Objective Obesity 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. Methods This 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. Results This 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. Conclusions This 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.

Obesity is a global health crisis that is influenced by both genetic and environmental factors.Rodent model organisms can be used to understand the biological and genetic basis of obesity and related morphological traits. A major advantage of model organisms is that they can be studied under uniform environmental conditions, thus reducing the complex role of environment and gene by environment interactions. Furthermore, fat pads and other tissues can be dissected and weighed, so that their role in determining body weight can be precisely defined. Highly recombinant populations allow for genetic fine-mapping of complex traits, greatly reducing the number of plausible candidate genes. We performed the largest rat GWAS ever undertaken, using 3,173 male and female adult N/NIH heterogeneous stock (HS) rats, which were created by mixing 8 inbred strains. We identified 31 independent loci for body weight, body length, body mass index, fat pad weight (retroperitoneal, epididymal, and parametrial), and fasting glucose.We observed strong evidence of pleotropic effects across multiple phenotypes. Three loci contained only a single gene (Epha5, Nrg1 and Klhl14), whereas others were larger and contained many genes. We replicated a locus containing Prlhr, and a second locus containing Adcy3, which we had previously identified in a smaller HS rat study. Finally, by subsampling our dataset, we showed an exponential growth of significant loci as sample size increased towards 3,173. Our results demonstrate the potential for rodent studies to add to our understanding of the molecular genetic factors that contribute to obesity-relevant traits and emphasize the importance of sample size.

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 evaluated multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We have 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.

30Sprague Dawley (SD) rats are one of the most commonly used outbred rat strains. Despite 31 this, the genetic characteristics of SD are poorly understood. We collected behavioral data from 32 4,625 SD rats acquired predominantly from two commercial vendors, Charles River Laboratories 33 and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we 34 obtained dense, high-quality genotypes at 234,887 SNPs across 4,061 rats. This genetic data 35 allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that 36 the two populations are highly diverged (FST > 0.4). We also used these data to perform a genome-37 wide association study (GWAS) of Pavlovian conditioned approach (PavCA), which assesses the 38 propensity for rats to attribute motivational value to discrete, reward-associated cues. Due to the 39 genetic divergence between rats from Charles River and Harlan, we performed two separate 40 GWAS by fitting a linear mixed model that accounted for within vendor population structure and 41 using meta-analysis to jointly analyze the two studies. We identified 18 independent loci that were 42 significantly associated with one or more metrics used to describe PavCA; we also identified 3 43 loci that were body weight, which was only measured in a subset of the rats. The genetic 44 characterization of SD rats is a valuable resource for the rat community that can be used to inform 45 future study design. 46 AuthorSummary 47 Outbred Sprague Dawley rats are among the most commonly used rats for neuroscience, 48 physiology and pharmacological research. SD rats are sold by several commercial vendors, 49 including Charles River Laboratories and Harlan Sprague Dawley Inc. (now Envigo). Despite their 50wide spread use, little is known about the genetic diversity of SD. We genotyped more than 4,000 51 2 SD rats, which we used to characterize genetic differences between SD rats from Charles River 52 Laboratories and Harlan. Our analysis revealed that the two SD colonies are highly divergent. We 53 also performed a genome-wide association study (GWAS) for Pavlovian conditioned approach 54 (PavCA), which assesses the propensity for rats to attribute motivational value to discrete, reward-55 associated cues. Our results demonstrate that, despite sharing an identical name, SD rats are 56 obtained from different vendors are genetically very different. We conclude that results obtained 57 using SD rats should not be presented without also carefully noting the vendor. 58 Introduction 59Rats are among the most commonly used organisms for experimental psychology and 60 biomedical research. Whereas research using mice makes extensive use of inbred strains, in rats, 61 it is more common to use commercially available outbred populations. Among the commercially 62 available outbred rat populations, the Sprague Dawley strain (SD) is one of the most widely used. 63SD rats are distributed by several vendors. Each vendor has multiple breeding locations, and each 64 breeding locatio...

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 for 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.

ABSTRACTThe 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.

The semaphorin protein family is a diverse set of extracellular signaling proteins that perform fundamental roles in the development and operation of numerous biological systems, notably the nervous, musculoskeletal, cardiovascular, endocrine, and reproductive systems. Recently, recessive loss‐of‐function (LoF) variants in SEMA3A (semaphorin 3A) have been shown to result in a recognizable syndrome characterized by short stature, skeletal abnormalities, congenital heart defects, and variable additional anomalies. Here, we describe the clinical and molecular characterization of a female patient presenting with skeletal dysplasia, hypogonadotropic hypogonadism (HH), and anosmia who harbors a nonsense variant c.1633C>T (p.Arg555*) and a deletion of exons 15, 16, and 17 in SEMA3A in the compound heterozygous state. These variants were identified through next‐generation sequencing analysis of a panel of 26 genes known to be associated with HH/Kallmann syndrome. Our findings further substantiate the notion that biallelic LoF SEMA3A variants cause a syndromic form of short stature and expand the phenotypic spectrum associated with this condition to include features of Kallmann syndrome.

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.