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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.

Power analyses are often used to determine the number of animals required for a genome wide association analysis (GWAS). These analyses are typically intended to estimate the sample size needed for at least one 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 dataset that consisted of 3,173 male and female adult N/NIH heterogeneous stock (HS) rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in sub-samples of the full dataset. The sub-sampling analysis was conducted for four 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 sub-sampled 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.

Elevated intraocular pressure (IOP) is influenced by environmental and genetic factors. Increased IOP is a major risk factor for most types of glaucoma, including primary open angle glaucoma (POAG). Investigating the genetic basis of IOP may lead to a better understanding of the molecular mechanisms of POAG. The goal of this study was to identify genetic loci involved in regulating IOP using outbred heterogeneous stock (HS) rats. HS rats are a multigenerational outbred population derived from eight inbred strains that have been fully sequenced. This population is ideal for genome-wide association studies (GWASs) owing to the accumulated recombinations among well-defined haplotypes, the relatively high allele frequencies, the accessibility to a large collection of tissue samples, and the large allelic effect size compared to human studies. Both male and female HS rats (N=1,812) were used in the study. Genotyping-by-sequencing was used to obtain ~3.5 million single nucleotide polymorphisms (SNP) from each individual. SNP heritability for IOP in HS rats was 0.32, which agrees with other studies. We performed a GWAS for the IOP phenotype using a linear mixed model and used permutation to determine a genome-wide significance threshold. We identified three genome-wide significant loci for IOP on chromosomes 1, 5, and 16. Next, we sequenced the mRNA of 51 whole eye samples to find cis-eQTLs to aid in identification of candidate genes. We report 5 candidate genes within those loci:Tyr,Ctsc,Plekhf2,Ndufaf6 and Angpt2.Tyr,Ndufaf6andAngpt2genes have been previously implicated by human GWAS of IOP-related conditions.CtscandPlekhf2genes represent novel findings that may provide new insight into the molecular basis of IOP. This study highlights the efficacy of HS rats for investigating the genetics of elevated IOP and identifying potential candidate genes for future functional testing.Contribution to the field statementGlaucoma is the leading cause of irreversible blindness worldwide. Intraocular pressure (IOP) is the only known modifiable risk factor. This study describes results of the genome-wide association study (GWAS) performed in outbred rats that identifies known and novel genes involved in IOP regulation. To our knowledge, this is the first GWAS performed for IOP in a rat model. Identifying novel candidate genes in the rat model provides insight into the risk factors for glaucoma in humans and potential pharmacological targets for regulating IOP. The rat model is advantageous for studying natural variations in IOP, controlling environmental exposures, and providing easier access to tissue that can be used in phenotyping and gene expression in future studies.

We developed a framework for identifying trait-associated genes in rats and facilitating the transfer of polygenic evidence across species by expanding the transcriptome-wide association (TWAS) approach to rats. Our analysis successfully trained transcript predictors for over 8000 genes in each of the five brain regions of rats, revealing several shared properties of gene regulation with humans. Moreover, mirroring trends observed in humans, our findings showed that sparse predictors using variants in cis are more effective than polygenic predictors and that gene expression prediction in rats is highly correlated across brain regions. Importantly, our analysis also identified a significant overlap between genes associated with rat and human body length and BMI, indicating rat models may be useful for studying the genetic basis of complex traits in humans. RatXcan represents a valuable tool for uncovering shared biological mechanisms of complex traits across species, with potential applications in a wide range of research fields.

Author(s): Chitre, Apurva S; Polesskaya, Oksana; Holl, Katie; Gao, Jianjun; Cheng, Riyan; Bimschleger, Hannah; Garcia Martinez, Angel; George, Tony; Gileta, Alexander F; Han, Wenyan; Horvath, Aidan; Hughson, Alesa; Ishiwari, Keita; King, Christopher P; Lamparelli, Alexander; Versaggi, Cassandra L; Martin, Connor; St Pierre, Celine L; Tripi, Jordan A; Wang, Tengfei; Chen, Hao; Flagel, Shelly B; Meyer, Paul; Richards, Jerry; Robinson, Terry E; Palmer, Abraham A; Solberg Woods, Leah C | Abstract: ObjectiveObesity is influenced by genetic and environmental factors. Despite the success of human genome-wide association studies, the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify the genetic loci underlying obesity and related morphometric and metabolic traits.MethodsThis study measured obesity-relevant traits, including body weight, body length, BMI, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat genome-wide association study to date. Genetic loci were identified using a linear mixed model to account for the complex family relationships of the HS and using covariates to account for differences among the three phenotyping centers.ResultsThis study identified 32 independent loci, several of which contained only a single gene (e.g., Epha5, Nrg1, Klhl14) or obvious candidate genes (e.g., Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and there was extensive pleiotropy at individual loci.ConclusionsThis study demonstrates the utility of HS rats for investigating the genetics of obesity-related traits across institutions and identify several candidate genes for future functional testing.

