Resources for Systems Genetics

Systems genetics analysis reveals the common genetic basis for pain sensitivity and cognitive function

BACKGROUND

There is growing evidence of a strong correlation between pain sensitivity and cognitive function under both physiological and pathological conditions. However, the detailed mechanisms remain largely unknown. In the current study, we sought to explore candidate genes and common molecular mechanisms underlying pain sensitivity and cognitive function with a transcriptome-wide association study using recombinant inbred mice from the BXD family.

METHODS

The pain sensitivity determined by Hargreaves' paw withdrawal test and cognition-related phenotypes were systematically analyzed in 60 strains of BXD mice and correlated with hippocampus transcriptomes, followed by quantitative trait locus (QTL) mapping and systems genetics analysis.

RESULTS

The pain sensitivity showed significant variability across the BXD strains and co-varies with cognitive traits. Pain sensitivity correlated hippocampual genes showed a significant involvement in cognition-related pathways, including glutamatergic synapse, and PI3K-Akt signaling pathway. Moreover, QTL mapping identified a genomic region on chromosome 4, potentially regulating the variation of pain sensitivity. Integrative analysis of expression QTL mapping, correlation analysis, and Bayesian network modeling identified Ring finger protein 20 (Rnf20) as the best candidate. Further pathway analysis indicated that Rnf20 may regulate the expression of pain sensitivity and cognitive function through the PI3K-Akt signaling pathway, particularly through interactions with genes Ppp2r2b, Ppp2r5c, Col9a3, Met, Rps6, Tnc, and Kras.

CONCLUSIONS

Our study demonstrated that pain sensitivity is associated with genetic background and Rnf20-mediated PI3K-Akt signaling may involve in the regulation of pain sensitivity and cognitive functions.

Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models

Animal genetic models have and will continue to provide important new information about the behavioral and physiological adaptations associated with alcohol use disorder (AUD). This chapter focuses on two models, ethanol preference and drinking in the dark (DID), their usefulness in interrogating brain gene expression data and the relevance of the data obtained to interpret AUD-related GWAS and TWAS studies. Both the animal and human data point to the importance for AUD of changes in synaptic transmission (particularly glutamate and GABA transmission), of changes in the extracellular matrix (specifically including collagens, cadherins and protocadherins) and of changes in neuroimmune processes. The implementation of new technologies (e.g., cell type-specific gene expression) is expected to further enhance the value of genetic animal models in understanding AUD.

Systems genetics approaches for understanding complex traits with relevance for human disease

Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.

Pierre CL, Tripi JA, Richards JB, Wang T, Chen H, Flagel SB, Meyer P, Robinson TE, Solberg Woods LC, Palmer AA. An exponential increase in QTL detection with an increased sample size

Power analyses are often used to determine the number of animals required for a genome-wide association study (GWAS). These analyses are typically intended to estimate the sample size needed for at least 1 locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real data set that consisted of 3,173 male and female adult N/NIH heterogeneous stock rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in subsamples of the full data set. The subsampling analysis was conducted for 4 traits with low (0.15 ± 0.03), medium (0.31 ± 0.03 and 0.36 ± 0.03), and high (0.46 ± 0.03) SNP-based heritabilities. For each trait, we subsampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency

Preclinical models of neurodevelopmental disorders typically use single inbred mouse strains, which fail to capture the genetic diversity and symptom heterogeneity that is common clinically. We tested whether modeling genetic background diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. We measured clinically relevant phenotypes in >1,000 mice from 33 strains, including brain and body weights and cognition, activity, anxiety, and social behaviors, using 5 behavioral assays: cued fear conditioning, open field tests in dark and bright light, direct social interaction, and social dominance. Trait disruptions mimicked those seen clinically, with robust strain and sex differences. Some strains exhibited large effect-size trait disruptions, sometimes in opposite directions, and-remarkably-others expressed resilience. Therefore, systematically introducing genetic diversity into models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies.

