Cortex and Hypothalamus Gene Expression in bred High Responder (bHR) vs. bred Low Responder (bLR) Rats: Affymetrix Microarray Data from Generation F4. Cortex and Hypothalamus Gene Expression in bred High Responder (bHR) vs. bred Low Responder (bLR) Rats: Affymetrix Microarray Data from Generation F4

The strong pattern of comorbidity amongst psychiatric disorders is believed to be generated by a spectrum of latent liability, arising from a complex interplay of genetic risk and environmental factors, such as stress and childhood adversity. At one end of this spectrum are internalizing disorders, which are associated with neuroticism, anxiety, and depression. At the other end of the spectrum are externalizing disorders, which are associated with risk-taking and novelty-seeking, as seen in mania, substance abuse, and impulse-control disorders. We model the genetic contributions underlying both extremes of this spectrum by selectively breeding rats that react differently to a novel environment. “Bred high responder” (bHR) rats are highly exploratory with a disinhibited, novelty-seeking temperament, including hyperactivity, aggression, and drug-seeking. “Bred low responder” (bLR) rats are highly-inhibited, exhibiting reduced locomotor activity and anxious and depressive-like behavior. These behavioral propensities are robust and stable, beginning early in development similar to temperament in humans. This Affymetrix (Rat Expression Set 230 A) microarray study examined gene expression in the hippocampus, cortex, and hypothalamus in generation F4 adult male bHR rats and bLR rats (n=6 per group). The hippocampal data was previously analyzed and uploaded as GSE140596, whereas the cortex and hypothalamus data are included in this GEO record. Overall design: Overall Design: This microarray study examined gene expression in the hippocampus, cortex, and hypothalamus in generation F4 adult male bHR rats and bLR rats (n=6 per group). The hippocampal data was previously analyzed and uploaded as GSE140596, whereas the cortex and hypothalamus data are included in this GEO record. Behavioral testing: Locomotor response to a novel environment was assessed between age P50–75 as part of our selective breeding paradigm (protocol: Stead et al., 2006, Behav Genet. 36: 697–712). Sacrifice & RNA Extraction: The rats were sacrificed in adulthood (between P102-P108) via rapid decapitation followed by immediate brain extraction. The whole hippocampus, frontal cortex, and hypothalamus samples were rapidly dissected on ice, fast-frozen at –40°C, and stored at –80°C before processing. TRIzol reagent (Invitrogen, Calsbad, CA) was used to extract total RNA, followed by purification using RNeasy RNA purification columns (Qiagen, Valencia, CA). The quality and concentration of the RNA was determined using an Agilent bioanalyzer (Palo Alto, CA) and wavelength absorbance (260/280 nm ratio) by Nanodrop. Microarray: The samples were transcriptionally profiled using Affymetrix Rat Expression Set 230 A (RAE230A) microarray according to standard manufacturer’s procedures. The samples were run in two batches: the first included the hippocampus and cortex samples and the second included the hypothalamus samples. Each brain region was run on a separate chip. Only data from the cortex and hypothalamus samples are included in this data release. Microarray Data Preprocessing: For our current analyses, the ReadAffy() function (from R package affy, v.1.84.0; (Gautier et al., 2004)) was used to read the data from the .CEL files into R studio (v.1.0.153). An expression set was generated using the Robust Multi-Array Average method (RMA: (Irizarry et al., 2003)). An updated custom chip definition file for the RAE230A chip (.cdf (Dai et al., 2005): “rae230arnentrezgcdf_25.0.0”) was used to summarize the probe signals into probesets targeting genes annotated by Entrez Gene ID (downloaded from http://brainarray.mbni.med.umich.edu/Brainarray/Database/CustomCDF/25.0.0/entrezg.asp on Dec 9 2024, released on Jan 5, 2021). Additional gene annotation was later added using the org.Rn.eg.db package (v.3.20.0, (Carlson, 2019)). Quality control identified two hippocampal samples with low sample-sample correlation values (median R= 0.68 & 0.89, respectively), leaving a final sample size of n=5/group for the hippocampus, and n=6/group for both the cortex and hypothalamus. Separate bHR/bLR differential expression analyses were conducted for each brain region using the limma pipeline (no covariates, v.3.62.1, (Ritchie et al., 2015)), followed by an empirical Bayes correction. Nominal p-values were corrected for multiple comparisons using the Benjamini-Hochberg method (False Discovery Rate or FDR) within the multtest package (v. 2.62.0, (Pollard et al., 2005)).The full analysis code is available at: https://github.com/hagenaue/NIDA_bLRvsbHR_F2Cross_HC_RNASeq.