The heterogeneous stock (HS) is an outbred rat population derived from eight inbred rat strains. HS rats are ideally suited for genome wide association studies; however, only a few genotyping microarrays have ever been designed for rats and none of them are currently in production. To address the need for an efficient and cost effective method of genotyping HS rats, we have adapted genotype-by-sequencing (GBS) to obtain genotype information at large numbers of single nucleotide polymorphisms (SNPs). In this paper, we have outlined the laboratory and computational steps we took to optimize double digest genotype-by-sequencing (ddGBS) for use in rats. We also evaluate multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We also compared various rat genetic maps, which are necessary for imputation, including a recently developed map specific to the HS. Using our approach, we obtained concordance rates of 99% with data obtained using data from a genotyping array. The principles and computational pipeline that we describe could easily be adapted for use in other species for which reliable reference genome sets are available.

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.

Many personality traits are influenced by genetic factors. Rodents models provide an efficient system for analyzing genetic contribution to these traits. Using 1,246 adolescent heterogeneous stock (HS) male and female rats, we conducted a genome-wide association study (GWAS) of behaviors measured in an open field, including locomotion, novel object interaction, and social interaction. We identified 30 genome-wide significant quantitative trait loci (QTL). Using multiple criteria, including the presence of high impact genomic variants and co-localization of cis-eQTL, we identified 13 candidate genes (Adarb2, Ankrd26, Cacna1c, Clock, Crhr1, Ctu2, Cyp26b1, Eva1a, Fam114a1, Kcnj9, Mlf2, Rab27b, Sec11a) for these traits. Most of these genes have been implicated by human GWAS of various psychiatric traits. For example, Cacna1c, a gene known to be critical for social behavior in rodents and implicated in human schizophrenia and bipolar disorder, is a candidate gene for distance to the social zone. In addition, the QTL region for total distance to the novel object zone, on Chr1 at 144 Mb, is syntenic to a hotspot on human Chr15 (82.5-90.8 Mb) that contains 14 genes associated with psychiatric or substance abuse traits. Although some of the genes identified by this study appear to replicate findings from prior human GWAS, others likely represent novel findings that can be the catalyst for future molecular and genetic insights into human psychiatric diseases. Together, these findings provide strong support for the use of the HS population to study psychiatric disorders.

Allele-specific expression (ASE) is a phenomenon in which one allele is preferentially expressed over the other. Genetic and epigenetic factors cause ASE by altering the final composition of a gene's product, leading to expression imbalances that can have functional consequences on phenotypes. Environmental signals also impact allele-specific expression, but how they contribute to this cross talk remains understudied. Here, we explored how genotype, parent-of-origin, tissue, sex, and dietary fat simultaneously influence ASE biases. Male and female mice from a F1 reciprocal cross of the LG/J and SM/J strains were fed a high or low fat diet. We harnessed strain-specific variants to distinguish between two ASE classes: parent-of-origin-dependent (unequal expression based on parental origin) and sequence-dependent (unequal expression based on nucleotide identity). We present a comprehensive map of ASE patterns in 2853 genes across three tissues and nine environmental contexts. We found that both ASE classes are highly dependent on tissue and environmental context. They vary across metabolically relevant tissues, between males and females, and in response to dietary fat. We also found 45 genes with inconsistent ASE biases that switched direction across tissues and/or environments. Finally, we integrated ASE and QTL data from published intercrosses of the LG/J and SM/J strains. Our ASE genes are often enriched in QTLs for metabolic and musculoskeletal traits, highlighting how this orthogonal approach can prioritize candidate genes. Together, our results provide novel insights into how genetic, epigenetic, and environmental mechanisms govern allele-specific expression, which is an essential step toward deciphering the genotype-to-phenotype map.