Genetic Mapping of Behavioral Traits Using the Collaborative Cross Resource

The complicated interactions between genetic background, environment and lifestyle factors make it difficult to study the genetic basis of complex phenotypes, such as cognition and anxiety levels, in humans. However, environmental and other factors can be tightly controlled in mouse studies. The Collaborative Cross (CC) is a mouse genetic reference population whose common genetic and phenotypic diversity is on par with that of humans. Therefore, we leveraged the power of the CC to assess 52 behavioral measures associated with locomotor activity, anxiety level, learning and memory. This is the first application of the CC in novel object recognition tests, Morris water maze tasks, and fear conditioning tests. We found substantial continuous behavioral variations across the CC strains tested, and mapped six quantitative trait loci (QTLs) which influenced these traits, defining candidate genetic variants underlying these QTLs. Overall, our findings highlight the potential of the CC population in behavioral genetic research, while the identified genomic loci and genes driving the variation of relevant behavioral traits provide a foundation for further studies.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Integration of evidence across human and model organism studies: A meeting report

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.

Sex and Strain Variation in Initial Sensitivity and Rapid Tolerance to Δ9-Tetrahydrocannabinol

Background and Objectives: For cannabis and other drugs of abuse, initial response and/or tolerance to drug effects can predict later dependence and problematic use. Our objective is to identify sex and genetic (strain) differences in initial response and rapid tolerance to Δ9–tetrahydrocannabinol (THC), the main psychoactive ingredient in cannabis, between highly genetically divergent inbred mouse strains—C57BL/6J (B6) and DBA/2J (D2).

Experimental Approach: Sex and strain responses relative to baseline were quantified following daily exposure (i.p.) to 10 mg/kg THC or vehicle (VEH) over the course of 5 days. Dependent measures included hypothermia (decreased body temperature) and ataxia (decreased spontaneous activity in the open field), and antinociception (increase in tail withdrawal latency to a thermal stimulus). Initial sensitivity to THC was defined as the difference in response between baseline and day 1. Rapid tolerance to THC was defined as the difference in response between days 1 and 2.

Results: B6 exhibited greater THC-induced motor activity suppression and initial sensitivity to ataxia relative to the D2 strain. Females demonstrated greater levels of THC-induced hypothermia and initial sensitivity relative to males. Higher levels of THC-induced antinociception and initial sensitivity were observed for D2 relative to B6. Rapid tolerance to THC was observed for hypothermia and antinociception. Much less tolerance was observed for THC-induced ataxia. D2 exhibited rapid tolerance to THC-induced hypothermia and antinociception at time points associated with peak THC initial response. Likewise, at the peak initial THC response time point, females demonstrated greater levels of rapid tolerance to hypothermic effects relative to males.

Conclusions: Both sex and genetic factors drive variation in initial response and rapid tolerance to the ataxic, antinociceptive, and hypothermic effects of THC. As these traits directly result from THC activation of the cannabinoid receptor 1, gene variants between B6 and D2 in cannabinoid signaling pathways are likely to mediate strain differences in response to THC.

Exploring the Role of Chemokine Receptor 6 (Ccr6) in the BXD Mouse Model of Gulf War Illness

Gulf War illness (GWI) is a chronic and multi-symptomatic disorder with persistent neuroimmune symptomatology. Chemokine receptor 6 (CCR6) has been shown to be involved in several inflammation disorders in humans. However, the causative relationship between CCR6 and neuroinflammation in GWI has not yet been investigated. By using RNA-seq data of prefrontal cortex (PFC) from 31 C57BL/6J X DBA/2J (BXD) recombinant inbred (RI) mouse strains and their parental strains under three chemical treatment groups – saline control (CTL), diisopropylfluorophosphate (DFP), and corticosterone combined with diisopropylfluorophosphate (CORT+DFP), we identified Ccr6 as a candidate gene underlying individual differences in susceptibility to GWI. The Ccr6 gene is cis-regulated and its expression is significantly correlated with CORT+DFP treatment. Its mean transcript abundance in PFC of BXD mice decreased 1.6-fold (p < 0.0001) in the CORT+DFP group. The response of Ccr6 to CORT+DFP is also significantly different (p < 0.0001) between the parental strains, suggesting Ccr6 is affected by both host genetic background and chemical treatments. Pearson product-moment correlation analysis revealed 1473 Ccr6-correlated genes (p < 0.05). Enrichment of these genes was seen in the immune, inflammation, cytokine, and neurological related categories. In addition, we also found five central nervous system-related phenotypes and fecal corticosterone concentration have significant correlation (p < 0.05) with expression of Ccr6 in the PFC. We further established a protein-protein interaction subnetwork for the Ccr6-correlated genes, which provides an insight on the interaction of G protein-coupled receptors, kallikrein-kinin system and neuroactive ligand-receptors. This analysis likely defines the heterogeneity and complexity of GWI. Therefore, our results suggest that Ccr6 is one of promising GWI biomarkers.

