The Center for GWAS in Outbred Rats Database (C-GORD)

This collection consists of data from published studies performed in N/NIH heterogeneous stock (HS) outbred rats. The effort is led by Prof. Abraham Palmer, who serves as director. The Center for GWAS in Outbred Rats Database (C-GORD) provides access to the data generated by the NIDA Center for Genetic Studies of Drug Abuse and Other Behaviors as well as physiological phenotypes that comprise of more than 15 research projects. To date, our center has allowed us to accumulate extensive data from more than 8,000 HS rats, with funding already in place to reach 16,000 rats by 2025. HS rats are an important model for genetic studies of a wide array of biomedically important traits. HS rats were created in 1984 by intercrossing 8 inbred rat strains and have been maintained since then as an outbred population for almost 100 generations. Because recombinations of the founder haplotypes accumulate with each generation, HS rats have unparalleled ability to precisely map alleles that influence a given phenotype. Our center has served as the foundation for more than 10 additional grants that are united by their use of HS rats and core services that support genotyping and analysis. We have carefully stored data about all of these rats in a relational database that includes extensive behavioral and physiological data: DNA sequencing, RNA-seq, 16S microbiome, gut metabolomics and whole genome shotgun, single-cell RNA-seq, and ATAC-seq. Objects within this collection contain the data sets and scripts that support published peer-reviewed manuscripts authored by C-GORD researchers. Each object also contains extensive documentation (“readme” files) to aid fellow scientists in understanding, verifying, and reproducing results generated from the provided data as well as contacting the relevant researchers. Finally, each object links to the related manuscript on the journal’s website as well as an open-access version when/if it becomes available. We anticipate that C-GORD will be used for many unforeseen analyses in the future.