Parent-of-origin effects are unexpectedly common in complex traits, including metabolic and neurological diseases. Parent-of-origin effects can be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific parent-of-origin effects on metabolic traits were mapped in the F16generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these parent-of-origin effects phenomena. We propose that non-imprinted genes can generate complex parent-of-origin effects on metabolic traits through interactions with imprinted genes. Here, we employ data from mouse populations at different levels of intercrossing (F0, F1, F2, F16) of the LG/J and SM/J inbred mouse lines to test this hypothesis. Using multiple populations and incorporating genetic, genomic, and physiological data, we leverage orthogonal evidence to identify networks of genes through which parent-of-origin effects propagate. We identify a network comprised of 3 imprinted and 6 non-imprinted genes that show parent-of-origin effects. This epistatic network forms a nutritional responsive pathway and the genes comprising it jointly serve cellular functions associated with growth. We focus on 2 genes,NnatandF2r, whose interaction associates with serum glucose levels across generations in high fat-fed females. Single-cell RNAseq reveals thatNnatandF2rare negatively correlated in pre-adipocytes along an adipogenic trajectory, a result that is consistent with our observations in bulk white adipose tissue.

Sprague Dawley (SD) rats are among the most widely used outbred laboratory rat populations. Despite this, the genetic characteristics of SD rats have not been clearly described, and SD rats are rarely used for experiments aimed at exploring genotype-phenotype relationships. In order to use SD rats to perform a genome-wide association study (GWAS), we collected behavioral data from 4,625 SD rats that were predominantly obtained from two commercial vendors, Charles River Laboratories and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we obtained dense, high-quality genotypes at 291,438 SNPs across 4,061 rats. This genetic data allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that the two populations are highly diverged (FST > 0.4). Furthermore, even for rats obtained from the same vendor, there was strong population structure across breeding facilities and even between rooms at the same facility. We performed multiple separate GWAS by fitting a linear mixed model that accounted population structure and using meta-analysis to jointly analyze all cohorts. Our study examined Pavlovian conditioned approach (PavCA) behavior, which assesses the propensity for rats to attribute incentive salience to reward-associated cues. We identified 46 significant associations for the various metrics used to define PavCA. The surprising degree of population structure among SD rats from different sources has important implications for their use in both genetic and non-genetic studies.Author SummaryOutbred Sprague Dawley rats are among the most commonly used rats for neuroscience, physiology and pharmacological research; in the year 2020, 4,188 publications contained the keyword “Sprague Dawley”. Rats identified as “Sprague Dawley” are sold by several commercial vendors, including Charles River Laboratories and Harlan Sprague Dawley Inc. (now Envigo). Despite their widespread use, little is known about the genetic diversity of SD. We genotyped more than 4,000 SD rats, which we used for a genome-wide association study (GWAS) and to characterize genetic differences between SD rats from Charles River Laboratories and Harlan. Our analysis revealed extensive population structure both between and within vendors. The GWAS for Pavlovian conditioned approach (PavCA) identified a number of genome-wide significant loci for that complex behavioral trait. Our results demonstrate that, despite sharing an identical name, SD rats that are obtained from different vendors are very different. Future studies should carefully define the exact source of SD rats being used and may exploit their genetic diversity for genetic studies of complex traits.

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.

Maintenance of functional β‐cell mass is critical to preventing diabetes, but the physiological mechanisms that cause β‐cell populations to thrive or fail in the context of obesity are unknown. High fat‐fed SM/J mice spontaneously transition from hyperglycemic‐obese to normoglycemic‐obese with age, providing a unique opportunity to study β‐cell adaptation. Here, we characterize insulin homeostasis, islet morphology, and β‐cell function during SM/J’s diabetic remission. As they resolve hyperglycemia, obese SM/J mice dramatically increase circulating and pancreatic insulin levels while improving insulin sensitivity. Immunostaining of pancreatic sections reveals that obese SM/J mice selectively increase β‐cell mass but not α‐cell mass. Obese SM/J mice do not show elevated β‐cell mitotic index, but rather elevated α‐cell mitotic index. Functional assessment of isolated islets reveals that obese SM/J mice increase glucose‐stimulated insulin secretion, decrease basal insulin secretion, and increase islet insulin content. These results establish that β‐cell mass expansion and improved β‐cell function underlie the resolution of hyperglycemia, indicating that obese SM/J mice are a valuable tool for exploring how functional β‐cell mass can be recovered in the context of obesity., High fat‐fed SM/J mice spontaneously transition from hyperglycemic‐obese to normoglycemic‐obese with age, providing a unique opportunity to study β‐cell adaptation. Here we characterize insulin homeostasis, islet morphology, and β‐cell function during SM/J's diabetic remission.

