Identification of transcriptional macromolecular associations in human bone using browser based in silico analysis in a giant correlation matrix

Intracellular signaling is critically dependent on gene regulatory networks comprising physical molecular interactions. Presently, there is a lack of comprehensive databases for most human tissue types to verify such macromolecular interactions. We present a user friendly browser which helps to identify functional macromolecular interactions in human bone as significant correlations at the transcriptional level. The molecular skeletal phenotype has been characterized by transcriptome analysis of iliac crest bone biopsies from 84 postmenopausal women through quantifications of ~ 23,000 mRNA species. When the signal levels were inter-correlated, an array containing > 260 million correlations was generated, thus recognizing the human bone interactome at the RNA level. The matrix correlation and p values were made easily accessible by a freely available online browser. We show that significant correlations within the giant matrix are reproduced in a replica set of 13 male vertebral biopsies. The identified correlations differ somewhat from transcriptional interactions identified in cell culture experiments and transgenic mice, thus demonstrating that care should be taken in extrapolating such results to the in vivo situation in human bone.The current giant matrix and web browser are a valuable tool for easy access to the human bone transcriptome and molecular interactions represented as significant correlations at the RNA-level. The browser and matrix should be a valuable hypothesis generating tool for identification of regulatory mechanisms and serve as a library of transcript relationships in human bone, a relatively inaccessible tissue.

► Global expression profiling was performed on iliac bone biopsies from 84 postmenopausal women and ~ 23,000 transcripts were quantified. ► Signal values of ~ 23,000 transcripts were inter-correlated, generating a matrix of > 260,000,000 r- and p-values. ► A user friendly and freely available online browser was programmed for targeted search within the matrix (located at http://app.uio.no/med/klinmed/correlation-browser/iliac-v1.1/). ► The matrix and browser provide a hypothesis generating tool and indirect confirmation of candidate regulatory events in human bone. ► The paper presents new insight to the function of centrally ubiquitously expressed transcription factors (glucocorticoid receptor, SMAD4, CREB1).