Systems Genetics of Optic Nerve Axon Necrosis During Glaucoma

In this study, we identify genomic regions that modulate the number of necrotic axons in optic nerves of a family of mice, some of which have severe glaucoma, and define a set of high priority positional candidate genes that modulate retinal ganglion cell (RGC) axonal degeneration. A large cohort of the BXD family were aged to greater than 13 months of age. Optic nerves from 74 strains and the DBA/2J (D2) parent were harvested, sectioned, and stained with p-phenylenediamine. Numbers of necrotic axons per optic nerve cross-section were counted from 1 to 10 replicates per genotype. Strain means and standard errors were uploaded into GeneNetwork 2 for mapping and systems genetics analyses (Trait 18614). The number of necrotic axons per nerve ranged from only a few hundred to more than 4,000. Using conventional interval mapping as well as linear mixed model mapping, we identified a single locus on chromosome 12 between 109 and 112.5 Mb with a likelihood ratio statistic (LRS) of ~18.5 (p genome-wide ~0.1). Axon necrosis is not linked to locations of major known glaucoma genes in this family, including Gpnmb, Tyrp1, Cdh11, Pou6f2, and Cacna2d1. This indicates that although these genes contribute to pigmentary dispersion or elevated IOP, none directly modulates axon necrosis. Of 156 positional candidates, eight genes—CDC42 binding protein kinase beta (Cdc42bpb); eukaryotic translation initiation factor 5 (Eif5); BCL2-associated athanogene 5 (Bag5); apoptogenic 1, mitochondrial (Apopt1); kinesin light chain 1 (Klc1); X-ray repair cross complementing 3 (Xrcc3); protein phosphatase 1, regulatory subunit 13B (Ppp1r13b); and transmembrane protein 179 (Tmem179)—passed stringent criteria and are high priority candidates. Several candidates are linked to mitochondria and/or axons, strengthening their plausible role as modulators of ON necrosis. Additional studies are required to validate and/or eliminate plausible candidates. Surprisingly, IOP and ON necrosis are inversely correlated across the BXD family in mice >13 months of age and these two traits share few genes among their top ocular and retinal correlates. These data suggest that the two traits are independently modulated or that a more complex and multifaceted approach is required to reveal their association.

Offspring genetic effects on maternal care

Parental care is found widely across animal taxa and is manifest in a range of behaviours from basic provisioning in cockroaches to highly complex behaviours seen in mammals. The evolution of parental care is viewed as the outcome of an evolutionary cost/benefit trade-off between investing in current and future offspring, leading to the selection of traits in offspring that influence parental behaviour. Thus, level and quality of parental care are affected by both parental and offspring genetic differences that directly and indirectly influence parental care behaviour. While significant research effort has gone into understanding how parental genomes affect parental, and mostly maternal, behaviour, few studies have investigated how offspring genomes affect parental care. In this review, we bring together recent findings across different fields focussing on the mechanism and genetics of offspring effects on maternal care in mammals.