The alteration of gene expression due to variations in the sequences of transcriptional regulatory elements has been a focus of substantial inquiry in humans and model organisms. However, less is known about the extent to which natural variation contributes to post-transcriptional regulation. Allelic Expression Imbalance (AEI) is a classical approach for studying the association of specific haplotypes with relative changes in transcript abundance. Here, we piloted a new TRAP based approach to associate genetic variation with transcript occupancy on ribosomes in specific cell types, to determine if it will allow examination of Allelic Translation Imbalance (ATI), and Allelic Translation Efficiency Imbalance, using as a test case mouse astrocytesin vivo. We show that most changes of the mRNA levels on ribosomes were reflected in transcript abundance, though ∼1.5% of transcripts have variants that clearly alter loading onto ribosomes orthogonally to transcript levels. These variants were often in conserved residues and altered sequences known to regulate translation such as upstream ORFs, PolyA sites, and predicted miRNA binding sites. Such variants were also common in transcripts showing altered abundance, suggesting some genetic regulation of gene expression may function through post-transcriptional mechanisms. Overall, our work shows that naturally occurring genetic variants can impact ribosome occupancy in astrocytesin vivoand suggests that mechanisms may also play a role in genetic contributions to disease.

Maintenance of functional β-cell mass is critical to preventing diabetes, but the physiological mechanisms that cause β-cell populations to thrive or fail in the context of obesity are unknown. High fat-fed SM/J mice spontaneously transition from hyperglycemic-obese to normoglycemic-obese with age, providing a unique opportunity to study β-cell adaptation. Here, we characterize insulin homeostasis, islet morphology, and β-cell function during SM/J’s diabetic remission. As they resolve hyperglycemia, obese SM/J mice dramatically increase circulating and pancreatic insulin levels while improving insulin sensitivity. Immunostaining of pancreatic sections reveals that obese SM/J mice selectively increase β-cell mass but not α-cell mass. Obese SM/J mice do not show elevated β-cell mitotic index, but rather elevated α-cell mitotic index. Functional assessment of isolated islets reveals that obese SM/J mice increase glucose stimulated insulin secretion, decrease basal insulin secretion, and increase islet insulin content. These results establish that β-cell mass expansion and improved β-cell function underlie the resolution of hyperglycemia, indicating that obese SM/J mice are a valuable tool for exploring how functional β-cell mass can be recovered in the context of obesity.

SUMMARY We leverage the SM/J mouse to understand glycemic control in obesity. High-fat-fed SM/J mice initially develop poor glucose homeostasis relative to controls. Strikingly, their glycemic dysfunction resolves by 30 weeks of age despite persistent obesity. The mice dramatically expand their brown adipose depots as they resolve glycemic dysfunction. This occurs naturally and spontaneously on a high-fat diet, with no temperature or genetic manipulation. Removal of the brown adipose depot impairs insulin sensitivity, indicating that the expanded tissue is functioning as an insulin-stimulated glucose sink. We describe morphological, physiological, and transcriptomic changes that occur during the brown adipose expansion and remission of glycemic dysfunction, and focus on Sfrp1 (secreted frizzled-related protein 1) as a compelling candidate that may underlie this phenomenon. Understanding how the expanded brown adipose contributes to glycemic control in SM/J mice will open the door for innovative therapies aimed at improving metabolic complications in obesity., Graphical Abstract, In Brief Carson et al. characterize the spontaneous development of a disproportionate expansion of brown adipose tissue in obese SM/J mice. They find the mice with increased brown adipose tissue have improved glucose tolerance and insulin sensitivity without weight loss, and identify the cytokine Sfrp1 as a likely cause of brown adipogenesis.

SummaryMouse substrains are an invaluable model for understanding disease. We compared C57BL/6J, which is the most commonly used inbred mouse strain, with 8 C57BL/6 and 5 C57BL/10 closely related inbred substrains. Whole genome sequencing and RNA-sequencing analysis yielded 352,631 SNPs, 109,096 INDELs, 150,344 short tandem repeats (STRs), 3,425 structural variants (SVs) and 2,826 differentially expressed genes (DEGenes) among these 14 strains. 312,981 SNPs (89%) distinguished the B6 and B10 lineages. These SNPs were clustered into 28 short segments that are likely due to introgressed haplotypes rather than new mutations. Outside of these introgressed regions, we identified 53 SVs, protein-truncating SNPs and frameshifting INDELs that were associated with DEGenes. Our results can be used for both forward and reverse genetic approaches, and illustrate how introgression and mutational processes give rise to differences among these widely used inbred substrains.

