Authors: Mustafa Hakan Gunturkun [ORCID ID: 0000-0003-0612-6432]Tengfei Wang[ORCID ID:=0000-0003-3527-3394] Apurva Chitre [ORCID ID=0000-0003-1709-9214] Angel Garcia Martinez, Katie Holl ,Celine St. Pierre [ORCID ID=0000-0001-5465-6601], Hannah Bimschleger [ORCID ID=0000-0001-6578-7201], Jianjun Gao, Riyan Cheng [ORCID ID=0000-0002-8670-795X], Oksana Polesskaya [ORCID ID=0000-0003-3024-114X], Leah C Solberg-Woods [ORCID ID=0000-0002-7943-798X] Abraham Palmer[ORCID ID=0000-0003-3634-0747]
Principle investigator: Hao Chen [ORCID ID: 0000-0002-2680-6921] (PI),
Study purpose This dataset was produced to perform genome-wide association study (GWAS) for behaviors tested in an open field to identify genetic contributions to these traits.
Subjects: We used 1,246 adolescent heterogeneous stock (HS)( RGD_13673907) male and female rats
- Behavior phenotypes: we conducted behavior tests measured in an open field, including locomotion, novel object interaction, and social interaction.
- Genotypes were generated as described in [PMID: 23979941, DOI: 10.1534/g3.113.007948]
- The gene expression data were collected from 88 naive adult HS rats. Five brain regions (prelimbic, infralimbic, and orbitofrontal cortex, lateral habenula, and nucleus accumbens core) were collected for RNA-seq from each rat.
This dataset is associated with the manuscript (https://doi.org/10.3389/fpsyt.2022.790566)
- Behavior phenotypes Two Open Field Test arenas were constructed and placed side by side. No source of visible light was present during behavioral testing. A digital camera fitted with an infrared filter and located next to the infrared light source was used to record the behavior of the rats. All rats were released at the same corner of the test chamber, and data were collected for 1 hour.
- Genotyping was performed using genotyping-by-sequencing (GBS)
- The gene expression was measured in 88 HS rats using fastENLoc (38) and a LD cutoff-based method to colocalize behavioral and gene expression QTLs
GWAS analysis employed a linear mixed model, as implemented in the software GCTA, using a genetic relatedness matrix (GRM) to account for the complex family relationships within the HS population. Significance thresholds were calculated using permutation.