Giving the Genes a Shuffle: Using Natural Variation to Understand Host Genetic Contributions to Viral Infections

The laboratory mouse has proved an invaluable model to identify host factors that regulate the progression and outcome of virus-induced disease. The paradigm is to use single-gene knockouts in inbred mouse strains or genetic mapping studies using biparental mouse populations. However, genetic variation among these mouse strains is limited compared with the diversity seen in human populations. To address this disconnect, a multiparental mouse population has been developed to specifically dissect the multigenetic regulation of complex disease traits. The Collaborative Cross (CC) population of recombinant inbred mouse strains is a well-suited systems-genetics tool to identify susceptibility alleles that control viral and microbial infection outcomes and immune responses and to test the promise of personalized medicine.

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.

Short-Term Genetic Selection for Adolescent Locomotor Sensitivity to Delta9-Tetrahydrocannabinol (THC)

Cannabis use is linked to positive and negative outcomes. Identifying genetic targets of susceptibility to the negative effects of cannabinoid use is of growing importance. The current study sought to complete short-term selective breeding for adolescent sensitivity and resistance to the locomotor effects of a single 10 mg/kg THC dose in the open field. Selection for THC-locomotor sensitivity was moderately heritable, with the greatest estimates of heritability seen in females from the F2 to S3 generations. Selection for locomotor sensitivity also resulted in increased anxiety-like activity in the open field. These results are the first to indicate that adolescent THC-locomotor sensitivity can be influenced via selective breeding. Development of lines with a genetic predisposition for THC-sensitivity or resistance to locomotor effects allow for investigation of risk factors, differences in consequences of THC use, identification of correlated behavioral responses, and detection of genetic targets that may contribute to heightened cannabinoid sensitivity.

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.

Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice

Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is not well understood. Here, we obtain a broad view of how heritable factors affect a mouse model of response to IAV infection using an 8 × 8 diallel of the eight inbred founder strains of the Collaborative Cross (CC). Expanding on a prior statistical framework for modeling treatment response in diallels, we explore how a range of heritable effects modify acute host response to IAV through 4 d postinfection. Heritable effects in aggregate explained ∼57% of the variance in IAV-induced weight loss. Much of this was attributable to a pattern of additive effects that became more prominent through day 4 postinfection and was consistent with previous reports of antiinfluenza myxovirus resistance 1 (Mx1) polymorphisms segregating between these strains; these additive effects largely recapitulated haplotype effects observed at the Mx1 locus in a previous study of the incipient CC, and are also replicated here in a CC recombinant intercross population. Genetic dominance of protective Mx1 haplotypes was observed to differ by subspecies of origin: relative to the domesticus null Mx1 allele, musculus acts dominantly whereas castaneus acts additively. After controlling for Mx1, heritable effects, though less distinct, accounted for ∼34% of the phenotypic variance. Implications for future mapping studies are discussed.

Acute and long-term effects of Δ9-tetrahydrocannabinol on object recognition and anxiety-like activity are age- and strain-dependent in mice

Use of exogenous cannabinoids disrupts the fine-tuned endocannabinoid receptor system, possibly leading to alterations in cognition, memory, and emotional processes that endure long after cannabinoid use has stopped. Long-term adolescent use may uniquely disrupt these behaviors when compared to adult use. The current study explored the acute and long-term behavioral effects of six 10mg/kg Δ9-tetrahydrocannabinol (THC) injections across the adolescent or early adult period in male inbred C57Bl/6J and DBA/2J mice. The acute and prolonged effects of THC on object memory using the novel object recognition task, unconditioned anxiety in the elevated plus maze and open field, and sedative effects in the open field were examined. Acute THC treatment resulted in anxiogenic activity in both strains, but only caused sedation in B6 mice. Repeated THC treatment resulted in a protracted effect on object recognition, but not unconditioned anxiety, assessed 4weeks later. In both strains, an adolescent history of THC treatment disrupted later object recognition. Interestingly, in B6 mice an adult history of THC exposure appeared to rescue a deficit in object recognition observed in vehicle-treated adults. Repeated THC administration also produced a protracted effected on CB1R protein expression. Animals treated with THC in adolescence maintained increased levels of CB1R protein expression compared to their adult THC-treated counterparts at five weeks following the last injection. These results indicate that THC use may have long-lasting effects with adolescence being a unique period of susceptibility.