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well annotated genome, wealth of genetic resources and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost effective, informative and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole genome sequencing. Here we describe the content and performance of a new Mouse Universal Genotyping Array (MUGA). MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: 1) chromosomal sex determination, 2) discrimination between substrains from multiple commercial vendors, 3) diagnostic SNPs for popular laboratory strains, 4) detection of constructs used in genetically engineered mice, and 5) an easy to interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA we genotyped 6,899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived and recombinant inbred lines. Here we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, the extension of the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. There is preliminary but striking evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the main stock for a significant action of the genotyped inbred samples. We conclude that MiniMUGA is a valuable platform for genetic QC and important new tool to the increase rigor and reproducibility of mouse research.

Mouse substrains are an invaluable model for understanding disease. We compared C57BL/6J, which is the most commonly used inbred mouse strain, with eight C57BL/6 and five C57BL/10 closely related inbred substrains. Whole-genome sequencing and RNA-sequencing analysis yielded 352,631 SNPs, 109,096 indels, 150,344 short tandem repeats (STRs), 3,425 structural variants (SVs), and 2,826 differentially expressed genes (DE genes) among these 14 strains; 312,981 SNPs (89%) distinguished the B6 and B10 lineages. These SNPs were clustered into 28 short segments that are likely due to introgressed haplotypes rather than new mutations. Outside of these introgressed regions, we identified 53 SVs, protein-truncating SNPs, and frameshifting indels that were associated with DE genes. Our results can be used for both forward and reverse genetic approaches and illustrate how introgression and mutational processes give rise to differences among these widely used inbred substrains.

Anxiety, depression, and stress-related disorders are complex neurobehavioral diseases with a partially heritable genetic basis. This chapter explores how the appropriate use of rodent models can illuminate the neurobiological underpinnings of these disorders. Because these psychiatric disorders are uniquely human, rodent models typically model individual components rather than trying to recapitulate the disease itself. This chapter considers how both intermediate phenotypes and rodent models fit into this framework. Integrating these two concepts can be bidirectional: studying intermediate phenotypes in rodent models may lead to identifying risk genes that are present in humans, or human studies may uncover genetic variants linked to intermediate phenotypes and subsequent experiments in rodents may be employed to examine the causal mechanisms. This dynamic interplay is explored throughout the chapter.

Parent-of-origin effects (POE) are unexpectedly common in complex traits, including metabolic and neurological diseases. POE can also be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific POE on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these POE phenomena. Here, we use a simple yet powerful F1 reciprocal cross model to test the hypothesis that non-imprinted genes can generate complex POE on metabolic traits through genetic interactions with imprinted genes. Male and female mice from a F1 reciprocal cross of LG/J and SM/J strains were fed either high or low fat diets. We generated expression profiles from three metabolically-relevant tissues: hypothalamus, white adipose, and liver. We identified two classes of parent-of-origin expression biases: genes showing parent-of-origin-dependent allele-specific expression and biallelic genes that are differentially expressed by reciprocal cross. POE patterns of both gene classes are highly tissue-and context-specific, sometimes occurring only in one sex and/or diet cohort in a particular tissue. We then constructed tissue-specific interaction networks among genes from these two classes of POE. A key subset of gene pairs show significant epistasis in the F16 LG/J x SM/J advanced intercross data in cases where the biallelic gene fell within a previously-identified metabolic POE QTL interval. We highlight one such interaction in adipose, between Nnat and Mogat1, which associates with POE on multiple adiposity traits. Both genes localize to the endoplasmic reticulum of adipocytes and play a role in adipogenesis. Additionally, expression of both genes is significantly correlated in human visceral adipose tissue. The genes and networks we present here represent a set of actionable interacting candidates that can be probed to further identify the machinery driving POE on complex traits.

