Prediction of transcriptional signatures in glomeruli of a mouse model of nephropathy using the human Global Prior rank
Authors: Gonzalez-Vicente Agustin , Wu Zhenzhen , Nair Viji , Barisoni Laura , Kretzler Matthias , Bruggeman Leslie , O’Toole John F. , Sedor John R. 
Published: April 2020

BackgroundDifferential gene expression is commonly used to provide insight into the molecular mechanisms of disease. Each human or murine cell contains roughly 20000 protein coding genes and 30 to 50% are expected to be significantly expressed. Recent analysis of human transcriptomes studies showed that generic transcriptional signatures commonly occur. The Global Prior ranks human genes based on the likelihood of being differentially expressed regardless of experimental conditions. Given that rodent models are extensively used to infer mechanisms of human disease, we tested whether the predictability of gene expression found in humans applies to a mouse model of renal disease.HypothesisThe human Global Prior rank would predict differential gene expression in the transgenic Tg26 mouse.MethodsTranscriptomes of isolated glomeruli from Tg26 mice and non‐transgenic controls were obtained using Affymetrix microarrays. Differential gene expression between groups was assessed with Limma. The human Global Prior was obtained from GitHub. The differentially expressed genes (DEG) by Limma were extracted and mapped to the Global Prior for exploratory data analysis.ResultsThe Global Prior contained 19171 human genes, while our complete Limma results list contained 19525 mouse genes. There were 15183 human‐mouse orthologues present in both lists. We further subset the overlapping genes according to the following criteria: 1st) a Limma FDR <= 0.05, and 2nd) at least 25% change in Tg26 as compared to control (log2FC < −0.42 or log2FC > 0.32). This process yielded a list of 449 DEG by Limma, with corresponding human orthologues in the Global Prior. We then explored the distribution of the Limma DEG along the Global Prior rank. Roughly 50% of the Limma DEG mapped to the top‐10% Global Prior rank interval, and 70% of the Limma DEG map to the top 20% Global Prior rank, p < 2×10−16, as measured by a Fisher’s exact test using all 15183 common genes as background list. To further characterize the predictive power of the Global Prior we examined the overlap between the top‐20% of the Global Prior (n = 3361 genes) and the Limma DEG list (n = 449 genes). The 312 genes common to both list, represent only a small fraction (9%) of the top‐20% of genes in the Global Prior. This indicate that part of the Global Prior predictive power resides in the large number of genes with 80% or more likelihood of being differentially expressed.ConclusionThe human Global Prior successfully predicted differential gene expression in mouse glomeruli. These data does not mean that the transcriptional responses in the Tg26 kidney are generic. The Global Prior does not predict the outcome of any particular study, instead it ranks commonly used transcriptional responses. Thus, the transcriptional response in Tg26 glomeruli is specific to the model, but not unique to it. Our analysis also highlights the similarities between mouse and human transcriptional responses, and validate the usefulness of experimental animals to model human diseases.Support or Funding InformationDK007470, DK097836, DK108329, DK114908