Computational protocol: Natural and molecular history of prolactinoma: insights from a Prlr–/– mouse model

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Protocol publication

[…] Two and four month-old wild-type (n = 6 and 6 respectively) and Prlr–/– (n = 6 and 6 respectively) mice were sacrified by decapitation. Pituitaries were removed, pooled three by three to form duplicates for each genotype, and frozen at –80°C before RNA extraction. Fifty ng total RNA was amplified and labeled with Cy3 using Low input Quick Amp labeling Kit (Agilent technologies, Santa Clara, California, USA) according to manufacturer’s instructions. Labeled cRNA was then fragmented and hybridized over 1 Sureprint G3 Mm9 8 × 60 K array (Agilent technologies), allowing the study of the 8 samples in parallel and interrogating over 40K annotated transcripts of Mm9 assembly. Hybridization was performed according to manufacturer’s instructions. Raw fluorescence data were extracted using Genespring software v12 (Agilent technologies) and normalized using the 75th percentile method. Values were then log2 normalized and subtracted of the median value for each replicate. The whole experiment was replicated with another set of animals (12 wild-type and 12 Prlr–/– mice). Differential gene expression (DE) was assessed using Significance Analysis of Microarrays []. The DE gene list was explored using the gene set enrichment analysis program Enrichr [] to identify upstream regulators (kinases and transcription factors) for which known targets are significantly enriched in DE genes. This analysis was performed on 25 March 2016. The network was constructed using Cytoscape 3.3 and the GeneMania plugin to automatically retrieve known direct protein-protein interactions (interactome) from databases and manually curated bibliographic sources [, ] and additional manual search. […]

Pipeline specifications

Software tools GeneSpring GX, SAM, Enrichr, GeneMANIA
Application Gene expression microarray analysis
Organisms Mus musculus, Homo sapiens, Rattus norvegicus
Diseases Pituitary Neoplasms, Prolactinoma
Chemicals Estrogens