Author(s): Johnson, Emma C; St Pierre, Celine L; Meyers, Jacquelyn L; Aliev, Fazil; McCutcheon, Vivia V; Lai, Dongbing; Dick, Danielle M; Goate, Alison M; Kramer, John; Kuperman, Samuel; Nurnberger, John I; Schuckit, Marc A; Porjesz, Bernice; Edenberg, Howard J; Bucholz, Kathleen K; Agrawal, Arpana | Abstract: BackgroundGenomewide association studies (GWAS) have begun to identify loci related to alcohol consumption, but little is known about whether this genetic propensity overlaps with specific indices of problem drinking in ascertained samples.MethodsIn 6,731 European Americans who had been exposed to alcohol, we examined whether polygenic risk scores (PRS) from a GWAS of weekly alcohol consumption in the UK Biobank predicted variance in 6 alcohol-related phenotypes: alcohol use, maximum drinks within 24 hours (MAXD), total score on the Self-Rating of the Effects of Ethanol Questionnaire (SRE-T), DSM-IV alcohol dependence (DSM4AD), DSM-5 alcohol use disorder symptom counts (DSM5AUDSX), and reduction/cessation of problematic drinking. We also examined the extent to which an single nucleotide polymorphism (rs1229984) in ADH1B, which is strongly associated with both alcohol consumption and dependence, contributed to the polygenic association with these phenotypes and whether PRS interacted with sex, age, or family history of alcoholism to predict alcohol-related outcomes. We performed mixed-effect regression analyses, with family membership and recruitment site included as random effects, as well as survival modeling of age of onset of DSM4AD.ResultsPRS for alcohol consumption significantly predicted variance in 5 of the 6 outcomes: alcohol use (Δmarginal R2 = 1.39%, Δ area under the curve [AUC] = 0.011), DSM4AD (Δmarginal R2 = 0.56%; ΔAUC = 0.003), DSM5AUDSX (Δmarginal R2 = 0.49%), MAXD (Δmarginal R2 = 0.31%), and SRE-T (Δmarginal R2 = 0.22%). PRS were also associated with onset of DSM4AD (hazard ratio = 1.11, p = 2.08e-5). The inclusion of rs1229984 attenuated the effects of the alcohol consumption PRS, particularly for DSM4AD and DSM5AUDSX, but the PRS continued to exert an independent effect for all 5 alcohol measures (Δmarginal R2 after controlling for ADH1B = 0.14 to 1.22%). Interactions between PRS and sex, age, or family history were nonsignificant.ConclusionsGenetic propensity for typical alcohol consumption was associated with alcohol use and was also associated with 4 of the additional 5 outcomes, though the variance explained in this sample was modest. Future GWAS that focus on the multifaceted nature of AUD, which goes beyond consumption, might reveal additional information regarding the polygenic underpinnings of problem drinking.

ObjectiveObesity is influenced by genetic and environmental factors. Despite success of human genome wide association studies (GWAS), the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify genetic loci underlying obesity and related morphometric and metabolic traits.MethodsWe measured obesity-relevant traits including body weight, body length, body mass index, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat GWAS to date. Genetic loci were identified using a linear mixed model that accounted for the complex family relationships of the HS and covariate to account for differences among the three phenotyping centers.ResultsWe identified 32 independent loci, several of which contained only a single gene (e.g. Epha5, Nrg1 and Klhl14) or obvious candidate genes (Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and extensive pleiotropy at individual loci.ConclusionsThese studies demonstrate utility of HS rats for investigating the genetics of obesity related traits across institutions and identify several candidate genes for future functional testing.

Replication is considered to be critical for genome-wide association studies (GWAS) in humans, but is not routinely performed in model organisms. We explored replication using an advanced intercross line (AIL) which is the simplest possible multigenerational intercross. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n=428) using a denser marker set and also genotyped a novel cohort of AIL mice (F39-43; n=600) for the first time. We identified 110 significant loci in the F34cohort, 36 of which were new discoveries attributable to the denser marker set; we also identified 27 novel significant loci in the F39-43cohort. For traits measured in both cohorts (locomotor activity, body weight, and coat color), the genetic correlations were high, although, the F39-43cohort showed systematically lower SNP-heritability estimates. We then attempted to replicate loci identified in either F34or F39-43in the other cohort. Albino coat color was robustly replicated; we observed only partial replication of associations for locomotor activity and body weight. Finally, we performed a mega-analysis of locomotor activity and body weight by combining F34and F39-43cohorts (n=1,028), which identified four novel loci. The incomplete replication was inconsistent with simulations we performed to estimate our power to replicate. This may reflect: 1) false positives errors in the discovery cohort, 2) environmental or genetic heterogeneity between the two samples, or 3) the systematic over estimation of the effect sizes at significant loci (“Winner’s Curse”). Our results demonstrate that it is difficult to replicate GWAS results even when using similarly sized discovery and replication cohorts drawn from the same population.

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., Multigenerational outbred populations from an advanced intercross line (AIL) of mice represent useful resources for genome wide association analysis. Here, the authors analyze 1,063 LG x SM AIL mice to identify significant associations for 50 traits relevant to human health and disease.