seeking in rodents. Several lines of evidence suggest that chronic stress increases sensation seeking and addiction-like drug seeking through common genetic mechanisms. Discovery and characterization of these mechanisms would reveal how chronic stress interacts with the genome to influence sensation seeking and how drugs of abuse hijack these fundamental reward mechanisms to drive addiction. To this end, we tested the hypothesis that chronic isolation housing stress (relative to environmental enrichment) influences operant sensation seeking as a function of strain, sex, or their interaction. To determine if the BXD recombinant inbred panel could be used to identify genetic and epigenetic mechanisms underlying any identified gene-by-environment interactions, we used mice from the two BXD founder strains. Following 10 weeks of differential housing, we assessed operant sensation seeking using several reinforcement schedules. The primary finding from this study was that DBA/2J but not C57BL/6J mice were significantly vulnerable to an isolation-induced increase (relative to environmental enrichment) in sensation seeking during extinction when the sensory reward was no longer available; this effect was significantly more robust in females. These data reveal a previously unknown isolation-induced effect on extinction of operant sensation seeking that is sex-dependent, addiction-relevant, and that can be dissected using the BXD recombinant inbred panel.